Transcriptome Based System Biology Exploration Reveals Homogeneous Tumorigenicity of Alimentary Tract Malignancy

Malignancies of alimentary tract include esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ). Despite of their similarities in cancer development and progression, there are numerous researches concentrating on single tumor but relatively little on their common mechanisms. Our study explored the transcriptomic data of digestive tract cancers from The Cancer Genome Atlas database, yielding their common differentially expressed genes including 1,700 mRNAs, 29 miRNAs, and 362 long non-coding RNAs (lncRNAs). There were 12 mRNAs, 5 miRNAs, and 16 lncRNAs in the core competitive endogenous RNAs network by RNA-RNA interactions, highlighting the prognostic nodes of SERPINE1, hsa-mir-145, and SNHG1. In addition, the weighted gene co-expression network analysis (WGCNA) illustrated 20 gene modules associated with clinical traits. By taking intersections of modules related to the same trait, we got 67 common genes shared by ESCA and READ and screened 5 hub genes, including ADCY6, CXCL3, NPBWR1, TAS2R38, and PTGDR2. In conclusion, the present study found that SERPINE1/has-mir-145/SNHG1 axis acted as promising targets and the hub genes reasoned the similarity between ESCA and READ, which revealed the homogeneous tumorigenicity of digestive tract cancers at the transcriptome level and led to further comprehension and therapeutics for digestive tract cancers.

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Cancer Type-Dependent Correlations betweenTP53Mutations and Antitumor Immunity

10.1101/692715 ◽

2019 ◽

Author(s):

Lin Li ◽

Mengyuan Li ◽

Xiaosheng Wang

Keyword(s):

Antitumor Immunity ◽

Colon Adenocarcinoma ◽

Joint Effect ◽

The Cancer Genome Atlas ◽

Cancer Type ◽

Mutation Burden ◽

Cancer Genome Atlas ◽

Negative Role ◽

Stomach Adenocarcinoma ◽

Cancer Types

AbstractMany studies have shown thatTP53mutations play a negative role in antitumor immunity. However, a few studies reported thatTP53mutations could promote antitumor immunity. To explain these contradictory findings, we analyzed five cancer cohorts from The Cancer Genome Atlas (TCGA) project. We found thatTP53-mutated cancers had significantly higher levels of antitumor immune signatures thanTP53-wildtype cancers in breast invasive carcinoma (BRCA) and lung adenocarcinoma (LUAD). In contrast,TP53-mutated cancers had significantly lower antitumor immune signature levels thanTP53-wildtype cancers in stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and head and neck squamous cell carcinoma (HNSC). Moreover,TP53-mutated cancers likely had higher tumor mutation burden (TMB) and tumor aneuploidy level (TAL) thanTP53-wildtype cancers. However, the TMB differences were more marked betweenTP53-mutated andTP53-wildtype cancers than the TAL differences in BRCA and LUAD, and the TAL differences were more significant in STAD and COAD. Furthermore, we showed that TMB and TAL had a positive and a negative correlation with antitumor immunity and that TMB affected antitumor immunity more greatly than TAL did in BRCA and LUAD while TAL affected antitumor immunity more strongly than TMB in STAD and HNSC. These findings indicate that the distinct correlations betweenTP53mutations and antitumor immunity in different cancer types are a consequence of the joint effect of the altered TMB and TAL caused byTP53mutations on tumor immunity. Our data suggest that theTP53mutation status could be a useful biomarker for cancer immunotherapy response depending on cancer types.

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Identification of novel autophagy-related lncRNAs associated with a poor prognosis of colon adenocarcinoma through bioinformatics analysis

Scientific Reports ◽

10.1038/s41598-021-87540-0 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Dejun Wu ◽

Zhenhua Yin ◽

Yisheng Ji ◽

Lin Li ◽

Yunxin Li ◽

...

Keyword(s):

High Risk ◽

Poor Prognosis ◽

Notch Pathway ◽

Colon Adenocarcinoma ◽

High Risk Group ◽

The Cancer Genome Atlas ◽

Future Research ◽

Risk Patients ◽

Cancer Genome Atlas ◽

Immune Score

AbstractLncRNAs play a pivotal role in tumorigenesis and development. However, the potential involvement of lncRNAs in colon adenocarcinoma (COAD) needs to be further explored. All the data used in this study were obtained from The Cancer Genome Atlas database, and all analyses were conducted using R software. Basing on the seven prognosis-related lncRNAs finally selected, we developed a prognosis-predicting model with powerful effectiveness (training cohort, 1 year: AUC = 0.70, 95% Cl = 0.57–0.78; 3 years: AUC = 0.71, 95% Cl = 0.6–0.8; 5 years: AUC = 0.76, 95% Cl = 0.66–0.87; validation cohort, 1 year: AUC = 0.70, 95% Cl = 0.58–0.8; 3 years: AUC = 0.73, 95% Cl = 0.63–0.82; 5 years: AUC = 0.68, 95% Cl = 0.5–0.85). The VEGF and Notch pathway were analyzed through GSEA analysis, and low immune and stromal scores were found in high-risk patients (immune score, cor = − 0.15, P < 0.001; stromal score, cor = − 0.18, P < 0.001) , which may partially explain the poor prognosis of patients in the high-risk group. We screened lncRNAs that are significantly associated with the survival of patients with COAD and possibly participate in autophagy regulation. This study may provide direction for future research.

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Deep Learning for Automatic Subclassification of Gastric Carcinoma Using Whole-Slide Histopathology Images

Cancers ◽

10.3390/cancers13153811 ◽

2021 ◽

Vol 13 (15) ◽

pp. 3811

Author(s):

Hyun-Jong Jang ◽

In-Hye Song ◽

Sung-Hak Lee

Keyword(s):

Deep Learning ◽

Relative Proportion ◽

The Cancer Genome Atlas ◽

Cancer Tissue ◽

Mucinous Tumor ◽

Receiver Operating Characteristic Curves ◽

Tumor Tissues ◽

Cancer Genome Atlas ◽

Stomach Adenocarcinoma ◽

Tumor Types

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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Effect of Different Expression of Immune-Related lncRNA on Colon Adenocarcinoma and Its Relation to Prognosis

BioMed Research International ◽

10.1155/2020/6942740 ◽

2020 ◽

Vol 2020 ◽

pp. 1-9

Author(s):

Meiwei Mu ◽

Yi Tang ◽

Zheng Yang ◽

Yuling Qiu ◽

Xiaohong Li ◽

...

Keyword(s):

Cox Regression ◽

Colon Adenocarcinoma ◽

The Cancer Genome Atlas ◽

Risk Scores ◽

Future Research ◽

Sequencing Data ◽

Tissue Samples ◽

Gene Sets ◽

Cancer Genome Atlas ◽

Immune Related Genes

Objective. To explore the expression of immune-related lncRNAs in colon adenocarcinoma and find out the effect on how these lncRNAs influence the development and prognosis of colon adenocarcinoma. Method. Transcriptome data of colon adenocarcinoma from The Cancer Genome Atlas (TCGA) were downloaded, and gene sets “IMMUNE RESPONSE” and “IMMUNE SYSTEM PROCESS” were sought from the Molecular Signatures Database (MSigDB). The expression of immune-related genes was extracted that were immune-related mRNAs. Then, the immune-related lncRNAs were sought out by utilizing of the above data. Clinical traits were combined with immune-related lncRNAs, so that prognostic-related lncRNAs were identified by Cox regression. Multivariate Cox regression was built to calculate risk scores. Relationships between clinical traits and immune-related lncRNAs were also calculated. Result. A total of 480 colorectal adenocarcinoma patients and 41 normal control patients’ transcriptome sequencing data of tissue samples were obtained from TCGA database. 918 immune-related lncRNAs were screened. Cox regression showed that 34 immune-related lncRNAs were associated with colon adenocarcinoma prognosis. Seven lncRNAs were independent risk factors. Conclusion. This study revealed that some lncRNAs can affect the development and prognosis of colon adenocarcinoma. It may provide new theory evidence of molecular mechanism for the future research and molecular targeted therapy of colon adenocarcinoma.

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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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Identification of novel mRNA-miRNA-lncRNA competing endogenous RNA network associated with prognosis of breast cancer

Epigenomics ◽

10.2217/epi-2019-0209 ◽

2019 ◽

Vol 11 (13) ◽

pp. 1501-1518 ◽

Cited By ~ 6

Author(s):

Guansheng Zhong ◽

Weiyang Lou ◽

Minya Yao ◽

Chengyong Du ◽

Haiyan Wei ◽

...

Keyword(s):

Breast Cancer ◽

Gene Expression Omnibus ◽

The Cancer Genome Atlas ◽

Cancer Prognosis ◽

Competing Endogenous Rna ◽

Hub Genes ◽

Cerna Network ◽

Competing Endogenous Rna Network ◽

Cancer Genome Atlas ◽

Genome Atlas

Aim: To identify novel competing endogenous RNA (ceRNA) network related to patients prognosis in breast cancer. Materials & methods: Dysregulated mRNA based on intersection of three Gene Expression Omnibus and The Cancer Genome Atlas datasets were analyzed by bioinformatics. Results: In total 72 upregulated and 208 downregulated genes were identified. Functional analysis showed that some pathways related to cancer were significantly enriched. By means of stepwise reverse prediction and validation from mRNA to lncRNA, 19 hub genes, nine key miRNA and four key lncRNAs were identified by expression and survival analysis. Ultimately, the coexpression analysis identified RRM2-let-7a-5p- SNHG16/ MAL2 as key ceRNA subnetwork associated with prognosis of breast cancer. Conclusion: We successfully constructed a novel ceRNA network, among which each component was significantly associated with breast cancer 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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ITGB1-DT/ARNTL2 axis may be a novel biomarker in lung adenocarcinoma: a bioinformatics analysis and experimental validation

Cancer Cell International ◽

10.1186/s12935-021-02380-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Bai-Quan Qiu ◽

Xia-Hui Lin ◽

Song-Qing Lai ◽

Feng Lu ◽

Kun Lin ◽

...

Keyword(s):

Lung Cancer ◽

Lung Adenocarcinoma ◽

Cox Regression ◽

Malignant Tumors ◽

Expression Profiles ◽

The Cancer Genome Atlas ◽

Hub Genes ◽

Immune Infiltration ◽

Prognostic Effect ◽

Cancer Genome Atlas

Abstract Background Lung cancer is one of the most lethal malignant tumors that endangers human health. Lung adenocarcinoma (LUAD) has increased dramatically in recent decades, accounting for nearly 40% of all lung cancer cases. Increasing evidence points to the importance of the competitive endogenous RNA (ceRNA) intrinsic mechanism in various human cancers. However, behavioral characteristics of the ceRNA network in lung adenocarcinoma need further study. Methods Groups based on SLC2A1 expression were used in this study to identify associated ceRNA networks and potential prognostic markers in lung adenocarcinoma. The Cancer Genome Atlas (TCGA) database was used to obtain the patients' lncRNA, miRNA, and mRNA expression profiles, as well as clinical data. Informatics techniques were used to investigate the effect of hub genes on prognosis. The Cox regression analyses were performed to evaluate the prognostic effect of hub genes. The methylation, GSEA, and immune infiltration analyses were utilized to explore the potential mechanisms of the hub gene. The CCK-8, transwell, and colony formation assays were performed to detect the proliferation and invasion of lung cancer cells. Results We eventually identified the ITGB1-DT/ARNTL2 axis as an independent fact may promote lung adenocarcinoma progression. Furthermore, methylation analysis revealed that hypo-methylation may cause the dysregulated ITGB1-DT/ARNTL2 axis, and immune infiltration analysis revealed that the ITGB1-DT/ARNTL2 axis may affect the immune microenvironment and the progression of lung adenocarcinoma. The CCK-8, transwell, and colonu formation assays suggested that ITGB1-DT/ARNTL2 promotes the progression of lung adenocarcinoma. And hsa-miR-30b-3p reversed the ITGB1/ARNTL2-mediated oncogenic processes. Conclusion Our study identified the ITGB1-DT/ARNTL2 axis as a novel prognostic biomarker affects the prognosis of lung adenocarcinoma.

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Identification of Potential Signatures and Their Functions for Acute Lymphoblastic Leukemia: A Study Based on the Cancer Genome Atlas

Frontiers in Genetics ◽

10.3389/fgene.2021.656042 ◽

2021 ◽

Vol 12 ◽

Author(s):

Weimin Wang ◽

Chunhui Lyu ◽

Fei Wang ◽

Congcong Wang ◽

Feifei Wu ◽

...

Keyword(s):

Acute Lymphoblastic Leukemia ◽

Real Time ◽

Lymphoblastic Leukemia ◽

Cancer Genome ◽

The Cancer Genome Atlas ◽

Hub Genes ◽

Cerna Network ◽

Cancer Genome Atlas ◽

Genome Atlas ◽

Real Time Qpcr

ObjectiveAcute lymphoblastic leukemia (ALL) is a malignant disease most commonly diagnosed in adolescents and young adults. This study aimed to explore potential signatures and their functions for ALL.MethodsDifferentially expressed mRNAs (DEmRNAs) and differentially expressed long non-coding RNAs (DElncRNAs) were identified for ALL from The Cancer Genome Atlas (TCGA) and normal control from Genotype-Tissue Expression (GTEx). DElncRNA–microRNA (miRNA) and miRNA–DEmRNA pairs were predicted using online databases. Then, a competing endogenous RNA (ceRNA) network was constructed. Functional enrichment analysis of DEmRNAs in the ceRNA network was performed. Protein–protein interaction (PPI) network was then constructed. Hub genes were identified. DElncRNAs in the ceRNA network were validated using Real-time qPCR.ResultsA total of 2,903 up- and 3,228 downregulated mRNAs and 469 up- and 286 downregulated lncRNAs were identified for ALL. A ceRNA network was constructed for ALL, consisting of 845 lncRNA-miRNA and 395 miRNA–mRNA pairs. These DEmRNAs in the ceRNA network were mainly enriched in ALL-related biological processes and pathways. Ten hub genes were identified, including SMAD3, SMAD7, SMAD5, ZFYVE9, FKBP1A, FZD6, FZD7, LRP6, WNT1, and SFRP1. According to Real-time qPCR, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were significantly upregulated in ALL bone marrow samples compared to normal samples.ConclusionOur results showed the lncRNA expression profiles and constructed ceRNA network in ALL. Furthermore, eight lncRNAs including ATP11A-AS1, ITPK1-AS1, ANO1-AS2, CRNDE, MALAT1, CACNA1C-IT3, PWRN1, and WT1-AS were identified. These results could provide a novel insight into the study of ALL.

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