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- Characteristics of Immune Checkpoint Inhibitor–Related Hepatotoxicity Based on the Baseline Liver Function
- Won-Jung Jung, Eun-Jung Jo, Ye-Jee Kim, Mihyun Park, Eunji Kim, Yu-Seon Jung, Sook Ryun Park, Ji Seon Oh, So-Hui Kim, Jeongbin Park, Sun-Young Jung, Nakyung Jeon
- Cancer Res Treat. 2026;58(3):709-719. Published online July 18, 2025
- DOI: https://doi.org/10.4143/crt.2025.040
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Abstract
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Supplementary Material
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ePub - Purpose
This study estimated the incidence of immune checkpoint inhibitor–related hepatotoxicity (ICH), identified risk factors, and characterized patients who developed ICH.
Materials and Methods
Adult patients treated with immune checkpoint inhibitors (ICIs) from January 2015 to June 2022 in a tertiary hospital were included, excluding those without liver function tests or those with liver cancer but normal baseline liver function. Patients were stratified by baseline liver function status; in overall and each of stratified cohorts ICH incidence was calculated as the number of events per 100 person-years with grade 3 hepatotoxicity as the primary outcome. Patient characteristics were assessed using descriptive statistics, and risk factors were identified through multivariable Cox regression. Causality between ICI use and hepatotoxicity was assessed using the Naranjo Algorithm.
Results
Among 803 patients, the ICH incidence was 19.5 cases per 100 person-years, with a higher incidence (47.3 vs. 9.3 cases per 100 person-years) and earlier onset (13 vs. 15 days) in the abnormal compared to the normal group. Significant risk factors for ICH included female sex in the normal group and liver cancer in the abnormal group. According to the Naranjo Algorithm, all the 60 ICH cases were classified as “probable” or “possible”. Among the 60 cases, 61.7% (n=37) resulted in ICI discontinuation. The baseline liver function did not impact on the severity or the likelihood of ICI discontinuation.
Conclusion
Future studies are needed to evaluate whether the impact of ICI discontinuation on survival outcomes in patients with ICH varies based on baseline liver function abnormalities. -
Citations
Citations to this article as recorded by
- Integrative multi-omics profiling identifies infiltrative hepatocellular carcinoma as an immunotherapy-resistant subtype with distinct molecular features
Won Suk Lee, Seonjeong Woo, Sung Hwan Lee, Gae Hoon Jo, Ilhwan Kim, Hyeyeong Kim, Chansik An, Sanghoon Jung, Gwangil Kim, Haeyoun Kang, Beodeul Kang, Jung Sun Kim, Ho Yeong Lim, Incheon Kang, Hannah Yang, So Jung Kong, Dahyeon Son, Dong Jun Shin, Woo Youn
Clinical and Molecular Hepatology.2026; 32(1): 258. CrossRef
- Integrative multi-omics profiling identifies infiltrative hepatocellular carcinoma as an immunotherapy-resistant subtype with distinct molecular features
- 2,475 View
- 142 Download
- 1 Crossref
- Gastrointestinal cancer
- Relationships between the Microbiome and Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer
- Hye In Lee, Bum-Sup Jang, Ji Hyun Chang, Eunji Kim, Tae Hoon Lee, Jeong Hwan Park, Eui Kyu Chie
- Cancer Res Treat. 2025;57(3):840-851. Published online December 16, 2024
- DOI: https://doi.org/10.4143/crt.2024.521
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Abstract
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- Purpose
This study aimed to investigate the dynamic changes in the microbiome of patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy (nCRT), focusing on the relationship between the microbiome and response to nCRT.
Materials and Methods
We conducted a longitudinal study involving 103 samples from 26 patients with LARC. Samples were collected from both the tumor and normal rectal tissues before and after nCRT. Diversity, taxonomic, and network analyses were performed to compare the microbiome profiles across different tissue types, pre- and post-nCRT time-points, and nCRT responses.
Results
Between the tumor and normal tissue samples, no differences in microbial diversity and composition were observed. However, when pre- and post-nCRT samples were compared, there was a significant decrease in diversity, along with notable changes in composition. Non-responders exhibited more extensive changes in their microbiome composition during nCRT, characterized by an increase in pathogenic microbes. Meanwhile, responders had relatively stable microbiome communities with more enriched butyrate-producing bacteria. Network analysis revealed distinct patterns of microbial interactions between responders and non-responders, where butyrate-producing bacteria formed strong networks in responders, while opportunistic pathogens formed strong networks in non-responders. A Bayesian network model for predicting the nCRT response was established, with butyrate-producing bacteria playing a major predictive role.
Conclusion
Our study demonstrated a significant association between the microbiome and nCRT response in LARC patients, leading to the development of a microbiome-based response-prediction model. These findings suggest potential applications of microbiome signatures for predicting and optimizing nCRT treatment in LARC patients. -
Citations
Citations to this article as recorded by- The Mediating Role of the Gut Microbiome in the Nutritional Prevention of Cancer
Priyanka Chambial, Neelam Thakur, Umesh Kumar, Saurabh Gupta
The Journal of Nutrition.2026; 156(2): 101301. CrossRef - Gut microbiota-associated predictors as biomarkers of neoadjuvant treatment response in rectal cancer-a systematic review
Astghik Stepanyan, Andromachi Kotsafti, Antonio Rosato, Ignazio Castagliuolo, Marco Scarpa, Melania Scarpa, Marco Agostini, Imerio Angriman, Michele Antoniutti, Quoc Riccardo Bao, Andrea Baldo, Mattia Barbareschi, Romeo Bardini, Giulia Becherucci, Frances
British Journal of Cancer.2026; 135(1): 139. CrossRef - The role of the microbiome in uterine cancer: insights into tumorigenesis, therapeutic implications, and clinical prospects
Yating Zhang, Xiaochuan Yu, Li Shi, Chen Qi, Huali Wang
Journal of the Egyptian National Cancer Institute.2026;[Epub] CrossRef - Gut-Microbiome Signatures Predicting Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer: A Systematic Review
Ielmina Domilescu, Bogdan Miutescu, Florin George Horhat, Alina Popescu, Camelia Nica, Ana Maria Ghiuchici, Eyad Gadour, Ioan Sîrbu, Delia Hutanu
Metabolites.2025; 15(6): 412. CrossRef
- The Mediating Role of the Gut Microbiome in the Nutritional Prevention of Cancer
- 5,182 View
- 143 Download
- 4 Web of Science
- 4 Crossref
- Integrating Deep Learning–Based Dose Distribution Prediction with Bayesian Networks for Decision Support in Radiotherapy for Upper Gastrointestinal Cancer
- Dong-Yun Kim, Bum-Sup Jang, Eunji Kim, Eui Kyu Chie
- Cancer Res Treat. 2025;57(1):186-197. Published online August 2, 2024
- DOI: https://doi.org/10.4143/crt.2024.333
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Abstract
PDFSupplementary MaterialPubReaderePub
- Purpose
Selecting the better techniques to harbor optimal motion management, either a stereotactic linear accelerator delivery using TrueBeam (TBX) or magnetic resonance–guided gated delivery using MRIdian (MRG), is time-consuming and costly. To address this challenge, we aimed to develop a decision-supporting algorithm based on a combination of deep learning-generated dose distributions and clinical data.
Materials and Methods
We retrospectively analyzed 65 patients with liver or pancreatic cancer who underwent both TBX and MRG simulations and planning process. We trained three-dimensional U-Net deep learning models to predict dose distributions and generated dose volume histograms (DVHs) for each system. We integrated predicted DVH metrics into a Bayesian network (BN) model incorporating clinical data.
Results
The MRG prediction model outperformed the TBX model, demonstrating statistically significant superiorities in predicting normalized dose to the planning target volume (PTV) and liver. We developed a final BN prediction model integrating the predictive DVH metrics with patient factors like age, PTV size, and tumor location. This BN model an area under the receiver operating characteristic curve index of 83.56%. The decision tree derived from the BN model showed that the tumor location (abutting vs. apart of PTV to hollow viscus organs) was the most important factor to determine TBX or MRG. It provided a potential framework for selecting the optimal radiation therapy (RT) system based on individual patient characteristics.
Conclusion
We demonstrated a decision-supporting algorithm for selecting optimal RT plans in upper gastrointestinal cancers, incorporating both deep learning-based dose prediction and BN-based treatment selection. This approach might streamline the decision-making process, saving resources and improving treatment outcomes for patients undergoing RT. -
Citations
Citations to this article as recorded by- Development of an artificial intelligence driven dose prediction pipeline for online adaptive magnetic resonance-guided radiotherapy
Benjamin Tengler, Moritz Schneider, Marcel Nachbar, Simon Boeke, Cihan Gani, Maximilian Niyazi, Paul Fischer, Christian F. Baumgartner, Daniela Thorwarth
Physics and Imaging in Radiation Oncology.2026; 40: 101048. CrossRef - Comprehensive review of Bayesian network applications in gastrointestinal cancers
Min-Na Zhang, Meng-Ju Xue, Bao-Zhen Zhou, Jing Xu, Hong-Kai Sun, Ji-Han Wang, Yang-Yang Wang
World Journal of Clinical Oncology.2025;[Epub] CrossRef
- Development of an artificial intelligence driven dose prediction pipeline for online adaptive magnetic resonance-guided radiotherapy
- 5,495 View
- 151 Download
- 2 Web of Science
- 2 Crossref
- Prognostic Significance of Bulky Nodal Disease in Anal Cancer Management: A Multi-institutional Study
- Seok-Joo Chun, Eunji Kim, Won Il Jang, Mi-Sook Kim, Hyun-Cheol Kang, Byoung Hyuck Kim, Eui Kyu Chie
- Cancer Res Treat. 2024;56(4):1197-1206. Published online April 11, 2024
- DOI: https://doi.org/10.4143/crt.2024.258
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Abstract
PDFSupplementary MaterialPubReaderePub
- Purpose
This study aimed to assess the prognostic significance of bulky nodal involvement in patients with anal squamous cell carcinoma treated with definitive chemoradiotherapy.
Materials and Methods
We retrospectively analyzed medical records of patients diagnosed with anal squamous cell carcinoma who underwent definitive chemoradiotherapy at three medical centers between 2004 and 2021. Exclusion criteria included distant metastasis at diagnosis, 2D radiotherapy, and salvage treatment for local relapse. Bulky N+ was defined as nodes with a long diameter of 2 cm or greater.
Results
A total of 104 patients were included, comprising 51 with N0, 46 with non-bulky N+, and seven with bulky N+. The median follow-up duration was 54.0 months (range, 6.4 to 162.2 months). Estimated 5-year progression-free survival (PFS), loco-regional recurrence-free survival (LRRFS), and overall survival (OS) rates for patients with bulky N+ were 42.9%, 42.9%, and 47.6%, respectively. Bulky N+ was significantly associated with inferior PFS, LRRFS, and OS compared to patients without or with non-bulky N+, even after multivariate analysis. We proposed a new staging system incorporating bulky N+ as N2 category, with estimated 5-year LRRFS, PFS, and OS rates of 81.1%, 80.6%, and 86.2% for stage I, 67.7%, 60.9%, and 93.3% for stage II, and 42.9%, 42.9%, and 47.6% for stage III disease, enhancing the predictability of prognosis.
Conclusion
Patients with bulky nodal disease treated with standard chemoradiotherapy experienced poor survival outcomes, indicating the potential necessity for further treatment intensification. -
Citations
Citations to this article as recorded by
- 4,003 View
- 89 Download
- 1 Web of Science
- 2 Crossref
- Impact of Mucin Proportion in the Pretreatment MRI on the Outcomes of Rectal Cancer Patients Undergoing Neoadjuvant Chemoradiotherapy
- Eunji Kim, Kyubo Kim, Se Hyung Kim, Sae-Won Han, Tae-You Kim, Seung-Yong Jeong, Kyu Joo Park, Jaemoon Koh, Gyeong Hoon Kang, Eui Kyu Chie
- Cancer Res Treat. 2019;51(3):1188-1197. Published online December 20, 2018
- DOI: https://doi.org/10.4143/crt.2018.434
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Abstract
PDFPubReaderePub
- Purpose
The purpose of this study was to evaluate treatment response to neoadjuvant chemoradiotherapy (CRT) with regard to mucin status in pathology and pretreatment magnetic resonance imaging (MRI) in locally advanced rectal cancer.
Materials and Methods
Between 2003 and 2011, 306 patients with locally advanced rectal cancer received neoadjuvant CRT followed by surgery, and mucinous adenocarcinoma (MAC) was found in 27 (8.8%). All MAC patients had MRI before and after CRT and mucin proportion at MRI was measured. Therapeutic response was assessed by pathology after total mesorectal excision. To determine the optimal cut-off for mucin proportion in predicting good CRT response (near total or total regression) and negative circumferential resection margin (CRM), the receiver-operating characteristic analysis was performed.
Results
After neoadjuvant CRT, overall downstaging occurred in 44.4% of MAC and 72.4% of non-MAC (p=0.001), and positive CRM (≤1 mm) was observed more frequently in MAC (p<0.001). The optimal threshold for treatment response was 30% for mucin proportion, and there are nine with low mucin proportion (<30%) and 18 with high mucin proportion (≥30%) in pretreatment MRI. Negative CRM and tumor downstaging occurred more common in patients with mucin <30%, although statistically insignificant (p=0.071 and p=0.072, respectively). Regarding oncologic outcomes, lower mucin proportion in pretreatment MRI was associated with better disease-free and overall survival in MAC group (p=0.092 and 0.056, respectively), but the difference did not reach statistical significance.
Conclusion
Poor treatment outcome with neoadjuvant CRT was observed in patients with MAC, especially those with high mucin proportion at pretreatment MRI. -
Citations
Citations to this article as recorded by- Incomplete Resection Is Twice as Likely in Locally Advanced Mucinous Compared to Nonmucinous Rectal Adenocarcinoma: A National Propensity‐Matched Analysis
Leah E. Hendrick, Samer Naffouje, Iman Imanirad, Allan Lima Pereira, Tiago Biachi, Julian Sanchez, Sophie Dessureault, Amalia Stefanou, Sean P. Dineen, Seth Felder
Journal of Surgical Oncology.2025; 131(6): 1090. CrossRef - Mucinous histology is a negative predictor of neoadjuvant chemoradiotherapy for locally advanced rectal adenocarcinoma
Xiangwen Tan, Yiwei Zhang, Xiaofeng Wu, Qing Fang, Yunhua Xu, Shuxiang Li, Jinyi Yuan, Xiuda Peng, Kai Fu, Shuai Xiao
BMC Gastroenterology.2024;[Epub] CrossRef - Accelerated T2W Imaging with Deep Learning Reconstruction in Staging Rectal Cancer: A Preliminary Study
Lan Zhu, Bowen Shi, Bei Ding, Yihan Xia, Kangning Wang, Weiming Feng, Jiankun Dai, Tianyong Xu, Baisong Wang, Fei Yuan, Hailin Shen, Haipeng Dong, Huan Zhang
Journal of Imaging Informatics in Medicine.2024; 38(4): 2537. CrossRef - Mucinous rectal cancers: clinical features and prognosis in a population-based cohort
Malin Enblad, Klara Hammarström, Joakim Folkesson, Israa Imam, Milan Golubovik, Bengt Glimelius
BJS Open.2022;[Epub] CrossRef - Mucin-Containing Rectal Cancer: A Review of Unique Imaging, Pathology, and Therapeutic Response Features
David D. Childs, Caio Max Sao Pedro Rocha Lima, Yi Zhou
Seminars in Roentgenology.2021; 56(2): 186. CrossRef - Advances in radiological staging of colorectal cancer
R.J. Goiffon, A. O'Shea, M.G. Harisinghani
Clinical Radiology.2021; 76(12): 879. CrossRef - A Comprehensive Evaluation of Associations Between Routinely Collected Staging Information and The Response to (Chemo)Radiotherapy in Rectal Cancer
Klara Hammarström, Israa Imam, Artur Mezheyeuski, Joakim Ekström, Tobias Sjöblom, Bengt Glimelius
Cancers.2020; 13(1): 16. CrossRef
- Incomplete Resection Is Twice as Likely in Locally Advanced Mucinous Compared to Nonmucinous Rectal Adenocarcinoma: A National Propensity‐Matched Analysis
- 10,889 View
- 177 Download
- 7 Web of Science
- 7 Crossref
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