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Cancer Research and Treatment > Volume 56(3); 2024 > Article
Kim, Shim, Kim, Lee, Kim, Yoon, Kim, Park, Jeong, Yoo, Cheon, Kim, Lee, Hong, Park, Jung, Kim, Kim, Cha, Lim, Kim, Lee, Kim, Chun, Yun, Park, Lee, Cho, Nam, Na, Yoon, Lee, Jang, Yun, Lee, Kim, and Kim: Clinical Practice Recommendations for the Use of Next-Generation Sequencing in Patients with Solid Cancer: A Joint Report from KSMO and KSP

Abstract

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Introduction

Over the past few years, next-generation sequencing (NGS)–based genetic testing has emerged as a crucial aspect of cancer patient care, with the number of tests performed rapidly increasing since its reimbursement by the national health insurance in Korea in 2017. However, as the use of NGS-based genetic testing continues to expand, there is an increasing need for maximizing benefits for patients while also considering cost-effectiveness.
The primary objective of NGS-based genetic testing is to identify targetable actionable genes that can guide treatment selection. However, its application has expanded to include diagnosis and exploration of resistance mechanisms, enabling more personalized treatment options. Moreover, biomarkers like homologous recombination deficiency (HRD), microsatellite instability–high (MSI-H)/mismatch repair deficiency (MMR-D), and high tumor mutational burden (TMB-H) have gained increasing significance. Consequently, NGS-based testing is now widely used to analyze these biomarkers and make well-informed treatment decisions.
With the expanding application of NGS-based genetic testing, there is a need for expert consensus on best practices and guidelines for its use. This recommendation aims to (1) provide guidance on the practical application of NGS in daily clinical practice and (2) classify actionable gene lists by cancer type, based on a comprehensive review of the literature and the consensus of experts. Furthermore, the recommendation will present expert opinions, based on existing evidence, regarding biomarkers including HRD, MSI-H/MMR-D, TMB, and circulating tumor DNA (ctDNA) panel testing.

Materials and Methods

The Korean Society of Medical Oncology (KSMO) and the Korean Society of Pathologists (KSP) have collaborated to develop subsequent clinical practice recommendations. These focus on key questions not addressed in the previous guidelines for NGS-based genetic testing and the molecular tumor board from the KSMO and Korean Cancer Study Group (KCSG) Precision Medicine Networking Group [1]. In March and April of 2022, the Steering Committee and Writing Committee were reestablished. They were comprised of medical oncologists, pathologists, and bioinformaticians convened by KSMO, KCSG, and KSP. Two main issues were addressed: the proper recommendations for NGS-based genetic testing in solid cancers, and the classification level determination of genes applicable in Korea. The committees initially conducted a survey to assess the appropriateness of key questions, achieving consensus through feedback from all committee members, to confirm the final selection of key questions. Subsequently, recommendations for these questions were drafted by the Steering Committee and further refined through extensive discussions with all committee members during a comprehensive workshop in September 2022. These modified recommendations were then finalized through a final survey in November 2022. Additionally, the Writing Committee classified actionable genes by cancer type using the Korean Precision Medicine Networking Group (KPMNG) scale for clinical actionability of molecular targets (Table 1). The references for determining the actionability of target genes include case series and clinical trials from all phases (phase I, II, III) published up to August 31, 2023. Studies that were part of basket trials were also considered for inclusion. Furthermore, significant abstracts from clinical trials presented at the American Society of Clinical Oncology Annual Meeting and the European Society for Medical Oncology (ESMO) Congress were incorporated. Subsequently, these gene lists, along with their corresponding references, were shared with disease-specific divisions within KCSG and KSP, where feedback and input from these committees were incorporated to further refine the rankings. The lists underwent one final review and confirmation by the entire committee. The finalized recommendations were presented at the 2023 KSMO annual meeting and announced at the 2023 KSP annual meeting. These recommendations have received endorsements from both KSMO and KSP.

Key Questions and Recommendations

1. Question 1. What are the appropriate recommendations for NGS-based genetic testing in solid cancers?

Recommendation 1. NGS-based genetic testing is recommended for patients with advanced or metastatic solid cancers who are eligible for systemic treatments.
There is mounting evidence that NGS-based matched treatments enhance outcomes in patients with advanced or metastatic cancers [2-6]. Even in tumor types like breast cancer, where the role of NGS has traditionally been less defined, a recent study has shown improved treatment outcomes when patients were matched to appropriate therapies through comprehensive genomic analysis, including NGS [7].
Genomic testing should be conducted in patients with advanced or metastatic solid cancers if there are approved treatments matching genomic biomarkers by a regulatory authority. For instance, several genetic tests, including those for EGFR, ALK, ROS1, BRAF, MET, KRAS, ERBB2, and RET, should be conducted in patients with non-squamous non–small cell lung cancer (NSCLC). In cases where multiple gene tests are required, NGS can efficiently utilize tumor tissue compared to testing individual genes. The National Comprehensive Cancer Network guideline for NSCLC also recommends panel-based genomic testing by NGS [8]. The use of a multi-gene panel by NGS is also recommended for tumors like ovarian cancer, prostate cancer, and pancreatic cancer. Testing for homologous recombination repair (HRR) related genes is required for these types of cancers to inform the use of poly(ADP-ribose) polymerase (PARP) inhibitors. Even for patients with cancers in which actionable genetic alterations are rarely found, NGS is recommended, taking into account tumor-agnostic biomarkers. MSI-H/MMR-D, TMB-H, BRAF V600E, RET fusion, and NTRK fusions have been approved by the U.S. Food and Drug Administration (FDA) as tumor-agnostic biomarkers [9-20]. In Korea, matched treatments for tumors with MSI-H/MMR-D and NTRK fusions have been approved.
If a biomarker-matched treatment showing clinical benefit has not yet received regulatory approval, we strongly encourage patients to participate in clinical trials based on molecular profiles from NGS. Our goal is to provide maximum treatment options for individual patients with advanced or metastatic cancer. The probability of detecting actionable genetic alterations using NGS varies based on the cancer type [2]. Given that the potential benefits of NGS may vary among individuals, it is essential to discuss its aims and limitations with the patient. Furthermore, NGS is not recommended when systemic treatment is unfeasible due to factors including the patient’s performance status, comorbidities, and socioeconomic conditions.
Recommendation 2. NGS-based genetic testing can be recommended for the pathological diagnosis of solid cancers.
Precise pathological diagnosis is a fundamental component of precision oncology and in predicting prognosis for patients with solid cancer. Notably, in the recently published classification of tumors by the World Health Organization (WHO), the diagnosis of tumors defined by genetic alterations is gradually expanding. Consequently, there are increasing cases in which a final pathological diagnosis is made based on NGS results. In addition, OncoKB [21], which is widely referred to in the interpretation of genetic alterations, provides information about diagnosis of hematologic malignancy by classifying the genetic alterations into ‘Diagnostic’ Level Dx1 (required for diagnosis), Dx2 (supports diagnosis), and Dx3 (investigational diagnosis). It is anticipated that this trend will soon be reflected in the diagnosis of solid cancers. We will briefly discuss the application of NGS in the diagnosis of bone and soft tissue sarcoma, renal cell carcinoma, and central nervous system tumors, using these as representatives.

1) Bone and soft tissue sarcomas

As more than half of soft tissue tumors and approximately a quarter of bone tumors harbor recurrent genetic alterations [22], molecular analysis is a strong diagnostic tool for the evaluation of bone and soft tissue sarcomas. There are several advantages of using NGS: simultaneous examination of multiple genomic regions, low-level tumor sample requirement and intuitive visualization of results [23]. NGS panels designed for sarcoma diagnosis utilize primers for the detection of fusions, amplifications, deletions and point mutations, which broadly cover genetic alterations in various sarcoma types. In daily practice, pathologists often encounter cases in which NGS provides the precise diagnosis by confirming or excluding differential diagnoses. Some cases can be even diagnosed toward unsuspected entities on the microscopic examination after NGS analysis [24].
NGS analysis may be applied for differential diagnosis of bone and soft tissue sarcomas as follows: (1) low-grade central osteosarcoma (MDM2) vs. fibrous dysplasia (GNAS); (2) chondroblastic osteosarcoma (chromosomal instability) vs. chondrosarcoma (IDH1/2); (3) malignant peripheral nerve sheath tumor (CDKN2A) vs. atypical neurofibroma; (4) liposarcoma (MDM2) vs. atypical pleomorphic lipomatous tumor (RB1); (5) alveolar rhabdomyosarcoma (PAX3/7::FOXO1) vs. embryonal rhabdomyosarcoma (mutations in RAS-MAPK pathway); (6) tumors of uncertain differentiation (Ewing sarcoma, round cell sarcoma with EWSR1-non-ETS fusions, CIC-rearranged sarcoma, sarcoma with BCOR genetic alterations, synovial sarcoma, alveolar soft part sarcoma, extraskeletal myxoid chondrosarcoma, clear cell sarcoma of soft tissue, etc.).

2) Renal cell carcinoma

NGS-based genetic panel test can be recommended for the pathological diagnosis of molecularly defined renal cell carcinoma (RCC), which includes fumarate hydratase (FH)–deficient RCC, succinate dehydrogenase (SDH)–deficient RCC, TFE3-rearranged RCC, TFEB -rearranged or TFEB -amplified RCC, ELOC (formerly TCEB1)-mutated RCC, SMARCB1 (INI1)-deficient RCC, and ALK-rearranged RCC according to the recent 2022 WHO classification [25]. The molecular alterations of these renal tumors are as follows: biallelic FH mutation/inactivation in FH-deficient RCC; inactivating mutations of one of SDH genes, most commonly SDHB, followed by SDHA and SDHC, and rarely SDHD in SDH-deficient RCC; translocations involving TFE3 in TFE3-rearranged RCC; translocations involving TFEB in TFEB -rearranged RCC; TFEB amplification in TFEB -amplified RCC; inactivating mutations exclusively at TCEB1 Y79 in ELOC (formerly TCEB1)-mutated RCC; translocations or deletions involving 22q11.23 in SMARCB1 (INI1)-deficient RCC; translocations involving ALK in ALK-rearranged RCC. In addition, NGS-based genetic panel test may also be recommended for morphologically defined renal tumors with characteristic molecular alteration. Clear cell RCC is characterized by the loss of chromosome 3p accompanied by the inactivation mutation or methylation of the remaining VHL gene. Papillary RCC commonly shows gains of chromosomes 7 and 17, and loss of the Y chromosome with MET alterations in the low-grade tumor. Chromophobe RCC has losses of multiple chromosomes including 1, 2, 6, 10, 13, 17, 21, and Y. Eosinophilic solid and cystic RCC can show TSC gene mutations or biallelic losses.

3) Central nervous system tumor

With the development of research techniques such as NGS, our understanding of the molecular and clinicopathological characteristics of brain tumors has advanced greatly. Based on these changes, following the 2016 Central Nervous System (CNS) WHO classification revised 4th edition [26] and cIMPACT-NOW [27], the 2021 CNS WHO classification 5th edition [28] fully included the molecular genetic characteristics of tumors in the WHO classification of brain tumors. In the 2021 CNS WHO classification, several molecular genetic characteristics such as gliomas, glioneuronal tumors, ependymomas, embryonic tumors (medulloblastoma, etc.), and meningiomas were introduced into the diagnostic criteria. Molecular genetic characteristics included in the diagnostic criteria range from those that can be identified with a single test (sequencing, fluorescence in situ hybridization, etc.) to those that require integrated identification of various genes involved in a specific pathway, as well as those that identify chromosomal arm-level copy number alterations. To cover all of these, NGS testing is essential. In addition, these molecular classifications determine the diagnosis of the tumor and further determine the WHO grade, which is a basic brain tumor grading system that determines the treatment strategy. The use of traditional histopathological morphological classification alone without NGS testing can mislead patients’ treatment strategies.
Recommendation 3. NGS-based genetic testing can be repeated in patients with solid cancer in case of disease recurrence or development of drug resistance.
Acquired resistance inevitably occurs with the growing use of targeted agents targeting various driver oncogenes. Representatively, we have seen the successful development of osimertinib, the third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) during the last decade [29]. At the time of drug development, osimertinib was developed for the patients who revealed the acquired EGFR threonine to methionine at codon 790 (T790M) mutation at the time of treatment failure with first- or second-generation EGFR TKI [30]. Therefore, the detection of EGFR T790M has been crucial for making treatment decisions in patients who experienced treatment failure with first- or second-generation EGFR TKIs [8]. Apart from EGFR T790M, other types of acquired resistance mechanisms were revealed by NGS, such as ERBB2 amplification or MET amplification [31]. Given the recent memorial imprint of resistance mechanism discovery, we have started using repeated NGS to detect acquired resistance in on-treatment tumor tissue, as well as in liquid biopsy samples.
Generally, acquired resistance can be classified into two categories: (1) target-dependent, such as target gene mutations, and (2) target-independent, such as gene aberrations in bypass pathways [32]. Beyond the EGFR T790M mutation, the EGFR C797S mutation is one of the most common EGFR-dependent resistance mechanisms against osimertinib [33]. MET amplification is another type of bypass pathway resistance mechanism across oncogene-driven subsets of NSCLC [34]. The EML4::ALK fusion, occurring in 3%-7% of all NSCLC cases, is currently treated with alectinib or brigatinib, the second-generation ALK TKIs, which are the standard treatments for treatment-naïve ALK-positive NSCLC patients [35-37]. ALK G1202R, solvent front mutation affecting drug binding to active site, is the most common target-dependent mutation [38]. Detecting the ALK G1202R mutation through NGS enables the prediction of a notable response with subsequent lorlatinib. NTRK fusion is a tumor agonistic driver oncogene, detected in less than 1% of solid cancers. With introduction of larotrectinib and entrectinib in clinic, several target-dependent point mutations were noted, which can be found by NGS [19,20]. Repotrectinib (TPX-0005) has demonstrated anti-tumor efficacy in patients previously treated with NTRK-targeting TKIs and who harbor target-dependent TRK mutations [39].
Since the 2000s, the clinical use of NGS has expanded beyond the detection of driver oncogenes. It has paved the way for the discovery of novel targets associated with acquired resistance and provided valuable insights into potential targets for the next generation of targeted therapeutics. However, it’s important to acknowledge certain limitations associated with the repetition of NGS testing. Challenges include the increased cost, difficulties in obtaining repeated tumor biopsies, and associated risks. Additionally, the likelihood of identifying actionable targets at the point of resistance can vary depending on the specific cancer type and drugs, with potential restrictions in drug availability. Nonetheless, it remains evident that NGS can play a crucial role in helping inform subsequent treatment decisions for certain patients who have experienced treatment failure with targeted therapy.

2. Question 2. How can we determine the classification level of genes applicable in Korea?

Advancements in NGS technologies have facilitated the identification of driver mutations in cancer, prompting a shift from a histology-based to a molecular-based approach in cancer treatment. Simultaneously, the advent of targeted therapies has allowed for treatments based on genetic alterations irrespective of the tumor’s origin. This concept, known as tissue-agnostic indication, has demonstrated promising results in recent studies and has become a crucial element in the standard care for cancer. Currently, the tissue-agnostic indications approved by the FDA are listed in Table 2 [9-20,40].
Taking into account both the evidence level of clinical research and clinical benefit, the committee members classified actionable genes for each type of cancer based on their level using KPMNG scale of Clinical Actionability of molecular Targets (K-CAT). We also included certain genes, such as POLE in endometrial cancer, that are clinically significant and thus necessitate testing. The actionable gene lists for NSCLC, breast cancer, esophageal cancer, stomach cancer, colorectal cancer, head and neck cancer, pancreatic cancer, biliary tract cancer, endometrial cancer, urothelial cancer, and kidney cancer are provided in Tables 3-17 [11-15,29,36,37,41-190]. Each table included genes corresponding to levels 1 through 3A.

3. Additional topics

1) Homologous recombination deficiency

Genomic instability is one of the most frequent underlying features of carcinogenesis, and defective DNA repair has been described as a cancer hallmark [191]. HRR is a series of interrelated pathways that function in the repair of DNA double-strand breaks and interstrand crosslinks [192]. Important genes involved in the HRR process include BRCA1, BRCA2, RAD51, RAD51C, RAD51D, ATM, ATR, PALB2, MRE11, NBS1, BARD1, CHEK1, and CHEK2 [193,194]. However, it is essential to note that the list of genes known to be related to the HRR process is continually evolving through ongoing research. A defect in the HRR pathway has been linked to several cancers, including breast, ovarian, prostate and pancreatic cancer [117,142,153,195], and HRD can make tumors more sensitive to platinum-based chemotherapy and PARP inhibitors [196,197]. Thus, it is critical to develop methods for determining the HRD status in order to maximize clinical benefit from these drugs.
There are three main categories of available tests for HRD analyzing (1) the etiology of HRD (mutation/methylation sequencing), (2) the current homologous recombination status (functional assays), and (3) prior HRD exposure (genomic scars). Each type of cancer (ovarian, breast, pancreatic and prostate) requires different tests. The germline BRCA 1/2 mutation test is useful for predicting response to PARP inhibitors in ovarian and breast cancer [76,143-146,198]. In ovarian cancer, tumor (incorporating germline and somatic) as well as somatic BRCA 1/2 mutation testing exhibit good clinical validity by reliably identifying the subset of patients who benefit from PARP inhibitor therapy [146-148]. Evidence regarding the benefit of mutation tests for each non-BRCA HRR gene for predicting responses to PARP inhibitors remains insufficient in ovarian cancer. HRD tests using genomic instability scores (GIS) or loss of heterozygosity (LOH) scores are useful for predicting the responses to PARP inhibitors in ovarian cancer patients without BRCA 1/2 mutation [142,144,146]. The GIS from myChoice CDx (Myriad Genetics) represents the sum of LOH, large-scale transitions, and telomeric allelic imbalance and a GIS of 42 has been established as the threshold to determine HRD positivity [199,200]. To date, GIS is the only genomic scar assay that has been evaluated in first-line randomized controlled trials for ovarian cancer [142,143]. The LOH test (FoundationOne CDx, Foundation Medicine) uses NGS to determine the percentage of genomic LOH and LOH-high is defined with a cut-off of 16% or higher, referencing The Cancer Genome Atlas data [201]. In metastatic pancreatic cancer, a germline BRCA 1/2 mutation test is recommended to evaluate the potential benefits of PARP inhibitors as maintenance treatment for patients whose tumors have not progressed after first-line platinum-based chemotherapy [117]. In castration-resistant prostate cancer, it is recommended to assess by sequencing for BRCA 1/2 mutations, at a minimum, using germline and/or somatic tumor DNA [153,202]. To date, insufficient evidence is available regarding the benefit of performing a HRD functional assays to predict response to PARP inhibitor; however, the potential for using functional assays in conjunction with HRR gene tests and genomic tests should be evaluated. While there have been multiple NGS assays to evaluate HRD status, only a limited number of tests are clinically accepted, and their technical details including evaluation criteria are unclear. Many methodological approaches have been proposed to measure HRD status using NGS data of various types, including whole genome sequencing (WGS), whole exome sequencing (WES) and targeted sequencing [203,204]. However, the absence of congruent measure remains a challenge to validate their reliability and consistency. Although WGS has not yet been approved for the diagnosis of HRD, it might become a promising diagnostic tool for HRD in the near future.

2) Microsatellite instability-high/mismatch repair deficiency

MSI-H/MMR-D has become an important biomarker of eligibility for immune checkpoint inhibitor (ICI) therapy as the FDA has approved ICIs for patients with unresectable or metastatic MSI-H/MMR-D solid cancers regardless of tumor types [9,40,205]. The polymerase chain reaction (PCR)–based assessment of selected microsatellite loci in a patient’s tumor and matched non-neoplastic tissue had been accepted as the gold standard method before the era of NGS. Nevertheless, the PCR-based MSI test can be misleading in certain cases because the selected microsatellite loci (typically, 5 to 8 loci) may not cover all affected microsatellite regions [206]. Alternatively, MMR-D can be inferred through immunohistochemistry (IHC) of MMR proteins, such as MLH1, MSH2, MSH6, and PMS2, since most MMR-deficient tumors exhibit a loss of MMR protein expression. However, there are limitations to detecting MMR-D by the IHC method. Certain tumors harboring pathogenic missense or in-frame insertion/deletion mutations of MMR genes may still show intact MMR protein expressions, and interpretation errors may occur when the staining quality is poor.
Since NGS is now widely used in clinical practice, it has been investigated whether NGS can be used to detect MSI-H/MMR-D in clinical setting. Numerous validation studies have demonstrated that NGS can accurately detect pathogenic or likely pathogenic mutations affecting MMR genes and can determine MMR-D reliably. Thus, there is a consensus that NGS can replace the standard PCR-based MSI test. NGS can detect MSI-H/MMR-D in various ways [207]. Several computational tools for detection of MSI-H/MMR-D using NGS data are available: mSINGS [208], MSIsensor [209], MANTIS [210], and MOSAIC [211]. Furthermore, NGS can detect MSI-H/MMR-D even in the absence of the patient’s matched normal tissue [212,213]. Furthermore, pathogenic or likely pathogenic MMR gene mutations detected by NGS testing may select candidates of germline genetic testing for Lynch syndrome. Finally, NGS-based MSI-H/MMR-D testing may provide information about eligibility for immunotherapy in tumor types where MMR IHC and/or PCR-based MSI tests have not been done during routine clinical practice.

3) Analysis of TMB by NGS panel

ICIs can enhance a durable anti-tumor immune response and prolong overall survival [214]. However, only a subset of the patients showed a dramatic response to immunotherapy, and the identification of predictive biomarkers was essential to identify responders to immunotherapy, such as programmed death-ligand 1 expression, MSI-H/MMR-D and TMB-H [215-217]. TMB is defined as the number of somatic mutations (mut) per megabase (Mb) of genomic sequence [217]. TMB is a surrogate marker for making immunogenic neopeptides shown on the surface of tumor cells by major histocompatibility complexes, which affect the anti-tumor immune response to ICIs [218,219].
In June 2020, the FDA authorized pembrolizumab for the treatment of adult and pediatric patients with unresectable or metastatic TMB-H (≥ 10 mut/Mb) solid tumors, as determined by FoundationOneCDx assay, that have progressed following prior treatment and who have no satisfactory alternative treatment options [220]. Therefore, determining the TMB value and identifying TMB-H tumors are among the most critical aspects in the clinical NGS analysis.
Although the TMB calculation can vary according to the test assays, the gold standard method for TMB estimation is WES with tumor tissues and matched normal samples. However, since WES has limitations in terms of time and costs to apply in clinical use, analytic methods and algorithms have been developed for calculating TMB from clinical targeted NGS panel tests [221,222]. Targeted NGS panel tests usually cover only a small limited size (about 1 to 2 Mb) of exonic regions, so sophisticated bioinformatic algorithms and statistical methods must be applied to filter out noise variants and artifacts caused by formalin-fixed tissues. For tumor-only sequencing, which is currently conducted in most targeted gene panels in Korea, germline variants are filtered out using genomic information from public databases or data on allele frequency in normal populations to avoid TMB overestimation. In several studies, the evaluated TMB from targeted NGS panel testing showed a high correlation with the TMB calculated by WES using analytic techniques [221,222].
Since the targeted gene panels currently used in the clinic have different analysis pipelines for variant calling and apply various filtering criteria to select variants used in TMB calculation, TMB values vary among the tests, and the criteria for TMB-H are diverse [223]. Also, the distribution of TMB values and criteria for TMB-H are different by tumor type, even when calculating TMB with the same panel. In general, more than TMB of 10 mut/Mb has been used for the definition of TMB-H tumors, but the reliable value of TMB-H can be different among the test panels and requires caution in interpreting the estimated TMB value. In some studies, the TMB of 17-20 mut/Mb is considered TMB-H and a candidate for immunotherapy conservatively [224]. Therefore, standardization of TMB analysis among test panels, validation of TMB-H tumors with different assays, and establishing reliable criteria for TMB-H will be needed for the further precise application of TMB analysis with the clinical tumor NGS panels.

4) Clinical utility and limitations of ctDNA-based genetic panel tests using blood sample

As the growing number of druggable oncogenic drivers has been identified in solid cancer [225], ctDNA-based approach can be used as an alternative approach for facilitating the identification of tumor tissue genotype. However, ctDNA can be influenced by multiple preanalytical factors and the methodology of analysis [226]. Since the ctDNA detection rate is highly related to tumor burden and is affected by various factors such as plasma levels of ctDNA, assay sensitivity, and tumor biology, a negative result from the ctDNA test may not necessarily indicate a true negative. In particular, low analytical sensitivity may occur because ctDNA assay are performed solely on DNA derived from tumor cells [227]. Recent studies have reported that gene fusions and splice variants have higher detection rates when sequencing is performed with RNA transcripts [228,229]. In addition, in the case of copy number variations (CNVs), determining the presence of CNVs remains challenging due to its dependence on ctDNA fractions [230,231]. Hence, ctDNA-based test reports should include essential elements, including pre-analytical elements, sequencing results, potential factors related to the germline variants, and limitations of assays to assist the interpretation of the report to the clinician [232].
ctDNA-based genotyping can be used as either complementary to tissue genotyping or as the first choice in certain circumstances. ctDNA-based genotyping has advantages over tissue-based genotyping in a short turnaround time, invasiveness, and feasibility in serial assessment [233-235]. Due to the limitation of tissue-based genotyping, which can be affected by tissue accessibility or tumor purity, ctDNA-based genotyping can be conducted as initial genotyping in the rapidly growing aggressive tumor when challenges or delays in sample acquisition are anticipated. In addition, the ctDNA-based genotyping first approach can be preferred for the evaluation of emerged resistance mechanism [236]. ctDNA-based genotyping can also be used as a complementary method, either concurrently or sequentially with tissue-based genotyping in case of incomplete tumor genotyping or foreseen inadequate results due to uncertain adequacy of tissue [237].
Before genotyping ctDNA sequences, the concentration of cell-free DNA in plasma can be used as a prognostic biomarker [238,239]. The sensitivity of ctDNA assay varies among the primary sites and tumor types and should be considered at applying ctDNA test in clinical use [240]. Similarly, the metastatic site of the tumor affects the ctDNA detection and should be taken into account for using ctDNA assay [241]. Additionally, MSI-H/MMR-D and TMB-H, as determined by ctDNA assay, have been widely studied [242-244]. Improving the accuracy of the MSI detection and TMB calculation from ctDNA and defining reliable criteria for MSI-H/MMR-D and TMB-H in the ctDNA assay is anticipated to broaden the use of ctDNA tests.

Conclusion

NGS-based genetic testing has become an essential tool in treating patients with advanced solid cancers. This report provides clinical recommendations for the application of NGS in such patients, offering expert opinions on its diagnostic uses, and gene classification in accordance with K-CAT, while taking the domestic Korean context into consideration.
As cancer genomics advances and new therapies emerge, the current gene classification is subject to dynamic changes, and the application of NGS is anticipated to continuously evolve. Consequently, healthcare providers and researchers are encouraged to stay abreast of the latest advancements in the field of precision oncology to ensure optimal patient care and further cancer research.

Notes

Author Contributions

Conceived and designed the analysis: Kim M, Kim JH (Jee Hyun Kim), Kim WS.

Collected the data: Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH (Jee Hung Kim), Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yung H, Lee S, Kim JH (Jee Hyun Kim), Kim SW.

Contributed data or analysis tools: Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH (Jee Hung Kim), Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yung H, Lee S, Kim JH (Jee Hyun Kim), Kim SW.

Performed the analysis: Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH (Jee Hung Kim), Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yung H, Lee S, Kim JH (Jee Hyun Kim), Kim SW.

Wrote the paper: Kim M, Shim HS, Kim S, Lee IH, Kim J, Yoon S, Kim HD, Park I, Jeong JH, Yoo C, Cheon J, Kim IH, Lee J, Hong SH, Park S, Jung HA, Kim JW, Kim HJ, Cha Y, Lim SM, Kim HS, Lee CK, Kim JH (Jee Hung Kim), Chun SH, Yun J, Park SY, Lee HS, Cho YM, Nam SJ, Na K, Yoon SO, Lee A, Jang KT, Yung H, Lee S, Kim JH (Jee Hyun Kim), Kim SW.

Conflicts of Interest

Conflict of interest relevant to this article was not reported.

Acknowledgments

This study was supported by the National R&D Program for Cancer Control through the National Cancer Center (NCC) funded by the Ministry of Health & Welfare, Republic of Korea (HA22C0052).

Table 1.
KPMNG scale of clinical actionability of molecular target (K-CAT) [1]
Level Clinical implication Required level of evidence
1 Treatment should be considered standard of care MFDS, FDA, EMA or equivalent-approved drug OR Prospective, randomized, phase III trials showing the benefit of survival endpoints
2 Treatment would be considered Prospective phase I/II trials show clinical benefita)
3 Clinical trials to be discussed with patients A: Retrospective study or case series show potential clinical benefit in a specific tumor type
B: Clinical studies show potential clinical benefit in other indications
4 Preclinical data only, lack of clinical data Preclinical evidence suggests the potential benefit
G Suspicious germline variant on tumor tissue NGS Suggestive actionable germline variant on tumor tissue testing
R Predictive biomarker of resistance FDA-recognized predictive biomarker of resistance

EMA, European Medicines Agency; FDA, U.S. Food and Drug Administration; K-CAT, KPMNG scale of Clinical Actionability of molecular Targets; KPMNG, Korean Precision Medicine Networking Group; MFDS, Ministry of Food and Drug Safety; NGS, next-generation sequencing.

a) Prospective phase I/II trials supporting level 2 targets include clinical trials across tumor types such as basket trials. In this case, the clinical benefit needs to be judged by expert consensus.

Table 2.
List of genetic alterations with tumor agnostic indications by FDA
Gene/Alteration Matched treatment K-CAT Reference
NTRK fusion Entrectinib 1 [19,20]
Larotrectinib
BRAF V600E Dabrafenib+trametinib (except colorectal cancer) 1 [11-17]
RET fusion Selpercatinib 1 [18]
Microsatellite instability–high/Mismatch repair deficiency Pembrolizumab 1 [9,40]
High tumor mutation burden Pembrolizumab 1 [10]

FDA, U.S. Food and Drug Administration; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of mole-cular Targets.

Table 3.
List of genomic alterations level 1/2/3A according to K-CAT in advanced NSCLC
Gene Alteration Prevalence (%) K-CAT Reference
EGFR Exon 19 in-frame deletions, L858R, G719X, L861Q, S761I 30-46 1 [41-45]
T790M 50 of treated EGFR mutant NSCLC 1, R [29,46,47]
Exon 20 in-frame insertion 3 1 [48,49]
BRAF V600E 2-4 1 [12,13,50]
ALK Rearrangement/Fusions 3-5 1 [36,37,51,52]
KRAS G12C 13 1 [53,54]
MET Exon 14 in-frame deletions, Exon 14 splice mutations 3-4 1 [55,56]
Amplification 3-5 2 [56]
RET Rearrangement/Fusions 1.7 1 [57,58]
ROS1 Rearrangement/Fusions 2.6 1 [59,60]
ERBB2 Exon 20 in-frame insertion 2.3 1 [61-64]
Amplification 2.4-38 2 [65,66]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; NSCLC, non–small cell lung cancer.

Table 4.
List of genomic alterations level 1/2/3A according to K-CAT in advanced breast cancer
Gene Alteration Prevalence (%) K-CAT Reference
ERBB2 Amplifications 15-20 1 [67-71]
Oncogenic mutations 4 2 [72,73]
PIK3CAa) Oncogenic mutations 30-40 1 [74,75]
BRCA1/2 Germline oncogenic mutations 4 1 [76,77]
BRCA1/2b) Somatic oncogenic mutationsc) 3 2 [78-80]
PTEN Oncogenic mutations 7 2 [81,82]
ESR1 Oncogenic mutations (mechanism of resistance) 10 R [83]
AKT1 E17K 5 2 [82,84]
PALB2d) Germline oncogenic mutations 0.5-1 2 [79,85]

HRD, homologous recombination deficiency; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; PARP, poly(adenosine diphosphate [ADP]–ribose) polymerase.

a) This applies only to breast cancer that is hormone receptor-positive/HER2-negative and has mutations including E542K, E545A, H1047R, H1047Y, Q546E, H1047L, Q546R, E545G, E545D, E545K, C420R. Other oncogenic mutations not included in this category, caution is needed, since it is unknown whether other mutations are associated with response to phosphoinositide 3-kinase inhibitor therapy,

b) Phase III trials of PARP inhibitors have been conducted in patients with germline BRCA mutations, and their therapeutic effects have been confirmed. In some studies, the effects of PARP inhibitors have also been reported in patients with somatic BRCA mutations, and somatic tumor sequencing can identify many germline BRCA mutations,

c) In addition to BRCA 1/2, there are several other genes associated with homologous recombination deficiency, including ATRX, BLM, BRIP1, CHEK2, FANCA/C/D2/E/F/G/L, MRE11A, NBN, PALB2, and RAD50. Although the discovery frequency of each gene is very low, they are collectively found in approximately 8% of all breast cancers,

d) There are multiple germline mutations associated with HRD in breast cancer patients, but this table only includes the two most frequent ones.

Table 5.
List of genomic alterations level 1/2/3A according to K-CAT in advanced esophageal cancer
Gene Alteration Prevalence (%) K-CAT Reference
ERBB2 Amplification 3.9-10 2 [86]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 6.
List of genomic alterations level 1/2/3A according to K-CAT in advanced stomach cancer
Gene Alteration Prevalence (%) K-CAT Reference
ERBB2 Amplification 15 1 [87-89]
FGFR2a) Amplification 5 2 [90]
MET Amplification 2-5 2 [91]
EGFR Amplification 5-10 3A [92]

ctDNA, circulating tumor DNA; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

a) FGFR2b overexpression or FGFR2 amplification by ctDNA analysis.

Table 7.
List of genomic alterations level 1/2/3A according to K-CAT in advanced colorectal cancer
Gene Alteration Prevalence (%) K-CAT Reference
KRAS Oncogenic mutations 40 R [93,94]
NRAS Oncogenic mutations 3-5 R [95,96]
BRAF V600E 5-10 1 [96-98]
Mismatch repair deficiency MSI-H/MMR-D 4-5 1 [99,100]
ERBB2 Amplification 4-5 1 [101]
KRAS G12C 3 2 [102,103]
POLE Exonuclease domain mutations 1-3 2 [104-106]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; MSI-H, microsatellite instability–high; MMR-D, mismatch repair deficiency.

Table 8.
List of genomic alterations level 1/2/3A according to K-CAT in advanced head and neck cancer
Gene Alteration Prevalence (%)a) K-CAT Reference
NOTCH1, 2, 3 Oncogenic mutations 10-12 2 [107,108]
ERRB2 Amplification 30-40 2 [109-111]
FGFR1, 3 Amplification/Oncogenic mutations 1-7 2 [112-114]
MET Amplification 1 3A [115,116]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

a) The above prevalence is about the representative subtype among various subtypes of head and neck cancer.

Table 9.
List of genomic alterations level 1/2/3A according to K-CAT in advanced pancreatic cancer
Gene Alteration Prevalence (%) K-CAT Reference
BRCA 1/2 Germline oncogenic mutations 1-4 1 [117,118]
PALB2 Oncogenic mutations 0.6 2 [118]
KRAS G12C 2-3 2 [119,120]
PIK3CA Oncogenic mutations 3 3A [121]
ERBB2 Amplifications/Oncogenic mutations 1-2 3A [72,122]
ALK Rearrangement/Fusions < 1 3A [123]
NRG1 Rearrangement/Fusions 1 3A [124]
ROS1 Rearrangement/Fusions < 1 3A [125]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 10.
List of genomic alterations level 1/2/3A according to K-CAT in advanced biliary tract cancer
Gene Alteration Prevalence (%) K-CAT Reference
IDH1 Oncogenic mutations 10-23 1 [126,127]
FGFR2 Rearrangement/Fusions 8-14 1 [128-130]
BRAF V600E 5 1 [14,15]
ERBB2 Amplification 10 2 [131-133]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 11.
List of genomic alterations level 1/2/3A according to K-CAT in advanced endometrial cancer
Gene Alteration Prevalence (%) K-CAT Reference
ERBB2 Amplification 30 of uterine serous carcinoma 2 [134]
AKT1 E17K 2 2 [84]
POLEa) Oncogenic mutations 5-15 NA [135,136]
TP53a),b) Oncogenic mutations 5-15 NA [135]

IHC, immunohistochemistry; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; MMR, mismatch repair; NGS, next-generation sequencing; TCGA, The Cancer Genome Atlas.

a) Adjuvant treatment of endometrial cancer based on molecular classification,

b) Considering the coverage limitations of NGS for detecting p53 loss, a combined IHC approach is recommended. The TCGA approach results in the molecular stratification of endometrial cancer (EC) into four distinct molecular groups [137]; (1) ultramutated [> 100 mut/Mb)] with pathogenic variations in the exonuclease domain of DNA polymerase epsilon (POLE)-ultramutated (POLEmut), (2) hypermutated (10-100 mut/Mb), microsatellite-unstable, (3) somatic copy number-high with frequent pathogenic variants in TP53, and (4) an MMR-proficient, low somatic copy number aberration subgroup with a low mutational burden. Extensive research on these surrogate markers has revealed a strong correlation with clinical outcome, thus proving their prognostic value [138-140]. POLEmut EC had generally has an excellent clinical outcome, while p53-abn EC has the worst, regardless of risk category, type of adjuvant treatment, tumor type, or grade. Adjuvant chemotherapy is beneficial in for patients with p53mut EC, while treatment de-escalation is being explored in patients with POLEmut EC [139], which exhibits a favorable outcome [141]. Consequently, all EC pathology specimens should undergo molecular classification, independent of histological type, using well-established IHC staining for p53 and MMR proteins (MLH1, PMS2, MSH2, MSH6), in conjunction with targeted tumor sequencing (POLE hotspot analysis). While POLE hotspot analysis is currently unavailable in Korea, and most NGS panels include the POLE gene, it has been incorporated into the recommendations. Moreover, since IHC plays a well-established role in identifying p53 mutations and NGS target sequencing of TP53 is insufficient to identify all loss of P53 function, IHC confirmation of p53 is recommended over NGS testing as a priority.

Table 12.
List of genomic alterations level 1/2/3A according to K-CAT in advanced ovarian cancer
Gene Alteration Prevalence (%) K-CAT Reference
BRCA 1/2 Oncogenic mutations 5-15 1 [142-149]
HRD score GIS, LOH 50 1 [142-144,146,148]
AKT1 E17K 2 2 [84]

GIS, genomic instability scores; HRD, homologous recombination deficiency; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; LOH, loss of heterozygosity.

Table 13.
List of genomic alterations level 1/2/3A according to K-CAT in advanced urothelial cancer
Gene Alteration Prevalence (%) K-CAT Reference
FGFR3 Oncogenic mutations 13-15 1 [150]
Rearrangement/Fusions
FGFR2 Rearrangement/Fusions Unknown 1 [150]
ERCC2 Oncogenic mutations 9-12 3A [151,152]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 14.
List of genomic alterations level 1/2/3A according to K-CAT in advanced prostate cancer
Gene Alteration Prevalence (%) K-CAT Reference
BRCA2 Germline and/or somatic oncogenic mutations 3-13 1 [153,154]
BRCA1 Germline and/or somatic oncogenic mutations 1 1 [153,154]
ATM Oncogenic mutations 6-7 1 [153,154]
BRIP1, BARD1, CDK12, CHEK1, CHEK2, FANCL, PALB2, RAD51B, RAD51C, RAD51D, RAD54L Oncogenic mutations < 1-5 1 [153,154]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 15.
List of genomic alterations level 1/2/3A according to K-CAT in advanced kidney cancer
Gene Alteration Prevalence (%) K-CAT Reference
VHL Germline oncogenic mutations 0.2 1 [155]
FH Germline oncogenic mutations 0.5 3A [156,157]
ALK Rearrangement/Fusions 0.3-0.5 3A [158]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 16.
List of genomic alterations level 1/2/3A according to K-CAT in advanced melanoma
Gene Alteration Prevalence (%) K-CAT Reference
BRAF V600E/K 35-50 1 [11,159-162]
V600 (excluding V600E/K) ~5 1 [163]
KIT D579del and 12 other oncogenic mutations 1-7 2 [164,165]
NRAS Oncogenic mutations ~20 2 [166,167]
BRAF Rearrangement/Fusions 3-7 3A [168,169]
K601, L597 < 1 3A [170-173]

K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets.

Table 17.
List of genomic alterations level 1/2/3A according to K-CAT in advanced sarcoma
Gene Alteration Prevalence (%) K-CAT Reference
KIT Oncogenic mutations ~75-80 in GIST 1 [174,175]
PDGFRA Oncogenic mutations ~8-10 in GIST 1 [175-177]
PDGFB Rearrangement/Fusions mostly COL1A1::PDGFB ~90 in DFSP 1 [178-179]
ALK Rearrangement/Fusions ~50 in IMT 1 [180-182]
SMARCB1 Deletion ~83 in ES 2 [183]
IDH1 Oncogenic mutations ~65 in chondrosarcoma 2 [184]
TSC2 Oncogenic mutations ~30 in PEComa 2 [185,186]
MDM2 Amplification ~90 in WDLPS/DDLPS; frequent in IS, low grade OSA 2 [187,188]
CDK4 Amplification ~90 in WDLPS/DDLPS; frequent in IS, low grade OSA 2 [187,189]
MET Oncogenic mutations, Rearrangement/Fusions, Amplification < 1 2 [190]

DFSP, dermatofibrosarcoma protuberans; ES, epithelioid sarcoma; GIST, gastrointestinal stromal tumor; IMT, inflammatory myofibroblastic tumor; IS, intimal sarcoma; K-CAT, Korean Precision Medicine Networking Group scale of Clinical Actionability of molecular Targets; OSA, osteosarcoma; WDLPS/DDLPS, well-differentiated/de-differentiated liposarcoma.

References

1. Yoon S, Kim M, Hong YS, Kim HS, Kim ST, Kim J, et al. Recommendations for the use of next-generation sequencing and the molecular tumor board for patients with advanced cancer: a report from KSMO and KCSG Precision Medicine Networking Group. Cancer Res Treat. 2022;54:1–9.
crossref pmid pmc pdf
2. Zehir A, Benayed R, Shah RH, Syed A, Middha S, Kim HR, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23:703–13.
pmid pmc
3. Tsimberidou AM, Hong DS, Ye Y, Cartwright C, Wheler JJ, Falchook GS, et al. Initiative for Molecular Profiling and Advanced Cancer Therapy (IMPACT): an MD Anderson precision medicine study. JCO Precis Oncol. 2017;2017:PO.17.00002.
crossref pmid pmc
4. Massard C, Michiels S, Ferte C, Le Deley MC, Lacroix L, Hollebecque A, et al. High-throughput genomics and clinical outcome in hard-to-treat advanced cancers: results of the MOSCATO 01 trial. Cancer Discov. 2017;7:586–95.
crossref pmid pdf
5. Cousin S, Grellety T, Toulmonde M, Auzanneau C, Khalifa E, Laizet Y, et al. Clinical impact of extensive molecular profiling in advanced cancer patients. J Hematol Oncol. 2017;10:45.
crossref pmid pmc pdf
6. Tsimberidou AM, Wen S, Hong DS, Wheler JJ, Falchook GS, Fu S, et al. Personalized medicine for patients with advanced cancer in the phase I program at MD Anderson: validation and landmark analyses. Clin Cancer Res. 2014;20:4827–36.
crossref pmid pmc pdf
7. Andre F, Filleron T, Kamal M, Mosele F, Arnedos M, Dalenc F, et al. Genomics to select treatment for patients with metastatic breast cancer. Nature. 2022;610:343–8.
crossref pmid pdf
8. Ettinger DS, Wood DE, Aisner DL, Akerley W, Bauman JR, Bharat A, et al. Non-small cell lung cancer, version 3.2022, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw. 2022;20:497–530.
pmid
9. Marabelle A, Le DT, Ascierto PA, Di Giacomo AM, De Jesus-Acosta A, Delord JP, et al. Efficacy of pembrolizumab in patients with noncolorectal high microsatellite instability/mismatch repair-deficient cancer: results from the phase II KEYNOTE-158 study. J Clin Oncol. 2020;38:1–10.
pmid
10. Marabelle A, Fakih M, Lopez J, Shah M, Shapira-Frommer R, Nakagawa K, et al. Association of tumour mutational burden with outcomes in patients with advanced solid tumours treated with pembrolizumab: prospective biomarker analysis of the multicohort, open-label, phase 2 KEYNOTE-158 study. Lancet Oncol. 2020;21:1353–65.
crossref pmid
11. Robert C, Karaszewska B, Schachter J, Rutkowski P, Mackiewicz A, Stroiakovski D, et al. Improved overall survival in melanoma with combined dabrafenib and trametinib. N Engl J Med. 2015;372:30–9.
crossref pmid
12. Planchard D, Besse B, Groen HJ, Souquet PJ, Quoix E, Baik CS, et al. Dabrafenib plus trametinib in patients with previously treated BRAF(V600E)-mutant metastatic non-small cell lung cancer: an open-label, multicentre phase 2 trial. Lancet Oncol. 2016;17:984–93.
crossref pmid pmc
13. Planchard D, Smit EF, Groen HJ, Mazieres J, Besse B, Helland A, et al. Dabrafenib plus trametinib in patients with previously untreated BRAF(V600E)-mutant metastatic non-small-cell lung cancer: an open-label, phase 2 trial. Lancet Oncol. 2017;18:1307–16.
crossref pmid
14. Subbiah V, Lassen U, Elez E, Italiano A, Curigliano G, Javle M, et al. Dabrafenib plus trametinib in patients with BRAF(V600E)-mutated biliary tract cancer (ROAR): a phase 2, open-label, single-arm, multicentre basket trial. Lancet Oncol. 2020;21:1234–43.
crossref pmid
15. Salama AK, Li S, Macrae ER, Park JI, Mitchell EP, Zwiebel JA, et al. Dabrafenib and trametinib in patients with tumors with BRAF(V600E) mutations: results of the NCI-MATCH trial subprotocol H. J Clin Oncol. 2020;38:3895–904.
crossref pmid pmc
16. Wen PY, Stein A, van den Bent M, De Greve J, Wick A, de Vos F, et al. Dabrafenib plus trametinib in patients with BRAF(V600E)-mutant low-grade and high-grade glioma (ROAR): a multicentre, open-label, single-arm, phase 2, basket trial. Lancet Oncol. 2022;23:53–64.
crossref pmid
17. Subbiah V, Kreitman RJ, Wainberg ZA, Cho JY, Schellens JHM, Soria JC, et al. Dabrafenib plus trametinib in patients with BRAF V600E-mutant anaplastic thyroid cancer: updated analysis from the phase II ROAR basket study. Ann Oncol. 2022;33:406–15.
crossref pmid pmc
18. Subbiah V, Wolf J, Konda B, Kang H, Spira A, Weiss J, et al. Tumour-agnostic efficacy and safety of selpercatinib in patients with RET fusion-positive solid tumours other than lung or thyroid tumours (LIBRETTO-001): a phase 1/2, openlabel, basket trial. Lancet Oncol. 2022;23:1261–73.
crossref pmid
19. Drilon A, Laetsch TW, Kummar S, DuBois SG, Lassen UN, Demetri GD, et al. Efficacy of larotrectinib in TRK fusion-positive cancers in adults and children. N Engl J Med. 2018;378:731–9.
pmid pmc
20. Doebele RC, Drilon A, Paz-Ares L, Siena S, Shaw AT, Farago AF, et al. Entrectinib in patients with advanced or metastatic NTRK fusion-positive solid tumours: integrated analysis of three phase 1-2 trials. Lancet Oncol. 2020;21:271–82.
crossref pmid
21. Chakravarty D, Gao J, Phillips SM, Kundra R, Zhang H, Wang J, et al. OncoKB: a precision oncology knowledge base. JCO Precis Oncol. 2017;2017:PO.17.00011.
pmid
22. McConnell L, Houghton O, Stewart P, Gazdova J, Srivastava S, Kim C, et al. A novel next generation sequencing approach to improve sarcoma diagnosis. Mod Pathol. 2020;33:1350–9.
crossref pmid pdf
23. Szurian K, Kashofer K, Liegl-Atzwanger B. Role of next-generation sequencing as a diagnostic tool for the evaluation of bone and soft-tissue tumors. Pathobiology. 2017;84:323–38.
crossref pmid pdf
24. Gounder MM, Agaram NP, Trabucco SE, Robinson V, Ferraro RA, Millis SZ, et al. Clinical genomic profiling in the management of patients with soft tissue and bone sarcoma. Nat Commun. 2022;13:3406.
pmid pmc
25. Moch H, Amin MB, Berney DM, Comperat EM, Gill AJ, Hartmann A, et al. The 2022 World Health Organization classification of tumours of the urinary system and male genital organs-part A: renal, penile, and testicular tumours. Eur Urol. 2022;82:458–68.
crossref pmid
26. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131:803–20.
crossref pmid pdf
27. Louis DN, Aldape K, Brat DJ, Capper D, Ellison DW, Hawkins C, et al. Announcing cIMPACT-NOW: the consortium to inform molecular and practical approaches to CNS tumor taxonomy. Acta Neuropathol. 2017;133:1–3.
crossref pmid pdf
28. WHO classification of tumours of the central nervous system tumours. 5th ed. Lyon: International Agency for Research on Cancer; 2021.

29. Mok TS, Wu YL, Ahn MJ, Garassino MC, Kim HR, Ramalingam SS, et al. Osimertinib or platinum-pemetrexed in EGFR T790M-positive lung cancer. N Engl J Med. 2017;376:629–40.
crossref pmid pmc
30. Janne PA, Yang JC, Kim DW, Planchard D, Ohe Y, Ramalingam SS, et al. AZD9291 in EGFR inhibitor-resistant nonsmall-cell lung cancer. N Engl J Med. 2015;372:1689–99.
crossref pmid
31. Westover D, Zugazagoitia J, Cho BC, Lovly CM, Paz-Ares L. Mechanisms of acquired resistance to first- and second-generation EGFR tyrosine kinase inhibitors. Ann Oncol. 2018;29:i10–9.
crossref pmid pmc
32. Wang Z, Xing Y, Li B, Li X, Liu B, Wang Y. Molecular pathways, resistance mechanisms and targeted interventions in non-small-cell lung cancer. Mol Biomed. 2022;3:42.
crossref pmid pmc pdf
33. He J, Zhou Z, Sun X, Yang Z, Zheng P, Xu S, et al. The new opportunities in medicinal chemistry of fourth-generation EGFR inhibitors to overcome C797S mutation. Eur J Med Chem. 2021;210:112995.
crossref pmid
34. Coleman N, Hong L, Zhang J, Heymach J, Hong D, Le X. Beyond epidermal growth factor receptor: MET amplification as a general resistance driver to targeted therapy in oncogene-driven non-small-cell lung cancer. ESMO Open. 2021;6:100319.
crossref pmid pmc
35. Soda M, Choi YL, Enomoto M, Takada S, Yamashita Y, Ishikawa S, et al. Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature. 2007;448:561–6.
crossref pmid pdf
36. Peters S, Camidge DR, Shaw AT, Gadgeel S, Ahn JS, Kim DW, et al. Alectinib versus crizotinib in untreated ALK-positive non-small-cell lung cancer. N Engl J Med. 2017;377:829–38.
crossref pmid
37. Camidge DR, Kim HR, Ahn MJ, Yang JC, Han JY, Lee JS, et al. Brigatinib versus crizotinib in ALK-positive non-small-cell lung cancer. N Engl J Med. 2018;379:2027–39.
pmid
38. Shiba-Ishii A, Johnson TW, Dagogo-Jack I, Mino-Kenudson M, Johnson TR, Wei P, et al. Analysis of lorlatinib analogs reveals a roadmap for targeting diverse compound resistance mutations in ALK-positive lung cancer. Nat Cancer. 2022;3:710–22.
crossref pmid pmc pdf
39. Yun MR, Kim DH, Kim SY, Joo HS, Lee YW, Choi HM, et al. Repotrectinib exhibits potent antitumor activity in treatment-naive and solvent-front-mutant ROS1-rearranged nonsmall cell lung cancer. Clin Cancer Res. 2020;26:3287–95.
pmid pmc
40. Le DT, Kim TW, Van Cutsem E, Geva R, Jager D, Hara H, et al. Phase II open-label study of pembrolizumab in treatment-refractory, microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer: KEYNOTE-164. J Clin Oncol. 2020;38:11–9.
crossref pmid pmc
41. Mok TS, Wu YL, Thongprasert S, Yang CH, Chu DT, Saijo N, et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N Engl J Med. 2009;361:947–57.
crossref pmid
42. Rosell R, Carcereny E, Gervais R, Vergnenegre A, Massuti B, Felip E, et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 2012;13:239–46.
pmid
43. Wu YL, Cheng Y, Zhou X, Lee KH, Nakagawa K, Niho S, et al. Dacomitinib versus gefitinib as first-line treatment for patients with EGFR-mutation-positive non-small-cell lung cancer (ARCHER 1050): a randomised, open-label, phase 3 trial. Lancet Oncol. 2017;18:1454–66.
crossref pmid
44. Soria JC, Ohe Y, Vansteenkiste J, Reungwetwattana T, Chewaskulyong B, Lee KH, et al. Osimertinib in untreated EGFR-mutated advanced non-small-cell lung cancer. N Engl J Med. 2018;378:113–25.
pmid
45. Cho BC, Han JY, Kim SW, Lee KH, Cho EK, Lee YG, et al. A phase 1/2 study of lazertinib 240 mg in patients with advanced EGFR T790M-positive NSCLC after previous EGFR tyrosine kinase inhibitors. J Thorac Oncol. 2022;17:558–67.
crossref pmid
46. Yun CH, Mengwasser KE, Toms AV, Woo MS, Greulich H, Wong KK, et al. The T790M mutation in EGFR kinase causes drug resistance by increasing the affinity for ATP. Proc Natl Acad Sci U S A. 2008;105:2070–5.
crossref pmid pmc
47. Cross DA, Ashton SE, Ghiorghiu S, Eberlein C, Nebhan CA, Spitzler PJ, et al. AZD9291, an irreversible EGFR TKI, overcomes T790M-mediated resistance to EGFR inhibitors in lung cancer. Cancer Discov. 2014;4:1046–61.
crossref pmid pmc pdf
48. Zhou C, Ramalingam SS, Kim TM, Kim SW, Yang JC, Riely GJ, et al. Treatment outcomes and safety of mobocertinib in platinum-pretreated patients with EGFR exon 20 insertionpositive metastatic non-small cell lung cancer: a phase 1/2 open-label nonrandomized clinical trial. JAMA Oncol. 2021;7:e214761
crossref pmid pmc
49. Park K, Haura EB, Leighl NB, Mitchell P, Shu CA, Girard N, et al. Amivantamab in EGFR exon 20 insertion-mutated non-small-cell lung cancer progressing on platinum chemotherapy: initial results from the CHRYSALIS phase I study. J Clin Oncol. 2021;39:3391–402.
pmid pmc
50. Planchard D, Kim TM, Mazieres J, Quoix E, Riely G, Barlesi F, et al. Dabrafenib in patients with BRAF(V600E)-positive advanced non-small-cell lung cancer: a single-arm, multicentre, open-label, phase 2 trial. Lancet Oncol. 2016;17:642–50.
crossref pmid pmc
51. Soria JC, Tan DS, Chiari R, Wu YL, Paz-Ares L, Wolf J, et al. First-line ceritinib versus platinum-based chemotherapy in advanced ALK-rearranged non-small-cell lung cancer (ASCEND-4): a randomised, open-label, phase 3 study. Lancet. 2017;389:917–29.
crossref pmid
52. Shaw AT, Bauer TM, de Marinis F, Felip E, Goto Y, Liu G, et al. First-line lorlatinib or crizotinib in advanced ALK-positive lung cancer. N Engl J Med. 2020;383:2018–29.
crossref pmid
53. Janne PA, Riely GJ, Gadgeel SM, Heist RS, Ou SI, Pacheco JM, et al. Adagrasib in non-small-cell lung cancer harboring a KRAS(G12C) mutation. N Engl J Med. 2022;387:120–31.
crossref pmid
54. Skoulidis F, Li BT, Dy GK, Price TJ, Falchook GS, Wolf J, et al. Sotorasib for lung cancers with KRAS p.G12C mutation. N Engl J Med. 2021;384:2371–81.
crossref pmid pmc
55. Paik PK, Felip E, Veillon R, Sakai H, Cortot AB, Garassino MC, et al. Tepotinib in non-small-cell lung cancer with MET exon 14 skipping mutations. N Engl J Med. 2020;383:931–43.
pmid pmc
56. Wolf J, Seto T, Han JY, Reguart N, Garon EB, Groen HJ, et al. Capmatinib in MET exon 14-mutated or MET-amplified nonsmall-cell lung cancer. N Engl J Med. 2020;383:944–57.
pmid
57. Drilon A, Oxnard GR, Tan DS, Loong HH, Johnson M, Gainor J, et al. Efficacy of selpercatinib in RET fusion-positive non-small-cell lung cancer. N Engl J Med. 2020;383:813–24.
pmid pmc
58. Gainor JF, Curigliano G, Kim DW, Lee DH, Besse B, Baik CS, et al. Pralsetinib for RET fusion-positive non-small-cell lung cancer (ARROW): a multi-cohort, open-label, phase 1/2 study. Lancet Oncol. 2021;22:959–69.
crossref pmid
59. Shaw AT, Riely GJ, Bang YJ, Kim DW, Camidge DR, Solomon BJ, et al. Crizotinib in ROS1-rearranged advanced non-small-cell lung cancer (NSCLC): updated results, including overall survival, from PROFILE 1001. Ann Oncol. 2019;30:1121–6.
crossref pmid pmc pdf
60. Drilon A, Siena S, Dziadziuszko R, Barlesi F, Krebs MG, Shaw AT, et al. Entrectinib in ROS1 fusion-positive nonsmall-cell lung cancer: integrated analysis of three phase 1-2 trials. Lancet Oncol. 2020;21:261–70.
pmid
61. Mazieres J, Lafitte C, Ricordel C, Greillier L, Negre E, Zalcman G, et al. Combination of trastuzumab, pertuzumab, and docetaxel in patients with advanced non-small-cell lung cancer harboring HER2 mutations: results from the IFCT-1703 R2D2 trial. J Clin Oncol. 2022;40:719–28.
crossref pmid
62. Li BT, Smit EF, Goto Y, Nakagawa K, Udagawa H, Mazieres J, et al. Trastuzumab deruxtecan in HER2-mutant non-smallcell lung cancer. N Engl J Med. 2022;386:241–51.
pmid
63. Le X, Cornelissen R, Garassino M, Clarke JM, Tchekmedyian N, Goldman JW, et al. Poziotinib in non-small-cell lung cancer harboring HER2 exon 20 insertion mutations after prior therapies: ZENITH20-2 trial. J Clin Oncol. 2022;40:710–8.
crossref pmid pmc
64. Iwama E, Zenke Y, Sugawara S, Daga H, Morise M, Yanagitani N, et al. Trastuzumab emtansine for patients with nonsmall cell lung cancer positive for human epidermal growth factor receptor 2 exon-20 insertion mutations. Eur J Cancer. 2022;162:99–106.
crossref pmid
65. Peters S, Stahel R, Bubendorf L, Bonomi P, Villegas A, Kowalski DM, et al. Trastuzumab emtansine (T-DM1) in patients with previously treated HER2-overexpressing metastatic non-small cell lung cancer: efficacy, safety, and biomarkers. Clin Cancer Res. 2019;25:64–72.
crossref pmid pdf
66. Yang G, Xu H, Yang Y, Zhang S, Xu F, Hao X, et al. Pyrotinib combined with apatinib for targeting metastatic non-small cell lung cancer with HER2 alterations: a prospective, openlabel, single-arm phase 2 study (PATHER2). BMC Med. 2022;20:277.
crossref pmid pmc pdf
67. Slamon DJ, Leyland-Jones B, Shak S, Fuchs H, Paton V, Bajamonde A, et al. Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N Engl J Med. 2001;344:783–92.
crossref pmid
68. Verma S, Miles D, Gianni L, Krop IE, Welslau M, Baselga J, et al. Trastuzumab emtansine for HER2-positive advanced breast cancer. N Engl J Med. 2012;367:1783–91.
crossref pmid pmc
69. Krop IE, Kim SB, Gonzalez-Martin A, LoRusso PM, Ferrero JM, Smitt M, et al. Trastuzumab emtansine versus treatment of physician’s choice for pretreated HER2-positive advanced breast cancer (TH3RESA): a randomised, open-label, phase 3 trial. Lancet Oncol. 2014;15:689–99.
crossref pmid
70. Swain SM, Baselga J, Kim SB, Ro J, Semiglazov V, Campone M, et al. Pertuzumab, trastuzumab, and docetaxel in HER2-positive metastatic breast cancer. N Engl J Med. 2015;372:724–34.
crossref pmid pmc
71. Murthy RK, Loi S, Okines A, Paplomata E, Hamilton E, Hurvitz SA, et al. Tucatinib, trastuzumab, and capecitabine for HER2-positive metastatic breast cancer. N Engl J Med. 2020;382:597–609.
pmid
72. Hyman DM, Piha-Paul SA, Won H, Rodon J, Saura C, Shapiro GI, et al. HER kinase inhibition in patients with HER2- and HER3-mutant cancers. Nature. 2018;554:189–94.
crossref pmid pmc pdf
73. Smyth LM, Piha-Paul SA, Won HH, Schram AM, Saura C, Loi S, et al. Efficacy and determinants of response to HER kinase inhibition in HER2-mutant metastatic breast cancer. Cancer Discov. 2020;10:198–213.
crossref pmid pmc pdf
74. Andre F, Ciruelos E, Rubovszky G, Campone M, Loibl S, Rugo HS, et al. Alpelisib for PIK3CA-mutated, hormone receptor-positive advanced breast cancer. N Engl J Med. 2019;380:1929–40.
pmid
75. Rugo HS, Lerebours F, Ciruelos E, Drullinsky P, Ruiz-Borrego M, Neven P, et al. Alpelisib plus fulvestrant in PIK3CAmutated, hormone receptor-positive advanced breast cancer after a CDK4/6 inhibitor (BYLieve): one cohort of a phase 2, multicentre, open-label, non-comparative study. Lancet Oncol. 2021;22:489–98.
crossref pmid
76. Robson M, Im SA, Senkus E, Xu B, Domchek SM, Masuda N, et al. Olaparib for metastatic breast cancer in patients with a germline BRCA mutation. N Engl J Med. 2017;377:523–33.
pmid
77. Litton JK, Rugo HS, Ettl J, Hurvitz SA, Goncalves A, Lee KH, et al. Talazoparib in patients with advanced breast cancer and a germline BRCA mutation. N Engl J Med. 2018;379:753–63.
crossref pmid pmc
78. Balasubramaniam S, Beaver JA, Horton S, Fernandes LL, Tang S, Horne HN, et al. FDA approval summary: rucaparib for the treatment of patients with deleterious BRCA mutation-associated advanced ovarian cancer. Clin Cancer Res. 2017;23:7165–70.
crossref pmid pdf
79. Tung NM, Robson ME, Ventz S, Santa-Maria CA, Nanda R, Marcom PK, et al. TBCRC 048: phase II study of olaparib for metastatic breast cancer and mutations in homologous recombination-related genes. J Clin Oncol. 2020;38:4274–82.
crossref pmid
80. Gennari A, Andre F, Barrios CH, Cortes J, de Azambuja E, DeMichele A, et al. ESMO Clinical Practice Guideline for the diagnosis, staging and treatment of patients with metastatic breast cancer. Ann Oncol. 2021;32:1475–95.
crossref pmid
81. Schmid P, Abraham J, Chan S, Wheatley D, Brunt AM, Nemsadze G, et al. Capivasertib plus paclitaxel versus placebo plus paclitaxel as first-line therapy for metastatic triple-negative breast cancer: the PAKT trial. J Clin Oncol. 2020;38:423–33.
crossref pmid
82. Howell SJ, Casbard A, Carucci M, Ingarfield K, Butler R, Morgan S, et al. Fulvestrant plus capivasertib versus placebo after relapse or progression on an aromatase inhibitor in metastatic, oestrogen receptor-positive, HER2-negative breast cancer (FAKTION): overall survival, updated progression-free survival, and expanded biomarker analysis from a randomised, phase 2 trial. Lancet Oncol. 2022;23:851–64.
crossref pmid pmc
83. Bidard FC, Kaklamani VG, Neven P, Streich G, Montero AJ, Forget F, et al. Elacestrant (oral selective estrogen receptor degrader) versus standard endocrine therapy for estrogen receptor-positive, human epidermal growth factor receptor 2-negative advanced breast cancer: results from the randomized phase III EMERALD trial. J Clin Oncol. 2022;40:3246–56.
pmid pmc
84. Hyman DM, Smyth LM, Donoghue MT, Westin SN, Bedard PL, Dean EJ, et al. AKT inhibition in solid tumors with AKT1 mutations. J Clin Oncol. 2017;35:2251–9.
crossref pmid pmc
85. Kuemmel S, Harrach H, Schmutzler RK, Kostara A, Ziegler-Lohr K, Dyson MH, et al. Olaparib for metastatic breast cancer in a patient with a germline PALB2 variant. NPJ Breast Cancer. 2020;6:31.
crossref pmid pmc pdf
86. Janjigian YY, Maron SB, Chatila WK, Millang B, Chavan SS, Alterman C, et al. First-line pembrolizumab and trastuzumab in HER2-positive oesophageal, gastric, or gastrooesophageal junction cancer: an open-label, single-arm, phase 2 trial. Lancet Oncol. 2020;21:821–31.
crossref pmid pmc
87. Bang YJ, Van Cutsem E, Feyereislova A, Chung HC, Shen L, Sawaki A, et al. Trastuzumab in combination with chemotherapy versus chemotherapy alone for treatment of HER2-positive advanced gastric or gastro-oesophageal junction cancer (ToGA): a phase 3, open-label, randomised controlled trial. Lancet. 2010;376:687–97.
pmid
88. Shitara K, Bang YJ, Iwasa S, Sugimoto N, Ryu MH, Sakai D, et al. Trastuzumab deruxtecan in previously treated HER2-positive gastric cancer. N Engl J Med. 2020;382:2419–30.
crossref pmid
89. Chung HC, Bang YJ, Fuchs CS, Qin SK, Satoh T, Shitara K, et al. First-line pembrolizumab/placebo plus trastuzumab and chemotherapy in HER2-positive advanced gastric cancer: KEYNOTE-811. Future Oncol. 2021;17:491–501.
crossref pmid pmc
90. Wainberg ZA, Enzinger PC, Kang YK, Qin S, Yamaguchi K, Kim IH, et al. Bemarituzumab in patients with FGFR2bselected gastric or gastro-oesophageal junction adenocarcinoma (FIGHT): a randomised, double-blind, placebo-controlled, phase 2 study. Lancet Oncol. 2022;23:1430–40.
crossref pmid
91. Lee J, Kim ST, Kim K, Lee H, Kozarewa I, Mortimer PG, et al. Tumor genomic profiling guides patients with metastatic gastric cancer to targeted treatment: the VIKTORY Umbrella trial. Cancer Discov. 2019;9:1388–405.
crossref pmid pdf
92. Maron SB, Moya S, Morano F, Emmett MJ, Chou JF, Sabwa S, et al. Epidermal growth factor receptor inhibition in epidermal growth factor receptor-amplified gastroesophageal cancer: retrospective global experience. J Clin Oncol. 2022;40:2458–67.
crossref pmid pmc
93. Karapetis CS, Khambata-Ford S, Jonker DJ, O’Callaghan CJ, Tu D, Tebbutt NC, et al. K-ras mutations and benefit from cetuximab in advanced colorectal cancer. N Engl J Med. 2008;359:1757–65.
crossref pmid
94. Van Cutsem E, Kohne CH, Hitre E, Zaluski J, Chang Chien CR, Makhson A, et al. Cetuximab and chemotherapy as initial treatment for metastatic colorectal cancer. N Engl J Med. 2009;360:1408–17.
crossref pmid
95. Douillard JY, Oliner KS, Siena S, Tabernero J, Burkes R, Barugel M, et al. Panitumumab-FOLFOX4 treatment and RAS mutations in colorectal cancer. N Engl J Med. 2013;369:1023–34.
crossref pmid
96. Van Cutsem E, Lenz HJ, Kohne CH, Heinemann V, Tejpar S, Melezinek I, et al. Fluorouracil, leucovorin, and irinotecan plus cetuximab treatment and RAS mutations in colorectal cancer. J Clin Oncol. 2015;33:692–700.
crossref pmid
97. Kopetz S, Grothey A, Yaeger R, Van Cutsem E, Desai J, Yoshino T, et al. Encorafenib, binimetinib, and cetuximab in BRAF V600E-mutated colorectal cancer. N Engl J Med. 2019;381:1632–43.
pmid
98. Kopetz S, Guthrie KA, Morris VK, Lenz HJ, Magliocco AM, Maru D, et al. Randomized trial of irinotecan and cetuximab with or without vemurafenib in BRAF-mutant metastatic colorectal cancer (SWOG S1406). J Clin Oncol. 2021;39:285–94.
crossref pmid
99. Overman MJ, Lonardi S, Wong KY, Lenz HJ, Gelsomino F, Aglietta M, et al. Durable clinical benefit with nivolumab plus ipilimumab in DNA mismatch repair-deficient/microsatellite instability-high metastatic colorectal cancer. J Clin Oncol. 2018;36:773–9.
crossref pmid
100. Andre T, Shiu KK, Kim TW, Jensen BV, Jensen LH, Punt C, et al. Pembrolizumab in microsatellite-instability-high advanced colorectal cancer. N Engl J Med. 2020;383:2207–18.
pmid
101. Strickler JH, Cercek A, Siena S, Andre T, Ng K, Van Cutsem E, et al. Tucatinib plus trastuzumab for chemotherapy-refractory, HER2-positive, RAS wild-type unresectable or metastatic colorectal cancer (MOUNTAINEER): a multicentre, open-label, phase 2 study. Lancet Oncol. 2023;24:496–508.
pmid
102. Fakih MG, Kopetz S, Kuboki Y, Kim TW, Munster PN, Krauss JC, et al. Sotorasib for previously treated colorectal cancers with KRAS(G12C) mutation (CodeBreaK100): a prespecified analysis of a single-arm, phase 2 trial. Lancet Oncol. 2022;23:115–24.
crossref pmid
103. Yaeger R, Weiss J, Pelster MS, Spira AI, Barve M, Ou SI, et al. Adagrasib with or without cetuximab in colorectal cancer with mutated KRAS G12C. N Engl J Med. 2023;388:44–54.
crossref pmid pmc
104. Garmezy B, Gheeya J, Lin HY, Huang Y, Kim T, Jiang X, et al. Clinical and molecular characterization of POLE mutations as predictive biomarkers of response to immune checkpoint inhibitors in advanced cancers. JCO Precis Oncol. 2022;6:e2100267
crossref pmid pmc
105. Rousseau B, Bieche I, Pasmant E, Hamzaoui N, Leulliot N, Michon L, et al. PD-1 blockade in solid tumors with defects in polymerase epsilon. Cancer Discov. 2022;12:1435–48.
pmid pmc
106. Wang F, Zhao Q, Wang YN, Jin Y, He MM, Liu ZX, et al. Evaluation of POLE and POLD1 mutations as biomarkers for immunotherapy outcomes across multiple cancer types. JAMA Oncol. 2019;5:1504–6.
crossref pmid pmc
107. Ferrarotto R, Eckhardt G, Patnaik A, LoRusso P, Faoro L, Heymach JV, et al. A phase I dose-escalation and dose-expansion study of brontictuzumab in subjects with selected solid tumors. Ann Oncol. 2018;29:1561–8.
crossref pmid
108. Ferrarotto R, Mitani Y, Diao L, Guijarro I, Wang J, Zweidler-McKay P, et al. Activating NOTCH1 mutations define a distinct subgroup of patients with adenoid cystic carcinoma who have poor prognosis, propensity to bone and liver metastasis, and potential responsiveness to Notch1 inhibitors. J Clin Oncol. 2017;35:352–60.
crossref pmid pmc
109. Jhaveri KL, Wang XV, Makker V, Luoh SW, Mitchell EP, Zwiebel JA, et al. Ado-trastuzumab emtansine (T-DM1) in patients with HER2-amplified tumors excluding breast and gastric/gastroesophageal junction (GEJ) adenocarcinomas: results from the NCI-MATCH trial (EAY131) subprotocol Q. Ann Oncol. 2019;30:1821–30.
crossref pmid pmc pdf
110. Kurzrock R, Bowles DW, Kang H, Meric-Bernstam F, Hainsworth J, Spigel DR, et al. Targeted therapy for advanced salivary gland carcinoma based on molecular profiling: results from MyPathway, a phase IIa multiple basket study. Ann Oncol. 2020;31:412–21.
crossref pmid pmc
111. Takahashi H, Tada Y, Saotome T, Akazawa K, Ojiri H, Fushimi C, et al. Phase II trial of trastuzumab and docetaxel in patients with human epidermal growth factor receptor 2-positive salivary duct carcinoma. J Clin Oncol. 2019;37:125–34.
crossref pmid
112. Tabernero J, Bahleda R, Dienstmann R, Infante JR, Mita A, Italiano A, et al. Phase I dose-escalation study of JNJ42756493, an oral pan-fibroblast growth factor receptor inhibitor, in patients with advanced solid tumors. J Clin Oncol. 2015;33:3401–8.
crossref pmid
113. Nogova L, Sequist LV, Perez Garcia JM, Andre F, Delord JP, Hidalgo M, et al. Evaluation of BGJ398, a fibroblast growth factor receptor 1-3 kinase inhibitor, in patients with advanced solid tumors harboring genetic alterations in fibroblast growth factor receptors: results of a global phase I, dose-escalation and dose-expansion study. J Clin Oncol. 2017;35:157–65.
crossref pmid pmc
114. Goke F, Franzen A, Hinz TK, Marek LA, Yoon P, Sharma R, et al. FGFR1 expression levels predict BGJ398 sensitivity of FGFR1-dependent head and neck squamous cell cancers. Clin Cancer Res. 2015;21:4356–64.
crossref pmid pmc pdf
115. Kochanny SE, Worden FP, Adkins DR, Lim DW, Bauman JE, Wagner SA, et al. A randomized phase 2 network trial of tivantinib plus cetuximab versus cetuximab in patients with recurrent/metastatic head and neck squamous cell carcinoma. Cancer. 2020;126:2146–52.
crossref pmid pmc pdf
116. Rothenberger NJ, Stabile LP. Hepatocyte growth factor/c-Met signaling in head and neck cancer and implications for treatment. Cancers (Basel). 2017;9:39.
crossref pmid pmc
117. Golan T, Hammel P, Reni M, Van Cutsem E, Macarulla T, Hall MJ, et al. Maintenance olaparib for germline BRCA-mutated metastatic pancreatic cancer. N Engl J Med. 2019;381:317–27.
crossref pmid pmc
118. Reiss KA, Mick R, O’Hara MH, Teitelbaum U, Karasic TB, Schneider C, et al. Phase II study of maintenance rucaparib in patients with platinum-sensitive advanced pancreatic cancer and a pathogenic germline or somatic variant in BRCA1, BRCA2, or PALB2. J Clin Oncol. 2021;39:2497–505.
crossref pmid
119. Strickler JH, Satake H, George TJ, Yaeger R, Hollebecque A, Garrido-Laguna I, et al. Sotorasib in KRAS p.G12C-mutated advanced pancreatic cancer. N Engl J Med. 2023;388:33–43.
pmid
120. Bekaii-Saab TS, Yaeger R, Spira AI, Pelster MS, Sabari JK, Hafez N, et al. Adagrasib in advanced solid tumors harboring a KRAS(G12C) mutation. J Clin Oncol. 2023;41:4097–106.
crossref pmid pmc
121. Payne SN, Maher ME, Tran NH, Van De Hey DR, Foley TM, Yueh AE, et al. PIK3CA mutations can initiate pancreatic tumorigenesis and are targetable with PI3K inhibitors. Oncogenesis. 2015;4:e169
crossref pmid pmc pdf
122. Harder J, Ihorst G, Heinemann V, Hofheinz R, Moehler M, Buechler P, et al. Multicentre phase II trial of trastuzumab and capecitabine in patients with HER2 overexpressing metastatic pancreatic cancer. Br J Cancer. 2012;106:1033–8.
crossref pmid pmc pdf
123. Singhi AD, Ali SM, Lacy J, Hendifar A, Nguyen K, Koo J, et al. Identification of targetable ALK rearrangements in pancreatic ductal adenocarcinoma. J Natl Compr Canc Netw. 2017;15:555–62.
crossref pmid
124. Schram AM, O’Reilly EM, O’Kane GM, Goto K, Kim DW, Neuzillet C, et al. Efficacy and safety of zenocutuzumab in advanced pancreas cancer and other solid tumors harboring NRG1 fusions. J Clin Oncol. 2021;39(15 Suppl):3003.
crossref
125. Pishvaian MJ, Garrido-Laguna I, Liu SV, Multani PS, ChowManeval E, Rolfo C. Entrectinib in TRK and ROS1 fusionpositive metastatic pancreatic cancer. JCO Precis Oncol. 2018;2:1–7.
crossref
126. Abou-Alfa GK, Macarulla T, Javle MM, Kelley RK, Lubner SJ, Adeva J, et al. Ivosidenib in IDH1-mutant, chemotherapy-refractory cholangiocarcinoma (ClarIDHy): a multicentre, randomised, double-blind, placebo-controlled, phase 3 study. Lancet Oncol. 2020;21:796–807.
crossref pmid pmc
127. Zhu AX, Macarulla T, Javle MM, Kelley RK, Lubner SJ, Adeva J, et al. Final overall survival efficacy results of ivosidenib for patients with advanced cholangiocarcinoma with IDH1 mutation: the phase 3 randomized clinical ClarIDHy trial. JAMA Oncol. 2021;7:1669–77.
crossref pmid pmc
128. Abou-Alfa GK, Sahai V, Hollebecque A, Vaccaro G, Melisi D, Al-Rajabi R, et al. Pemigatinib for previously treated, locally advanced or metastatic cholangiocarcinoma: a multicentre, open-label, phase 2 study. Lancet Oncol. 2020;21:671–84.
crossref pmid pmc
129. Javle M, Roychowdhury S, Kelley RK, Sadeghi S, Macarulla T, Weiss KH, et al. Infigratinib (BGJ398) in previously treated patients with advanced or metastatic cholangiocarcinoma with FGFR2 fusions or rearrangements: mature results from a multicentre, open-label, single-arm, phase 2 study. Lancet Gastroenterol Hepatol. 2021;6:803–15.
crossref pmid
130. Goyal L, Meric-Bernstam F, Hollebecque A, Valle JW, Morizane C, Karasic TB, et al. Futibatinib for FGFR2-rearranged intrahepatic cholangiocarcinoma. N Engl J Med. 2023;388:228–39.
pmid
131. Javle M, Borad MJ, Azad NS, Kurzrock R, Abou-Alfa GK, George B, et al. Pertuzumab and trastuzumab for HER2-positive, metastatic biliary tract cancer (MyPathway): a multicentre, open-label, phase 2a, multiple basket study. Lancet Oncol. 2021;22:1290–300.
crossref pmid
132. Lee CK, Chon HJ, Cheon J, Lee MA, Im HS, Jang JS, et al. Trastuzumab plus FOLFOX for HER2-positive biliary tract cancer refractory to gemcitabine and cisplatin: a multi-institutional phase 2 trial of the Korean Cancer Study Group (KCSG-HB19-14). Lancet Gastroenterol Hepatol. 2023;8:56–65.
crossref pmid
133. Ohba A, Morizane C, Ueno M, Kobayashi S, Kawamoto Y, Komatsu Y, et al. Multicenter phase II trial of trastuzumab deruxtecan for HER2-positive unresectable or recurrent biliary tract cancer: HERB trial. Future Oncol. 2022;18:2351–60.
crossref pmid
134. Fader AN, Roque DM, Siegel E, Buza N, Hui P, Abdelghany O, et al. Randomized phase II trial of carboplatin-paclitaxel versus carboplatin-paclitaxel-trastuzumab in uterine serous carcinomas that overexpress human epidermal growth factor receptor 2/neu. J Clin Oncol. 2018;36:2044–51.
pmid
135. Oaknin A, Bosse TJ, Creutzberg CL, Giornelli G, Harter P, Joly F, et al. Endometrial cancer: ESMO Clinical Practice Guideline for diagnosis, treatment and follow-up. Ann Oncol. 2022;33:860–77.
crossref pmid
136. Leon-Castillo A, Britton H, McConechy MK, McAlpine JN, Nout R, Kommoss S, et al. Interpretation of somatic POLE mutations in endometrial carcinoma. J Pathol. 2020;250:323–35.
crossref pmid pmc pdf
137. Rios-Doria E, Momeni-Boroujeni A, Friedman CF, Selenica P, Zhou Q, Wu M, et al. Integration of clinical sequencing and immunohistochemistry for the molecular classification of endometrial carcinoma. Gynecol Oncol. 2023;174:262–72.
crossref pmid pmc
138. Talhouk A, McConechy MK, Leung S, Li-Chang HH, Kwon JS, Melnyk N, et al. A clinically applicable molecular-based classification for endometrial cancers. Br J Cancer. 2015;113:299–310.
crossref pmid pmc pdf
139. Leon-Castillo A, de Boer SM, Powell ME, Mileshkin LR, Mackay HJ, Leary A, et al. Molecular classification of the PORTEC-3 trial for high-risk endometrial cancer: impact on prognosis and benefit from adjuvant therapy. J Clin Oncol. 2020;38:3388–97.
crossref pmid pmc
140. Kommoss S, McConechy MK, Kommoss F, Leung S, Bunz A, Magrill J, et al. Final validation of the ProMisE molecular classifier for endometrial carcinoma in a large population-based case series. Ann Oncol. 2018;29:1180–8.
crossref pmid
141. van den Heerik A, Horeweg N, Nout RA, Lutgens L, van der Steen-Banasik EM, Westerveld GH, et al. PORTEC-4a: international randomized trial of molecular profile-based adjuvant treatment for women with high-intermediate risk endometrial cancer. Int J Gynecol Cancer. 2020;30:2002–7.
crossref pmid pmc
142. Gonzalez-Martin A, Pothuri B, Vergote I, DePont Christensen R, Graybill W, Mirza MR, et al. Niraparib in patients with newly diagnosed advanced ovarian cancer. N Engl J Med. 2019;381:2391–402.
pmid
143. Coleman RL, Fleming GF, Brady MF, Swisher EM, Steffensen KD, Friedlander M, et al. Veliparib with first-line chemotherapy and as maintenance therapy in ovarian cancer. N Engl J Med. 2019;381:2403–15.
crossref pmid pmc
144. Mirza MR, Monk BJ, Herrstedt J, Oza AM, Mahner S, Redondo A, et al. Niraparib maintenance therapy in platinum-sensitive, recurrent ovarian cancer. N Engl J Med. 2016;375:2154–64.
pmid
145. Moore K, Colombo N, Scambia G, Kim BG, Oaknin A, Friedlander M, et al. Maintenance olaparib in patients with newly diagnosed advanced ovarian cancer. N Engl J Med. 2018;379:2495–505.
crossref pmid
146. Ray-Coquard I, Pautier P, Pignata S, Perol D, Gonzalez-Martin A, Berger R, et al. Olaparib plus bevacizumab as first-line maintenance in ovarian cancer. N Engl J Med. 2019;381:2416–28.
crossref pmid
147. Ledermann J, Harter P, Gourley C, Friedlander M, Vergote I, Rustin G, et al. Olaparib maintenance therapy in patients with platinum-sensitive relapsed serous ovarian cancer: a preplanned retrospective analysis of outcomes by BRCA status in a randomised phase 2 trial. Lancet Oncol. 2014;15:852–61.
crossref pmid
148. Coleman RL, Oza AM, Lorusso D, Aghajanian C, Oaknin A, Dean A, et al. Rucaparib maintenance treatment for recurrent ovarian carcinoma after response to platinum therapy (ARIEL3): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2017;390:1949–61.
pmid pmc
149. Pujade-Lauraine E, Ledermann JA, Selle F, Gebski V, Penson RT, Oza AM, et al. Olaparib tablets as maintenance therapy in patients with platinum-sensitive, relapsed ovarian cancer and a BRCA1/2 mutation (SOLO2/ENGOT-Ov21): a double-blind, randomised, placebo-controlled, phase 3 trial. Lancet Oncol. 2017;18:1274–84.
pmid
150. Loriot Y, Necchi A, Park SH, Garcia-Donas J, Huddart R, Burgess E, et al. Erdafitinib in locally advanced or metastatic urothelial carcinoma. N Engl J Med. 2019;381:338–48.
crossref pmid
151. Van Allen EM, Mouw KW, Kim P, Iyer G, Wagle N, AlAhmadie H, et al. Somatic ERCC2 mutations correlate with cisplatin sensitivity in muscle-invasive urothelial carcinoma. Cancer Discov. 2014;4:1140–53.
crossref pmid pmc pdf
152. Liu D, Plimack ER, Hoffman-Censits J, Garraway LA, Bellmunt J, Van Allen E, et al. Clinical validation of chemotherapy response biomarker ERCC2 in muscle-invasive urothelial bladder carcinoma. JAMA Oncol. 2016;2:1094–6.
crossref pmid pmc
153. de Bono J, Mateo J, Fizazi K, Saad F, Shore N, Sandhu S, et al. Olaparib for metastatic castration-resistant prostate cancer. N Engl J Med. 2020;382:2091–102.
crossref pmid
154. Hussain M, Mateo J, Fizazi K, Saad F, Shore N, Sandhu S, et al. Survival with olaparib in metastatic castration-resistant prostate cancer. N Engl J Med. 2020;383:2345–57.
pmid
155. Jonasch E, Donskov F, Iliopoulos O, Rathmell WK, Narayan VK, Maughan BL, et al. Belzutifan for renal cell carcinoma in von Hippel-Lindau disease. N Engl J Med. 2021;385:2036–46.
crossref pmid pmc
156. Choi Y, Keam B, Kim M, Yoon S, Kim D, Choi JG, et al. Bevacizumab plus erlotinib combination therapy for advanced hereditary leiomyomatosis and renal cell carcinoma-associated renal cell carcinoma: a multicenter retrospective analysis in Korean patients. Cancer Res Treat. 2019;51:1549–56.
crossref pmid pmc pdf
157. Srinivasan R, Gurram S, Harthy MA, Singer EA, Sidana A, Shuch BM, et al. Results from a phase II study of bevacizumab and erlotinib in subjects with advanced hereditary leiomyomatosis and renal cell cancer (HLRCC) or sporadic papillary renal cell cancer. J Clin Oncol. 2020;38(15 Suppl):5004.
crossref
158. Iannantuono GM, Riondino S, Sganga S, Roselli M, Torino F. Activity of ALK inhibitors in renal cancer with ALK clterations: a systematic review. Int J Mol Sci. 2022;23:3995.
pmid pmc
159. Dummer R, Ascierto PA, Gogas HJ, Arance A, Mandala M, Liszkay G, et al. Encorafenib plus binimetinib versus vemurafenib or encorafenib in patients with BRAF-mutant melanoma (COLUMBUS): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 2018;19:603–15.
crossref pmid
160. Larkin J, Ascierto PA, Dreno B, Atkinson V, Liszkay G, Maio M, et al. Combined vemurafenib and cobimetinib in BRAF-mutated melanoma. N Engl J Med. 2014;371:1867–76.
crossref pmid
161. Long GV, Hauschild A, Santinami M, Atkinson V, Mandala M, Chiarion-Sileni V, et al. Adjuvant dabrafenib plus trametinib in stage III BRAF-mutated melanoma. N Engl J Med. 2017;377:1813–23.
crossref pmid
162. Long GV, Stroyakovskiy D, Gogas H, Levchenko E, de Braud F, Larkin J, et al. Combined BRAF and MEK inhibition versus BRAF inhibition alone in melanoma. N Engl J Med. 2014;371:1877–88.
pmid
163. Gutzmer R, Stroyakovskiy D, Gogas H, Robert C, Lewis K, Protsenko S, et al. Atezolizumab, vemurafenib, and cobimetinib as first-line treatment for unresectable advanced BRAF (V600) mutation-positive melanoma (IMspire150): primary analysis of the randomised, double-blind, placebo-controlled, phase 3 trial. Lancet. 2020;395:1835–44.
crossref pmid
164. Carvajal RD, Antonescu CR, Wolchok JD, Chapman PB, Roman RA, Teitcher J, et al. KIT as a therapeutic target in metastatic melanoma. JAMA. 2011;305:2327–34.
crossref pmid pmc
165. Hodi FS, Corless CL, Giobbie-Hurder A, Fletcher JA, Zhu M, Marino-Enriquez A, et al. Imatinib for melanomas harboring mutationally activated or amplified KIT arising on mucosal, acral, and chronically sun-damaged skin. J Clin Oncol. 2013;31:3182–90.
crossref pmid pmc
166. Dummer R, Schadendorf D, Ascierto PA, Arance A, Dutriaux C, Di Giacomo AM, et al. Binimetinib versus dacarbazine in patients with advanced NRAS-mutant melanoma (NEMO): a multicentre, open-label, randomised, phase 3 trial. Lancet Oncol. 2017;18:435–45.
crossref pmid
167. Shin SJ, Lee J, Kim TM, Kim JS, Kim YJ, Hong YS, et al. A phase Ib trial of belvarafenib in combination with cobimetinib in patients with advanced solid tumors: interim results of dose-escalation and patients with NRAS-mutant melanoma of dose-expansion. J Clin Oncol. 2021;39(15 Suppl):3007.
crossref
168. Menzies AM, Yeh I, Botton T, Bastian BC, Scolyer RA, Long GV. Clinical activity of the MEK inhibitor trametinib in metastatic melanoma containing BRAF kinase fusion. Pigment Cell Melanoma Res. 2015;28:607–10.
crossref pmid pmc pdf
169. Hutchinson KE, Lipson D, Stephens PJ, Otto G, Lehmann BD, Lyle PL, et al. BRAF fusions define a distinct molecular subset of melanomas with potential sensitivity to MEK inhibition. Clin Cancer Res. 2013;19:6696–702.
crossref pmid pmc pdf
170. Bowyer SE, Rao AD, Lyle M, Sandhu S, Long GV, McArthur GA, et al. Activity of trametinib in K601E and L597Q BRAF mutation-positive metastatic melanoma. Melanoma Res. 2014;24:504–8.
crossref pmid
171. Dankner M, Lajoie M, Moldoveanu D, Nguyen TT, Savage P, Rajkumar S, et al. Dual MAPK inhibition is an effective therapeutic strategy for a subset of class II BRAF mutant melanomas. Clin Cancer Res. 2018;24:6483–94.
crossref pmid pdf
172. Kim KB, Kefford R, Pavlick AC, Infante JR, Ribas A, Sosman JA, et al. Phase II study of the MEK1/MEK2 inhibitor trametinib in patients with metastatic BRAF-mutant cutaneous melanoma previously treated with or without a BRAF inhibitor. J Clin Oncol. 2013;31:482–9.
pmid
173. Marconcini R, Galli L, Antonuzzo A, Bursi S, Roncella C, Fontanini G, et al. Metastatic BRAF K601E-mutated melanoma reaches complete response to MEK inhibitor trametinib administered for over 36 months. Exp Hematol Oncol. 2017;6:6.
crossref pmid pmc pdf
174. Demetri GD, van Oosterom AT, Garrett CR, Blackstein ME, Shah MH, Verweij J, et al. Efficacy and safety of sunitinib in patients with advanced gastrointestinal stromal tumour after failure of imatinib: a randomised controlled trial. Lancet. 2006;368:1329–38.
crossref pmid
175. Heinrich MC, Rankin C, Blanke CD, Demetri GD, Borden EC, Ryan CW, et al. Correlation of long-term results of imatinib in advanced gastrointestinal stromal tumors with next-generation sequencing results: analysis of phase 3 SWOG Intergroup Trial S0033. JAMA Oncol. 2017;3:944–52.
crossref pmid pmc
176. Cassier PA, Fumagalli E, Rutkowski P, Schoffski P, Van Glabbeke M, Debiec-Rychter M, et al. Outcome of patients with platelet-derived growth factor receptor alpha-mutated gastrointestinal stromal tumors in the tyrosine kinase inhibitor era. Clin Cancer Res. 2012;18:4458–64.
crossref pmid pdf
177. Heinrich MC, Jones RL, von Mehren M, Schoffski P, Serrano C, Kang YK, et al. Avapritinib in advanced PDGFRA D842V-mutant gastrointestinal stromal tumour (NAVIGATOR): a multicentre, open-label, phase 1 trial. Lancet Oncol. 2020;21:935–46.
crossref pmid
178. McArthur GA, Demetri GD, van Oosterom A, Heinrich MC, Debiec-Rychter M, Corless CL, et al. Molecular and clinical analysis of locally advanced dermatofibrosarcoma protuberans treated with imatinib: Imatinib Target Exploration Consortium Study B2225. J Clin Oncol. 2005;23:866–73.
crossref pmid
179. Navarrete-Dechent C, Mori S, Barker CA, Dickson MA, Nehal KS. Imatinib treatment for locally advanced or metastatic dermatofibrosarcoma protuberans: a systematic review. JAMA Dermatol. 2019;155:361–9.
crossref pmid pmc
180. Butrynski JE, D’Adamo DR, Hornick JL, Dal Cin P, Antonescu CR, Jhanwar SC, et al. Crizotinib in ALK-rearranged inflammatory myofibroblastic tumor. N Engl J Med. 2010;363:1727–33.
crossref pmid pmc
181. Nishio M, Murakami H, Horiike A, Takahashi T, Hirai F, Suenaga N, et al. Phase I study of ceritinib (LDK378) in Japanese patients with advanced, anaplastic lymphoma kinaserearranged non-small-cell lung cancer or other tumors. J Thorac Oncol. 2015;10:1058–66.
crossref pmid pmc
182. Gettinger SN, Bazhenova LA, Langer CJ, Salgia R, Gold KA, Rosell R, et al. Activity and safety of brigatinib in ALK-rearranged non-small-cell lung cancer and other malignancies: a single-arm, open-label, phase 1/2 trial. Lancet Oncol. 2016;17:1683–96.
crossref pmid
183. Gounder M, Schoffski P, Jones RL, Agulnik M, Cote GM, Villalobos VM, et al. Tazemetostat in advanced epithelioid sarcoma with loss of INI1/SMARCB1: an international, openlabel, phase 2 basket study. Lancet Oncol. 2020;21:1423–32.
crossref pmid
184. Tap WD, Villalobos VM, Cote GM, Burris H, Janku F, Mir O, et al. Phase I study of the mutant IDH1 inhibitor ivosidenib: safety and clinical activity in patients with advanced chondrosarcoma. J Clin Oncol. 2020;38:1693–701.
crossref pmid pmc
185. Akumalla S, Madison R, Lin DI, Schrock AB, Yakirevich E, Rosenzweig M, et al. Characterization of clinical cases of malignant PEComa via comprehensive genomic profiling of DNA and RNA. Oncology. 2020;98:905–12.
crossref pmid pdf
186. Wagner AJ, Ravi V, Riedel RF, Ganjoo K, Van Tine BA, Chugh R, et al. nab-Sirolimus for patients with malignant perivascular epithelioid cell tumors. J Clin Oncol. 2021;39:3660–70.
pmid pmc
187. Abdul Razak AR, Bauer S, Suarez C, Lin CC, Quek R, Hutter-Kronke ML, et al. Co-targeting of MDM2 and CDK4/6 with siremadlin and ribociclib for the treatment of patients with well-differentiated or dedifferentiated liposarcoma: results from a proof-of-concept, phase Ib study. Clin Cancer Res. 2022;28:1087–97.
crossref pmid pdf
188. LoRusso P, Yamamoto N, Patel MR, Laurie SA, Bauer TM, Geng J, et al. The MDM2-p53 antagonist brigimadlin (BI 907828) in patients with advanced or metastatic solid tumors: results of a phase Ia, first-in-human, dose-escalation study. Cancer Discov. 2023;13:1802–13.
crossref pmid pmc pdf
189. Dickson MA, Schwartz GK, Keohan ML, D’Angelo SP, Gounder MM, Chi P, et al. Progression-free survival among patients with well-differentiated or dedifferentiated liposarcoma treated with CDK4 inhibitor palbociclib: a phase 2 clinical trial. JAMA Oncol. 2016;2:937–40.
crossref pmid pmc
190. Schoffski P, Wozniak A, Stacchiotti S, Rutkowski P, Blay JY, Lindner LH, et al. Activity and safety of crizotinib in patients with advanced clear-cell sarcoma with MET alterations: European Organization for Research and Treatment of Cancer phase II trial 90101 ‘CREATE’. Ann Oncol. 2017;28:3000–8.
crossref pmid pmc
191. Negrini S, Gorgoulis VG, Halazonetis TD. Genomic instability: an evolving hallmark of cancer. Nat Rev Mol Cell Biol. 2010;11:220–8.
crossref pmid pdf
192. Lord CJ, Ashworth A. The DNA damage response and cancer therapy. Nature. 2012;481:287–94.
crossref pmid pdf
193. Yamamoto H, Hirasawa A. Homologous recombination deficiencies and hereditary tumors. Int J Mol Sci. 2021;23:348.
crossref pmid pmc
194. Toh M, Ngeow J. Homologous recombination deficiency: cancer predispositions and treatment implications. Oncologist. 2021;26:e1526–37.
crossref pmid pmc pdf
195. Robson ME, Tung N, Conte P, Im SA, Senkus E, Xu B, et al. OlympiAD final overall survival and tolerability results: olaparib versus chemotherapy treatment of physician’s choice in patients with a germline BRCA mutation and HER2-negative metastatic breast cancer. Ann Oncol. 2019;30:558–66.
crossref pmid pmc pdf
196. Norquist BM, Brady MF, Harrell MI, Walsh T, Lee MK, Gulsuner S, et al. Mutations in homologous recombination genes and outcomes in ovarian carcinoma patients in GOG 218: an NRG Oncology/Gynecologic Oncology Group Study. Clin Cancer Res. 2018;24:777–83.
crossref pmid pmc pdf
197. Pennington KP, Walsh T, Harrell MI, Lee MK, Pennil CC, Rendi MH, et al. Germline and somatic mutations in homologous recombination genes predict platinum response and survival in ovarian, fallopian tube, and peritoneal carcinomas. Clin Cancer Res. 2014;20:764–75.
pmid
198. Geyer CE Jr, Garber JE, Gelber RD, Yothers G, Taboada M, Ross L, et al. Overall survival in the OlympiA phase III trial of adjuvant olaparib in patients with germline pathogenic variants in BRCA1/2 and high-risk, early breast cancer. Ann Oncol. 2022;33:1250–68.
pmid
199. Telli ML, Timms KM, Reid J, Hennessy B, Mills GB, Jensen KC, et al. Homologous recombination deficiency (HRD) score predicts response to platinum-containing neoadjuvant chemotherapy in patients with triple-negative breast cancer. Clin Cancer Res. 2016;22:3764–73.
crossref pmid pmc pdf
200. Watkins JA, Irshad S, Grigoriadis A, Tutt AN. Genomic scars as biomarkers of homologous recombination deficiency and drug response in breast and ovarian cancers. Breast Cancer Res. 2014;16:211.
crossref pmid pmc pdf
201. Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature. 2011;474:609–15.
crossref pmid pmc pdf
202. Lotan TL, Tomlins SA, Bismar TA, Van der Kwast TH, Grignon D, Egevad L, et al. Report From the International Society of Urological Pathology (ISUP) Consultation Conference on Molecular Pathology of Urogenital Cancers. I. Molecular Biomarkers in Prostate Cancer. Am J Surg Pathol. 2020;44:e15–29.
crossref pmid
203. Sztupinszki Z, Diossy M, Krzystanek M, Reiniger L, Csabai I, Favero F, et al. Migrating the SNP array-based homologous recombination deficiency measures to next generation sequencing data of breast cancer. NPJ Breast Cancer. 2018;4:16.
crossref pmid pmc pdf
204. Wang X, Xu Y, Zhang Y, Wang S, Zhang X, Yi X, et al. HRDMILN: accurately estimate tumor homologous recombination deficiency status from targeted panel sequencing data. Front Genet. 2022;13:990244.
crossref pmid pmc
205. Lemery S, Keegan P, Pazdur R. First FDA approval agnostic of cancer site: when a biomarker defines the indication. N Engl J Med. 2017;377:1409–12.
crossref pmid
206. Bonneville R, Krook MA, Chen HZ, Smith A, Samorodnitsky E, Wing MR, et al. Detection of microsatellite instability biomarkers via next-generation sequencing. Methods Mol Biol. 2020;2055:119–32.
crossref pmid pmc
207. Haraldsdottir S. Microsatellite instability testing using nextgeneration sequencing data and therapy implications. JCO Precis Oncol. 2017;1:1–4.
crossref
208. Salipante SJ, Scroggins SM, Hampel HL, Turner EH, Pritchard CC. Microsatellite instability detection by next generation sequencing. Clin Chem. 2014;60:1192–9.
crossref pmid pdf
209. Niu B, Ye K, Zhang Q, Lu C, Xie M, McLellan MD, et al. MSIsensor: microsatellite instability detection using paired tumor-normal sequence data. Bioinformatics. 2014;30:1015–6.
crossref pmid pdf
210. Kautto EA, Bonneville R, Miya J, Yu L, Krook MA, Reeser JW, et al. Performance evaluation for rapid detection of pancancer microsatellite instability with MANTIS. Oncotarget. 2017;8:7452–63.
crossref pmid
211. Hause RJ, Pritchard CC, Shendure J, Salipante SJ. Classification and characterization of microsatellite instability across 18 cancer types. Nat Med. 2016;22:1342–50.
crossref pmid pdf
212. Kim JE, Chun SM, Hong YS, Kim KP, Kim SY, Kim J, et al. Mutation burden and I index for detection of microsatellite instability in colorectal cancer by targeted next-generation sequencing. J Mol Diagn. 2019;21:241–50.
crossref pmid
213. Middha S, Zhang L, Nafa K, Jayakumaran G, Wong D, Kim HR, et al. Reliable Pan-cancer microsatellite instability assessment by using targeted next-generation sequencing data. JCO Precis Oncol. 2017;2017:PO.17.00084.
crossref pmid
214. Sharma P, Siddiqui BA, Anandhan S, Yadav SS, Subudhi SK, Gao J, et al. The next decade of immune checkpoint therapy. Cancer Discov. 2021;11:838–57.
crossref pmid pdf
215. Patel SP, Kurzrock R. PD-L1 expression as a predictive biomarker in cancer immunotherapy. Mol Cancer Ther. 2015;14:847–56.
crossref pmid pdf
216. Le DT, Durham JN, Smith KN, Wang H, Bartlett BR, Aulakh LK, et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science. 2017;357:409–13.
pmid pmc
217. Sha D, Jin Z, Budczies J, Kluck K, Stenzinger A, Sinicrope FA. Tumor mutational burden as a predictive biomarker in solid tumors. Cancer Discov. 2020;10:1808–25.
crossref pmid pmc pdf
218. Samstein RM, Lee CH, Shoushtari AN, Hellmann MD, Shen R, Janjigian YY, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet. 2019;51:202–6.
pmid pmc
219. Jardim DL, Goodman A, de Melo Gagliato D, Kurzrock R. The challenges of tumor mutational burden as an immunotherapy biomarker. Cancer Cell. 2021;39:154–73.
crossref pmid
220. Marcus L, Fashoyin-Aje LA, Donoghue M, Yuan M, Rodriguez L, Gallagher PS, et al. FDA approval summary: pembrolizumab for the treatment of tumor mutational burden-high solid tumors. Clin Cancer Res. 2021;27:4685–9.
crossref pmid pmc pdf
221. Chalmers ZR, Connelly CF, Fabrizio D, Gay L, Ali SM, Ennis R, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9:34.
crossref pmid pmc pdf
222. Buchhalter I, Rempel E, Endris V, Allgauer M, Neumann O, Volckmar AL, et al. Size matters: dissecting key parameters for panel-based tumor mutational burden analysis. Int J Cancer. 2019;144:848–58.
crossref pmid pdf
223. Fumet JD, Truntzer C, Yarchoan M, Ghiringhelli F. Tumour mutational burden as a biomarker for immunotherapy: Current data and emerging concepts. Eur J Cancer. 2020;131:40–50.
crossref pmid pmc
224. Luchini C, Bibeau F, Ligtenberg MJL, Singh N, Nottegar A, Bosse T, et al. ESMO recommendations on microsatellite instability testing for immunotherapy in cancer, and its relationship with PD-1/PD-L1 expression and tumour mutational burden: a systematic review-based approach. Ann Oncol. 2019;30:1232–43.
crossref pmid pdf
225. Gambardella V, Tarazona N, Cejalvo JM, Lombardi P, Huerta M, Rosello S, et al. Personalized medicine: recent progress in cancer therapy. Cancers (Basel). 2020;12:1009.
crossref pmid pmc
226. Cescon DW, Bratman SV, Chan SM, Siu LL. Circulating tumor DNA and liquid biopsy in oncology. Nat Cancer. 2020;1:276–90.
crossref pmid pdf
227. Sugimoto A, Matsumoto S, Udagawa H, Itotani R, Usui Y, Umemura S, et al. A large-scale prospective concordance study of plasma- and tissue-based next-generation targeted sequencing for advanced non-small cell lung cancer (LCSCRUM-Liquid). Clin Cancer Res. 2023;29:1506–14.
crossref pmid pdf
228. Benayed R, Offin M, Mullaney K, Sukhadia P, Rios K, Desmeules P, et al. High yield of RNA sequencing for targetable kinase fusions in lung adenocarcinomas with no mitogenic driver alteration detected by DNA sequencing and low tumor mutation burden. Clin Cancer Res. 2019;25:4712–22.
crossref pmid pmc pdf
229. Heydt C, Wolwer CB, Velazquez Camacho O, Wagener-Ryczek S, Pappesch R, Siemanowski J, et al. Detection of gene fusions using targeted next-generation sequencing: a comparative evaluation. BMC Med Genomics. 2021;14:62.
crossref pmid pmc pdf
230. Wyatt AW, Annala M, Aggarwal R, Beja K, Feng F, Youngren J, et al. Concordance of circulating tumor DNA and matched metastatic tissue biopsy in prostate cancer. J Natl Cancer Inst. 2017;109:djx118.
crossref pmid pmc
231. Kingston B, Cutts RJ, Bye H, Beaney M, Walsh-Crestani G, Hrebien S, et al. Genomic profile of advanced breast cancer in circulating tumour DNA. Nat Commun. 2021;12:2423.
crossref pmid pmc pdf
232. Pascual J, Attard G, Bidard FC, Curigliano G, De Mattos-Arruda L, Diehn M, et al. ESMO recommendations on the use of circulating tumour DNA assays for patients with cancer: a report from the ESMO Precision Medicine Working Group. Ann Oncol. 2022;33:750–68.
crossref pmid
233. Pisapia P, Malapelle U, Troncone G. Liquid biopsy and lung cancer. Acta Cytol. 2019;63:489–96.
crossref pmid pdf
234. Kim H, Park KU. Clinical circulating tumor DNA testing for precision oncology. Cancer Res Treat. 2023;55:351–66.
crossref pmid pmc pdf
235. Cha Y, Kim S, Han SW. Utilizing plasma circulating tumor DNA sequencing for precision medicine in the management of solid cancers. Cancer Res Treat. 2023;55:367–84.
crossref pmid pmc pdf
236. Mack PC, Banks KC, Espenschied CR, Burich RA, Zill OA, Lee CE, et al. Spectrum of driver mutations and clinical impact of circulating tumor DNA analysis in non-small cell lung cancer: analysis of over 8000 cases. Cancer. 2020;126:3219–28.
crossref pmid pdf
237. Leighl NB, Page RD, Raymond VM, Daniel DB, Divers SG, Reckamp KL, et al. Clinical utility of comprehensive cell-free DNA analysis to identify genomic biomarkers in patients with newly diagnosed metastatic non-small cell lung cancer. Clin Cancer Res. 2019;25:4691–700.
crossref pmid pdf
238. Viller Tuxen I, Barlebo Ahlborn L, Mau-Soerensen M, Staal Rohrberg K, Cilius Nielsen F, Oestrup O, et al. Plasma total cell-free DNA is a prognostic biomarker of overall survival in metastatic solid tumour patients. Br J Cancer. 2019;121:125–30.
crossref pmid pmc pdf
239. Mirtavoos-Mahyari H, Ghafouri-Fard S, Khosravi A, Motevaseli E, Esfahani-Monfared Z, Seifi S, et al. Circulating free DNA concentration as a marker of disease recurrence and metastatic potential in lung cancer. Clin Transl Med. 2019;8:14.
pmid pmc
240. Zhang Y, Yao Y, Xu Y, Li L, Gong Y, Zhang K, et al. Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients. Nat Commun. 2021;12:11.
crossref pmid pmc pdf
241. Kim S, Lim Y, Kang JK, Kim HP, Roh H, Kim SY, et al. Dynamic changes in longitudinal circulating tumour DNA profile during metastatic colorectal cancer treatment. Br J Cancer. 2022;127:898–907.
crossref pmid pmc pdf
242. Cai Z, Wang Z, Liu C, Shi D, Li D, Zheng M, et al. Detection of microsatellite instability from circulating tumor DNA by targeted deep sequencing. J Mol Diagn. 2020;22:860–70.
crossref pmid
243. Fridland S, Choi J, Nam M, Schellenberg SJ, Kim E, Lee G, et al. Assessing tumor heterogeneity: integrating tissue and circulating tumor DNA (ctDNA) analysis in the era of immunooncology - blood TMB is not the same as tissue TMB. J Immunother Cancer. 2021;9:e002551
crossref pmid pmc
244. Gilson P, Merlin JL, Harle A. Detection of microsatellite instability: state of the art and future applications in circulating tumour DNA (ctDNA). Cancers (Basel). 2021;13:1491.
crossref pmid pmc
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