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Classification of gastric cancer by EBV status combined with molecular profiling predicts patient prognosis.

ABSTRACT: PURPOSE:To identify how Epstein-Barr virus (EBV) status combined with molecular profiling predicts the prognosis of gastric cancer patients and their associated clinical actionable biomarkers. EXPERIMENTAL DESIGN:A next-generation sequencing assay targeting 295 cancer-related genes was performed in 73 EBV-associated gastric cancer (EBVaGC) and 75 EBV-negative gastric cancer (EBVnGC) specimens and these results were compared with overall survival (OS). RESULTS:PIK3CA, ARID1A, SMAD4, and PIK3R1 mutated significantly more frequently in EBVaGC compared with their corresponding mutation rate in EBVnGC. As the most frequently mutated gene in EBVnGC (62.7%), TP53 also displayed a mutation rate of 15.1% in EBVaGC. PIK3R1 was revealed as a novel mutated gene (11.0%) associated almost exclusively with EBVaGC. PIK3CA, SMAD4, PIK3R1, and BCOR were revealed to be unique driver genes in EBVaGC. ARID1A displayed a significantly large proportion of inactivated variants in EBVaGC. A notable finding was that integrating the EBV status with tumor mutation burden (TMB) and large genomic instability (LGI) categorized the tumors into four distinct molecular subtypes and optimally predicted patient prognosis. The corresponding median OSs for the EBV+/TMB-high, EBV+/TMB-low, EBV-/LGI-, and EBV-/LGI+ subtypes were 96.2, 75.3, 44.4, and 20.2 months, respectively. The different subtypes were significantly segregated according to distinct mutational profiles and pathways. CONCLUSIONS:Novel mutations in PIK3R1 and TP53 genes, driver genes such as PIK3CA, SMAD4, PIK3R1, BCOR, and ARID1A, and distinguished genomic profiles from EBVnGC were identified in EBVaGC tumors. The classification of gastric cancer by EBV, TMB, and LGI could be a good prognostic indicator, and provides distinguishing, targetable markers for treatment.

SUBMITTER: He CY

PROVIDER: S-EPMC7240851 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Classification of gastric cancer by EBV status combined with molecular profiling predicts patient prognosis.

He Cai-Yun CY Qiu Miao-Zhen MZ Yang Xin-Hua XH Zhou Da-Lei DL Ma Jiang-Jun JJ Long Ya-Kang YK Ye Zu-Lu ZL Xu Bo-Heng BH Zhao Qi Q Jin Ying Y Lu Shi-Xun SX Wang Zhi-Qiang ZQ Guan Wen-Long WL Zhao Bai-Wei BW Zhou Zhi-Wei ZW Shao Jian-Yong JY Xu Rui-Hua RH

Clinical and translational medicine 20200101 1

<h4>Purpose</h4>To identify how Epstein-Barr virus (EBV) status combined with molecular profiling predicts the prognosis of gastric cancer patients and their associated clinical actionable biomarkers.<h4>Experimental design</h4>A next-generation sequencing assay targeting 295 cancer-related genes was performed in 73 EBV-associated gastric cancer (EBVaGC) and 75 EBV-negative gastric cancer (EBVnGC) specimens and these results were compared with overall survival (OS).<h4>Results</h4>PIK3CA, ARID1A ...[more]

PMID: 32508039

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Project description:Lauren-classification and human epidermal growth factor receptor 2 (HER2) status are two important pathological features of gastric cancer patients. The prognostic value of HER2 in gastric cancer remains controversial. Intestinal type gastric cancer has better prognosis and higher HER2 positive proportion. What is the interaction between these two factors? We hypothesized that a combination of Lauren-classification and human epidermal growth factor receptor 2 (HER2) status (L-H status) might be more meaningful than either factor alone.We collected 838 gastric cancer patients at all stages who had received treatment in our cancer center. This study was registered in the website of ClinicalTrials.Gov, with the number NCT01927146. We divided the patients into six groups according to their L-H status: Group A, HER2 negative and intestinal type; Group B, HER2 positive and intestinal type; Group C, HER2 negative and diffuse type; Group D, HER2 positive and diffuse type; Group E, HER2 negative and mixed type; and Group F, HER2 positive and mixed type.Diffuse type and intestinal type accounted for 51.0% and 33.9%, respectively. The proportion of HER2 positive patients was 11.2%, 25.4%, 2.1% and 10.2% in the whole patient group, intestinal, diffuse and mixed type, respectively. Median overall survival was 34.0 months, 25.3 months, 27.6 months, 19.2 months, 25.9 months and 26.4 months in the six groups patients, P?=?0.053. There was a significant difference in survival among the first four groups (P?<?0.001). HER2 was an independent prognostic factor in the intestinal type and in stage I?+?II patients, but not in the diffuse type or stage III?+?IV patients. L-H status was an independent prognostic factor in patients at all stages. For the diffuse and intestinal types, the multivariate analysis showed that HER2 was not an independent prognostic factor, while Lauren classification and L-H status were. Moreover, L-H status was a better prognostic factor than the Lauren classification.L-H status is a prognostic factor in diffuse and intestinal type patients, but not in the mixed type. Patients with HER2 negative and intestinal type had the best survival, while patients with HER2 positive status and diffuse type had the worst survival.

Project description:BackgroundGastric cancer (GC) is characterized by high morbidity and mortality rates, and the prognosis is not optimistic. Therefore, the search for new biomarkers is crucial. Methylation modifications in RNA modifications play a crucial role in tumors. However, the role of methylation modification of integrated m6A/m5C/m1A/m7G, in GC and its related analysis have not been reported. It still needs to be studied in depth. Our study aims to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provide new strategies for GC treatment.MethodsWe used TCGA-STAD (The Cancer Genome Atlas-Stomach Adenocarcinoma) as a training set and GSE84433 as a validation set to analyze and determine potential associations between m6A/m5C/m1A/m7G-related genes and clinical risk of GC. In addition, we explored the prognostic value and potential biological mechanisms of m6A/m5C/m1A/m7G-related genes in GC through consistent clustering, differential expression gene identification, enrichment analysis, and immune infiltration analysis. Finally, we constructed m6A/m5C/m1A/m7G-related risk signature (MRRS) to evaluate the correlation between risk grade and survival prognosis, drug sensitivity, and immune infiltration, and validated the validity by immunohistochemical staining.ResultsWe identified subgroups of C1, C2, and C3 patients by consensus clustering using data from 45 m6A/m5C/m1A/m7G-related genes. The three groups showed significant differences in survival, immune scores, and immune cell infiltration. We then constructed MRRS using least absolute shrinkage and selection operator (LASSO) regression analysis, including SLC5A6, FKBP10, GPC3, and GGH, which could accurately differentiate between high-/low-risk populations. Its accuracy was further validated in the validation set and immunohistochemical staining. These results suggest that m6A/m5C/m1A/m7G are closely related to the GC tumor immune microenvironment, and MRRS has good performance in predicting the survival of GC patients.ConclusionsIn this study, we highlighted the association of m6A/m5C/m1A/m7G subtypes with changes in the GC immunotumor microenvironment. We constructed and validated MRRS, which is valuable in predicting survival, immune infiltration and drug sensitivity in GC patients. This helps to deepen our understanding of m6A/m5C/m1A/m7G methylation and potentially provides new strategies for GC treatment.

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Classification of gastric cancer by EBV status combined with molecular profiling predicts patient prognosis.

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Classification of gastric cancer by EBV status combined with molecular profiling predicts patient prognosis.

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