Bioinformatics approach reveals systematic mechanism underlying lung adenocarcinoma

Oncogenic mechanisms of COL10A1 in cancer and clinical challenges (Review)

Collagen type X α1 chain (COL10A1), a gene encoding the α‑1 chain of type X collagen, serves a key role in conferring tensile strength and structural integrity to tissues. Upregulation of COL10A1 expression has been observed in different malignancies, including lung, gastric and pancreatic cancer, and is associated with poor prognosis. The present review provides an updated synthesis of the evolving biological understanding of COL10A1, with a particular focus on its mechanisms of action and regulatory functions within the context of tumorigenesis. For example, it has been established that increased COL10A1 expression promotes cancer progression by activating multiple signaling pathways, including the TGF‑β1/Smad, MEK/ERK and focal adhesion kinase signaling pathways, thereby inducing proliferation, invasion and migration. Additionally, COL10A1 has been demonstrated to induce epithelial‑mesenchymal transition and reshapes the extracellular matrix within tumor tissues. Furthermore, on the basis of methyltransferase‑like 3‑mediated N6‑methyladenosine methylation, COL10A1 intricately regulates the epitranscriptomic machinery, thereby augmenting its oncogenic role. However, although COL10A1 serves a pivotal role in gene transcription and the orchestration of tumor growth, the question of whether COL10A1 would serve as a viable therapeutic target remains a subject of scientific hypothesis requiring rigorous examination. Variables such as distinct tumor microenvironments and treatment associations necessitate further experimental validation. Therefore, a comprehensive assessment and understanding of the functional and mechanistic roles of COL10A1 in cancer may pave the way for the development of innovative cancer treatment strategies.

A novel APA-based prognostic signature may predict the prognosis of lung adenocarcinoma in an East Asian population

The role of alternative polyadenylation (APA) in tumor development is becoming increasingly evident, but the impact of APA events on the prognosis of LUAD patients is unclear. Therefore, in the present study, we aimed to analyze specific APA events in LUAD to identify novel prognostic biomarkers for LUAD. We first identified prognostic candidate genes for LUAD associated with APA events and validated them in both the East Asian and the USA cohorts, finding that five genes (DCUN1D5, PSMC4, TFAM, THRA, and TMEM100) were of prognostic significance in both populations. Based on this, an APA-based prognostic signature was constructed for the East Asian population. The predictive accuracy of the prognostic signature was further evaluated by the time-dependent ROC, with 1-, 2-, and 3-year AUCs of 0.86, 0.81, and 0.71, respectively. This study may provide new markers for individualized diagnosis and prognostic assessment of LUAD and potential targets for precision treatment.

DNA Repair-Based Gene Expression Signature and Distinct Molecular Subtypes for Prediction of Clinical Outcomes in Lung Adenocarcinoma

Objective: To conduct a robust prognostic gene expression signature and characterize molecular subtypes with distinct clinical characteristics for lung adenocarcinoma (LUAD).

Methods: Based on DNA repair genes from the GSEA database, a prognostic signature was conducted in the TCGA-LUAD training set via univariate and multivariate cox regression analysis. Its prediction power was validated by overall survival analysis, relative operating characteristic (ROC) curves and stratification analysis in the GSE72094 verification set. Involved pathways in the high- and low-risk groups were analyzed by GSEA. A nomogram was built based on the signature and clinical features and its performance was assessed by calibration plots. LUAD samples were clustered via the ConsensusClusterPlus package. The differences in clinical outcomes, single nucleotide polymorphism (SNP) and sensitivity to chemotherapy drugs between molecular subtypes were analyzed.

Results: A 13-DNA repair gene-signature was constructed for LUAD prognosis. Following validation, it can robustly and independently predict patients' clinical outcomes. The GSEA results exhibited the differences in pathways between high- and low- risk groups. A nomogram combining the signature and stage could accurately predict 1-, 3-, and 5-year survival probability. Two distinct molecular subtypes were characterized based on DNA repair genes. Patients in the Cluster 2 exhibited a worse prognosis and were more sensitive to common chemotherapy than those in the Cluster 1.

Conclusion:This study proposed a 13-DNA repair gene-signature as a prognostic factor for LUAD patients, which can independently predict clinical outcomes by complement of the stage. Moreover, we characterized two LUAD subtypes with distinct clinical outcomes, somatic gene mutations, and drug sensitivity in cancer based on DNA repair genes.

MiR-384 induces apoptosis and autophagy of non-small cell lung cancer cells through the negative regulation of Collagen α-1(X) chain gene

The present study aims to investigate the mechanism of miR-384 in non-small cell lung cancer (NSCLC) cell apoptosis and autophagy by regulating Collagen α-1(X) chain (COL10A1). Bioinformatics methods were applied to evaluate potential miRNAs and genes that might correlate with NSCLC. Tumor tissues and adjacent tissues from 104 NSCLC patients were collected and human NSCLC A549 cell line was selected for subsequent experiments. A549 cells were treated with miR-384 mimic, miR-384 inhibitor, or knockdown of COL10A1. Quantitative real-time PCR (qRT-PCR) and Western blotting were utilized to detect the levels of miR-384, COL10A, Survivin, Bcl-2, Bax, Bcl-xl, Beclin 1, and LC3 in tissues and cells. A series of biological assays including MTT assay, Annexin V-FITC/PI (propidium iodide) staining, immunofluorescence, monodansylcadaverine (MDC) staining were conducted to investigate the effects of miR-384 and COL10A1 on NSCLC cells. Tumorigenicity assay for nude rats was applied. Results obtained from the present study indicated that miR-384 down-regulated COL10A1 by targetting it. Compared with adjacent tissues, miR-384 expression was obviously reduced while COL10A1 expression was significantly enhanced in NSCLC tissues (all P<0.05). Outcomes in vivo and in vitro suggested that cell proliferation and tumorigenicity were inhibited while cell apoptosis and autophagy were induced in NSCLC cells treated with up-regulation of miR-384 or silence of COL10A1. In miR-384 inhibitor group, cell proliferation was improved, while cell apoptosis was reduced and cell autophagy was decreased whereas tumorigenicity of cells was strengthened. Based on the findings of our study, it was established that miR-384 could down-regulate COL10A1 levels, subsequently inhibiting cell proliferation and promoting cell apoptosis and autophagy in NSCLC cells.

Developing DNA methylation-based prognostic biomarkers of acute myeloid leukemia

Acute myeloid leukemia (AML) is a heterogeneous clonal neoplasm characterized by complex genomic alterations. The incidence of AML increases with age, and most cases experience serious illness and poor prognosis. To explore the relationship between abnormal DNA methylation and the occurrence and development of AML based on the Gene Expression Database (GEO), this study extracted data related to methylation in AML and identified a methylated CpG site that was significantly different in terms of expression and distribution between the primary cells of AML patients, and hematopoietic stem/progenitor cells from normal bone marrow. To further investigate the differences caused by the dysfunction of methylation sites, bioinformatics analysis was used to screen methylation-related biomarkers, and the potential prognostic genes were selected by univariate and multivariate Cox proportional hazards regressions. Finally, five independent prognostic indicators were identified. In addition, these results provide new insight into the molecular mechanisms of methylation.

TGF-β1-SOX9 axis-inducible COL10A1 promotes invasion and metastasis in gastric cancer via epithelial-to-mesenchymal transition

Molecular biomarkers that predict disease progression might promote drug development and therapeutic strategies in aggressive cancers, such as gastric cancer (GC). High-throughput mRNA sequencing (RNA-seq) revealed that collagen type X alpha 1 (COL10A1) is a disease progression-associated gene. Analysis of 103 GC patients showed that high COL10A1 mRNA expression was associated with GC metastasis and reduced survival. We analyzed the COL10A1 promoter using the UCSC genome website and JASPAR database, and we found potential SOX9 binding site. Here, we demonstrated that SOX9 and COL10A1 were both up-regulated in GC. We observed a positive correlation between the expression patterns of SOX9 and COL10A1 in GC cells and tissues. The results of electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP) assay and promoter reporter indicated that SOX9 could directly bind to the COL10A1 gene promoter and activate its transcription. Biological function experiments showed that COL10A1 regulated the migration and invasion of GC cells. Knockdown COL10A1 inhibited lung and abdominal cavity metastasis in a nude mouse model. Moreover, transforming growth factor-β1 (TGF-β1) treatment up-regulated the phosphorylation of Smad2 and increased SOX9 and COL10A1 expression. COL10A1 was confirmed to be a potential inducer of epithelial-to-mesenchymal transition (EMT). SOX9 was essential for COL10A1-mediated EMT, and cell migration, invasion and metastasis. Co-expression of SOX9 and COL10A1 was associated with tumor progression and was strongly predictive of overall survival in GC patients. In summary, this study elucidated the mechanistic link between COL10A1 and the TGF-β1-SOX9 axis. These findings indicated that COL10A1 might play a crucial role in GC progression and serve as a potential biomarker and therapeutic target in GC patients.

Prediction of potential drivers connecting different dysfunctional levels in lung adenocarcinoma via a protein-protein interaction network

Lung cancer is a serious disease that threatens an affected individual's life. Its pathogenesis has not yet to be fully described, thereby impeding the development of effective treatments and preventive measures. "Cancer driver" theory considers that tumor initiation can be associated with a number of specific mutations in genes called cancer driver genes. Four omics levels, namely, (1) methylation, (2) microRNA, (3) mutation, and (4) mRNA levels, are utilized to cluster cancer driver genes. In this study, the known dysfunctional genes of these four levels were used to identify novel driver genes of lung adenocarcinoma, a subtype of lung cancer. These genes could contribute to the initiation and progression of lung adenocarcinoma in at least two levels. First, random walk with restart algorithm was performed on a protein-protein interaction (PPI) network constructed with PPI information in STRING by using known dysfunctional genes as seed nodes for each level, thereby yielding four groups of possible genes. Second, these genes were further evaluated in a test strategy to exclude false positives and select the most important ones. Finally, after conducting an intersection operation in any two groups of genes, we obtained several inferred driver genes that contributed to the initiation of lung adenocarcinoma in at least two omics levels. Several genes from these groups could be confirmed according to recently published studies. The inferred genes reported in this study were also different from those described in a previous study, suggesting that they can be used as essential supplementary data for investigations on the initiation of lung adenocarcinoma. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang.

Identification of miRNA-mRNA Network Associated with Acute Myeloid Leukemia Survival

Background

Acute myeloid leukemia (AML) is a common hematologic malignancy of adults. The pathophysiological mechanism of AML is not well understood. The purpose of this study was to examine the crucial miRNAs and mRNAs associated with AML survival.

Material/Methods

The full clinical dataset of miRNA and mRNA expression profiling of AML patients was downloaded from The Cancer Genome Atlas database. Univariate Cox regression analysis was performed to obtain those miRNAs and mRNAs associated with AML survival. A miRNA-mRNA interaction network was constructed. The underlying functions of mRNAs were predicted through Kyoto Encyclopedia of Genes and Genomes (KEEG) pathway enrichment. The expression levels of miRNAs and mRNAs were detected by quantitative real-time polymerase chain reaction (qRT-PCR).

Results

Fourteen miRNAs and 830 mRNAs associated with AML survival were identified. Of the 14 miRNAs, hsa-mir-425, hsa-mir-1201, and hsa-mir-1978 were identified as risk factors and the other 11 miRNAs were identified as protective factors of AML survival. For target-genes of miRNAs, GTSF1, RTN4R, and CD44 were the top risk factor target-genes associated with AML survival. An interaction network was constructed that including 607 miRNA-target gene pairs associated with AML survival. Target-genes associated with AML survival were significantly enriched in several pathways including pancreatic secretion, calcium signaling pathway, natural killer cell mediated cytotoxicity, and Alzheimer’s disease. The qRT-PCR results were consistent with our bioinformatics analyses.

Conclusions

The miRNA hsa-mir-425 was identified as the top risk factor miRNA of AML survival and CD44 was identified as one of the top three risk factor target-genes associated with AML survival. Both hsa-mir-425 and CD44 may play key roles in progression and development of AML through calcium signaling pathway and natural killer cell mediated cytotoxicity.