Sarcopenia and a 5-mRNA risk module as a combined factor to predict prognosis for patients with stomach adenocarcinoma

Histomorphologic types of gastric cancer (GC) have significant prognostic values that should be considered during treatment planning. Because the thorough quantitative review of a tissue slide is a laborious task for pathologists, deep learning (DL) can be a useful tool to support pathologic workflow. In the present study, a fully automated approach was applied to distinguish differentiated/undifferentiated and non-mucinous/mucinous tumor types in GC tissue whole-slide images from The Cancer Genome Atlas (TCGA) stomach adenocarcinoma dataset (TCGA-STAD). By classifying small patches of tissue images into differentiated/undifferentiated and non-mucinous/mucinous tumor tissues, the relative proportion of GC tissue subtypes can be easily quantified. Furthermore, the distribution of different tissue subtypes can be clearly visualized. The patch-level areas under the curves for the receiver operating characteristic curves for the differentiated/undifferentiated and non-mucinous/mucinous classifiers were 0.932 and 0.979, respectively. We also validated the classifiers on our own GC datasets and confirmed that the generalizability of the classifiers is excellent. The results indicate that the DL-based tissue classifier could be a useful tool for the quantitative analysis of cancer tissue slides. By combining DL-based classifiers for various molecular and morphologic variations in tissue slides, the heterogeneity of tumor tissues can be unveiled more efficiently.

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Detecting Overlapping Gene Communities during Stomach Adenocarcinoma: A Discrete NMF-based Integrative Approach

2020 IEEE International Conference on Advent Trends in Multidisciplinary Research and Innovation (ICATMRI) ◽

10.1109/icatmri51801.2020.9398458 ◽

2020 ◽

Author(s):

Sk Md Mosaddek Hossain ◽

Sumanta Ray ◽

Anirban Mukhopadhyay

Keyword(s):

Integrative Approach ◽

Overlapping Gene ◽

Stomach Adenocarcinoma

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Ferroptosis-Related Long Non-Coding RNAs and the Roles of LASTR in Stomach Adenocarcinoma

10.21203/rs.3.rs-714235/v1 ◽

2021 ◽

Author(s):

Gongjun Wang ◽

Libin Sun ◽

Shasha Wang ◽

Jing Guo ◽

Hui Li ◽

...

Keyword(s):

Cox Regression ◽

Comprehensive Evaluation ◽

Progression Free Survival ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Differentially Expressed ◽

Sequencing Data ◽

Regulatory Relationship ◽

Data Resource ◽

Stomach Adenocarcinoma

Abstract Background: Ferroptosis is a form of cell death involved in diverse physiological context. Increasing evidence suggests that there is a closely regulatory relationship between ferroptosis and long noncoding RNAs (lncRNAs).Method: RNA-sequencing data from The Cancer Genome Atlas (TCGA) data resource and ferroptosis-related genes from FerrDb (http://www.zhounan.org/ferrdb/) data resource were employed to select differentially expressed lncRNAs. We performed Univariate Cox regression and multivariate Cox analyses analysis on these differentially expressed lncRNAs to screen independent predictive factors. Subsequently, we established two signatures for predicting overall survival (OS) and progression-free survival (PFS). Finally, experiments were conducted to verify the roles of LASTR in gastric cancer (GC).Results: We identified 12 differentially expressed lncRNAs linked with OS and 13 associated with PFS. Kaplan-Meier(K-M) analyses exhibited that the high-risk group was related to a poor prognosis of stomach adenocarcinoma (STAD). The AUCs of the OS, as well as PFS signatures of lncRNAs were 0.734 and 0.771, respectively, indicating their excellent efficacy in predicting STAD prognosis. Our experimental results illustrated that the inhibition of LASTR inhibited tumor proliferation and migration in GC.Conclusion: This comprehensive evaluation of the ferroptosis-related lncRNA landscape in STAD unearthed novel lncRNAs related to carcinogenesis. In addition, we also experimentally confirmed the effects of LASTR on proliferation, migration and ferroptosis. These results provide potential novel targets for tumor treatment and promote personalized medicine.

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MEX3A and MEX3B as Potential Prognostic Indicators in Stomach Adenocarcinoma

10.21203/rs.3.rs-599484/v1 ◽

2021 ◽

Author(s):

Junwei Zou ◽

Yong Huang ◽

Zhaoying Wu ◽

Hao Xie ◽

Rongsheng Wang ◽

...

Keyword(s):

Overall Survival ◽

Rna Splicing ◽

Rna Binding ◽

The Cancer Genome Atlas ◽

Prognostic Indicators ◽

Kaplan Meier ◽

Cancer Genome Atlas ◽

Stomach Adenocarcinoma ◽

Tumor Pathogenesis ◽

Kaplan Meier Plotter

Abstract Stomach adenocarcinoma(STAD) is one of the deadliest cancers in the world. The expression levels of family members of mex-3 RNA that bound MEX3A (member A) and MEX3B (member B) were high expressions in different cancers and interconnected to deficient prognosis. The present research assessed the potential regarding the expression of MEX3A and MEX3B in STAD by analysing the facts of STAD (viz. The Cancer Genome Atlas). TCGA, MEX3A and MEX3B in the cancers were analyzed using TIMER2.0, Kaplan Meier Plotter, and cBioPortal. The data was visualized using version 4.0.3 of R. We found MEX3A and MEX3B had various expressions regarding major cancer and relevant common tissues. Especially, high expression of MEX3A and MEX3B had relationships with the OS (namely overall survival) with deficiency and RFS (viz. relapse-free survival) concerning STAD. The expressions of MEX3B had correlations to T stage with P being 0.012 and to the race with P being 0.049. MEX3B was highly expressed in T3 and T4 stages, and was highly expressed in the white race. MEX3A mutation had a better survival without diseases, with P being 0.0205. However, the situation was different with non-overall survival, with P being 0.194, in comparison with the patients who did not have MEX3A change. MEX3A and MEX3B on tumor pathogenesis might be related to "RNA splicing" and "spliceosomal complex" and "single-stranded RNA binding". We further investigated the association between MEX3A and MEX3B and immune cells. The mast cells of the most connections to MEX3A (R=-0.300, P<0.001) and the NK cells were positively correlation with MEX3B (R=0.590, P<0.001). It showed that they might be potential prognostic molecular biomarkers in patients with STAD.

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Construction of Prognostic Prediction Model for Stomach Adenocarcinoma Based on the TCGA Database.

10.21203/rs.3.rs-114928/v1 ◽

2020 ◽

Author(s):

Zhengzhong Gu ◽

Xiaohan Cui ◽

Xudong Wang

Keyword(s):

Gastric Cancer ◽

Extracellular Matrix ◽

Protein Kinase ◽

Network Analysis ◽

Differentially Expressed Genes ◽

Differentially Expressed ◽

Stomach Adenocarcinoma ◽

Matrix Organization ◽

Prognostic Prediction ◽

New Biomarkers

Abstract Background: Prognostic prediction models have been developed to detect new biomarkers of gastric cancer (GC). The identification of new biomarkers could provide theoretical foundations for the application of molecular targeted therapy in advanced GC. The aim of this study was to construct a prognostic prediction model for stomach adenocarcinoma (STAD) based on The Cancer Genome Atlas (TCGA) database. Methods: First, we used the "limma" package to screen differentially expressed genes (DEGs) based on TCGA database. Gene ontology (GO) analysis was performed using the "ClusterProfiler" package. The interactions between proteins and the relationships between differentially expressed genes and clinical features were analyzed by protein-protein interaction (PPI) network analysis and weighted gene coexpression network analysis (WGCNA), respectively. Then, gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were used to identify differentially enriched pathways. The GenVisR package and CIBERSORT were used to identify mutations and assess immune infiltration. Finally, the expression of COL3A1 in STAD tissues was verified by reverse transcription quantitative polymerase chain reaction (RT-qPCR) and western blotting.Results: Six differentially expressed genes were screened out, namely, COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3. The enrichment results showed that differentially expressed genes were involved in multiple pathways in STAD, such as those related to the extracellular matrix, extracellular structure organization, and extracellular matrix organization. The differentially expressed genes were related to immune infiltration via the mitogen-activated protein kinase (MAPK) and phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT) pathways. The western blotting and RT-qPCR results suggested that COL3A1 was overexpressed in STAD tissues compared with normal tissues.Conclusion: COL3A1, ADAMTS12, BGN, FNDC1, AEBP1 and HTRA3 could play important roles in the tumorigenesis and progression of STAD via various pathways, including those involving the extracellular matrix, extracellular structure organization, and extracellular matrix organization. COL3A1, ADAMTS12, BGN, FNDC1, AEBP1, and HTRA3 act as oncogenes in most cancers and may be biomarkers. Additionally, the identification of COL3A1 as a candidate biomarker provides a direction for further research on the role of tumor immunity in gastric cancer.

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Identification of Early Diagnostic and Prognostic Biomarkers via WGCNA in Stomach Adenocarcinoma

Frontiers in Oncology ◽

10.3389/fonc.2021.636461 ◽

2021 ◽

Vol 11 ◽

Author(s):

Ruoyue Tan ◽

Guanghui Zhang ◽

Ruochen Liu ◽

Jianbing Hou ◽

Zhen Dong ◽

...

Keyword(s):

Gastric Cancer ◽

Extracellular Matrix ◽

Early Detection ◽

Early Stage ◽

Gene Set Enrichment Analysis ◽

Stage I ◽

Tyrosine Kinase Receptor ◽

Stomach Adenocarcinoma ◽

Early Diagnostic ◽

Potential Biomarkers

Stomach adenocarcinoma (STAD) is a leading cause of cancer deaths, and the outcome of the patients remains dismal for the lack of effective biomarkers of early detection. Recent studies have elucidated the landscape of genomic alterations of gastric cancer and reveal some biomarkers of advanced-stage gastric cancer, however, information about early-stage biomarkers is limited. Here, we adopt Weighted Gene Co-expression Network Analysis (WGCNA) to screen potential biomarkers for early-stage STAD using RNA-Seq and clinical data from TCGA database. We find six gene clusters (or modules) are significantly correlated with the stage-I STADs. Among these, five hub genes, i.e., MS4A1, THBS2, VCAN, PDGFRB, and KCNA3 are identified and significantly de-regulated in the stage-I STADs compared with the normal stomach gland tissues, which suggests they can serve as potential early diagnostic biomarkers. Moreover, we show that high expression of VCAN and PDGFRB is associated with poor prognosis of STAD. VCAN encodes a large chondroitin sulfate proteoglycan that is the main component of the extracellular matrix, and PDGFRB encodes a cell surface tyrosine kinase receptor for members of the platelet-derived growth factor (PDGF) family. Consistently, Gene Ontology (GO) analysis of differentially expressed genes in the STADs indicates terms associated with extracellular matrix and receptor ligand activity are significantly enriched. Protein-protein network interaction analysis (PPI) and Gene Set Enrichment Analysis (GSEA) further support the core role of VCAN and PDGFRB in the tumorigenesis. Collectively, our study identifies the potential biomarkers for early detection and prognosis of STAD.

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A novel microRNA signature predicts survival in stomach adenocarcinoma

Oncotarget ◽

10.18632/oncotarget.15961 ◽

2017 ◽

Vol 8 (17) ◽

pp. 28144-28153 ◽

Cited By ~ 4

Author(s):

Bowen Ding ◽

Xujie Gao ◽

Hui Li ◽

Liren Liu ◽

Xishan Hao

Keyword(s):

Stomach Adenocarcinoma

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Comprehensive Characterization of Transforming Growth Factor Beta Receptor 1 in Stomach Adenocarcinoma Identifies a Prognostic Signature for Predicting Clinical Outcomes and Immune Infiltrates

10.21203/rs.3.rs-1119461/v1 ◽

2021 ◽

Author(s):

Yi He ◽

Haiyang Zhang ◽

Yan Zhang ◽

Peiyun Wang ◽

Kegan Zhu ◽

...

Keyword(s):

Receiver Operating Characteristic ◽

Signaling Pathway ◽

Operating Characteristic ◽

Immune Cell ◽

Cell Infiltration ◽

Immune Cell Infiltration ◽

Prognostic Signature ◽

Pathologic Stage ◽

Stomach Adenocarcinoma ◽

Receiver Operating

Abstract Background: Stomach adenocarcinoma (STAD) is the common cancer and ranks third leading cause of cancer death worldwide. TGF‑β receptor 1 (TGFBR1), serving important roles in the TGF‑β family, the mechanisms whereby TGFβ2 governs tumor progression, immune cell infiltration and its correlation with tumor microenvironment (TME) in STAD remains unintelligible. Methods: First, we used the data in the TCGA, GEPIA, and HPA databases to explore the expression level of TGFBR1 in STAD, the correlation between TGFBR1 expression and the clinical features of STAD, its impact on the survival of STAD. Subsequently, a receiver operating characteristic (ROC) curve and nomogram were constructed and LASSO (the Least Absolute Shrinkage and Selection Operator)-selected features were used to build the TGFBR1 prognostic signature. Moreover, GSEA enrichment analysis is used to find the potential molecular mechanism of TGFBR1 to promote the malignant process of STAD. Finally, we further explored the influence of theTGFBR1 expression on the immune microenvironment of STAD patients through the TIMER2.0 and GEPIA database.Results: In our study, TGFBR1 expression was significantly elevated in patients with STAD and positively co-expression with pathologic stage, lymph node metastases (LNM) stage and histopathological grade of STAD. LASSO-selected features were used to build the TGFBR1 prognostic signature. 9 factors with non-zero coefficients were identified. The corresponding risk scores were computed, according to the following formula: Risk score = (-0.2914) *DIXDC1+ (0.1113) *STON1-GTF2A1L+(0.3092) *FERMT2+(-0.0146) *BHMT2+(0.1798) *ABCC9+(0.068) *MSRB3+(-0.1007) *SYNC+(-0.0891) *SORBS1+(0.0828) *TGFBR1.Survival analysis revealed that patients with high TGFBR1 had shorter OS, FP, and PPS. Multivariate Cox analysis revealed TGFBR1 was an independent prognostic factor for OS in STAD. The receiver operating characteristic (ROC) analysis suggested high diagnostic value with the area under curve (AUC) of TGFBR1 was 0.739, and a prognostic nomogram involving age, T, N, M classification, pathologic stage, primary therapy outcome, histologic grade and TGFBR1 to predict the 1, 3, 5-year OS was constructed. GSEA revealed that high TGFBR1 expression was correlated with pathway in cancer, MAPK signaling pathway, NOTCH signaling pathway, focal adhesion and VEGF-C production. ssGSEA showed that TGFBR1 is correlated with NK cells, Tem and Th17 cells. Furthermore, elevated TGFBR1 expression was found to be significantly correlated with several immune checkpoint and immune markers associated with immune cell subsets. Conclusion: In summary, TGFBR1 could be a prognostic biomarker and an important regulator of immune cell infiltration in STAD. The present study revealed the probable underlying molecular mechanisms of TGFBR1 in STAD and provided a potential target for improving the prognosis.

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Heterogeneity of MSI-H gastric cancer identifies a subtype with worse survival

Journal of Medical Genetics ◽

10.1136/jmedgenet-2019-106609 ◽

2020 ◽

Vol 58 (1) ◽

pp. 12-19 ◽

Cited By ~ 1

Author(s):

Yanmei Yang ◽

Zhong Shi ◽

Rui Bai ◽

Wangxiong Hu

Keyword(s):

Immune Checkpoint Blockade ◽

The Cancer Genome Atlas ◽

Consensus Clustering ◽

Synonymous Mutations ◽

The Poor ◽

Symptom Alleviation ◽

Cancer Genome Atlas ◽

Stomach Adenocarcinoma ◽

Asian Cohort ◽

Matrix Factorisation

BackgroundMicrosatellite instability-high (MSI-H) tumour patients generally have a better prognosis than microsatellite-stable (MSS) ones due to the large number of non-synonymous mutations. However, an increasing number of studies have revealed that less than half of MSI-H patients gain survival benefits or symptom alleviation from immune checkpoint-blockade treatment. Thus, an in-depth inspection of heterogeneous MSI-H tumours is urgently required.MethodsHere, we used non-negative matrix factorisation (non-NMF)-based consensus clustering to define stomach adenocarcinoma (STAD) MSI-H subtypes in samples from The Cancer Genome Atlas and an Asian cohort, GSE62254.ResultsMSI-H STAD samples are basically clustered into two subgroups (MSI-H1 and MSI-H2). Further examination of the immune landscape showed that immune suppression factors were enriched in the MSI-H1 subgroup, which may be associated with the poor prognosis in this subgroup.ConclusionsOur results illustrate the genetic heterogeneity within MSI-H STADs, with important implications for cancer patient risk stratification, prognosis and treatment.

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