Identification of GUCA2A and COL3A1 as prognostic biomarkers in colorectal cancer by integrating analysis of RNA-Seq data and qRT-PCR validation

Unveiling ADAMTS12: A key driver of bladder cancer progression via COL3A1-Mediated activation of the FAK/PI3K/AKT signaling pathway

Bladder cancer (BCa) is a common and lethal disease characterized by high recurrence rates and limited treatment options. Understanding the molecular pathways of BCa progress is crucial for investigating more effective targeted therapies. While ADAMTS12 is known to contribute to cancer progression and treatment resistance, its prognostic significance and underlying mechanisms in BCa remain poorly understood. To elucidate the molecular pathways and functions of ADAMTS12 in BCa, we employed various experimental approaches, including Transwell invasion assays, flow cytometry analysis, wound-healing assays, CCK-8 assays, and a xenograft tumor model. Our results demonstrated that overexpression of ADAMTS12 significantly enhanced cell growth, migration, and invasion while inhibiting apoptosis through the activation of the FAK/PI3K/AKT signaling pathway. Conversely, the knockdown of ADAMTS12 produced the opposite effects. In vivo studies further confirmed that the inhibition of ADAMTS12 effectively suppressed tumor progression. Comprehensive bioinformatics analysis of the TCGA-BLCA dataset and protein-protein interaction networks revealed a strong positive correlation between COL3A1 and ADAMTS12, identifying COL3A1 as a potential downstream target of ADAMTS12. Additionally, we observed a significant increase in the expression levels of ADAMTS12 and COL3A1 in BCa tissues compared to healthy tissues, as confirmed by Western blotting and qRT-PCR analysis. Notably, inhibition of COL3A1 reversed the enhanced cell growth and invasion associated with ADAMTS12 overexpression and suppressed cell apoptosis. Our findings suggest that ADAMTS12 promotes BCa progression through the FAK/PI3K/AKT signaling pathway by regulating COL3A1, highlighting its potential as a valuable marker for diagnosis and prognosis in BCa.

Role and mechanism of COL3A1 in regulating the growth, metastasis, and drug sensitivity in cisplatin-resistant non-small cell lung cancer cells

Non-small cell lung cancer (NSCLC) is among the most difficult malignancies to treat. Type III collagen (COL3A1) can affect the progression and chemoresistance development of NSCLC. We herein explored the mechanism that drives COL3A1 dysregulation in NSCLC. Potential RNA-binding proteins (RBPs) and transcription factors (TFs) that could bind to COL3A1 were searched by bioinformatics. mRNA expression was detected by quantitative PCR. Protein expression was evaluated using immunoblotting and immunohistochemistry. The effects of the variables were assessed by gauging cell growth, invasiveness, migratory capacity, apoptosis, and cisplatin (DDP) sensitivity. The direct YY1/COL3A1 relationship was confirmed by ChIP and luciferase reporter experiments. Xenograft experiments were done to examine COL3A1's function in DDP efficacy. COL3A1 showed enhanced expression in DDP-resistant NSCLC. In H460/DDP and A549/DDP cells, downregulation of COL3A1 exerted inhibitory functions in cell growth, invasiveness, and migration, as well as promoting effects on cell DDP sensitivity and apoptosis. Mechanistically, ELAV-like RNA binding protein 1 (ELAVL1) enhanced the mRNA stability and expression of COL3A1, and Yin Yang 1 (YY1) promoted the transcription and expression of COL3A1. Furthermore, upregulation of COL3A1 reversed ELAVL1 inhibition- or YY1 deficiency-mediated functions in DDP-resistant NSCLC cells. Additionally, COL3A1 downregulation enhanced the anti-tumor efficacy of DDP in vivo. Our investigation demonstrates that COL3A1 upregulation, induced by both RBP ELAVL1 and TF YY1, exerts important functions in phenotypes of NSCLC cells with DDP resistance, offering an innovative opportunity in the treatment of drug-resistant NSCLC.

Transcriptomics and Metabolomics Reveal Biosynthetic Pathways and Regulatory Mechanisms of Phenylpropanes in Different Ploidy of Capsicum frutescens

Pepper is a significant cash crop, and Capsicum frutescens is an exemplary variety of pepper cultivated for its distinctive flavor and substantial nutritional value. Polyploidization of plants often leads to an increase in their biomass and improved stress tolerance, and thus has important applications in plant breeding and improvement. In this study, germplasm innovation was carried out by polyploidy induction of C. frutescens by colchicine. To investigate the effects of polyploidization on C. frutescens, we conducted transcriptomic and metabolomic analyses of diploids and homotetraploids of C. frutescens to gain insights into the mechanisms of metabolite composition and molecular regulation of C. frutescens by polyploidization. Based on the analysis of metabolomics and transcriptomics data, a total of 551 differential metabolites were identified in the leaves of C. frutescens of different ploidy and 634 genes were significantly differentially expressed. In comparison, 241 differential metabolites and 454 genes were significantly differentially expressed in the mature fruits of C. frutescens of different ploidy. Analysis of KEGG enrichment of differentially expressed genes and differential metabolites revealed that both differential metabolites and differentially expressed genes were highly enriched in the phenylalanine metabolic pathway. It is worth noting that phenylpropanoids are highly correlated with capsaicin synthesis and also have an effect on fruit development. Therefore, we comprehensively analyzed the phenylalanine metabolic pathway and found that chromosome doubling significantly down-regulated the expression of genes upstream of phenylalanine (PAL, 4CL), which promoted lignin accumulation, and we suggested that this might have led to the enlargement of polyploid C. frutescens fruits. This study provides some references for further research on the phenotypic traits of different ploidy of C. frutescens, cloning of key regulatory genes, and using genetic engineering techniques in C. frutescens breeding for germplasm improvement.

Unraveling the genetic landscape of pulmonary arterial hypertension in Indian patients: A transcriptome study

BACKGROUND

Pulmonary hypertension (PH) is the abnormal elevation of pressure in the pulmonary vascular system, with various underlying causes. A specific type of PH is pulmonary arterial hypertension (PAH), a severe condition characterized by high pulmonary arterial pressure resulting from structural changes in distal pulmonary vessels, altered arterial tone, and inflammation. This leads to right ventricular hypertrophy and heart failure. The molecular mechanisms behind PAH are not well understood. This manuscript aims to elucidate these mechanisms using the genetic tool, aiding in diagnosis and treatment selection.

METHOD

In our present study, we have obtained blood samples from both patients with pulmonary arterial hypertension (PAH) and healthy individuals. We conducted a comparative transcriptome analysis to identify genes that are either upregulated or downregulated in PAH patients when compared to the control group. Subsequently, we carried out a validation study focusing on the log2-fold downregulated genes in PAH, employing Quantitative Real-Time PCR for confirmation. Additionally, we quantified the proteins encoded by the validated genes using the ELISA technique.

RESULTS

The results of the transcriptome analysis revealed that 97 genes were significantly upregulated, and 6 genes were significantly downregulated. Among these, we chose to focus on and validate only four of the downregulated genes, as they were directly or indirectly associated with the hypertension pathway. We also conducted validation studies for the proteins encoded by these genes, and the results were consistent with those obtained in the transcriptome analysis.

CONCLUSION

In conclusion, the findings of this study indicate that the four validated genes identified in the context of PAH can be further explored as potential targets for both diagnostic and therapeutic applications.

Integrating network analysis with differential expression to uncover therapeutic and prognostic biomarkers in esophageal squamous cell carcinoma

Introduction: Esophageal squamous cell carcinoma (ESCC) accounts for over 90% of all esophageal tumors. However, the molecular mechanism underlying ESCC development and prognosis remains unclear, and there are still no effective molecular biomarkers for diagnosing or predicting the clinical outcome of patients with ESCC. Here, we used bioinformatics analysis to identify potential biomarkers and therapeutic targets for ESCC. Methodology: Differentially expressed genes (DEGs) between ESCC and normal esophageal tissue samples were obtained by comprehensively analyzing publicly available RNA-seq datasets from the TCGA and GTEX. Gene Ontology (GO) annotation and Reactome pathway analysis identified the biological roles of the DEGs. Moreover, the Cytoscape 3.10.1 platform and subsidiary tools such as CytoHubba were used to visualize the DEGs' protein-protein interaction (PPI) network and identify hub genes, Furthermore our results are validated by using Single-cell RNA analysis. Results: Identification of 2524 genes exhibiting altered expression enriched in pathways including keratinization, epidermal cell differentiation, G alpha(s) signaling events, and biological process of cell proliferation and division, extracellular matrix (ECM) disassembly, and muscle function. Moreover, upregulation of hallmarks E2F targets, G2M checkpoints, and TNF signaling. CytoHubba revealed 20 hub genes that had a valuable influence on the progression of ESCC in these patients. Among these, the high expression levels of four genes, CDK1 MAD2L1, PLK1, and TOP2A, were associated with critical dependence for cell survival in ESCC cell lines, as indicated by CRISPR dependency scores, gene expression data, and cell line metadata. We also identify the molecules targeting these essential hub genes, among which GSK461364 is a promising inhibitor of PLK1, BMS265246, and Valrubicin inhibitors of CDK1 and TOP2A, respectively. Moreover, we identified that elevated expression of MMP9 is associated with worse overall survival in ESCC patients, which may serve as potential prognostic biomarker or therapeutic target for ESCC. The single-cell RNA analysis showed MMP9 is highly expressed in myeloid, fibroblast, and epithelial cells, but low in T cells, endothelial cells, and B cells. This suggests MMP9's role in tumor progression and matrix remodeling, highlighting its potential as a prognostic marker and therapeutic target. Discussion: Our study identified key hub genes in ESCC, assessing their potential as therapeutic targets and biomarkers through detailed expression and dependency analyses. Notably, MMP9 emerged as a significant prognostic marker with high expression correlating with poor survival, underscoring its potential for targeted therapy. These findings enhance our understanding of ESCC pathogenesis and highlight promising avenues for treatment.

Elucidating the role of angiogenesis-related genes in colorectal cancer: a multi-omics analysis

Background

Angiogenesis plays a pivotal role in colorectal cancer (CRC), yet its underlying mechanisms demand further exploration. This study aimed to elucidate the significance of angiogenesis-related genes (ARGs) in CRC through comprehensive multi-omics analysis.

Methods

CRC patients were categorized according to ARGs expression to form angiogenesis-related clusters (ARCs). We investigated the correlation between ARCs and patient survival, clinical features, consensus molecular subtypes (CMS), cancer stem cell (CSC) index, tumor microenvironment (TME), gene mutations, and response to immunotherapy. Utilizing three machine learning algorithms (LASSO, Xgboost, and Decision Tree), we screen key ARGs associated with ARCs, further validated in independent cohorts. A prognostic signature based on key ARGs was developed and analyzed at the scRNA-seq level. Validation of gene expression in external cohorts, clinical tissues, and blood samples was conducted via RT-PCR assay.

Results

Two distinct ARC subtypes were identified and were significantly associated with patient survival, clinical features, CMS, CSC index, and TME, but not with gene mutations. Four genes (S100A4, COL3A1, TIMP1, and APP) were identified as key ARCs, capable of distinguishing ARC subtypes. The prognostic signature based on these genes effectively stratified patients into high- or low-risk categories. scRNA-seq analysis showed that these genes were predominantly expressed in immune cells rather than in cancer cells. Validation in two external cohorts and through clinical samples confirmed significant expression differences between CRC and controls.

Conclusion

This study identified two ARG subtypes in CRC and highlighted four key genes associated with these subtypes, offering new insights into personalized CRC treatment strategies.