Abstract
BackgroundGastrointestinal adenocarcinoma (GIAD) has caused a serious disease burden globally. Targeted therapy for the transforming growth factor beta (TGF-β) signaling pathway is becoming a reality. However, the molecular characterization of TGF-β associated signatures in GIAD requires further exploration.MethodsMulti-omics data were collected from TCGA and GEO database. A pivotal unsupervised clustering for TGF-β level was performed by distinguish status of TGF-β associated genes. We analyzed differential mRNAs, miRNAs, proteins gene mutations and copy number variations in both clusters for comparison. Enrichment of pathways and gene sets were identified in each type of GIAD. Then we performed differential mRNA related drug response by collecting data from GDSC. At last, a summarized deep neural network for TGF-β status and GIADs was constracted.ResultsThe TGF-βhigh group had a worse prognosis in overall GIAD patients, and had a worse prognosis trend in gastric cancer and colon cancer specifically. Signatures (including mRNA and proteins) of the TGF-βhigh group is highly correlated with EMT. According to miRNA analysis, miR-215-3p, miR-378a-5p, and miR-194-3p may block the effect of TGF-β. Further genomic analysis showed that TGF-βlow group had more genomic changes in gastric cancer, such as TP53 mutation, EGFR amplification, and SMAD4 deletion. And drug response dataset revealed tumor-sensitive or tumor-resistant drugs corresponding to TGF-β associated mRNAs. Finally, the DNN model showed an excellent predictive effect in predicting TGF-β status in different GIAD datasets.ConclusionsWe provide molecular signatures associated with different levels of TGF-β to deepen the understanding of the role of TGF-β in GIAD and provide potential drug possibilities for therapeutic targets in different levels of TGF-β in GIAD.
Highlights
Cancer of the digestive tract share a large quantity of global cancer incidences. gastrointestinal adenocarcinomas (GIADs), including esophageal adenocarcinoma (ESAD), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectum adenocarcinoma (READ), revealed a nonnegligible global health burden in recent years [1]
In order to evaluate different Transforming growth factor beta (TGF-β) levels, two evaluation methods were used: (1) Unsupervised K-means clustering analysis based on the 39 mRNA of TGF-β-related signatures for each sample in GIAD; (2) Gene set variation analysis based on single sample gene-set enrichment analysis method was used to calculate the TGF-β score of each sample in GIAD
Identification of two TGF‐β subtypes based on the deep neural network (DNN) associated with TGF‐β signatures In order to better examine the application of TGF-β associated signatures in the classification of TGF-β subtypes, we developed a DNN model to identify TGF-β subtypes (Fig. 7a)
Summary
Cancer of the digestive tract share a large quantity of global cancer incidences. gastrointestinal adenocarcinomas (GIADs), including esophageal adenocarcinoma (ESAD), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectum adenocarcinoma (READ), revealed a nonnegligible global health burden in recent years [1]. Gastrointestinal adenocarcinomas (GIADs), including esophageal adenocarcinoma (ESAD), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), rectum adenocarcinoma (READ), revealed a nonnegligible global health burden in recent years [1]. As a prototypical factor in TGF-β family proteins, encoded by 33 genes in mammals, TGF-β is a multifunctional regulator involved in cell proliferation and differentiation [5], even in immune suppression within tumor microenvironment [6]. Some cell-surface transmembrane receptors with serine or threonine kinase activity can interact with activated TGF-βs, following phosphorylation of SMAD proteins, which regulate the expression of TGF-β target genes [7]. Targeted therapy for the transforming growth factor beta (TGF-β) signaling pathway is becoming a reality. The molecular characterization of TGF-β associated signatures in GIAD requires further exploration
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
