A LASSO-based survival prediction model for patients with synchronous colorectal carcinomas based on SEER

Deciphering the role of wound healing genes in skin cutaneous melanoma: Insights into expression, methylation, mutations, and therapeutic implications

Skin Cutaneous Melanoma (SKCM) is a form of cancer that originates in the pigment-producing cells, known as melanocytes, of the skin. Delay wound healing is often correlated with the occurrence of and progression of SKCM. In this comprehensive study, we investigated the intricate roles of two important wound healing genes in SKCM, including Matrix Metalloproteinase-2 (MMP2) and Matrix Metalloproteinase-9 (MMP9). Through a multi-faceted approach, we collected clinical samples, conducted molecular experiments, including RT-qPCR, bisulphite sequencing, cell culture, cell Counting Kit-8, colony formation, and wound healing assays. Beside this, we also used various other databases/tools/approaches for additional analysis including, UALCAN, GEPIA, HPA, MEXPRESS, cBioPortal, KM plotter, DrugBank, and molecular docking. Our results revealed a significant up-regulation of MMP2 and MMP9 in SKCM tissues compared to normal counterparts. Moreover, promoter methylation analysis suggested an epigenetic regulatory mechanism. Validations using TCGA datasets and immunohistochemistry emphasized the clinical relevance of MMP2 and MMP9 dysregulation. Functional assays demonstrated their synergistic impact on proliferation and migration in SKCM cells. Furthermore, we identified potential therapeutic candidates, Estradiol and Calcitriol, through drug prediction and molecular docking analyses. These compounds exhibited binding affinities, suggesting their potential as MMP2/MMP9 inhibitors. Overall, our study elucidates the diagnostic, prognostic, and therapeutic implications of MMP2 and MMP9 in SKCM, shedding light on their complex interplay in SKCM occurrence and progression.

Identifying and validating MMP family members (MMP2, MMP9, MMP12, and MMP16) as therapeutic targets and biomarkers in kidney renal clear cell carcinoma (KIRC)

Kidney Renal Clear Cell Carcinoma (KIRC) is a malignant tumor that carries a substantial risk of morbidity and mortality. The MMP family assumes a crucial role in tumor invasion and metastasis. This study aimed to uncover the mechanistic relevance of the MMP gene family as a therapeutic target and diagnostic biomarker in Kidney Renal Clear Cell Carcinoma (KIRC) through a comprehensive approach encompassing both computational and molecular analyses. STRING, Cytoscape, UALCAN, GEPIA, OncoDB, HPA, cBioPortal, GSEA, TIMER, ENCORI, DrugBank, targeted bisulfite sequencing (bisulfite-seq), conventional PCR, Sanger sequencing, and RT-qPCR based analyses were used in the present study to analyze MMP gene family members to accurately determine a few hub genes that can be utilized as both therapeutic targets and diagnostic biomarkers for KIRC. By performing STRING and Cytohubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP12 (matrix metallopeptidase 12), and MMP16 (matrix metallopeptidase 16) genes were denoted as hub genes having highest degree scores. After analyzing MMP2, MMP9, MMP12, and MMP16 via various TCGA databases and RT-qPCR technique across clinical samples and KIRC cell lines, interestingly, all these hub genes were found significantly overexpressed at mRNA and protein levels in KIRC samples relative to controls. The notable effect of the up-regulated MMP2, MMP9, MMP12, and MMP16 was also documented on the overall survival (OS) of the KIRC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (MMP2, MMP9, MMP12, and MMP16). In addition to this, hub genes were involved in various diverse oncogenic pathways. The MMP gene family members (MMP2, MMP9, MMP12, and MMP16) may serve as therapeutic targets and prognostic biomarkers in KIRC.

The predictive efficacy of programmed cell death in immunotherapy of melanoma: A comprehensive analysis of gene expression data for programmed cell death biomarker and therapeutic target discovery

In this study, genes linked to prognosis in skin cutaneous melanoma (SKCM) involved in programmed cell death (PCD) were identified and confirmed and prognostic models based on these genes were constructed. Acquisition and analysis of clinical data and RNA sequencing information from The Cancer Genome Atlas-SKCM (TCGA-SKCM) and Sangerbox databases, gene expression data for 477 tumor samples and 2 normal samples were successfully gathered. The patients were separated into two clusters based on consensus clustering of PCD-related genes, with Cluster A having greater tumor purity, ESTIMATE score, immune score, and matrix score, and Cluster B having a significantly distinct pattern of immune cell infiltration. The use of gene set enrichment analysis and weighted correlation network analysis showed significant associations between certain genes and factors such as tumor mutation burden, age, stage, grade, and tumor subtype. Finally, based on the 12 genes selected by Least Absolute Shrinkage and Selection Operator regression analysis (STAT3, IRF2, SLC7A11, ZEB1, LIPT1, PML, GCH1, GYS1, ABCC1, XBP1, TFAP2C, NOX4), a prognostic model of PGD-related genes was constructed. The effectiveness of the model's prognostic value was confirmed through survival analysis, time-dependent receiver operating characteristic curve, single-factor Cox regression analysis, and nomogram. We also verified the relationship between the GCH1 and MKI67 expression by wet experiment. This model has high prediction accuracy in SKCM patients and can provide a reference for clinical treatment.

Characterization and verification of MMP family members as potential biomarkers in kidney clear cell renal carcinoma

Renal cell carcinoma can arise from lesions in the renal epithelium. This particular type of cancer is prevalent in the realm of renal cancers and is associated with an unfavorable prognosis. Among these cases, over 70% are classified as kidney renal clear cell carcinoma (KIRC). Since the underlying causes of KIRC haven't been fully understood, there is an urgent need for deeper investigation into its pathogenesis. Various tools, software, and molecular analysis was used, including Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), Cytoscape, University of ALabama at Birmingham CANcer data analysis Portal (UALCAN), muTarget, Gene Expression Profiling Interactive Analysis (GEPIA), OncoDB, Human Protein Atlas (HPA), cBioPortal, Kaplan-Meier (KM) plotter, Gene Set Enrichment Analysis (GSEA), Tumor IMmune Estimation Resource (TIMER), Encyclopedia of RNA Interactomes (ENCORI), DrugBank, Encyclopedia of RNA Interactomes (RT-qPCR), targeted bisulfide sequencing (bisulfide-seq), and receiver operating curve (ROC) to matrix metallopeptidase (MMP) gene family constituents, with the precise objective of identifying a small set of hub genes. These hub genes hold the potential to be harnessed as molecular biomarkers for KIRC. By performing STRING and CytoHubba analyses of the 24 MMP gene family members, MMP2 (matrix metallopeptidase 2), MMP9 (matrix metallopeptidase 9), MMP14 (matrix metallopeptidase 14), and MMP16 (matrix metallopeptidase 16) were recognized as hub genes having highest degree scores. After conducting an in-depth expression analysis of MMP2, MMP9, MMP14, and MMP16 using various The Cancer Genome Atlas (TCGA) databases and RT-qPCR techniques, these displayed a significant increase in expression at both the mRNA and protein levels within KIRC samples when compared to control samples. The impact of the over expression of MMP2, MMP9, MMP14, and MMP16 also left a distinct mark on the worst overall survival (OS) rates of KIRC patients. Furthermore, a targeted bisulfide-seq investigation unveiled a correlation between promoter hypomethylation patterns and the up-regulation of these key genes in KIRC patients. Additionally, hub genes were involved in various diverse oncogenic pathways. In conclusion, four MMP gene family members, including MMP2, MMP9, MMP14, and MMP16 may serve as therapeutic target and molecular biomarker in KIRC.

Characterization of ferroptosis driver gene signature in head and neck squamous cell carcinoma (HNSC)

BACKGROUND

Head and neck squamous cell carcinoma (HNSC), a prevalent malignant tumor with a low survival rate, is often accompanied by ferroptosis, which is a recently-described type ofprogrammed cell death. Investigating the significance of ferroptosis driver genes in HNSC, this study aimed to assess their diagnostic and prognostic values, as well as their impact on treatment and tumor immune function. The results of this investigation provide novel insight into using ferroptosis-related genes as molecular biomarkers as well as precise chemotherapeutic targets for the therapy of HNSC.

METHODOLOGY

A detailed in silico and in vitro experiment-based methodology was adopted to achieve the goals.

RESULTS

A total of 233 ferroptosis driver genes were downloaded from the FerrDB database. After comprehensively analyzing these 233 ferroptosis driver genes by various TCGA databases, RNA-sequencing (RNA-seq), and Reverse Transcription Quantitative Real-Time Polymerase Chain Reaction (RT-qPCR) techniques, TP53 (tumor protein 53), PTEN (Phosphatase and TENsin homolog deleted on chromosome 10), KRAS (Ki-ras2 Kirsten rat sarcoma viral oncogene homolog), and HRAS (Harvey Rat sarcoma virus) were identified as differentially expressed hub genes. Interestingly, these hub genes were found to have significant (P < 0.05) variations in their mRNA and protein expressions and effects on overall survival of the HNSC patients. Moreover, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed that promoter hypomethylation pattern was associated with up-regulation of hub genes (TP53, PTEN, KRAS, and HRAS). In addition to this, hub genes were involved in diverse oncogenic pathways.

CONCLUSION

Since HNSC pathogenesis is a complex process, using ferroptosis driver hub genes (TP53, PTEN, KRAS, and HRAS) as a diagnostic and prognostic tool, and therapeutically targeting those genes through appropriate drugs could bring a milestone change in the drug discovery and management and survival in HNSC.

In vitro analysis of PI3K pathway activation genes for exploring novel biomarkers and therapeutic targets in clear cell renal carcinoma

OBJECTIVES

The regulation of various cellular functions such as growth, proliferation, metabolism, and angiogenesis, is dependent on the PI3K pathway. Recent evidence has indicated that kidney renal clear cell carcinoma (KIRC) can be triggered by the deregulation of this pathway. The objective of this research was to investigate 25 genes associated with activation of the PI3K pathway in KIRC and control samples to identify four hub genes that might serve as novel molecular biomarkers and therapeutic targets for treating KIRC.

METHODS

Multi-omics in silico and in vitro analysis was employed to find hub genes related to the PI3K pathway that may be biomarkers and therapeutic targets for KIRC.

RESULTS

Using STRING software, a protein-protein interaction (PPI) network of 25 PI3K pathway-related genes was developed. Based on the degree scoring method, the top four hub genes were identified using Cytoscape's Cytohubba plug-in. TCGA datasets, KIRC (786-O and A-498), and normal (HK2) cells were used to validate the expression of hub genes. Additionally, further bioinformatic analyses were performed to investigate the mechanisms by which hub genes are involved in the development of KIRC. Out of a total of 25 PI3K pathway-related genes, we developed and validated a diagnostic and prognostic model based on the up-regulation of TP53 (tumor protein 53) and CCND1 (Cyclin D1) and the down-regulation of PTEN (Phosphatase and TENsin homolog deleted on chromosome 10), and GSK3B (Glycogen synthase kinase-3 beta) hub genes. The hub genes included in our model may be a novel therapeutic target for KIRC treatment. Additionally, associations between hub genes and infiltration of immune cells can enhance comprehension of immunotherapy for KIRC.

CONCLUSION

We have created a new diagnostic and prognostic model for KIRC patients that uses PI3K pathway-related hub genes (TP53, PTEN, CCND1, and GSK3B). Nevertheless, further experimental studies are required to ascertain the efficacy of our model.