Predictions for high COL1A1 and COL10A1 expression resulting in a poor prognosis in esophageal squamous cell carcinoma by bioinformatics analyses

A pathway-based computational framework for identification of a new modal of multi-omics biomarkers and its application in esophageal cancer

BACKGROUND

The pathway-based strategy has been recently proposed for identifying biomarkers with the advantages of higher biological interpretability and cross-data robustness than the conventional gene-based strategy. However, its utility in clinical applications has been limited due to the high computational complexity and ill-defined performance.

OBJECTIVE

The current study presents a machine learning-based computational framework using multi-omics data for identifying a new modal of biomarkers, called pathway-derived core biomarkers, which have the advantages of both gene-based and pathway-based biomarkers.

METHODS

Machine-learning methods and gene-pathway network were integrated to select the pathway-derived core biomarkers. Multiple machine-learning algorithms were used to construct and validate the diagnostic models of the biomarkers based on more than 1400 multi-omics clinical samples of esophageal squamous cell carcinoma (ESCC).

RESULTS

The results showed that the classifier models based on the new modal biomarkers achieved superior performance in the training datasets with an average AUC/accuracy of 0.98/0.95 and 0.89/0.81 for mRNAs and miRNA, respectively, higher than the currently known classifier models based on the conventional gene-based strategy and pathway-based strategy. In the testing cohorts, the AUC/accuracy increased by 6.1 %/7.3 % than the models based on the native gene-based biomarkers. The improved performance was further confirmed in independent validation cohorts. Specifically, the sensitivity/specificity increased by ∼3 % and the variance significantly decreased by ∼69 % compared with that of the native gene-based biomarkers. Importantly, the pathway-derived core biomarkers also recovered 45 % more previously reported biomarkers than the gene-based biomarkers and are more functionally relevant to the ESCC etiology (involved in 14 versus 7 pathways related with ESCC or other cancer), highlighting the cross-data robustness of this new modal of biomarkers via enhanced functional relevance.

CONCLUSIONS

The results demonstrated that the new modal of biomarkers not only have improved predicting performance and robustness, but also exhibit higher functional interpretability thus leading to the potential application in cancer diagnosis.

RNA sequencing reveals the implication of the circRNA-associated ceRNA network in oesophageal squamous cell carcinoma

Circular RNAs (circRNAs) have attracted increasing attention in cancer research. However, there are few studies about the high-throughput sequencing for clinical cohorts focussing on the expression characteristics and regulatory networks of circRNAs in oesophageal squamous cell carcinoma (ESCC) until now. Present study aim to comprehensively recognize the functional and mechanistic patterns of circRNA through constructing a circRNA-related competing endogenous RNA (ceRNA) network in ESCC. Summarily, RNA high-throughput sequencing was adopted to assess the circRNA, miRNA and mRNA expression profiles in ESCC. Through bioinformatics methods, a circRNA-miRNA-mRNA coexpression network was constructed and hub genes was identified. Finally, cellular function experiments combined with bioinformatics analysis were conducted to verify the identified circRNA was involved in the progression of ESCC through ceRNA mechanism. In this study, we established a ceRNA regulatory network, including 5 circRNAs, 7 miRNAs and 197 target mRNAs, and 20 hub genes were screened and identified to exert important roles in the progression of ESCC. As a verification, hsa_circ_0002470 (circIFI6) was revealed to be highly expressed in ESCC and regulate the expression of hub genes by absorbing miR-497-5p and miR-195-5p through ceRNA mechanism. Our results further indicated that silencing of circIFI6 repressed proliferation and migration of ESCC cells, highlighting the tumour promotion effects of circIFI6 in ESCC. Collectively, our study contributes a new insight into the progression of ESCC from the perspective of the circRNA-miRNA-mRNA network, shedding light on the circRNA research in ESCC.

LncRNA BBOX1-AS1 targets miR-361-3p/COL1A1 axis to drive the progression of oesophageal carcinoma

BACKGROUND

Oesophageal carcinoma (EC) is one of the types of prevalent malignant cancer in the globe. Many researchers reported the vital role played by long-coding RNAs in EC. In the current research, we investigated the mechanisms of the action of lncRNA BBOX1-AS1 in EC progression.

METHODS

In EC tissues and EC cells, the expression levels of miR-361-3p along with COL1A1 and BBOX1-AS1 were detected through RT-qPCR or western blotting. MiR-361-3p interactions with BBOX1-AS1 or COL1A1 were verified through Luciferase reporter and RIP tests. Loss of function combined with caspase-3 activity, CCK-8 and Transwell assays was performed to investigate cell apoptosis, proliferation and migration, respectively. Knockdown of BBOX1-AS1 was used for evaluating BBOX1-AS1 effects on tumour development in vivo.

RESULTS

BBOX1-AS1 was remarkably elevated in EC tissues and cells. In addition, the silencing of BBOX1-AS1 attenuated the cell viability, cell migration and enhanced cell apoptosis of EC, as well as suppressed EC tumour formation in vivo. Moreover, BBOX1-AS1 was found to be a sponge of miR-361-3p, which downregulated miR-361-3p expression. MiR-361-3p inhibitor rescued the anti-tumour effect of BBOX1-AS1 knockdown on the progression of EC. Furthermore, we discovered that miR-361-3p specially bound to COL1A1 3'UTR and downregulated COL1A1 and COL1A1 reduction declined the promoting effect of silencing miR-361-3p on EC cell malignant phenotypes.

CONCLUSION

BBOX1-AS1 facilitated the EC development and malignancy via miR-361-3p/COL1A1 axis, indicating BBOX1-AS1 could be a novel therapy target for the diagnostic of EC.

High expression COL10A1 promotes breast cancer progression and predicts poor prognosis

Background

As a common malignant disease in females, breast cancer (BCa) causes increasing numbers of cancer-related death. Collagen X alpha 1 chain (COL10A1) plays a critical role in the oncogenesis and progression of malignant tumors. However, a systematic analysis of COL10A1 in BCa has not been conducted.

Methods

The COL10A1 expression level and prognostic value in BCa were defined through the Cancer Genome Atlas (TCGA) as well as the Kaplan-Meier plotter data respectively. The expression pattern of COL10A1 was subsequently confirmed on tissue microarray (TMA) by immunochemistry (IHC) staining. Moreover, cellular functional assays which aimed to evaluate cell proliferation, migration, invasion, and apoptosis, were conducted to investigate the oncogenic activity of COL10A1 in BCa. Then, Tumor Immune Estimation Resource (TIMER) was adopted to determine the association between COL10A1 expression and immune cell infiltration.

Results

Bioinformatics analysis revealed that COL10A1 was significantly overexpressed and had notable prognostic value, especially for distant metastasis-free survival (DMFS) in BCa. Moreover, IHC analysis of 140 BCa tissues on TMA chips exhibited the overexpression of COL10A1 was correlated to advanced clinical stage, poor overall survival (OS), and worse recurrence-free survival (RFS). Besides, knockdown of COL10A1 remarkably suppressed cell proliferation, migration, and invasion in BCa cells, and notably promoted cell apoptosis as well. Furthermore, COL10A1 was positively associated with immune cell infiltration including B cell, CD8⁺ T cell, CD4⁺ T cell, macrophage, neutrophil, and dendritic cell.

Conclusion

The results revealed that COL10A1 is a novel oncogene and could serve as a potential prognostic biomarker in BCa. Besides, the downregulation of COL10A1 could inhibit BCa progression, which could be a potential target for BCa therapy.

High-Intensity Aerobic Exercise Suppresses Cancer Growth by Regulating Skeletal Muscle-Derived Oncogenes and Tumor Suppressors

High-intensity aerobic exercise (90% of the maximal heart rate) can effectively suppress cancer cell proliferation in vivo. However, the molecular effects of exercise and its relevance to cancer prevention remain uninvestigated. In this study, mice with colorectal cancer were subjected to high-intensity aerobic exercise, and mRNA-seq analysis was performed on the heart, lungs, and skeletal muscle tissues to analyze the genome-wide molecular effects of exercise. The skeletal muscle-derived genes with exercise-dependent differential expression were further evaluated for their effects on colorectal cancer cell viability. Compared to the results obtained for the control groups (healthy and cancer with no exercise), the regular and high-intensity aerobic physical activity in the mice produced positive results in comprehensive parameters (i.e., food intake, weight gain, and survival rate). A heatmap of differentially expressed genes revealed markedly different gene expression patterns among the groups. RNA-seq analysis of 23,282 genes expressed in the skeletal muscle yielded several anticancer effector genes (e.g., Trim63, Fos, Col1a1, and Six2). Knockdown and overexpression of selected anticancer genes repressed CT26 murine colorectal carcinoma cell proliferation by 20% (p < 0.05). Our findings, based on the aerobic exercise cancer mouse model, suggest that high-intensity aerobic exercise results in a comprehensive change in the expression patterns of genes, particularly those that can affect cancer cell viability. Such an approach may identify key exercise-regulated genes that can help the body combat cancer.

Collagen type X alpha 1 promotes proliferation, invasion and epithelial-mesenchymal transition of cervical cancer through activation of TGF-β/Smad signaling

Background

Collagen type X alpha 1 (COL10A1) belongs to the collagen family and constitutes the main component of the interstitial matrix. COL10A1 was found to be dysregulated in various cancers, and to participate in tumorigenesis. However, the role of COL10A1 in cervical cancer (CC) remains unclear.

Methods

Expression of COL10A1 in CC cells and tissues was detected by western blot and qRT-PCR. CC cells were transfected with pcDNA-COL10A1 or si-COL10A1, and the effect of COL10A1 on cell proliferation of CC was assessed by MTT and colony formation assays. Cell metastasis was detected by wound healing and transwell assays. Western blot was applied to evaluate epithelial-mesenchymal transition.

Results

COL10A1 was significantly elevated in CC tissues and cells (P < 0.001). Over-expression of COL10A1 increased cell viability of CC (P < 0.001), and enhanced the number of colonies (P < 0.001). However, knockdown of COL10A1 reduced the cell proliferation of CC (P < 0.001). Over-expression of COL10A1 also promoted cell migration (P < 0.001) and invasion (P < 0.001) of CC, whereas silencing of COL10A1 suppressed cell metastasis (P < 0.001). Protein level of E-cadherin in CC was reduced (P < 0.05), whereas N-cadherin and vimentin were enhanced by COL10A1 over-expression (P < 0.001). Silencing of COL10A1 reduced the protein level of TGF-β1 (P < 0.01), and down-regulated the phosphorylation of Smad2 and Smad3 in CC (P < 0.001).

Conclusion

Down-regulation of COL10A1 suppressed cell proliferation, metastasis, and epithelial-mesenchymal transition of CC through inactivation of TGF-β/Smad signaling.

Bioinformatics-based identification of miRNAs, mRNA, and regulatory signaling pathways involved in esophageal squamous cell carcinoma

Aim

The current study analyzed the miRNA microarray dataset (GSE66274) and gene expression microarray dataset (GSE38129) with similar samples to achieve a better understanding of miRNA-mRNA interactions.

Background

The most common form of esophageal cancer is esophageal squamous cell carcinoma (ESCC). While, miRNAs are well recognized as having a critical regulatory role in human cancer, their responsibilities and mechanisms of miRNA-mRNA in ESCC are unknown.

Methods

Differentially expressed miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were identified using the LIMMA package in R. In total, 478 DEmRNA (224 upregulated and 254 downregulated) and 39 DEmiRNA (15 upregulated and 24 downregulated) were screened. The RNAInter database analyzed miRNA-mRNA interactions; then, the miRNA-mRNA network was visualized by Cytoscape software. ClusterProfiler packages were used to perform gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses for DEmRNA as targets of DEmiRNAs.

Results

KEGG pathway analysis indicated that the p53 signaling pathway, ECM-receptor interaction, and AGE-RAGE signaling pathway were significant. Cellular response to amino acid stimulus, negative regulation of apoptotic signaling pathway, and endoderm formation were most prevalent in the biological process category. Additionally, the collagen-containing extracellular matrix, actomyosin complex collagen trimers, basement membrane, and extracellular matrix structural constituent were more enriched.

Conclusion

Overall, the present survey provides evidence that could support the prognosis of esophageal tumors in the future.