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Immunohistochemistry Biomarkers Predict Survival in Stage II/III Gastric Cancer Patients: From a Prospective Clinical Trial.

ABSTRACT: 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.

SUBMITTER: Kim MH

PROVIDER: S-EPMC6473262 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Immunohistochemistry Biomarkers Predict Survival in Stage II/III Gastric Cancer Patients: From a Prospective Clinical Trial.

Kim Min Hwan MH Zhang Xianglan X Jung Minkyu M Jung Inkyung I Park Hyung Soon HS Beom Seung-Hoon SH Kim Hyo Song HS Rha Sun Young SY Kim Hyunki H Choi Yoon Young YY Son Taeil T Kim Hyoung-Il HI Cheong Jae-Ho JH Hyung Woo Jin WJ Noh Sung Hoon SH Chung Hyun Cheol HC

Cancer research and treatment 20180927 2

<h4>Purpose</h4>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.<h4>Materials and methods</h4>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 thymidyl ...[more]

PMID: 30282452

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Project description:Importance:The current staging system of gastric cancer is not adequate for defining a prognosis and predicting the patients most likely to benefit from chemotherapy. Objective:To construct a survival prediction model based on specific tumor and patient characteristics that enables individualized predictions of the net survival benefit of adjuvant chemotherapy for patients with stage II or stage III gastric cancer. Design, Setting, and Participants:In this multicenter retrospective analysis, a survival prediction model was constructed using data from a training cohort of 746 patients with stage II or stage III gastric cancer who satisfied the study's inclusion criteria and underwent surgery between January 1, 2004, and December 31, 2012, at Nanfang Hospital in Guangzhou, China. Patient and tumor characteristics were included as covariates, and their association with overall survival and disease-free survival with and without adjuvant chemotherapy was assessed. The model was internally validated for discrimination and calibration using bootstrap resampling. To externally validate the model, data were included from a validation cohort of 973 patients with stage II or stage III gastric cancer who met the inclusion criteria and underwent surgery at First Affiliated Hospital in Guangzhou, China, and at West China Hospital of Sichuan Hospital in Chendu, China, between January 1, 2000, and June 30, 2009. Data were analyzed from July 10, 2016, to September 1, 2016. Main Outcomes and Measures:Concordance index and decision curve analysis for each measure associated with postoperative overall survival and disease-free survival. Results:Of the 1719 patients analyzed, 1183 (68.8%) were men and 536 (31.2%) were women and the median (interquartile range) age was 57 (49-66) years. Age, location, differentiation, carcinoembryonic antigen, cancer antigen 19-9, depth of invasion, lymph node metastasis, and adjuvant chemotherapy were significantly associated with overall survival and disease-free survival, with P?<?.05. The survival prediction model demonstrated good calibration and discrimination, with relatively high bootstrap-corrected concordance indexes in the training and validation cohorts. In the validation cohort, the concordance index for overall survival was 0.693 (95% CI, 0.671-0.715) and for disease-free survival was 0.704 (95% CI, 0.681-0.728). Two nomograms and a calculating tool were built on the basis of specific input variables to estimate an individual's net survival gain attributable to adjuvant chemotherapy. Conclusions and Relevance:The survival prediction model can be used to make individualized predictions of the expected survival benefit from the addition of adjuvant chemotherapy for patients with stage II or stage III gastric cancer.

Project description:BackgroundEven though the post-operative outcome varies greatly among patients with nodal positive colon cancer (UICC stage III), personalized prediction of systemic disease recurrence is currently insufficient. We investigated in a retrospective setting whether genetic and immunological biomarkers can be applied for stratification of distant metastasis occurrence risk.MethodsEighty four patients with complete resection (R0) of stage III colon cancer from two clinical centres were analysed for genetic biomarkers: microsatellite instability, oncogenic mutations in KRAS exon2 and BRAF exon15, expression of osteopontin and the metastasis-associated genes SASH1 and MACC1. Tumor-infiltrating CD3 and CD8 positive T-cells were quantified by immunocytochemistry. Results were correlated with outcome and response to 5-FU based adjuvant chemotherapy, using Cox's proportional hazard models and integrative two-step cluster analysis.ResultsDistant metastasis risk was significantly correlated with oncogenic KRAS mutations (p?=?0.015), expression of SASH1 (p?=?0.016), and the density of CD8-positive T-cells (p?=?0.007) in Kaplan-Meier analysis. Upon multivariate Cox-regression analysis, KRAS mutation (p?=?0.008) and density of CD8-positive TILs (p?=?0.009) were retained as prognostic parameters for metachronous distant metastasis. Integrative two-step cluster analysis was used to combine all genetic markers, allowing stratification of patient subgroups. Post-operative distant metastasis risk ranged from 31% (low-risk) to 41% (intermediate), and 57% (high-risk) (p?=?0.032). Increased expression of osteopontin (p?=?0.019) and low density of CD8-positive T-cells (p?=?0.043) were significantly associated with unfavourable response to 5-FU.ConclusionsIntegrative biomarker analysis allows stratification of stage III colon cancer patients for the risk of metastatic disease recurrence and may indicate response to 5-FU. Thus, biomarker analysis might facilitate the use of adjuvant therapy for high risk patients.

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Immunohistochemistry Biomarkers Predict Survival in Stage II/III Gastric Cancer Patients: From a Prospective Clinical Trial.

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Immunohistochemistry Biomarkers Predict Survival in Stage II/III Gastric Cancer Patients: From a Prospective Clinical Trial.

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