Exploration of prognosis-related microRNA and transcription factor co-regulatory networks across cancer types

A Transcription Factor ZNF384, Regulated by LINC00265, Activates the Expression of IFI30 to Stimulate Malignant Progression in Glioma

Glioma remains one of the most challenging primary brain malignancies to treat. Long noncoding RNAs (lncRNAs) and mRNAs (mRNAs) are implicated in regulating the malignant phenotypes of cancers including glioma. This study aimed to elucidate the functions and mechanisms of lncRNA LINC00265 and mRNA IFI30 in the pathogenesis of glioma. Quantitative real-time polymerase chain reaction (RT-qPCR) analysis revealed the upregulated expression of LINC00265 and IFI30 in glioma cells compared to normal human astrocytes. Western blot (WB) quantified the associated proteins. Glioma stemness and epithelial-to-mesenchymal transition (EMT) were assessed by aldehyde dehydrogenase 1 (ALDH1) activity, sphere formation, and WB. Mechanistic and rescue assays evaluated the LINC00265/miR-let-7d-5p/IFI30/ZNF384/IGF2BP2 axis. The results demonstrated that LINC00265 and IFI30 were highly expressed in glioma cells, promoting stemness and EMT. ZNF384 was identified as a transcription factor that upregulates IFI30. Moreover, LINC00265 elevated ZNF384 by sponging miR-let-7d-5p and recruiting IGF2BP2. In conclusion, LINC00265 and IFI30 act as oncogenes in glioma by driving stemness and EMT, underscoring their potential as therapeutic targets.

Pan-cancer analyses of classical protein tyrosine phosphatases and phosphatase-targeted therapy in cancer

Protein tyrosine phosphatases function in dephosphorylating target proteins to regulate signaling pathways that control a broad spectrum of fundamental physiological and pathological processes. Detailed knowledge concerning the roles of classical PTPs in human cancer merits in-depth investigation. We comprehensively analyzed the regulatory mechanisms and clinical relevance of classical PTPs in more than 9000 tumor patients across 33 types of cancer. The independent datasets and functional experiments were employed to validate our findings. We exhibited the extensive dysregulation of classical PTPs and constructed the gene regulatory network in human cancer. Moreover, we characterized the correlation of classical PTPs with both drug-resistant and drug-sensitive responses to anti-cancer drugs. To evaluate the PTP activity in cancer prognosis, we generated a PTPscore based on the expression and hazard ratio of classical PTPs. Our study highlights the notable role of classical PTPs in cancer biology and provides novel intelligence to improve potential therapeutic strategies based on pTyr regulation.

The Role of Critical N6-Methyladenosine-Related Long Non-Coding RNAs and Their Correlations with Immune Checkpoints in Renal Clear Cell Carcinoma

Purpose

This study aimed to evaluate the functions of critical N6-methyladenosine (m6A)-related long non-coding RNAs (lncRNAs) and their correlations with immunotherapeutic targets in clear cell renal cell carcinoma (ccRCC).

Methods

m6A-related lncRNAs were analyzed using the dataset from The Cancer Genome Atlas database via Pearson correlation analysis. Then, their prognostic functions in patients with ccRCC were determined via univariate Cox analysis. A prognostic m6A-related lncRNA signature (MRLS) in ccRCC was established using the least absolute shrinkage and selection operator (LASSO) Cox regression model. In addition, the correlations between these prognostic m6A-related lncRNAs with immune checkpoints were further evaluated in clinical samples.

Results

MRLS was established by the LASSO Cox regression model on the basis of seven prognostic m6A-related lncRNAs. The risk score for each patient was calculated using the MRLS model, and the patients were further stratified into high- and low-risk subgroups. The MRLS model was validated with a robust prognostic ability by the stratification analysis. On the basis of age, grade, stage, and risk score, a nomogram was developed with a strong reliability in forecasting the overall survival percentages of the patients with ccRCC. Moreover, seven prognostic m6A-related lncRNAs enrolled in the MRLS model were found to be correlated with various immunotherapeutic targets, namely, PD-1, PD-L1, CTLA4, and LAG3, and the expression levels of which in the high-risk subgroup were significantly higher than those in the low-risk subgroup. The significant correlations between LINC00342 and the aforementioned immunotherapeutic targets were also confirmed in clinical samples.

Conclusion

In this study, seven m6A-related lncRNAs were identified as potential biomarkers for forecasting the prognosis of patients with ccRCC and evaluating the efficacy of immunotherapy for these patients. Furthermore, a prognostic and predictive MRLS model with a high reliability was constructed to predict the overall survival probability of patients with ccRCC.

IRF4-activated TEX41 promotes the malignant behaviors of melanoma cells by targeting miR-103a-3p/C1QB axis

BACKGROUND

Malignant melanoma is an aggressive skin cancer and a tumor of melanocytic origin. Recent studies have suggested that long non-coding RNAs (lncRNAs) play crucial regulatory roles in multiple malignancies, including melanoma. Testis expressed 41 (TEX41) is a relatively new lncRNA whose mechanism in melanoma remains vague.

AIMS

This study aimed to explore the role and specific mechanism of TEX41 in melanoma.

METHODS

The expression of genes involved in this study was determined by qRT-PCR. Functional assays were conducted to analyze the role of relevant genes in melanoma cells. The interaction between TEX41 promoter and IRF4 as well as the relationship among TEX41, miR-103a-3p and C1QB was verified by mechanism assays.

RESULTS

IRF4 up-regulated TEX41 at the transcriptional level in melanoma cells. TEX41 knockdown hindered melanoma cell proliferation, migration and invasion while promoting cell apoptosis. TEX41 bound to miR-103a-3p and regulated C1QB. The suppressive impact of TEX41 depletion on melanoma cell malignant behaviors could be counteracted by miR-103a-3p inhibition or C1QB overexpression. Moreover, IRF4 could facilitate melanoma cell growth via up-regulating C1QB.

CONCLUSIONS

IRF4-activated TEX41 sequestered miR-103a-3p and modulated C1QB to promote melanoma cell malignant behaviors, for which TEX41 might be regarded as a potential therapeutic target for melanoma.

HAHmiR.DB: a server platform for high-altitude human miRNA-gene coregulatory networks and associated regulatory circuits

Around 140 million people live in high-altitude (HA) conditions! and even a larger number visit such places for tourism, adventure-seeking or sports training. Rapid ascent to HA can cause severe damage to the body organs and may lead to many fatal disorders. During induction to HA, human body undergoes various physiological, biochemical, hematological and molecular changes to adapt to the extreme environmental conditions. Several literature references hint that gene-expression-regulation and regulatory molecules like miRNAs and transcription factors (TFs) control adaptive responses during HA stress. These biomolecules are known to interact in a complex combinatorial manner to fine-tune the gene expression and help in controlling the molecular responses during this stress and ultimately help in acclimatization. High-Altitude Human miRNA Database (HAHmiR.DB) is a unique, comprehensive and curated collection of miRNAs that have been experimentally validated to be associated with HA stress, their level of expression in different altitudes, fold change, experiment duration, biomarker association, disease and drug association, tissue-specific expression level, Gene Ontology (GO) and Kyoto Encyclopaedia of Gene and Genomes (KEGG) pathway associations. As a server platform, it also uniquely constructs and analyses interactive miRNA-TF-gene coregulatory networks and extracts regulatory circuits/feed-forward loops (FFLs). These regulatory circuits help to offer mechanistic insights into complex regulatory mechanisms during HA stress. The server can also build these regulatory networks between two and more miRNAs of the database and also identify the regulatory circuits from this network. Hence, HAHmiR.DB is the first-of-its-kind database in HA research, which is a reliable platform to explore, compare, analyse and retrieve miRNAs associated with HA stress, their coregulatory networks and FFL regulatory-circuits. HAHmiR.DB is freely accessible at http://www.hahmirdb.in.