Molecular Classification Of Gastric Cancer Research Articles

Current development of molecular classifications of gastric cancer based on omics (Review).

Gastric cancer (GC) is a complex and heterogeneous disease with significant phenotypic and genetic variation. Traditional classification systems rely mainly on the evaluation of clinical pathological features and conventional biomarkers and might not capture the diverse clinical processes of individual GCs. The latest discoveries in omics technologies such as next‑generation sequencing, proteomics and metabolomics have provided crucial insights into potential genetic alterations and biological events in GC. Clustering strategies for identifying subtypes of GC might offer new tools for improving GC treatment and clinical trial outcomes by enabling the development of therapies tailored to specific subtypes. However, the feasibility and therapeutic significance of implementing molecular classifications of GC in clinical practice need to addressed. The present review examines the current molecular classifications, delineates the prevailing landscape of clinically relevant molecular features, analyzes their correlations with traditional GC classifications, and discusses potential clinical applications.

Molecular classifications of gastric cancer and their clinical potential

Gastric cancer if the 5th most common oncological disease in the world and one of the leading causes of death associated with this pathology. In clinical practice, the Lauren classification is widely used for gastric cancer characterization, but it does not provide accurate information on tumor progression and does not allow to select the optimal therapeutic approach. More modern tumor typologies, for example proposed by the The Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG), are based on profiling of molecular changes in the tumor genome. Currently, several new classifications exist dividing gastric cancer into groups depending on response to different treatment, for example, checkpoint inhibitors or therapy based on activity of pathological pathways associated with immunity, DNA repair, oncogenic and stromal signatures. The proposed typologies improve diagnosis and treatment of this pathology. The review describes currently available classifications of gastric tumors and considers their practical potential.

PHGDH preserves one-carbon cycle to confer metabolic plasticity in chemoresistant gastric cancer during nutrient stress

Molecular classification of gastric cancer (GC) identified a subgroup of patients showing chemoresistance and poor prognosis, termed SEM (Stem-like/Epithelial-to-mesenchymal transition/Mesenchymal) type in this study. Here, we show that SEM-type GC exhibits a distinct metabolic profile characterized by high glutaminase (GLS) levels. Unexpectedly, SEM-type GC cells are resistant to glutaminolysis inhibition. We show that under glutamine starvation, SEM-type GC cells up-regulate the 3 phosphoglycerate dehydrogenase (PHGDH)-mediated mitochondrial folate cycle pathway to produce NADPH as a reactive oxygen species scavenger for survival. This metabolic plasticity is associated with globally open chromatin structure in SEM-type GC cells, with ATF4/CEBPB identified as transcriptional drivers of the PHGDH-driven salvage pathway. Single-nucleus transcriptome analysis of patient-derived SEM-type GC organoids revealed intratumoral heterogeneity, with stemness-high subpopulations displaying high GLS expression, a resistance to GLS inhibition, and ATF4/CEBPB activation. Notably, coinhibition of GLS and PHGDH successfully eliminated stemness-high cancer cells. Together, these results provide insight into the metabolic plasticity of aggressive GC cells and suggest a treatment strategy for chemoresistant GC patients.

Epigenetic Modification-Associated Molecular Classification of Gastric Cancer

Epigenetic modification is involved in tumorigenesis and cancer progression. We developed an epigenetic modification-associated molecular classification of gastric cancer (GC) to identify signature genes that accurately predict prognosis and the efficacy of immunotherapy. Least absolute shrinkage and selection operator and multivariate Cox regression analysis were conducted to develop an epigenetic modification-associated molecular classification. We investigated the significance of PIP4P2, an independent prognostic factor of the classification system, in predicting the prognosis and immunotherapy efficacy of patients with GC. The epigenetic modification-associated molecular classification was highly associated with the clinicopathological characteristics of patients and the existing classification of GC. PIP4P2 was highly expressed in GC tissue and tumor-associated macrophages. High PIP4P2 expression in GC tissue-induced tumor progression by activating PI3K/AKT signal transduction had a negative impact on immunotherapy efficacy. High expression of PIP4P2 in macrophages was correlated with poor prognosis in patients with GC. PIP4P2 is an independent unfavorable prognostic factor of epigenetic modification-associated molecular classification, is involved in tumorigenic progression, and is essential for assessing the prognosis and immunotherapy efficacy of GC.

The crosstalk between the RNA demethylase, non‐coding RNAs, and transcription factors in gastric cancer: An ALKBH5 perspective

The crosstalk between the RNA demethylase, non‐coding RNAs, and transcription factors in gastric cancer: An ALKBH5 perspective

Immunohistochemistry-based molecular classification of gastric cancer in India: How are we different?

462 Background: TCGA and ACRG have classified gastric cancer (GC) into molecular subgroups using genomics. We attempted to classify GC from our region using IHC (Immunohistochemistry) to understand its prognostic significance and compare with similar data from other parts of the world. Methods: This was a retrospective cohort of GC patients from years 2017-18. EBV (LMP), MSI (MLH1, MSH2, PMS2, MSH6),p53, E-cadherin and PIK3CA were assessed by IHC. Clinicopathological characteristics and survival were evaluated for association with molecular subtypes as defined by TCGA and ACRG classification system. Results: A total of 191patients were included with EBV positivity 35 (18.3 %), MSI 33(17.3 %), p-53 aberration 25(13.1%), E-cadherin negative (29.3%). On univariate analysis, p53 aberration was associated with higher age (>60 yrs), E- cadherin negative with diffuse histology & antro-pyloric region as predominant site. MSI with intestinal histology & antro-pyloric region as predominant site with MSI. The TCGA classification revealed EBV 35 (18%), MSI 28 (15 % ), GS 48 (25 %) and CIN 80 (42% ) subtypes respectively. CIN subtype was seen predominantly above 40 yrs of age (P=0.04), GS subtype was frequently associated with diffuse histology P<0.0001. The ACRG classification revealed MSI 33(17%), MSS/EMT 51 (26.7%), MSS/ p53 normal 91 (47.6%) and MSS/p53 aberrant 16 (8.4) subtypes. MSS/E-cad- subtype was associated with diffuse histology. PIK3CA positivity was higher in CIN (TCGA )& MSI (dmr) (ACRG) respectively. The median OS in MSI was 35 and 32 months higher compared to other subtypes (P<0.0001) in TCGA and ACRG classification respectively. Conclusions: The TCGA and ACRG classification identified molecular subtypes based on IHC from our region and significantly correlated with clinical factors and survival. PIK3CA as an additional marker may be further explored to be included in the classification system. Abbreviation: EBV - Epstein–Barr-virus, MSI – Microsatellite-Instability, GS- Genomic-instability, CIN- Chromosomal-instability, MSS- Microsatellite-stable, EMT-Epithelial-mesenchymal-transition.[Table: see text]

RHOJ Induces Epithelial-to-Mesenchymal Transition by IL-6/STAT3 to Promote Invasion and Metastasis in Gastric Cancer.

Background: Recently, the molecular classification of gastric cancer (GC) promotes the advances of GC patients' precision therapy and prognosis prediction. According to the Asian Cancer Research Group (ACRG), GC is classified as microsatellite instable (MSI) subtype GC, microsatellite stable/epithelial-to-mesenchymal transition (MSS/EMT) subtype GC, MSS/TP53- subtype GC, and MSS/TP53+ subtype GC. Due to the easy metastasis of EMT-subtype GC, it has the worst prognosis, the highest recurrence rate, and the tendency to occur at a younger age. Therefore, it is curious and crucial for us to understand the molecular basis of EMT-subtype GC. Methods: The expression of RHOJ was detected by quantitative real-time PCR (qPCR) and immunohistochemistry (IHC) in GC cells and tissues. Western blotting and immunofluorescence (IF) were conducted to examine the effects of RHOJ on the EMT markers' expression of GC cells. The GC cells' migration and invasion were investigated by transwell assay. The tumor growth and metastasis were demonstrated correspondingly in different xenograft models. Results: Firstly, it was noticed that RHOJ was significantly upregulated in EMT-subtype GC and RHOJ has close relationships with the EMT process of GC, based on the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Next, transwell assay and tail vein metastasis models were conducted to verify that RHOJ mediates the EMT to regulate the invasion and metastasis of GC in vitro and in vivo. In addition, weakened tumor angiogenesis was observed after RHOJ knockdown by the angiogenesis assay of HUVEC. RNA-seq and further study unveiled that RHOJ aggravates the malignant progression of GC by inducing EMT through IL-6/STAT3 to promote invasion and metastasis. Finally, blocking the IL-6/STAT3 signaling overcame RHOJ-mediated GC cells' growth and migration. Conclusions: These results indicate that the upregulation of RHOJ contributes to EMT-subtype GC invasion and metastasis via IL-6/STAT3 signaling, and RHOJ is expected to become a promising biomarker and therapeutic target for EMT-subtype GC patients.

A molecular classification of gastric cancer associated with distinct clinical outcomes and validated by an XGBoost-based prediction model

Gastric cancer (GC) is a heterogeneous disease and a leading cause of cancer-related deaths. Discovering robust, clinically relevant molecular classifications is critical for guiding personalized therapies for GC. Here, we propose a refined molecular classification scheme for GC using integrated optimal algorithms and multi-omics data. Based on the important features of mRNA, microRNA, and DNA methylation data selected by the multivariate Cox regression model, three subtypes linked to distinct clinical outcomes were identified by combining similarity network fusion and consensus clustering methods. Three subtypes were validated by an extreme gradient boosting machine learning prediction model with 125 differentially expressed genes in multiple independent cohorts. The molecular characteristics of mutation signatures, characteristic gene sets, driver genes, and chemotherapy sensitivity for each subtype were also identified: subtype 1 was associated with favorable prognosis and characterized by high ARID1A and PIK3CA mutations, subtype 2 was associated with a poor prognosis and harbored high recurrent TP53 mutations, and subtype 3 was associated with high CHD1, APOA1 mutations, and a poor prognosis. The proposed three-subtype scheme achieved a better clinical prediction performance (area under the curve value= 0.71) than The Cancer Genome Atlas classification, which may provide a practical subtyping framework to improve the treatment of GC.

Molecular Classification of Gastric Cancer With Emphasis on PDL-1 Expression: The First Report From Iran.

Background:Gastric cancer is one of the lethal cancers and there is no effective treatment for these patients and still, 5-year survival rate is about 25% to 30%. Finding reliable biomarkers for early-stage diagnosis, targeted therapy, and survival prediction is a priority in this cancer.Objectives:In this study we were trying to know about the molecular classification of gastric cancers in a group of patients from the South of Iran.Patients and Methods:In a cross sectional study, 50 specimens of gastric cancer were selected that have enough tissue to be stained by immunohistochemistry (IHC). IHC was performed for Her-2, mismatch repair genes (MLH-1, MSH-2, MSH-6, and PMS-2), and PDL-1. Frequency of positive makers was compared with survival and outcome.Results and Conclusion:In our study, deficient MMR (dMMR) was detected in 4 patients (8.0%). PD-L1 expression in tumor cells (TC) was observed in 1 of 4 cases (25%) with PMS2 loss. However, PD-L1 in TCs and TILs (tumor infiltrating lymphocytes) was negative in 1 case with MLH1 loss and in 3 of 4 cases with PMS2 loss, which was not statistically significant. All of our 50 cases were positive for MSH2 and MSH6, 24% of which showed TCs with PDL-1 expression and 32% of them in TIL. HER2 was positive in 2 (2/50, 4.0%) cases, among which all of the cases were positive for PD-L1 expression in TCs and TILs, respectively. However, in HER2-negative group, 26.2% (11/42) and 28.6% (12/42) of tumors were positive for PD-L1 in TCs and TILs, respectively. The expression rate of PD-L1 in HER2 negative TCs was significantly higher than that in HER2 positive TCs (P = .033). Immunohistochemistry for Her-2 was equivocal in 6 cases (12.0%) none of which expressed PD-L1 in tumor cells. In our study minimum and maximum survival times from detection of gastric cancer were 1 and 87 months, respectively. The mean ± SD and median ± SD of overall survival time were 30.69 ± 4.88 and 18 ± 1.45 months, respectively. One and 3-year survival rates of 40% and 24%, respectively. PD-L1 expression was not associated with survival, but its expression was associated with intestinal type Lauren classification and negative HER-2. PD-L1 positivity in tumor cells or tumor infiltrating lymphocytes was not an independent prognostic factor in gastric cancer.

Identification and Development of Subtypes with Poor Prognosis in Gastric Cancer Based on Both Hypoxia and Immune Cell Infiltration.

PurposeHypoxia and immune cell infiltration play an important role in the progression and metastasis of gastric cancer. However, the molecular classification of gastric cancer combined with hypoxia and immune cell infiltration remains unknown.Materials and MethodsssGSEA was used to evaluate the hypoxic state and immune cell infiltration of 1059 gastric cancer samples collected from the GEO and TCGA database. Based on the results, unsupervised clustering was performed to obtain different gastric cancer subtypes. The differentially expressed genes related to OS between these subtypes were utilized for LASSO analysis to construct a prognostic signature (HIscore). Subsequently, small-molecule drugs were predicted using the Connectivity Map (CMAP) database.ResultsWe obtained three hypoxic-immune infiltration patterns (HIcluster A-C) with different prognoses and classified them as low hypoxic/low immune, high hypoxic/high immune, and low hypoxic/high immune subtypes. Based on the differential genes between HIclusters, we have also obtained other three gastric cancer subtypes (genecluster A-C) and a 13-gene signature (HIscore). At the same time, we extensively explored the clinical and transcriptome traits in different clusters and groups with high or low HIscore. We proved that HIscore is an independent prognostic biomarker and an indicator of genome stability and EMT. Using the CMAP database, we found 96 small-molecule drugs that could reverse the poor prognosis and could serve as therapeutic drugs, especially for gastric cancer patients with high HIscore.ConclusionOur study evaluated the hypoxic state and immune cell infiltration in gastric tumors, and identified different gastric cancer subtypes. In addition, we established a hypoxia-immune signature to predict prognosis which is tightly linked to tumor EMT and genomic stability. Based on HIscore, we used the CMAP database to explore small-molecule drugs that may have the potential in serving as therapeutic drugs.

The updated WHO classification of digestive system tumours-gastric adenocarcinoma and dysplasia.

The fifth edition of the World Health Organization (WHO) classification of digestive system tumours was published in 2019. The classification of invasive carcinoma is basically the same as in the fourth edition, but the description of each histological type has been updated, and some rare subtypes such as micropapillary carcinoma, gastric adenocarcinoma of the fundic gland type and undifferentiated carcinoma have been added and explained. Although this classification did not provide specific numerical criteria for the diagnosis of signet-ring cell carcinoma in poorly cohesive carcinoma, an additional study defined signet-ring cell carcinoma as having more than 90% signet-ring cells. The molecular classification of gastric cancer (Epstein-Barr virus-positive type, microsatellite instability type, genomically stable type, chromosomally unstable type) was additionally introduced. Many pages in the present classification have been devoted to precancerous lesions, and this article focuses on foveolar-type adenoma/dysplasia.

Methods for modeling tumor growth in mice in experimental studies of human gastric cancer

Gastric cancer (GC) is a group of malignant tumors originating from the gastric mucosa cells. The highest incidence of GC is recorded in Japan, China and Russia, and the lowest one in the USA and New Zealand. Extensive molecular genetic research of GC has revealed its heterogeneity associated with the genomic instability of the tumor and the complexity of its phenotype due to simultaneous changes in several oncogenes and suppressors. This was the basis for the creation of the GC classification by molecular subtypes. The creation of a realistic preclinical model is essential for translational GC studies. Cancer cell lines and xenografts derived from them are among the most common preclinical models. They are easy to generate, but they also have limitations, since these models cannot sufficiently reproduce the unique characteristics of each cancer patient. Patient-derived xenografts (PDX) are currently the best model for testing targets and predictors of response to therapy. PDX models are created by transplanting surgically resected human tumors into immunodeficient mice. These models maintain morphological similarity and replicate the molecular characteristics of parental tumors providing an indispensable tool for assessing anticancer drug response. Statistical data from preclinical studies with PDX models can significantly save the time and resources required for clinical trials. Transgenic and knockout mouse models are also widely used in scientific laboratories in order to study specific genetic pathways of oncogenesis and develop experimental therapy for GC. This review discusses the molecular classifications of GC and experimental murine models that reproduce cancer in situ and are a universal platform for preclinical research in experimental oncology.

Updates on the molecular classification of gastric cancer

胃癌作为全球最常见的恶性肿瘤之一，其病死率排名第三。胃癌发生的分子机制较复杂，分子分型方法有利于帮助临床制定个体化治疗方案，预测预后。胃癌的分型方法有很多，包括病理组织学分型、分子分型以及免疫分型等。本文通过介绍几种常见的分型方法，分析不同分型方法与治疗和预后的关系，为精准医疗提供参考。.

34P Validation of a new scoring system for molecular subtyping of gastric cancer

Molecular classification of gastric cancer may potentially provide tailored treatment options by predicting survival outcomes and patients’ response to therapy. In our prior study by Setia et al. [Modern Patho 29.7 (2016): 772-784], we identified five groups of gastric cancers based on Epstein–Barr virus (EBV) positivity, microsatellite instability (MSI), aberrant E-cadherin, and p53 expression (normal/aberrant). The aim of this study was to validate the association between these molecular subtypes and the prognosis of patients with gastric cancer from Romania. The molecular classification was reproduced in a retrospective cohort of 121 resected gastric cancers at Fundeni Clinical Institute, Bucharest. EBER in situ hybridization, p53, microsatellite instability, and E-cadherin expression were analyzed using immunohistochemical, RT-PCR and in situ hybridization techniques. EBV-positive gastric cancers represented 30% of the cases (n=36); microsatellite instable adenocarcinoma constituted 9% of the cases (n=11); aberrant expression of E-cadherin was identified in 17% (n=20) while aberrant p53 expression was noted in 34% (n=42) of the gastric cancers. The remaining patients with normal p53 expression represent 10% (n=12) of total cases. The MSI high subtype was associated with a significantly more favorable prognosis while gastric cancers with aberrant E-cadherin expression had the least favorable prognosis (log-rank, p=0.001). Patients with EBV cancer subtype had superior median overall survival compared to those with aberrant E-cadherin expression (p=0.04). The proposed molecular classification successfully stratified patients by survival. Our results demonstrated a trend for superior survival in the MSIhigh subtype and EBV-positive gastric adenocarcinomas. These data warrant further validation of this scoring system and the role of anti-tumor immunity in MSI-high and EBV-positive subtypes.

Molecular classification of gastric cancer predicts survival in patients undergoing radical gastrectomy based on project HOPE.

Gastric cancer (GC) has been classified based on molecular profiling like The Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG), and attempts have been made to establish therapeutic strategies based on these classifications. However, it is difficult to predict the survival according to these classifications especially in radically resected patients. We aimed to establish a new molecular classification of GC which predicts the survival in patients undergoing radical gastrectomy. The present study included 499 Japanese patients with advanced GC undergoing radical (R0/R1) gastrectomy. Whole-exome sequencing, panel sequencing, and gene expression profiling were conducted (High-tech Omics-based Patient Evaluation [Project HOPE]). We classified patients according to TCGA and ACRG subtypes, and evaluated the clinicopathologic features and survival. Then, we attempted to classify patients according to their molecular profiles associated with biological features and survival (HOPE classification). TCGA and ACRG classifications failed to predict the survival. In HOPE classification, hypermutated (HMT) tumors were selected first as a distinctive feature, and T-cell-inflamed expression signature-high (TCI) tumors were then extracted. Finally, the remaining tumors were divided by the epithelial-mesenchymal transition (EMT) expression signature. HOPE classification significantly predicted the disease-specific and overall survival (p < 0.001 and 0.020, respectively). HMT + TCI showed the best survival, while EMT-high showed the worst survival. The HOPE classification was successfully validated in the TCGA cohort. We established a new molecular classification of gastric cancer that predicts the survival in patients undergoing radical surgery.

Conrad Hal Waddington phenomenon and a novel molecular classification of gastric cancer

Conrad Hal Waddington phenomenon and a novel molecular classification of gastric cancer

Expression profiles of gastric cancer molecular subtypes in remnant tumors.

BACKGROUNDRemnant gastric cancer (RGC) is a carcinoma arising in the stomach remnant after previous gastric resection. It is frequently reported as a tumor with a poor prognosis and distinct biological features from primary gastric cancer (PGC). However, as it is less frequent, its profile regarding the current molecular classifications of gastric cancer has not been evaluated.AIMTo evaluate a cohort of RGC according to molecular subtypes of GC using a panel of immunohistochemistry and in situ hybridization to determine whether the expression profile is different between PGC and RGC.METHODSConsecutive RGC patients who underwent gastrectomy between 2009 and 2019 were assessed using seven GC panels: Epstein-Barr virus in situ hybridization, immunohistochemistry for mismatch repair proteins (MutL homolog 1, MutS homolog 2, MutS homolog 6, and PMS1 homolog 2), p53 protein, and E-cadherin expression. Clinicopathological characteristics and survival of these patients were compared to 284 PGC patients.RESULTSA total of 40 RGC patients were enrolled in this study. Compared to PGC, older age (P < 0.001), male (P < 0.001), lower body mass index (P = 0.010), and lower hemoglobin level (P < 0.001) were associated with RGC patients. No difference was observed regarding Lauren’s type and pathologic Tumor Node Metastasis stage between the groups. Regarding the profiles evaluated, EBV-positive tumors were higher in RGC compared to PGC (P = 0.039). The frequency of microsatellite instability, aberrant p53 immunostaining, and loss of E-cadherin expression were similar between RGC and PGC. Higher rates of simultaneous alterations in two or more profiles were observed in RGC compared to PGC (P < 0.001). According to the molecular classification, the subtypes were defined as EBV in nine (22.5%) cases, microsatellite instability in nine (22.5%) cases, genomically stable in one (2.5%) case, and chromosomal instability in 21 (52.5%) cases. There was no significant difference in survival between molecular subtypes in RGC patients.CONCLUSIONRGC was associated with EBV positivity and higher rates of co-altered expression profiles compared to PGC. According to the molecular classification, there was no significant difference in survival between the subtypes of RGC.

Protein expression-based classification of gastric cancer by immunohistochemistry of tissue microarray.

Recently, the Cancer Genome Atlas and Asian Cancer Research Group propose two new classifications system of gastric cancer by using multi-platforms of molecular analyses. However, these highly complicated and cost technologies have not yet been translated into full clinical utility. In addition, the clinicians are expected to gain more guidance of treatment for different molecular subtypes. In this study, we developed a panel of gastric cancer patients in population from Southern China using commercially accessible TMA and immunohistochemical technology. A cohort of 259 GC patients was classified into 4 subtypes on the basis of expression of mismatch repair proteins (PMS2, MLH1, MSH2, and MSH6), E-cadherin and p21 protein. We observed that the subtypes presented distinct prognosis. dMMR-like subtype was associated with the best prognosis, and E-cadherin-a subtype was associated with the worst prognosis. Patients with p21-High and p21-Ligh subtypes had intermediate overall survival. In multivariate analysis, the dMMR-like subtype remained an independent prediction power for overall survival in the model. We described a molecular classification of gastric cancers using clinically applicable assay. The biological relevance of the four subtypes was illustrated by significant differences in prognosis. Our molecular classification provided an effective and inexpensive screening tool for improving prognostic models. Nevertheless, our study should be considered preliminary and carries a limited predictive value as a single-center retrospective study.

Abstract 5293: A molecular classification of gastric cancer in Chilean patients

Abstract Objective: Incidence and mortality rates of gastric cancer (GC) are characterized by their geographical heterogeneity. In Chile, GC is the leading cause of cancer death. To date, GC patients' response to standard therapies remains limited. A molecular classification of GCs may deliver better stratifications. Herein, we obtained clinical data, protein expression and genetic profiles in a cohort of Chilean patients and present a molecular classification that correlated with overall survival (OS) rates. Methods: A total of 71 patients were included. Clinical data were obtained from medical records; protein expression was analyzed by a Tissue MicroArray. We also performed Next Generation Sequencing to assess p53 status (WT or Mut). Supervised clustering was used to generate a molecular classification. Kaplan-Meier method was used to calculate OS. Hazard ratio was calculated by Cox regression. Results: We defined 5 GC subgroups: Epstein-Barr virus+ (EBV, n=9; 13%), Microsatellite Instable (MSI, n=9; 13%), E-cadherin loss (EMT-like, n=12; 17%). The remaining patients (those MSS-/EBV-/not EMT-like) were classified either as p53 WT (n=21; 30%) or p53 Mutated (n=20; 28%). According to subgroups, 5-year survival rates were: MSI=77,8%; EBV=43.2%; p53WT=43.5%; p53Mut=25% and EMT-like=16.7%. Hazard ratios for p53Mut and EMT-like were 5.1 (IC 95%: 1.16-22.41; p=0.031) and 6.81 (IC 95%: 1.48-31.24; p=0.014), respectively against the MSI group used as reference. This association is maintained in a multivariate model using age, gender and stage. Conclusions: Our study defined 5 GC subgroups. These are associated to OS rates. EMT-like and p53Mut subgroups displayed poorer survival. Future studies should explore actionable targets in these subsets in order to improve their survival. Citation Format: Mauricio P. Pinto, Matias Muñoz-Medel, Miguel Cordova-Delgado, Ignacio N. Retamal, Gareth Owen, Maria Loreto Bravo, Ricardo Armisen, Marcelo Garrido. A molecular classification of gastric cancer in Chilean patients [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5293.

The Better Survival of MSI Subtype Is Associated With the Oxidative Stress Related Pathways in Gastric Cancer.

Background: Gastric cancer (GC) is the third leading fatal cancer in the world and its incidence ranked second among all malignant tumors in China. The molecular classification of GC, proposed by the The Cancer Genome Atlas (TCGA), was added to the updated edition (2019) of WHO classification for digestive system tumor. Although MSI and EBV subtypes appeared as ever-increasingly significant roles in immune checkpoint inhibitor therapy, the underlying mechanisms are still unclear.Methods: We systematically summarized the relationship between EBV, d-MMR/MSI-H subtypes and clinicopathological parameters in 271 GC cases. Furthermore, GSE62254/ACRG and TCGA-STAD datasets, originated from Gene Expression Omnibus (GEO) and TCGA respectively, were analyzed to figure out the prognosis related molecular characteristics by bioinformatics methods.Results: Patients with MSI subtype had better prognosis than the MSS subtype (P = 0.013) and considered as an independent biomarker by the univariate analysis (P = 0.017) and multivariate analysis (P = 0.050). While there was no significant difference between EBV positive and negative tissues (P = 0.533). The positive prognostic value conferred by MSI in different cohorts was revalidated via the clinical analysis of GSE62254/ACRG and TCGA-STAD datasets regardless of race. Then key gene module that tightly associated with better status and longer OS time for MSI cases was obtained from weighted gene co-expression network analysis(WGCNA). NUBP2 and ENDOG were screened from the gene cluster and oxidative phosphorylation, reactive oxygen species(ROS) and glutathione metabolism were analyzed to be the differential pathways in their highly expressed groups.Conclusions: Our results manifested the significant prognostic value of MSI in Chinese GC cohort and comparisons with other populations. More opportunities to induce apoptosis of cancer cells, led by the unbalance between antioxidant system and ROS accumulation, lay foundations for unveiling the better prognosis in MSI phenotype through the bioinformatics analysis.