A Novel Prognostic Model for Oral Squamous Cell Carcinoma: The Functions and Prognostic Values of RNA-Binding Proteins

Comprehensive analysis of INTS family related to expression, prognosis, diagnosis and immune features in hepatocellular carcinoma

Purpose

The integrator subunit (INTS) family, a group exclusive to metazoans, participates in various biologic processes. However, their roles in hepatocellular carcinoma (HCC) remain largely unexplored.

Methods

Public databases were utilized to investigate the transcriptional and protein expression, and clinical relevance of the INTS family in HCC. Meanwhile, the effects of INTS13 knockdown and overexpression on cell proliferation and apoptosis were studied using HCC cell lines.

Results

The mRNA expression of most INTSs were higher in tumor than normal tissues. Higher expression of INTS1/2/3/4/7/8/9/11/12/13 were correlated with poorer overall survival (OS) in Kaplan-Meier Survival Analysis. Multivariate analysis revealed higher level of INTS13 was an independent prognostic factor for shorter OS. Furthermore, genetic alteration of INTS3/6/7/8/9/10 were found in HCC patients and was associated with shorter disease-free survival and progression-free survival. INTS1/2/3/5/7/11/13/14 were associated with activation of tumor-induced immune response and immune infiltration in HCC. Knockdown of INTS13 inhibited cell proliferation and induced apoptosis in HCC cell lines, while overexpression of INTS13 had the opposite effect.

Conclusion

Our results indicate that INTS13 is an independent prognostic biomarker in HCC. Furthermore, INTS13 enhances cell proliferation and decreases cell apoptosis in HCC cell lines leading to a poorer OS in HCC patients.

Nomogram incorporating potent inflammatory indicators for overall survival estimation of patients with primary oral squamous cell carcinoma

Background

Inflammation has been recognized to be a factor that substantially influences tumorigenesis and tumor prognosis. Hence, this study was aimed to investigate an inflammatory marker with the most potent prognostic ability and to evaluate the survival estimation capability of dynamic change in this marker for patients suffered from oral squamous cell carcinoma (OSCC).

Methods

469 patients' inflammatory indicators including lymphocyte-to-monocyte ratio (LMR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and systemic inflammatory response index (SIRI), were calculated. Their predictive abilities for overall survival (OS) were evaluated by Kaplan-Meier curves to screen for the one with the most potent prognostic value. The predictive ability of dynamic changes in this marker was verified and a predictive nomogram incorporating inflammatory indicators was developed.

Results

A high LMR was identified to be an indicator of a satisfactory survival rate. Compared with that of other inflammatory markers, area under the receiver operating characteristics (ROC) curve (AUC) of LMR for 1-year and 3-year OS was significantly larger (P<0.001). Dynamic LMR change remained an significant parameter for predicting OS (OR: 2.492, 95% CI: 1.246-4.981, p = 0.010). The nomogram incorporating LMR exhibited a superior prognostic significance than the TNM system, as suggested by the C-index (0.776 vs 0.651 in primary cohort; 0.800 vs 0.707 in validation cohort, P<0.001) and AUC.

Conclusions

LMR was demonstrated to possess a more potent survival estimation capability than the other three inflammatory parameters. Dynamic changes in LMR serves as a significant parameter for overall survival estimation of primary OSCC patients. The established nomogram incorporating inflammatory markers showed more accuracy and sensitivity for survival estimation of primary OSCC patients.

New Clues to Prognostic Biomarkers of Four Hematological Malignancies

Globally, one out of every two reported cases of hematologic malignancies (HMs) results in death. Each year approximately 1.24 million cases of HMs are recorded, of which 58% become fatal. Early detection remains critical in the management and treatment of HMs. However, this is thwarted by the inadequate number of reliable biomarkers. In this study, we mined public databases for RNA-seq data on four common HMs intending to identify novel biomarkers that could serve as HM management and treatment targets. A standard RNA-seq analysis pipeline was strictly adhered to in identifying differentially expressed genes (DEGs) with DESeq2, limma+voom and edgeR. We further performed gene enrichment analysis, protein-protein interaction (PPI) network analysis, survival analysis and tumor immune infiltration level detection on the genes using G:Profiler, Cytoscape and STRING, GEPIA tool and TIMER, respectively. A total of 2,136 highly-ranked DEGs were identified in HM vs. non-HM samples. Gene ontology and pathway enrichment analyses revealed the DEGs to be mainly enriched in steroid biosynthesis (5.075×10-4), cholesterol biosynthesis (2.525×10-8), protein binding (3.308×10-18), catalytic activity (2.158×10-10) and biogenesis (5.929×10-8). The PPI network resulted in 60 hub genes which were verified with data from TCGA, MET500, CPTAC and GTEx projects. Survival analyses with clinical data from TCGA showed that high expression of SRSF1, SRSF6, UBE2Z and PCF11, and low expression of HECW2 were correlated with poor prognosis in HMs. In summary, our study unraveled essential genes that could serve as potential biomarkers for prognosis and may serve as drug targets for HM management.

Transcription of the Envelope Protein by 1-L Protein-RNA Recognition Code Leads to Genes/Proteins That Are Relevant to the SARS-CoV-2 Life Cycle and Pathogenesis

The theoretical protein-RNA recognition code was used in this study to research the compatibility of the SARS-CoV-2 envelope protein (E) with mRNAs in the human transcriptome. According to a review of the literature, the spectrum of identified genes showed that the virus post-transcriptionally promotes or represses the genes involved in the SARS-CoV-2 life cycle. The identified genes/proteins are also involved in adaptive immunity, in the function of the cilia and wound healing (EMT and MET) in the pulmonary epithelial tissue, in Alzheimer's and Parkinson's disease and in type 2 diabetes. For example, the E-protein promotes BHLHE40, which switches off the IL-10 inflammatory "brake" and inhibits antiviral THαβ cells. In the viral cycle, E supports the COPII-SCAP-SREBP-HSP90α transport complex by the lowering of cholesterol in the ER and by the repression of insulin signaling, which explains the positive effect of HSP90 inhibitors in COVID-19 (geldanamycin), and E also supports importin α/β-mediated transport to the nucleus, which explains the positive effect of ivermectin, a blocker of importins α/β. In summary, transcription of the envelope protein by the 1-L protein-RNA recognition code leads to genes/proteins that are relevant to the SARS-CoV-2 life cycle and pathogenesis.