Cancer Research and Treatment

Xianglan Zhang

2 Articles

Immunohistochemistry Biomarkers Predict Survival in Stage II/III Gastric Cancer Patients: From a Prospective Clinical Trial: Min Hwan Kim, Xianglan Zhang, Minkyu Jung, Inkyung Jung, Hyung Soon Park, Seung-Hoon Beom, Hyo Song Kim, Sun Young Rha, Hyunki Kim, Yoon Young Choi, Taeil Son, Hyoung-Il Kim, Jae-Ho Cheong, Woo Jin Hyung, Sung Hoon Noh, Hyun Cheol Chung; Cancer Res Treat. 2019;51(2):819-831. Published online September 27, 2018; DOI: https://doi.org/10.4143/crt.2018.331

Abstract PDF Supplementary Material PubReader ePub

Purpose
Identification of biomarkers to predict recurrence risk is essential to improve adjuvant treatment strategies in stage II/III gastric cancer patients. This study evaluated biomarkers for predicting survival after surgical resection.
Materials and Methods
This post-hoc analysis evaluated patients from the CLASSIC trial who underwent D2 gastrectomy with or without adjuvant chemotherapy (capecitabine plus oxaliplatin) at the Yonsei Cancer Center. Tumor expressions of thymidylate synthase (TS), excision repair cross-complementation group 1 (ERCC1), and programmed death-ligand 1 (PD-L1) were evaluated by immunohistochemical (IHC) staining to determine their predictive values.
Results
Among 139 patients, IHC analysis revealed high tumor expression of TS (n=22, 15.8%), ERCC1 (n=23, 16.5%), and PD-L1 (n=42, 30.2%) in the subset of patients. Among all patients, high TS expression tended to predict poor disease-free survival (DFS; hazard ratio [HR], 1.80; p=0.053), whereas PD-L1 positivity was associated with favorable DFS (HR, 0.33; p=0.001) and overall survival (OS; HR, 0.38; p=0.009) in multivariate Cox analysis. In the subgroup analysis, poor DFS was independently predicted by high TS expression (HR, 2.51; p=0.022) in the adjuvant chemotherapy subgroup (n=66). High PD-L1 expression was associated with favorable DFS (HR, 0.25; p=0.011) and OS (HR, 0.22; p=0.015) only in the surgery-alone subgroup (n=73). The prognostic impact of high ERCC1 expression was not significant in the multivariate Cox analysis.
Conclusion
This study shows that high TS expression is a predictive factor for worse outcomes on capecitabine plus oxaliplatin adjuvant chemotherapy, whereas PD-L1 expression is a favorable prognostic factor in locally advanced gastric cancer patients.

Citations

Citations to this article as recorded by

Utility of TMPRSS4 as a Prognostic Biomarker and Potential Therapeutic Target in Patients with Gastric Cancer
Hirofumi Tazawa, Takahisa Suzuki, Akihisa Saito, Akira Ishikawa, Toshiaki Komo, Haruki Sada, Norimitsu Shimada, Naoto Hadano, Takashi Onoe, Takeshi Sudo, Yosuke Shimizu, Kazuya Kuraoka, Hirotaka Tashiro
Journal of Gastrointestinal Surgery.2022; 26(2): 305. CrossRef
Scoring systems for PD-L1 expression and their prognostic impact in patients with resectable gastric cancer
Marina Alessandra Pereira, Marcus Fernando Kodama Pertille Ramos, André Roncon Dias, Renan Ribeiro, Leonardo Cardili, Bruno Zilberstein, Ivan Cecconello, Ulysses Ribeiro, Evandro Sobroza de Mello, Tiago Biachi de Castria
Virchows Archiv.2021; 478(6): 1039. CrossRef
Epstein–Barr Virus Positive Gastric Cancer: A Distinct Subtype Candidate for Immunotherapy
Marina Alessandra Pereira, Daniel Amadeus Molon Batista, Marcus Fernando Kodama Pertille Ramos, Leonardo Cardili, Renan Ribeiro e Ribeiro, Andre Roncon Dias, Bruno Zilberstein, Ulysses Ribeiro Jr, Ivan Cecconello, Venâncio Avancini Ferreira Alves, Evandro
Journal of Surgical Research.2021; 261: 130. CrossRef
Cytotoxic T‐lymphocyte‐associated protein 4 in gastric cancer: Prognosis and association with PD‐L1 expression
Marina Alessandra Pereira, Tiago Biachi de Castria, Marcus Fernando Kodama Pertille Ramos, André Roncon Dias, Leonardo Cardili, Rafael Dyer Rodrigues de Moraes, Bruno Zilberstein, Sergio Carlos Nahas, Ulysses Ribeiro, Evandro Sobroza de Mello
Journal of Surgical Oncology.2021; 124(7): 1040. CrossRef
Remnant gastric cancer: a neglected group with high potential for immunotherapy
Marcus Fernando Kodama Pertille Ramos, Marina Alessandra Pereira, Tiago Biachi de Castria, Renan Ribeiro e Ribeiro, Leonardo Cardili, Evandro Sobroza de Mello, Bruno Zilberstein, Ulysses Ribeiro-Júnior, Ivan Cecconello
Journal of Cancer Research and Clinical Oncology.2020; 146(12): 3373. CrossRef
Molecular Bases of Mechanisms Accounting for Drug Resistance in Gastric Adenocarcinoma
Jose J. G. Marin, Laura Perez-Silva, Rocio I. R. Macias, Maitane Asensio, Ana Peleteiro-Vigil, Anabel Sanchez-Martin, Candela Cives-Losada, Paula Sanchon-Sanchez, Beatriz Sanchez De Blas, Elisa Herraez, Oscar Briz, Elisa Lozano
Cancers.2020; 12(8): 2116. CrossRef
Clinical Significance of CLDN18.2 Expression in Metastatic Diffuse-Type Gastric Cancer
Seo Ree Kim, Kabsoo Shin, Jae Myung Park, Han Hong Lee, Kyo Yong Song, Sung Hak Lee, Bohyun Kim, Sang-Yeob Kim, Junyoung Seo, Jeong-Oh Kim, Sang-Young Roh, In-Ho Kim
Journal of Gastric Cancer.2020; 20(4): 408. CrossRef
Prognostic and Predictive Factors for the Curative Treatment of Esophageal and Gastric Cancer in Randomized Controlled Trials: A Systematic Review and Meta-Analysis
van den Ende, ter Veer, Mali, van Berge Henegouwen, Hulshof, van Oijen, van Laarhoven
Cancers.2019; 11(4): 530. CrossRef

11,543 View
317 Download
9 Web of Science
8 Crossref

Use of a Combined Gene Expression Profile in Implementing a Drug Sensitivity Predictive Model for Breast Cancer: Xianglan Zhang, In-Ho Cha, Ki-Yeol Kim; Cancer Res Treat. 2017;49(1):116-128. Published online May 18, 2016; DOI: https://doi.org/10.4143/crt.2016.085

Abstract PDF PubReader ePub

Purpose
Chemotherapy targets all rapidly growing cells, not only cancer cells, and thus is often associated with unpleasant side effects. Therefore, examination of the chemosensitivity based on genotypes is needed in order to reduce the side effects. Materials and Methods Various computational approaches have been proposed for predicting chemosensitivity based on gene expression profiles. A linear regression model can be used to predict the response of cancer cells to chemotherapeutic drugs, based on genomic features of the cells, and appropriate sample size for this method depends on the number of predictors. We used principal component analysis and identified a combined gene expression profile to reduce the number of predictors
Results
The coefficients of determinanation (R²) of prediction models with combined gene expression and several independent gene expressions were similar. Corresponding F values, which represent model significances were improved by use of a combined gene expression profile, indicating that the use of a combined gene expression profile is helpful in predicting drug sensitivity. Even better, a prediction model can be used even with small samples because of the reduced number of predictors. Conclusion Combined gene expression analysis is expected to contribute to more personalized management of breast cancer cases by enabling more effective targeting of existing therapies. This procedure for identifying a cell-type-specific gene expression profile can be extended to other chemotherapeutic treatments and many other heterogeneous cancer types.

Citations

Citations to this article as recorded by

Clinical Oncogenomics and Personalized Medicine in Colorectal Cancer for the Surgeon: What We Need to Know and What the Future Holds
I. S. Reynolds, E. O’Connell, D. A. McNamara, J. H. M. Prehn, S. J. Furney, J. P. Burke
SN Comprehensive Clinical Medicine.2022;[Epub] CrossRef
OBIF: an omics-based interaction framework to reveal molecular drivers of synergy
Jezreel Pantaleón García, Vikram V Kulkarni, Tanner C Reese, Shradha Wali, Saima J Wase, Jiexin Zhang, Ratnakar Singh, Mauricio S Caetano, Humam Kadara, Seyed Javad Moghaddam, Faye M Johnson, Jing Wang, Yongxing Wang, Scott E Evans
NAR Genomics and Bioinformatics.2022;[Epub] CrossRef
Screening and Identification of Differentially Expressed Genes Expressed among Left and Right Colon Adenocarcinoma
Jing Han, Xue Zhang, Yang Yang, Li Feng, Gui-Ying Wang, Nan Zhang
BioMed Research International.2020; 2020: 1. CrossRef
Overexpression of miR-331 Indicates Poor Prognosis and Promotes Progression of Breast Cancer
Fuguo Jiang, Lei Zhang, Yunxia Liu, Yanhua Zhou, Honggang Wang
Oncology Research and Treatment.2020; 43(9): 441. CrossRef
Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis
Huan-Ming Hsu, Chi-Ming Chu, Yu-Jia Chang, Jyh-Cherng Yu, Chien-Ting Chen, Chen-En Jian, Chia-Yi Lee, Yueh-Tao Chiang, Chi-Wen Chang, Yu-Tien Chang
Scientific Reports.2019;[Epub] CrossRef
Prediction of Drug Target Sensitivity in Cancer Cell Lines Using Apache Spark
Shahid Hussain, Javed Ferzund, Raza Ul-Haq
Journal of Computational Biology.2019; 26(8): 882. CrossRef
Artificial Intelligence and Pharmacogenomics
Ravishankar K. Iyer, Arjun P. Athreya, Liewei Wang, Richard M. Weinshilboum
Advances in Molecular Pathology.2019; 2(1): 111. CrossRef

11,056 View
162 Download
7 Web of Science
7 Crossref

Author index