Prognostic characterization of OAS1/OAS2/OAS3/OASL in breast cancer

Zhang, Yujie; Yu, Chaoran

doi:10.1186/s12885-020-07034-6

Cited by 68 publications

(65 citation statements)

References 28 publications

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“…Our analysis identified a number of common dysregulated genes between COVID-19 and cancers. Among the identified common genes, MARCO and OAS2 were identified as dysregulated in breast cancer as consistent with previous report [ 38 , 39 ]. Previous studies suggested OAS2 as prognostic markers of breast cancer [ 39 ].…”

Section: Discussionsupporting

confidence: 91%

Diseasome and comorbidities complexities of SARS-CoV-2 infection with common malignant diseases

Satu

Khan

Rahman

et al. 2021

Briefings in Bioinformatics

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With the increasing number of immunoinflammatory complexities, cancer patients have a higher risk of serious disease outcomes and mortality with SARS-CoV-2 infection which is still not clear. In this study, we aimed to identify infectome, diseasome and comorbidities between COVID-19 and cancer via comprehensive bioinformatics analysis to identify the synergistic severity of the cancer patient for SARS-CoV-2 infection. We utilized transcriptomic datasets of SARS-CoV-2 and different cancers from Gene Expression Omnibus and Array Express Database to develop a bioinformatics pipeline and software tools to analyze a large set of transcriptomic data and identify the pathobiological relationships between the disease conditions. Our bioinformatics approach revealed commonly dysregulated genes (MARCO, VCAN, ACTB, LGALS1, HMOX1, TIMP1, OAS2, GAPDH, MSH3, FN1, NPC2, JUND, CHI3L1, GPNMB, SYTL2, CASP1, S100A8, MYO10, IGFBP3, APCDD1, COL6A3, FABP5, PRDX3, CLEC1B, DDIT4, CXCL10 and CXCL8), common gene ontology (GO), molecular pathways between SARS-CoV-2 infections and cancers. This work also shows the synergistic complexities of SARS-CoV-2 infections for cancer patients through the gene set enrichment and semantic similarity. These results highlighted the immune systems, cell activation and cytokine production GO pathways that were observed in SARS-CoV-2 infections as well as breast, lungs, colon, kidney and thyroid cancers. This work also revealed ribosome biogenesis, wnt signaling pathway, ribosome, chemokine and cytokine pathways that are commonly deregulated in cancers and COVID-19. Thus, our bioinformatics approach and tools revealed interconnections in terms of significant genes, GO, pathways between SARS-CoV-2 infections and malignant tumors.

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Section: Discussionsupporting

confidence: 91%

Diseasome and comorbidities complexities of SARS-CoV-2 infection with common malignant diseases

Satu

Khan

Rahman

et al. 2021

Briefings in Bioinformatics

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“…OASL expression showed a significant correlation with neutrophil infiltration. Consistently, Zhang et al also found that OAS1 and OASL were correlated to neutrophil cell infiltration in breast cancer ( 33 ). Thus, MET, OAS1, and OASL were distinctly correlated to tumor immune microenvironment.…”

Section: Discussionmentioning

confidence: 53%

Three Immune-Related Prognostic mRNAs as Therapeutic Targets for Pancreatic Cancer

Zhang

Zou²,

Zhu³

et al. 2021

Front. Med.

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Objective: Pancreatic cancer is a highly lethal malignancy globally. This study aimed to probe and validate immune-related prognostic mRNAs as therapeutic targets for pancreatic cancer.Methods: Gene transcriptome data of pancreatic cancer and normal pancreas were retrieved from TCGA-GTEx projects. Two thousand four hundred and ninety-eight immune-related genes were obtained from the IMMUPORT database. Abnormally expressed immune-related genes were then identified. Under univariate and multivariate cox models, a gene signature was constructed. Its predictive efficacy was assessed via ROCs. The interactions between the 21 genes were analyzed by Spearson analysis and PPI network. Using the GEPIA and The Human Protein Atlas databases, their expression and prognostic value were evaluated. The TIMER database was utilized to determine the relationships between MET, OAS1, and OASL mRNAs and immune infiltrates. Finally, their mRNA expression was externally verified in the GSE15471 and GSE62452 datasets.Results: An immune-related 21-gene signature was developed for predicting patients' prognosis. Following verification, this signature exhibited the well predictive performance. There were physical and functional interactions between them. MET, OAS1, and OASL mRNAs were all up-regulated in pancreatic cancer and associated with unfavorable prognosis. They showed strong correlations with tumor progression. Furthermore, the three mRNAs were distinctly associated with immune infiltrates. Their up-regulation was confirmed in the two external datasets.Conclusion: These findings identified three immune-related prognostic mRNAs MET, OAS1, and OASL, which may assist clinicians to choose targets for immunotherapy and make personalized treatment strategy for pancreatic cancer patients.

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“…The OASL gene has been found to be associated with the regulation of lung cancer cell sensitivity to acRoots, via the PI3K signal pathway [ 46 ]. OASL has also been associated with proliferation of cancer such as that of the gastric and breast type, and therefore can play a role in prognostication with potential mechanistic value in breast cancer [ 47 ]. Lohavanichbutr P et al, using L1/L2-penalized Cox regression models in HPV-negative OSCC, identified six genes, one of which was OASL, and reported that all these genes play a role in cell invasion and motility, cell-to-cell signaling, signal transduction, and proliferation, processes essential to metastasis and cancer progression [ 48 ].…”

Section: Discussionmentioning

confidence: 99%

Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC)

Singh

Rai

Verma

et al. 2021

Biology

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Head and neck squamous cell carcinoma (HNSC) is one of the most common malignant tumors worldwide with a high rate of morbidity and mortality, with 90% of predilections occurring for oral squamous cell carcinoma (OSCC). Cancers of the mouth account for 40% of head and neck cancers, including squamous cell carcinomas of the tongue, floor of the mouth, buccal mucosa, lips, hard and soft palate, and gingival. OSCC is the most devastating and commonly occurring oral malignancy, with a mortality rate of 500,000 deaths per year. This has imposed a strong necessity to discover driver genes responsible for its progression and malignancy. In the present study we filtered oral squamous cell carcinoma tissue samples from TCGA-HNSC cohort, which we followed by constructing a weighted PPI network based on the survival of patients and the expression profiles of samples collected from them. We found a total of 46 modules, with 18 modules having more than five edges. The KM and ME analyses revealed a single module (with 12 genes) as significant in the training and test datasets. The genes from this significant module were subjected to pathway enrichment analysis for identification of significant pathways and involved genes. Finally, the overlapping genes between gene sets ranked on the basis of weighted PPI module centralities (i.e., degree and eigenvector), significant pathway genes, and DEGs from a microarray OSCC dataset were considered as OSCC-specific hub genes. These hub genes were clinically validated using the IHC images available from the Human Protein Atlas (HPA) database.

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Prognostic characterization of OAS1/OAS2/OAS3/OASL in breast cancer

Cited by 68 publications

References 28 publications

Diseasome and comorbidities complexities of SARS-CoV-2 infection with common malignant diseases

Diseasome and comorbidities complexities of SARS-CoV-2 infection with common malignant diseases

Three Immune-Related Prognostic mRNAs as Therapeutic Targets for Pancreatic Cancer

Survival-Based Biomarker Module Identification Associated with Oral Squamous Cell Carcinoma (OSCC)

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