Bioinformatics Analysis of a Prognostic miRNA Signature and Potential Key Genes in Pancreatic Cancer

Type XII collagen is elevated in serum from patients with solid tumors: a non-invasive biomarker of activated fibroblasts

Understanding the tumor microenvironment (TME) and extracellular matrix (ECM) is crucial in cancer research due to their impact on tumor progression. Collagens, major ECM components, regulate cell signaling and behavior. Of the 28 reported collagens, type XII collagen is known to be vital for ECM organization. Over-produced by cancer-associated fibroblasts (CAFs), its upregulation correlates with poor survival in various cancers. This study aimed to develop an ELISA for quantifying circulating type XII collagen as a cancer biomarker. A specific ELISA targeting the C-terminal of type XII collagen was developed and used to analyze serum samples from cancer patients (n = 203) and healthy controls (n = 33). Additionally, type XII collagen expression was assessed in CAFs and normal fibroblasts (NFs) from different tissues, both under TGF-β stimulated and non-stimulated conditions. The nordicPRO-C12 ELISA demonstrated robustness and specificity for type XII collagen. PRO-C12 levels were significantly elevated in patients with various cancers compared to healthy controls and effectively distinguished between cancer patients and controls. Findings were validated using gene expression data. Furthermore, Western blot analysis revealed increased type XII collagen expression in both CAFs and NFs upon TGF-β1 stimulation, suggesting a potential role of TGF-β1 in modulating the expression of type XII collagen in cancerous and normal tissue microenvironments. This study unveils a promising avenue for harnessing PRO-C12 as a non-invasive serum biomarker, enabling the quantification of type XII collagen fragments in cancer patients. Further investigations are warranted to explore the potential of PRO-C12 across different cancer types and disease stages, shedding light on its multifaceted role in cancer development.

MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications

Pancreatic cancer remains a formidable malignancy characterized by high mortality rates, primarily attributable to late-stage diagnosis and a dearth of effective therapeutic interventions. The identification of reliable biomarkers holds paramount importance in enhancing early detection, prognostic evaluation, and targeted treatment modalities. Small non-coding RNAs, particularly microRNAs, have emerged as promising candidates for pancreatic cancer biomarkers in recent years. In this review, we delve into the evolving role of cellular and circulating miRNAs, including exosomal miRNAs, in the diagnosis, prognosis, and therapeutic targeting of pancreatic cancer. Drawing upon the latest research advancements in omics data-driven biomarker discovery, we also perform a case study using public datasets and address commonly identified research discrepancies, challenges, and limitations. Lastly, we discuss analytical approaches that integrate multimodal analyses incorporating clinical and molecular features, presenting new insights into identifying robust miRNA-centric biomarkers.

Integrating a microRNA signature as a liquid biopsy-based tool for the early diagnosis and prediction of potential therapeutic targets in pancreatic cancer

INTRODUCTION

Pancreatic cancer is a highly aggressive cancer, and early diagnosis significantly improves patient prognosis due to the early implementation of curative-intent surgery. Our study aimed to implement machine-learning algorithms to aid in early pancreatic cancer diagnosis based on minimally invasive liquid biopsies.

MATERIALS AND METHODS

The analysis data were derived from nine public pancreatic cancer miRNA datasets and two sequencing datasets from 26 pancreatic cancer patients treated in our medical center, featuring small RNAseq data for patient-matched tumor and non-tumor samples and serum. Upon batch-effect removal, systematic analyses for differences between paired tissue and serum samples were performed. The robust rank aggregation (RRA) algorithm was used to reveal feature markers that were co-expressed by both sample types. The repeatability and real-world significance of the enriched markers were then determined by validating their expression in our patients' serum. The top candidate markers were used to assess the accuracy of predicting pancreatic cancer through four machine learning methods. Notably, these markers were also applied for the identification of pancreatic cancer and pancreatitis. Finally, we explored the clinical prognostic value, candidate targets and predict possible regulatory cell biology mechanisms involved.

RESULTS

Our multicenter analysis identified hsa-miR-1246, hsa-miR-205-5p, and hsa-miR-191-5p as promising candidate serum biomarkers to identify pancreatic cancer. In the test dataset, the accuracy values of the prediction model applied via four methods were 94.4%, 84.9%, 82.3%, and 83.3%, respectively. In the real-world study, the accuracy values of this miRNA signatures were 82.3%, 83.5%, 79.0%, and 82.2. Moreover, elevated levels of these miRNAs were significant indicators of advanced disease stage and allowed the discrimination of pancreatitis from pancreatic cancer with an accuracy rate of 91.5%. Elevated expression of hsa-miR-205-5p, a previously undescribed blood marker for pancreatic cancer, is associated with negative clinical outcomes in patients.

CONCLUSION

A panel of three miRNAs was developed with satisfactory statistical and computational performance in real-world data. Circulating hsa-miRNA 205-5p serum levels serve as a minimally invasive, early detection tool for pancreatic cancer diagnosis and disease staging and might help monitor therapy success.

A nine-gene signature as prognostic biomarker in gastric cancer by bioinformatics analysis

PURPOSE

The prognosis of advanced gastric cancer (GC) remains poor. It is urgent and necessary to find suitable prognostic markers. miR-619-5p is highly expressed in GC. However, the value of miR-619-5p and its target genes as prognostic biomarkers of GC is unclear.

METHODS

RT-PCR was performed to verify the expression of miR-619-5p in GC cell lines and their exosomes. Western blotting and transmission electron microscope were used to identify exosomes. The target genes of miR-619-5p were predicted by RNA22 and TargetScan. The differentially expressed genes (DEGs) and prognosis-related genes (PRGs) were obtained using The Cancer Genome Atlas (TCGA) database. The DAVID database was used to analyse pathway enrichment and functional annotation of common target genes. The STRING database and Cytoscape software were used to screen key genes and visualize their functional modules. The survival analysis was conducted using TCGA and Kaplan-Meier Plotter (KMP) databases. Finally, a prognostic model was constructed on the foundation of the key genes to assess the reliability of the screening process.

RESULTS

The expression of miR-619-5p in GC cells and their exosomes was proved to be significantly higher than that in normal cell lines. There are 129 common target genes involved in 3 pathways and 28 functional annotations. Finally, nine key target genes of GC (BRCA1, RAD51, KIF11, ERCC6L, BRIP1, TIMELESS, CDC25A, CLSPN and NCAPG2) were identified, and a prognostic model was successfully constructed with a good predictive ability.

CONCLUSIONS

The model of 9-gene signature could effectively predict the prognosis of GC, and have great potential to be novel prognostic factors and therapeutic targets for patients with GC.

Role of Some microRNA/ADAM Proteins Axes in Gastrointestinal Cancers as a Novel Biomarkers and Potential Therapeutic Targets—A Review

Gastrointestinal (GI) cancers are some of the most common cancers in the world and their number is increasing. Their etiology and pathogenesis are still unclear. ADAM proteins are a family of transmembrane and secreted metalloproteinases that play a role in cancerogenesis, metastasis and neoangiogenesis. MicroRNAs are small single-stranded non-coding RNAs that take part in the post-transcriptional regulation of gene expression. Some ADAM proteins can be targets for microRNAs. In this review, we analyze the impact of microRNA/ADAM protein axes in GI cancers.

COL12A1 Acts as a Novel Prognosis Biomarker and Activates Cancer-Associated Fibroblasts in Pancreatic Cancer through Bioinformatics and Experimental Validation

Pancreatic cancer remains one of the most challenging malignancies to date and is associated with poor survival. Cancer-associated fibroblasts (CAFs) are key stromal cells in the tumor microenvironment (TME) that play a crucial role in tumor progression in pancreatic cancer. Thus, uncovering the key genes involved in CAF progression and determining their prognostic value is critically important. Herein, we report our discoveries in this research area. Analysis of The Cancer Genome Atlas (TCGA) dataset and investigation of our clinical tissue samples indicated that COL12A1 expression was aberrantly highly expressed in pancreatic cancer. Survival and COX regression analyses revealed the significant clinical prognostic value of COL12A1 expression in pancreatic cancer. COL12A1 was mainly expressed in CAFs but not in tumor cells. This was verified with our PCR analysis in cancer cells and CAFs. The knocking down of COL12A1 decreased the proliferation and migration of CAFs and down-regulated the expression of CAF activation markers actin alpha 2 (ACTA2), fibroblast activation protein (FAP), and fibroblast-specific protein 1 (FSP1). Meanwhile, the interleukin 6 (IL6), CXC chemokine Ligand-5 (CXCL5), and CXC chemokine Ligand-10 (CXCL10) expressions were inhibited, and the cancer-promoting effect was reversed by COL12A1 knockdown. Therefore, we demonstrated the potential prognostic and target therapy value of COL12A1 expression in pancreatic cancer and elucidated the molecular mechanism underlying its role in CAFs. The findings of this study might provide new opportunities for TME-targeted therapies in pancreatic cancer.

[MiR-4772 modulates tumor immune microenvironment by regulating immune- related genes in ovarian cancer]

OBJECTIVE

To explore the regulatory role of miR-4772 in the formation of tumor immune microenvironment in ovarian cancer.

METHODS

The optimal cutoff level of PD-L1 expression was calculated based on data from 294 ovarian cancer patients in the TCGA database. The differentially expressed genes (DEGs) between high and low PD-L1 expression groups were screened, and the important DEGs were identified by correlation analysis. WGCNA analysis was performed to select the weighted genes and PD-L1-related miRNAs, from which the hub genes were obtained by intersection analysis. ssGSEA analysis was used to evaluate the effect of PD-L1 and miR-4772 expressions on the tumor immune microenvironment in ovarian cancer. KEGG analysis was used to identify the involved signal pathways, and the interactions between the hub genes were mapped by protein-protein interaction (PPI) analysis. Survival analysis was carried out to identify the survival-related hub genes, and the results were validated using the data of 399 patients with ovarian cancer from GEO database and the sequencing results of SKOV3 cells transfected with miR-4772 mimics or inhibitor.

RESULTS

According the optimal cutoff level of PD-L1 expression of 1.31582 (90th quantile), the patients were divided into high- and low-PD-L1 expression groups. A total of 840 DEGs were identified, including 549 significantly up-regulated genes and 291 down-regulated genes. Among them, 20 important DEGs were found to closely correlate with miR-4772 expression, and WGCNA analysis identified 48 weighted genes significantly correlated with miR-4772. Twelve genes were identified as both key DEGs and weighted genes and were treated as the hub genes. ssGSEA analysis showed that both the patients with high PD-L1 expressions and those with high miR-4772 expressions showed more active immune infiltration and functional activity. The 12 hub genes were involved mainly in immune-related signaling pathways, and PPI analysis suggested significant interactions among the hub genes. The two hub genes CD96 and TBX21 showed close correlation with the survival of ovarian cancer patients. The sequencing results of SKOV3 cells transfected with miR-4772 mimics or inhibitor showed that the changes in miR-4772 expression level caused obvious changes in the expressions of the 12 hub genes and PD-L1.

CONCLUSION

MiR-4772 plays a regulatory role in the formation of tumor immune microenvironment in ovarian cancer by regulating 12 hub genes.

An immune-related microRNA signature prognostic model for pancreatic carcinoma and association with immune microenvironment

To establish a prognostic model based on immune-related microRNA (miRNA) for pancreatic carcinoma. Weighted correlation network analysis (WGCNA) was performed using the "WGCNA" package to find the key module genes involved in pancreatic carcinoma. Spearman correlation analysis was conducted to screen immune-related miRNAs. Uni- and multi-variate COX regression analyses were carried out to identify miRNAs prognostic for overall survival (OS) of pancreatic carcinoma, which were then combined to generate a prognostic model. Kaplan–Meier survival analysis, receiver operating characteristic (ROC) analysis, distribution plot of survival status in patients and regression analysis were collectively performed to study the accuracy of the model in prognosis. Target genes of the miRNAs in the model were intersected with the key module genes, and a miRNA–mRNA network was generated and visualized by Cytoscape3.8.0. TIMER analysis was conducted to study the abundance of immune infiltrates in tumor microenvironment of pancreatic carcinoma. Expression levels of immune checkpoint genes in subgroups stratified by the model were compared by Wilcoxon test. Gene Set Enrichment Analysis (GSEA) was performed to analyze the enriched signaling pathways between subgroups. Differential analysis revealed 1826 genes differentially up-regulated in pancreatic carcinoma and 1276 genes differentially down-regulated. A total of 700 immune-related miRNAs were obtained, of which 7 miRNAs were significantly associated with OS of patients and used to establish a prognostic model with accurate predictive performance. There were 99 mRNAs overlapped from the 318 target genes of the 7 miRNAs and the key modules genes analyzed by WGCNA. Patient samples were categorized as high or low risk according to the prognostic model, which were significantly associated with dendritic cell infiltration and expression of immune checkpoint genes (TNFSF9, TNFRSF9, KIR3DL1, HAVCR2, CD276 and CD80). GSEA showed remarkably enriched signaling pathways in the two subgroups. This study identified an immune-related 7-miRNA based prognostic model for pancreatic carcinoma, which could be used as a reliable tool for prognosis.

Effect of SARS-CoV-2 infection on asthma patients

Background

SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma.

Methods

To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates.

Results

There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets.

Conclusion

We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

Integrated Analysis of ECT2 and COL17A1 as Potential Biomarkers for Pancreatic Cancer

Background

Pancreatic cancer (PC) is a malignant tumor of the digestive tract. It presents with atypical clinical symptoms and lacks specific diagnostic indicators. This study is aimed at exploring the potential biomarkers of PC.

Methods

TCGA database pancreatic cancer dataset was normalized and used to identify differentially expressed genes (DEGs). Survival, independent prognostic, and clinical correlation analyses were performed on DEGs to screen for key genes. DNA methylation, mutation, and copy number variation (CNV) analyses were used to analyze genetic variants in key genes. GSEA was performed to explore the functional enrichment of the key genes. Based on the expression of key genes, construction of a competing endogenous RNA (ceRNA) network, analysis of the tumor microenvironment (TME), and prediction of chemotherapeutic drug sensitivity were performed. Furthermore, the GEO database was used to validate the reliability of key genes.

Results

Two key genes (ECT2 and COL17A1) were identified, which were highly expressed in PC. The mRNA expression of ECT2 and COL17A1 was associated with DNA methylation and CNV. The cell cycle, proteasome, and pathways in cancer were enriched in the high-COL17A1 and ECT2 groups. The TME results showed that immune scores were decreased in the high-ECT2 group. CeRNA network results showed that there were eleven miRNAs were involved in the regulation of ECT2 and COL17A1. Moreover, pRRophetic analysis showed that 20 chemotherapeutic drugs were associated with ECT2 and COL17A1 expression.

Conclusions

Collectively, ECT2 and COL17A1 may be potential biomarkers for PC, providing a new direction for clinical diagnosis and treatment.

Ultrasound-targeted microbubble destruction-mediated silencing of FBXO11 suppresses development of pancreatic cancer

Ultrasound-targeted microbubble destruction (UTMD) has been a promising noninvasive tool for organ- or tissue-specific gene or drug delivery. This study aimed to explore the function of F-box protein 11 (FBXO11), an E3 ubiquitin ligase, in the development of pancreatic cancer (PCa). Differentially expressed genes in PCa were identified using the GSE62452 and GSE28735 datasets, and FBXO11 was significantly highly expressed in PCa. UTMD-mediated FBXO11 silencing significantly suppressed growth activity, epithelial-mesenchymal transition, migration, and invasion while reduced apoptosis of PCa cells in vitro and reduced the growth and metastasis of xenograft tumors in vivo. Importantly, UTMD-mediated sh-FBXO11 showed more pronounced tumor-suppressive effects than direct administration of sh-FBXO11 alone. The potential substrates of FBXO11 as an E3 ubiquitin ligase were predicted using the Ubibrowser. TP53 was predicted and validated as a downstream substrate of FBXO11. FBXO11 induced ubiquitination and degradation of the tumor suppressor protein TP53 to induce PCa progression. In conclusion, this study suggests that silencing of FBXO11, especially that mediated by UTMD, might suppress the malignant biological behaviors of PCa cells and serve as a potential therapeutic strategy for PCa management.

Exposure to trace levels of metals and fluoroquinolones increases inflammation and tumorigenesis risk of zebrafish embryos

Exposure to trace-level heavy metals and antibiotics may elicit metabolic disorder, alter protein expression, and then induce pathological changes in zebrafish embryos, despite negligible physiological and developmental toxicity. This study investigated the single and combined developmental toxicity of fluoroquinolones (enrofloxacin [ENR] and ciprofloxacin [CIP]) (≤0.5 μM) and heavy metals (Cu and Cd) (≤0.5 μM) to zebrafish embryos, and molecular responses of zebrafish larvae upon exposure to the single pollutant (0.2 μM) or a binary metal-fluoroquinolone mixture (0.2 μM). In all single and mixture exposure groups, no developmental toxicity was observed, but oxidative stress, inflammation, and lipid depletion were found in zebrafish embryos, which was more severe in the mixture exposure groups than in the single exposure groups, probably due to increased metal bioaccumulation in the presence of ENR or CIP. Metabolomics analysis revealed the up-regulation of amino acids and down-regulation of fatty acids, corresponding to an active response to oxidative stress and the occurrence of inflammation. The up-regulation of antioxidase and immune proteins revealed by proteomics analysis further confirmed the occurrence of oxidative stress and inflammation. Furthermore, the KEGG pathway enrichment analysis showed a significant disturbance of pathways related to immunity and tumor, indicating the potential risk of tumorigenesis in zebrafish larvae. The findings provide molecular-level insights into the adverse effects of heavy metals and antibiotics (especially in chemical mixtures) on zebrafish embryos, and highlight the potential ecotoxicological risks of trace-level heavy metals and antibiotics in the environment.

NOV/CCN3 Promotes Cell Migration and Invasion in Intrahepatic Cholangiocarcinoma via miR-92a-3p

Intrahepatic cholangiocarcinoma (ICC) is a common type of human cancer with a poor prognosis, and investigating the potential molecular mechanisms that can contribute to gene diagnosis and therapy. Herein, based on the recently concerned vertebrate-specific Cyr61/CTGF/NOV (CCN) gene family because of its important roles in diverse diseases, we obtained NOV/CCN3 to query for its potential roles in tumorigenesis via bioinformatics analysis. Experimental validations confirmed that both NOV mRNA and protein are up-regulated in two ICC cell lines, suggesting that it may promote cell migration and invasion by promoting EMT. To elucidate the detailed regulatory mechanism, miR-92a-3p is screened and identified as a negative regulatory small RNA targeting NOV, and further experimental validation demonstrates that miR-92a-3p contributes to NOV-mediated migration and invasion of ICC via the Notch signaling pathway. Our study reveals that NOV may be a potential target for diagnosing and treating ICC, which will provide experimental data and molecular theoretical foundation for cancer treatment, particularly for future precision medicine.

Short- and long-range cis interactions between integrated HPV genomes and cellular chromatin dysregulate host gene expression in early cervical carcinogenesis

Development of cervical cancer is directly associated with integration of human papillomavirus (HPV) genomes into host chromosomes and subsequent modulation of HPV oncogene expression, which correlates with multi-layered epigenetic changes at the integrated HPV genomes. However, the process of integration itself and dysregulation of host gene expression at sites of integration in our model of HPV16 integrant clone natural selection has remained enigmatic. We now show, using a state-of-the-art 'HPV integrated site capture' (HISC) technique, that integration likely occurs through microhomology-mediated repair (MHMR) mechanisms via either a direct process, resulting in host sequence deletion (in our case, partially homozygously) or via a 'looping' mechanism by which flanking host regions become amplified. Furthermore, using our 'HPV16-specific Region Capture Hi-C' technique, we have determined that chromatin interactions between the integrated virus genome and host chromosomes, both at short- (<500 kbp) and long-range (>500 kbp), appear to drive local host gene dysregulation through the disruption of host:host interactions within (but not exceeding) host structures known as topologically associating domains (TADs). This mechanism of HPV-induced host gene expression modulation indicates that integration of virus genomes near to or within a 'cancer-causing gene' is not essential to influence their expression and that these modifications to genome interactions could have a major role in selection of HPV integrants at the early stage of cervical neoplastic progression.

Hsa-miR-4277 Decelerates the Metabolism or Clearance of Sorafenib in HCC Cells and Enhances the Sensitivity of HCC Cells to Sorafenib by Targeting cyp3a4

Increasing evidence has shown that the metabolism and clearance of molecular targeted agents, such as sorafenib, plays an important role in mediating the resistance of HCC cells to these agents. Metabolism of sorafenib is performed by oxidative metabolism, which is initially mediated by CYP3A4. Thus, targeting CYP3A4 is a promising approach to enhance the sensitivity of HCC cells to chemotherapeutic agents. In the present work, we examined the association between CYP3A4 and the prognosis of HCC patients receiving sorafenib. Using the online tool miRDB, we predicted that has-microRNA-4277 (miR-4277), an online miRNA targets the 3’UTR of the transcript of cyp3a4. Furthermore, overexpression of miR-4277 in HCC cells repressed the expression of CYP3A4 and reduced the elimination of sorafenib in HCC cells. Moreover, miR-4277 enhanced the sensitivity of HCC cells to sorafenib in vitro and in vivo. Therefore, our results not only expand our understanding of CYP3A4 regulation in HCC, but also provide evidence for the use of miR-4277 as a potential therapeutic in advanced HCC.