Cancer Research and Treatment

Original Articles

Breast cancer

Harnessing Institutionally Developed Clinical Targeted Sequencing to Improve Patient Survival in Breast Cancer: A Seven-Year Experience: Jiwon Koh, Jinyong Kim, Go-Un Woo, Hanbaek Yi, So Yean Kwon, Jeongmin Seo, Jeong Mo Bae, Jung Ho Kim, Jae Kyung Won, Han Suk Ryu, Yoon Kyung Jeon, Dae-Won Lee, Miso Kim, Tae-Yong Kim, Kyung-Hun Lee, Tae-You Kim, Jee-Soo Lee, Moon-Woo Seong, Sheehyun Kim, Sungyoung Lee, Hongseok Yun, Myung Geun Song, Jaeyong Choi, Jong-Il Kim, Seock-Ah Im; Cancer Res Treat. 2025;57(2):443-456. Published online August 21, 2024; DOI: https://doi.org/10.4143/crt.2024.296

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Purpose
Considering the high disease burden and unique features of Asian patients with breast cancer (BC), it is essential to have a comprehensive view of genetic characteristics in this population. An institutional targeted sequencing platform was developed through the Korea Research-Driven Hospitals project and was incorporated into clinical practice. This study explores the use of targeted next-generation sequencing (NGS) and its outcomes in patients with advanced/metastatic BC in the real world.
Materials and Methods
We reviewed the results of NGS tests administered to BC patients using a customized sequencing platform—FiRST Cancer Panel (FCP)—over 7 years. We systematically described clinical translation of FCP for precise diagnostics, personalized therapeutic strategies, and unraveling disease pathogenesis.
Results
NGS tests were conducted on 548 samples from 522 patients with BC. Ninety-seven point six percentage of tested samples harbored at least one pathogenic alteration. The common alterations included mutations in TP53 (56.2%), PIK3CA (31.2%), GATA3 (13.8%), BRCA2 (10.2%), and amplifications of CCND1 (10.8%), FGF19 (10.0%), and ERBB2 (9.5%). NGS analysis of ERBB2 amplification correlated well with human epidermal growth factor receptor 2 immunohistochemistry and in situ hybridization. RNA panel analyses found potentially actionable and prognostic fusion genes. FCP effectively screened for potentially germline pathogenic/likely pathogenic mutation. Ten point three percent of BC patients received matched therapy guided by NGS, resulting in a significant overall survival advantage (p=0.022), especially for metastatic BCs.
Conclusion
Clinical NGS provided multifaceted benefits, deepening our understanding of the disease, improving diagnostic precision, and paving the way for targeted therapies. The concrete advantages of FCP highlight the importance of multi-gene testing for BC, especially for metastatic conditions.

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Genomic and transcriptomic analyses of residual invasive triple-negative breast cancer after neoadjuvant chemotherapy in the prospective MIRINAE trial (a randomized phase II trial of adjuvant atezolizumab plus capecitabine compared to capecitabine; KCSG-B
S.-A. Im, K. Park, J. Koh, C. Park, K.H. Jung, J. Lee, H.K. Ahn, A. Lee, S.H. Sim, M.H. Kim, J.H. Kim, J.H. Kim, K.E. Lee, K.H. Park, J. Bae, M.H. Lee, S. Lim, H.J. Kim, D.-W. Lee, J.H. Jeong, K.S. Lee, J. Sohn, K.J. Suh, J.-Y. Kim, Y.J. Cha, J. Moon, C.-
ESMO Open.2025; 10(10): 105804. CrossRef

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Gastrointestinal cancer

Identification of New Pathogenic Variants of Hereditary Diffuse Gastric Cancer: Seung-Young Oh, Giyong Jang, Jaeryuk Kim, Kyoung-Yun Jeong, Hyun Myong Kim, Yoon Jin Kwak, Seong-Ho Kong, Do Joong Park, Hyuk-Joon Lee, Sung-Yup Cho, Jong-Il Kim, Han-Kwang Yang; Cancer Res Treat. 2024;56(4):1126-1135. Published online April 11, 2024; DOI: https://doi.org/10.4143/crt.2024.328

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Purpose
Hereditary diffuse gastric cancer (HDGC) presents a significant genetic predisposition, notably linked to mutations in the CDH1 and CTNNA1. However, the genetic basis for over half of HDGC cases remains unidentified. The aim of this study is to identify novel pathogenic variants in HDGC and evaluate their protein expression.
Materials and Methods
Among 20 qualifying families, two were selected based on available pedigree and DNA. Whole genome sequencing (WGS) on DNA extracted from blood and whole exome sequencing on DNA from formalin-fixed paraffin-embedded tissues were performed to find potential pathogenic variants in HDGC. After selection of a candidate variant, functional validation, and enrichment analysis were performed.
Results
As a result of WGS, three candidate germline mutations (EPHA5, MCOA2, and RHOA) were identified in one family. After literature review and in-silico analyses, the RHOA mutation (R129W) was selected as a candidate. This mutation was found in two gastric cancer patients within the family. In functional validation, it showed RhoA overexpression and a higher GTP-bound state in the Rhoa^R129W mutant. Decreased phosphorylation at Ser127/397 suggested altered YAP1 regulation in the Rho-ROCK pathway. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses linked Rhoa^R129W overexpression to changed migration/adhesion in MKN1 cell line. However, this RHOA mutation (R129W) was not found in index patients in other families.
Conclusion
The RHOA mutation (R129W) emerges as a potential causative gene for HDGC, but only in one family, indicating a need for further studies to understand its role in HDGC pathogenesis fully.

Citations

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Hereditary diffuse gastric cancer: the evolution of a cancer syndrome
Lyvianne Decourtye-Espiard, Tanis Godwin, Parry Guilford
Journal of the Royal Society of New Zealand.2025; 55(6): 2636. CrossRef
A Comprehensive Review of Genetic Mutations Occurring in the Development and Progression of Gastric Cancer
Yalan Li, Qianqian Xu, Zhuo Chen, Mengting Chen, Kunyu Han, Zhuqing Zhang, Aling Shen, Xiaoyan Fu
Digestive Diseases.2025; 43(6): 630. CrossRef
Helicobacter pylori infection status and evolution of gastric cancer
Wenlin Zhang, Yuxin Zhang, Jing Ning, Weiwei Fu, Shigang Ding
Chinese Medical Journal.2025; 138(23): 3083. CrossRef
Current advances and challenges in Managing Hereditary Diffuse Gastric Cancer (HDGC): a narrative review
L. van der Sluis, J.M. van Dieren, R.S. van der Post, T.M. Bisseling
Hereditary Cancer in Clinical Practice.2024;[Epub] CrossRef

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Sarcoma

Case Series of Soft Tissue Sarcoma Patients with Brain Metastasis with Implications from Genomic and Transcriptomic Analysis: Changhee Park, Rokhyun Kim, Jaeyong Choi, Miso Kim, Tae Min Kim, Ilkyu Han, Jong-Il Kim, Han-Soo Kim; Cancer Res Treat. 2024;56(2):665-674. Published online September 27, 2023; DOI: https://doi.org/10.4143/crt.2023.864

Abstract PDF Supplementary Material PubReader ePub: Purpose
Brain metastasis rarely occurs in soft tissue sarcoma (STS). Here, we present five cases of STS with brain metastases with genetic profiles.
Materials and Methods
We included five patients from Seoul National University Hospital who were diagnosed with STS with metastasis to the brain. Tissue from the brain metastasis along with that from the primary site or other metastases were used for DNA and RNA sequencing to identify genetic profiles. Gene expression profiles were compared with sarcoma samples from The Cancer Genome Atlas.
Results
The overall survival after diagnosis of brain metastasis ranged from 2.2 to 34.3 months. Comparison of mutational profiles between brain metastases and matched primary or other metastatic samples showed similar profiles. In two patients, copy number variation profiles between brain metastasis and other tumors showed several differences including MYCL, JUN, MYC, and DDR2 amplification. Gene ontology analysis showed that the group of genes significantly highly expressed in the brain metastasis samples was enriched in the G-protein coupled receptor activity, structural constituent of chromatin, protein heterodimerization activity, and binding of DNA, RNA, and protein. Gene set enrichment analysis showed enrichment in the pathway of neuroactive ligand-receptor interaction and systemic lupus erythematosus.
Conclusion
The five patients had variable ranges of clinical courses and outcomes. Genomic and transcriptomic analysis of STS with brain metastasis implicates possible involvement of complex expression modification and epigenetic changes rather than the addition of single driver gene alteration.

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General

Radiation Response Prediction Model Based on Integrated Clinical and Genomic Data Analysis: Bum-Sup Jang, Ji-Hyun Chang, Seung Hyuck Jeon, Myung Geun Song, Kyung-Hun Lee, Seock-Ah Im, Jong-Il Kim, Tae-You Kim, Eui Kyu Chie; Cancer Res Treat. 2022;54(2):383-395. Published online August 24, 2021; DOI: https://doi.org/10.4143/crt.2021.759

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Purpose
The value of the genomic profiling by targeted gene-sequencing on radiation therapy response prediction was evaluated through integrated analysis including clinical information. Radiation response prediction model was constructed based on the analyzed findings.
Materials and Methods
Patients who had the tumor sequenced using institutional cancer panel after informed consent and received radiotherapy for the measurable disease served as the target cohort. Patients with irradiated tumor locally controlled for more than 6 months after radiotherapy were defined as the durable local control (DLC) group, otherwise, non-durable local control (NDLC) group. Significant genomic factors and domain knowledge were used to develop the Bayesian Network model to predict radiotherapy response.
Results
Altogether, 88 patients were collected for analysis. Of those, 41 (43.6%) and 47 (54.4%) patients were classified as the NDLC and DLC group, respectively. Somatic mutations of NOTCH2 and BCL were enriched in the NDLC group, whereas, mutations of CHEK2, MSH2, and NOTCH1 were more frequently found in the DLC group. Altered DNA repair pathway was associated with better local failure–free survival (hazard ratio, 0.40; 95% confidence interval, 0.19 to 0.86; p=0.014). Smoking somatic signature was found more frequently in the DLC group. Area under the receiver operating characteristic curve of the Bayesian network model predicting probability of 6-month local control was 0.83.
Conclusion
Durable radiation response was associated with alterations of DNA repair pathway and smoking somatic signature. Bayesian network model could provide helpful insights for high precision radiotherapy. However, these findings should be verified in prospective cohort for further individualization.

Citations

Citations to this article as recorded by

Predicting radiation-acute esophagitis via machine learning algorithms
Mostafa Alizade-Harakiyan, Amin Khodaei, Hamed Zamani, Hamed Jalili-Majdi, Asghar Mesbahi
Computational Biology and Chemistry.2025; 119: 108592. CrossRef
Estimating the risk and benefit of radiation therapy in (y)pN1 stage breast cancer patients: A Bayesian network model incorporating expert knowledge (KROG 22–13)
Bum-Sup Jang, Seok-Joo Chun, Hyeon Seok Choi, Ji Hyun Chang, Kyung Hwan Shin
Computer Methods and Programs in Biomedicine.2024; 245: 108049. CrossRef
Prediction of Overall Disease Burden in (y)pN1 Breast Cancer Using Knowledge-Based Machine Learning Model
Seok-Joo Chun, Bum-Sup Jang, Hyeon Seok Choi, Ji Hyun Chang, Kyung Hwan Shin
Cancers.2024; 16(8): 1494. CrossRef
Selection of patients with pancreatic adenocarcinoma who may benefit from radiotherapy
I-Shiow Jan, Hui Ju Ch’ang
Radiation Oncology.2023;[Epub] CrossRef
Characterization of the gene signature correlated with favorable response to chemoradiotherapy in rectal cancer: A hypothesis‐generating study
Seung Hyuck Jeon, Eui Kyu Chie
Cancer Medicine.2023; 12(7): 8981. CrossRef
Krüppel-like Factor 10 as a Prognostic and Predictive Biomarker of Radiotherapy in Pancreatic Adenocarcinoma
Yi-Chih Tsai, Min-Chieh Hsin, Rui-Jun Liu, Ting-Wei Li, Hui-Ju Ch’ang
Cancers.2023; 15(21): 5212. CrossRef

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