Survival-associated alternative splicing events interact with the immune microenvironment in stomach adenocarcinoma

Deep learning and machine learning approaches to classify stomach distant metastatic tumors using DNA methylation profiles

Distant metastasis of cancer is a significant contributor to cancer-related complications, and early identification of unidentified stomach adenocarcinoma is crucial for a positive prognosis. Changes inDNA methylation are being increasingly recognized as a crucial factor in predicting cancer progression. Within this research, we developed machine learning and deep learning models for distinguishing distant metastasis in samples of stomach adenocarcinoma based on DNA methylation profile. Employing deep neural networks (DNN), support vector machines (SVM), random forest (RF), Naive Bayes (NB) and decision tree (DT), and models for forecasting distant metastasis in stomach adenocarcinoma. The results show that the performance of DNN is better than that of other models, AUC and AUPR achieving 99.9 % and 99.5 % respectively. Additionally, a weighted random sampling technique was utilized to address the issue of imbalanced datasets, enabling the identification of crucial methylation markers associated with functionally significant genes in stomach distant metastasis tumors with greater performance.

A prognostic model established using bile acid genes to predict the immunity and survival of patients with gastrointestinal cancer

BACKGROUND

The metabolism of abnormal bile acids (BAs) is implicated in the initiation and development of gastrointestinal (GI) cancer. However, there was a lack of research on the molecular mechanisms of BAs metabolism in GI.

METHODS

Genes involved in BAs metabolism were excavated from public databases of The Cancer Genome Atlas (TCGA) database, Gene Expression Omnibus (GEO) database, and Molecular Signatures Database (MSigDB). ConsensusClusterPlus was used to classify molecular subtypes for GI. To develop a RiskScore model for predicting GI prognosis, univariate Cox analysis was performed on the genes in protein-protein interaction (PPI) network, followed by using Lasso regression and stepwise regression to refine the model and to determine the key prognostic genes. Tumor immune microenvironment in GI patients from different risk groups was assessed using the ESTIMATE algorithm and enrichment analysis. Reverse transcription-quantitative real-time PCR (RT-qPCR), Transwell assay, and wound healing assay were carried out to validate the expression and functions of the model genes.

RESULTS

This study defined three molecular subtypes (C1, C2, and C3). Specifically, C1 had the best prognosis, while C3 had the worst prognosis with high immune checkpoint gene expression levels and TIDE scores. We selected nine key genes (AXIN2, ATOH1, CHST13, PNMA2, GYG2, MAGEA3, SNCG, HEYL, and RASSF10) that significantly affected the prognosis of GI and used them to develop a RiskScore model accordingly. Combining the verification results from a nomogram, the prediction of the model was proven to be accurate. The high RiskScore group was significantly enriched in tumor and immune-related pathways. Compared with normal gastric mucosal epithelial cells, the mRNA levels of the nine genes were differential in the gastric cancer cells. Inhibition of PNMA2 suppressed migration and invasion of the cancer cells.

CONCLUSION

We distinguished three GI molecular subtypes with different prognosis based on the genes related to BAs metabolism and developed a RiskScore model, contributing to the diagnosis and treatment of patients with GI.

Prognostic value of RNA methylation-related genes in gastric adenocarcinoma based on bioinformatics

Background

Gastric cancer (GC) is a malignant tumor that originates from the epithelium of the gastric mucosa and has a poor prognosis. Stomach adenocarcinoma (STAD) covers 95% of total gastric cancer. This study aimed to identify the prognostic value of RNA methylation-related genes in gastric cancer.

Methods

In this study, The Cancer Genome Atlas (TCGA)-STAD and GSE84426 cohorts were downloaded from public databases. Patients were classified by consistent cluster analysis based on prognosis-related differentially expressed RNA methylation genes Prognostic genes were obtained by differential expression, univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. The prognostic model was established and validated in the training set, test set and validation set respectively. Independent prognostic analysis was implemented. Finally, the expression of prognostic genes was affirmed by reverse transcription quantitative PCR (RT-qPCR).

Results

In total, four prognostic genes (ACTA2, SAPCD2, PDK4 and APOD) related to RNA methylation were identified and enrolled into the risk signature. The STAD patients were divided into high- and low-risk groups based on the medium value of the risk score, and patients in the high-risk group had a poor prognosis. In addition, the RNA methylation-relevant risk signature was validated in the test and validation sets, and was authenticated as a reliable independent prognostic predictor. The nomogram was constructed based on the independent predictors to predict the 1/3/5-year survival probability of STAD patients. The gene set enrichment analysis (GSEA) result suggested that the poor prognosis in the high-risk subgroup may be related to immune-related pathways. Finally, the experimental results indicated that the expression trends of RNA methylation-relevant prognostic genes in gastric cancer cells were in agreement with the result of bioinformatics.

Conclusion

Our study established a novel RNA methylation-related risk signature for STAD, which was of considerable significance for improving prognosis of STAD patients and offering theoretical support for clinical therapy.

Transcription factor E2F3 activates CDC25B to regulate DNA damage and promote mitoxantrone resistance in stomach adenocarcinoma

BACKGROUND

CDC25B, as a member of the cell cycle regulating protein family, is located in the cytoplasm and is involved in the transition of the cell cycle and mitosis. CDC25B is highly expressed in various tumors and is a newly discovered oncogene. This study aimed to investigate the impact of CDC25B on mitoxantrone resistance in stomach adenocarcinoma (STAD) and its possible mechanisms.

METHODS

This study analyzed the expression of CDC25B and its potential transcription factor E2F3 in STAD, as well as the IC50 values of tumor tissues by bioinformatics analysis. Expression levels of CDC25B and E2F3 in STAD cells were measured by qRT-PCR. MTT was utilized to evaluate cell viability and IC50 values of STAD cells, and comet assay was utilized to analyze the level of DNA damage in STAD cells. Western blot was used to analyze the expression of DNA damage-related proteins. The targeting relationship between E2F3 and CDC25B was validated by dual-luciferase and ChIP assays.

RESULTS

Bioinformatics analysis and molecular experiments showed that CDC25B and E2F3 were highly expressed in STAD, and CDC25B was enriched in the mismatch repair and nucleotide excision repair pathways. The IC50 values of tumor tissues with high expression of CDC25B were relatively high. Dual-luciferase and ChIP assays confirmed that CDC25B could be transcriptionally activated by E2F3. Cell experiments revealed that CDC25B promoted mitoxantrone resistance in STAD cells by regulating DNA damage. Further research found that low expression of E2F3 inhibited mitoxantrone resistance in STAD cells by DNA damage, but overexpression of CDC25B reversed the impact of E2F3 knockdown on mitoxantrone resistance in STAD cells.

CONCLUSION

This study confirmed a novel mechanism by which E2F3/CDC25B mediated DNA damage to promote mitoxantrone resistance in STAD cells, providing a new therapeutic target for STAD treatment.

SRSF7 is a promising prognostic biomarker in hepatocellular carcinoma and is associated with immune infiltration

BACKGROUND

Previous studies indicate that the splicing process, regulated by the cellular machinery of tumors (spliceosome), undergoes alterations, leading to oncogenic splicing events associated with the progression of tumors towards aggressiveness. However, the role of serine/arginine-rich splicing factor 7 (SRSF7) in hepatocellular carcinoma (HCC) and the tumor microenvironment (TME) remains unclear.

METHODS

This study was aimed to explore the role and clinical significance of SRSF7 in HCC. By conducting functional analysis and gene set enrichment analysis, it was discovered that SRSF7 contributes to multiple pathways associated with immune response and tumor advancement. Further experiments verified that silencing of SRSF7 obviously inhibits progression of HCC.

RESULTS

Aberrant expression of SRSF7, which were referred as an independent prognostic risk factor, effectively predicts the prognosis of patients with HCC. Functional and gene enrichment analyses revealed that SRSF7 is linked with multiple immune and tumor progression-related pathways, including the B cell receptor signaling pathway, positive regulation of leukocyte and immunoglobulin receptor binding cell activation, nuclear division, membrane invagination, cell cycle, as well as mTOR signaling pathway. Furthermore, increased SRSF7 expression was associated with tumor-infiltrating inflammatory cells (CD4+, monocytes/macrophages, CD8 + and endothelial). Additionally, multiple immune checkpoint genes were markedly positively related to SRSF7. The efficiency of SRSF7 in predicting immunomodulator and chemokine responses were also assessed in microenvironment. Moreover, in vitro analyses demonstrated that knockdown of SRSF7 suppressed the malignant evolution of HCC possibly by deactivating the PI3K/AKT/mTOR signaling.

CONCLUSION

The role of SRSF7 in the tumor microenvironment has been successfully assessed. It may be a valid bio-index for predicting the HCC prognosis, thereby guiding individualized immunotherapy for cancer.

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

BACKGROUND

Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment.

METHODS

LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre).

RESULTS

AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the "p53 signaling pathway" and "cell cycle". Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified.

CONCLUSION

Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity.

Rab31 promotes metastasis and cisplatin resistance in stomach adenocarcinoma through Twist1-mediated EMT

Stomach adenocarcinoma (STAD) is one of the leading causes of cancer-related death globally. Metastasis and drug resistance are two major causes of failures in current chemotherapy. Here, we found that the expression of Ras-related protein 31 (Rab31) is upregulated in human STAD tissues and high expression of Rab31 is closely associated with poor survival time. Furthermore, we revealed that Rab31 promotes cisplatin resistance and metastasis in human STAD cells. Reduced Rab31 expression induces tumor cell apoptosis and increases cisplatin sensitivity in STAD cells; Rab31 overexpression yielded the opposite result. Rab31 silencing prevented STAD cell migration, whereas the overexpression of Rab31 increased the metastatic potential. Further work showed that Rab31 mediates cisplatin resistance and metastasis via epithelial-mesenchymal transition (EMT) pathway. In addition, we found that both Rab31 overexpression and cisplatin treatment results in increased Twist1 expression. Depletion of Twist1 enhances sensitivity to cisplatin in STAD cells, which cannot be fully reversed by Rab31 overexpression. Rab31 could activate Twist1 by activating Stat3 and inhibiting Mucin 1 (MUC-1). The present study also demonstrates that Rab31 knockdown inhibited tumor growth in mice STAD models. These findings indicate that Rab31 is a novel and promising biomarker and potential therapeutic target for diagnosis, treatment and prognosis prediction in STAD patients. Our data not only identifies a novel Rab31/Stat3/MUC-1/Twist1/EMT pathway in STAD metastasis and drug resistance, but it also provides direction for the exploration of novel strategies to predict and treat STAD in the future.

Cellular resistance to an oncolytic virus is driven by chronic activation of innate immunity

The emergence of cellular resistances to oncolytic viruses is an underexplored process that could compromise the efficacy of cancer virotherapy. Here, we isolated and characterized B16 mouse melanoma cells that evolved resistance to an oncolytic vesicular stomatitis virus (VSV-D51). RNA-seq revealed that resistance was associated to broad changes in gene expression, which typically involved chronic upregulation of interferon-stimulated genes. Innate immunity activation was maintained in the absence of the virus or other infection signals, and conferred cross-resistance to wild-type VSV and the unrelated Sindbis virus. Furthermore, we identified differentially expressed genes with no obvious role in antiviral immunity, such as Mnda, Psmb8 and Btn2a2, suggesting novel functions for these genes. Transcriptomic changes associated to VSV resistance were similar among B16 clones and in some clones derived from the mouse colon carcinoma cell line CT26, suggesting that oncolytic virus resistance involves certain conserved mechanisms and is therefore a potentially predictable process.

The Role of Alternative Splicing in Cancer: Regulatory Mechanism, Therapeutic Strategy, and Bioinformatics Application

[Formula: see text] Alternative splicing (AS) can generate distinct transcripts and subsequent isoforms that play differential functions from the same pre-mRNA. Recently, increasing numbers of studies have emerged, unmasking the association between AS and cancer. In this review, we arranged AS events that are closely related to cancer progression and presented promising treatments based on AS for cancer therapy. Obtaining proliferative capacity, acquiring invasive properties, gaining angiogenic features, shifting metabolic ability, and getting immune escape inclination are all splicing events involved in biological processes. Spliceosome-targeted and antisense oligonucleotide technologies are two novel strategies that are hopeful in tumor therapy. In addition, bioinformatics applications based on AS were summarized for better prediction and elucidation of regulatory routines mingled in. Together, we aimed to provide a better understanding of complicated AS events associated with cancer biology and reveal AS a promising target of cancer treatment in the future.

Comprehensive characterization of 11 prognostic alternative splicing events in ovarian cancer interacted with the immune microenvironment

Alternative splicing (AS) events play a crucial role in the tumorigenesis and progression of cancer. Transcriptome data and Percent Spliced In (PSI) values of ovarian cancer patients were downloaded from TCGA database and TCGA SpliceSeq. Totally we identified 1472 AS events that were associated with survival of ovarian serous cystadenocarcinoma (OC) and exon skipping (ES) was the most important type. Univariate and multivariate Cox regression analysis were performed to identify survival-associated AS events and developed the prognostic model based on 11-AS events. The immune cells and different response to cytotoxic T lymphocyte associated antigen 4 (CTLA-4) and programmed cell death protein 1 (PD-1) blockers in low-risk and high-risk group of OC patients were analyzed. Ten kinds of immune cells were found up-regulated in low-risk group. Activated B cell, natural killer T cell, natural killer cell and regulatory T cell were associated with survival of OC. The patients in low-risk group had good response to CTLA-4 and PD-1 blockers treatment. Moreover, a regulatory network was established according to the correlation between AS events and splicing factors (SFs). The present study provided valuable insights into the underlying mechanisms of OC. AS events that were correlated with the immune system might be potential therapeutic targets.

The pattern of alternative splicing in lung adenocarcinoma shows novel events correlated with tumorigenesis and immune microenvironment

Lung adenocarcinoma (LUAD) is the leading cause of cancer deaths worldwide due to the lack of early diagnostic markers and specific drugs. Previous studies have shown the association of LUAD growth with aberrant alternative splicing (AS). Herein, clinical data of 535 tumor tissues and 59 normal tissues were extracted from The Cancer Genome Atlas (TCGA) database. Each sample was analyzed using the ESTIMATE algorithm; a comparison between higher and lower score groups (stromal or immune) was made to determine the overall- and progression-free survival-related differentially expressed AS (DEAS) events. We then performed unsupervised clustering of these DEASs, followed by determining their relationship with survival rate, immune cells, and the tumor microenvironment (TME). Next, two prognostic signatures were developed using bioinformatics tools to explore the prognosis of cases with LUAD. Five OS- and six PFS-associated DEAS events were implemented to establish a prognostic risk score model. When compared to the high-risk group (HRG), the PFS and OS of the low-risk group (LRG) were found to be considerable. Additionally, a better prognosis was found considerably associated with the ESTIMATE score of the patients as well as immune cells infiltration. Our analysis of AS events in LUAD not only helps to clarify the tumorigenesis mechanism of AS but also provides ideas for revealing potential prognostic biomarkers and therapeutic targets.

Sulforaphane suppresses autophagy during the malignant progression of gastric carcinoma via activating miR-4521/PIK3R3 pathway

OBJECTIVE

Sulforaphane, which exerts an effective anti-cancer ability, is a phytochemical converted from cruciferous plants. Here, we aimed to identify whether sulforaphane could suppress autophagy during the malignant progression of gastric carcinoma and to explore the underlying mechanisms.

METHODS

SGC7901 cells were transfected with miR-4521 mimics, inhibitor, and pcDNA3.1-PIK3R3, and treated with sulforaphane or autophagy inhibitor. Cell proliferation, apoptosis, and miR-4521 or PIK3R3 expression were detected.

RESULTS

MiR-4521 over-expression suppressed LC3-II/I ratio and Beclin-1 expression but induced p62 expression in SGC7901 cells. MiR-4521 also reduced gastric carcinoma cell proliferation and promoted apoptosis in vitro. In the mechanical observation, we identified that miR-4521 directly targeted PIK3R3 to repress its expression, and PIK3R3 up-regulation partly antagonized miR-4521-mediated autophagy, proliferation, and apoptosis in gastric carcinoma cells. In addition, sulforaphane exerted effective anti-cancer functions by repressing autophagy and growth in tumor cells at a concentration-dependent way. MiR-4521 inhibition or PIK3R3 over-expression weakened the anti-cancer functions of sulforaphane in gastric carcinoma cells.

CONCLUSION

Consequently, miR-4521 suppressed autophagy during the malignant progression of gastric carcinoma by targeting PIK3R3. Thus, miR-4521 may be applied as a therapeutic target for sulforaphane in gastric carcinoma.