Helicobacter pylori regulated microRNA map of human gastric cells

Helicobacter pylori and gastric cancer: mechanisms and new perspectives

Gastric cancer remains a significant global health challenge, with Helicobacter pylori (H. pylori) recognized as a major etiological agent, affecting an estimated 50% of the world's population. There has been a rapidly expanding knowledge of the molecular and pathogenetic mechanisms of H. pylori over the decades. This review summarizes the latest research advances to elucidate the molecular mechanisms underlying the H. pylori infection in gastric carcinogenesis. Our investigation of the molecular mechanisms reveals a complex network involving STAT3, NF-κB, Hippo, and Wnt/β-catenin pathways, which are dysregulated in gastric cancer caused by H. pylori. Furthermore, we highlight the role of H. pylori in inducing oxidative stress, DNA damage, chronic inflammation, and cell apoptosis-key cellular events that pave the way for carcinogenesis. Emerging evidence also suggests the effect of H. pylori on the tumor microenvironment and its possible implications for cancer immunotherapy. This review synthesizes the current knowledge and identifies gaps that warrant further investigation. Despite the progress in our previous knowledge of the development in H. pylori-induced gastric cancer, a comprehensive investigation of H. pylori's role in gastric cancer is crucial for the advancement of prevention and treatment strategies. By elucidating these mechanisms, we aim to provide a more in-depth insights for the study and prevention of H. pylori-related gastric cancer.

HNCDrugResDb: a platform for deciphering drug resistance in head and neck cancers

Drug resistance poses a significant obstacle to the success of anti-cancer therapy in head and neck cancers (HNCs). We aim to develop a platform for visualizing and analyzing molecular expression alterations associated with HNC drug resistance. Through data mining, we convened differentially expressed molecules and context-specific signaling events involved in drug resistance. The driver genes, interaction networks and transcriptional regulations were explored using bioinformatics approaches. A total of 2364 differentially expressed molecules were identified in 78 distinct drug-resistant cells against 14 anti-cancer drugs, comprising 1131 mRNAs, 746 proteins, 62 lncRNAs, 257 miRNAs, 1 circRNA, and 166 post-translational modifications. Among these, 255 molecules were considerably, the signature driver genes of HNC drug resistance. Further, we also developed a landscape of signaling pathways and their cross-talk with diverse signaling modules involved in drug resistance. Additionally, a publicly-accessible database named "HNCDrugResDb" was designed with browse, query, and pathway explorer options to fetch and enrich molecular alterations and signaling pathways altered in drug resistance. HNCDrugResDb is also enabled with a Drug Resistance Analysis tool as an initial platform to infer the likelihood of resistance based on the expression pattern of driver genes. HNCDrugResDb is anticipated to have substantial implications for future advancements in drug discovery and optimization of personalized medicine approaches.

Delineating protein biomarkers for gastric cancers: A catalogue of mass spectrometry-based markers and assessment of their suitability for targeted proteomics applications

Gastric cancer (GC) is a global health concern. To facilitate improved management of GCs, protein biomarkers have been identified through mass spectrometry-based proteomics platforms. In order to exhibit clinical utility of such data, we congregated over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the mass spectrometry platforms, association of the protein with infectious agents, protein identifiers, sample size and clinical characters of samples used with details on validation. Development of targeted proteomics methods is the cornerstone for pursuing these markers into clinical utility. Therefore, we developed Protein Biomarker Matrix for Gastric Cancer (PBMGC), a simple catalogue of robustness of each protein. This analysis yielded the identification of robust tissue, serum, and urine diagnostic and prognostic protein biomarker panels which can be further tested for their clinical utility. We also ascertained proteotypic tryptic peptides of 5631 proteins suitable for developing multiple reaction monitoring (MRM) assays. Extensive characterization of these peptides was carried out to record peptide ions, mass/charge and enhanced specific peptide features. With the vision of catering to proteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). Users can browse and download the data and improve GCPDB by submitting recently published data. SIGNIFICANCE: Mass spectrometry-based proteomics platforms have accumulated substantial data on proteins differentially regulated in gastric cancer (GC) clinical samples. The utility of such data in clinical applications is limited by search for suitable biomarker panels for assessment of GCs. We assembled over 6800 differentially regulated proteins in GCs from proteomics studies and recorded the corresponding details including mass spectrometry platforms, status on the association of the protein with infectious agents, protein identifiers from different databases, sample size and clinical characters of samples used in test and control conditions along with details on their validation. Towards the vision of utilizing these markers in clinical assays, Protein Biomarker Matrix for Gastric Cancer (PBMGC) was developed and clinically relevant multi-protein panels were identified. We also demonstrated identification and characterization of tryptic proteotypic tryptic peptides of 5631 proteins biomarkers of GCs which are suitable for development of MRM assays in a SCIEX QTRAP instrument. Aimed to caterproteomics researchers, the data generated through this analysis has been catalogued at Gastric Cancer Proteomics DataBase (GCPDB) (https://ciods.in/gcpdb/). The users can browse and download details on different markers and improve GCPDB by submitting recently published data. Such an analysis could lay a cornerstone for building more such resources or conduct such analysis in different clinical conditions to uptake and develop targeted proteomics as the method of choice for clinical applications.

MicroRNAs in Helicobacter pylori-infected gastric cancer: Function and clinical application

Gastric cancer (GC) is the leading cause of cancer-related death worldwide, and it is associated with a combination of genetic, environmental, and microbial risk factors. Helicobacter pylori (H. pylori) is classified as a type I carcinogen, however, the exact regulatory mechanisms underlying H. pylori-induced GC are incompletely defined. MicroRNAs (miRNAs), one of small non-coding RNAs, negatively regulate gene expression through binding to their target genes. Dysregulation of miRNAs is crucial in human cancer. A noteworthy quantity of aberrant miRNAs induced by H. pylori through complex regulatory networks have been identified. These miRNAs substantially affect genetic instability, cell proliferation, apoptosis, invasion, metastasis, autophagy, chemoresistance, and the tumor microenvironment, leading to GC development and progression. Importantly, some H. pylori-associated miRNAs hold promise as therapeutic tools and biomarkers for GC prevention, diagnosis, and prognosis. Nonetheless, clinical application of miRNAs remains in its infancy with multiple issues, including sensitivity and specificity, stability, reliable delivery systems, and off-target effects. Additional research on the specific molecular mechanisms and more clinical data are still required. This review investigated the biogenesis, regulatory mechanisms, and functions of miRNAs in H. pylori-induced GC, offering novel insights into the potential clinical applications of miRNA-based therapeutics and biomarkers.

Etiologically Significant microRNAs in Hepatitis B Virus-Induced Hepatocellular Carcinoma

Hepatitis B virus (HBV) infection has been causally linked to hepatocellular carcinoma (HCC) in more than 50% cases. MicroRNAs (miRNAs) play cross-cutting mechanistic roles in the complex interplay between viral pathogenesis, host survival, and clinical outcomes. The present study set out to identify etiologically significant human miRNAs associated with HBV infection in liver-related pathologies leading to HCC. In diverse tissue types, we assembled 573 miRNAs differentially expressed in HBV-associated liver pathologies, HBV infection, fibrosis, cirrhosis, acute on chronic liver failure, and HCC. Importantly, 43 human differentially expressed miRNAs (hDEmiRs) were regulated in serum/plasma and liver tissue of patients with HBV-positive conditions. However, only two hDEmiRs, hsa-miR-21-5p and hsa-miR-143-3p, were regulated across all disease conditions. To shortlist the functional miRNAs in HBV-induced HCC pathogenesis, a reverse bioinformatics analysis was performed using eight GEO datasets and the TCGA database containing the list of differentially regulated mRNAs in HCC. A comparative study using these data with the identified targets of hDEmiRs, a set of unidirectionally regulated hDEmiRs with the potential to modulate mRNAs in HCC, were found. Moreover, our study identified five miRNAs; hsa-miR-98-5p, hsa-miR-193b-3p, hsa-miR-142-5p, hsa-miR-522-5p, and hsa-miR-370-3p targeting PIGC, KNTC1, CSTF2, SLC41A2, and RAB17, respectively, in HCC. These hDEmiRs and their targets could be pivotal in HBV infection and subsequent liver pathologies modulating HCC clinical progression. HBV infection is the largest contributor to HCC, and the present study comprises the first of its kind compendium of hDEmiRs related to HBV-related pathologies.

Non-Coding RNA as Biomarkers and Their Role in the Pathogenesis of Gastric Cancer-A Narrative Review

Non-coding RNAs (ncRNAs) represent a broad family of molecules that regulate gene expression, including microRNAs, long non-coding RNAs and circular RNAs, amongst others. Dysregulated expression of ncRNAs alters gene expression, which is implicated in the pathogenesis of several malignancies and inflammatory diseases. Gastric cancer is the fifth most frequently diagnosed cancer and the fourth most common cause of cancer-related death. Studies have found that altered expression of ncRNAs may contribute to tumourigenesis through regulating proliferation, apoptosis, drug resistance and metastasis. This review describes the potential use of ncRNAs as diagnostic and prognostic biomarkers. Moreover, we discuss the involvement of ncRNAs in the pathogenesis of gastric cancer, including their interactions with the members of major signalling pathways.

Machine Learning Strategies in MicroRNA Research: Bridging Genome to Phenome

MicroRNAs (miRNAs) have emerged as a prominent layer of regulation of gene expression. This article offers the salient and current aspects of machine learning (ML) tools and approaches from genome to phenome in miRNA research. First, we underline that the complexity in the analysis of miRNA function ranges from their modes of biogenesis to the target diversity in diverse biological conditions. Therefore, it is imperative to first ascertain the miRNA coding potential of genomes and understand the regulatory mechanisms of their expression. This knowledge enables the efficient classification of miRNA precursors and the identification of their mature forms and respective target genes. Second, and because one miRNA can target multiple mRNAs and vice versa, another challenge is the assessment of the miRNA-mRNA target interaction network. Furthermore, long-noncoding RNA (lncRNA)and circular RNAs (circRNAs) also contribute to this complexity. ML has been used to tackle these challenges at the high-dimensional data level. The present expert review covers more than 100 tools adopting various ML approaches pertaining to, for example, (1) miRNA promoter prediction, (2) precursor classification, (3) mature miRNA prediction, (4) miRNA target prediction, (5) miRNA- lncRNA and miRNA-circRNA interactions, (6) miRNA-mRNA expression profiling, (7) miRNA regulatory module detection, (8) miRNA-disease association, and (9) miRNA essentiality prediction. Taken together, we unpack, critically examine, and highlight the cutting-edge synergy of ML approaches and miRNA research so as to develop a dynamic and microlevel understanding of human health and diseases.

Integrative Placental Multi-Omics Analysis Reveals Perturbed Pathways and Potential Prognostic Biomarkers in Gestational Hypertension

BACKGROUND

Gestational hypertension (GH) is a severe complication that occurs after 20 weeks of pregnancy; however, its molecular mechanisms are not yet fully understood.

OBJECTIVE

Through this case-control discovery phase study, we aimed to find disease-specific candidate placental microRNAs (miRNAs) and metabolite markers for differentiating GH by integrating next-generation sequencing and metabolomics multi-omics analysis of placenta. Using small RNA sequencing and metabolomics of placental tissues of healthy pregnant (HP, n = 24) and GH subjects (n = 20), the transcriptome and metabolome were characterized in both groups.

RESULTS

The study identified a total of 44 downregulated placental miRNAs which includes three novel, three mature and 38 precursor miRNAs. Six miRNAs including three mature (hsa-miR-181a-5p, hsa-miR-498-5p, and hsa-miR-26b-5p) and three novel (NC_000016.10_1061, NC_000005.10_475, and NC_000001.11_53) were considered for final target prediction and functional annotation. Integrative analysis of differentially expressed miRNAs and metabolites yielded five pathways such as purine, glutathione, glycerophospholipid, inositol phosphate and β-alanine to be significantly perturbed in GH. We present fourteen genes (LPCAT1, LPCAT2, DGKH, PISD, GPAT2, PTEN, SACM1L, PGM2, AMPD3, AK7, AK3, CNDP1, IDH2, and ODC1) and eight metabolites (xanthosine, xanthine, spermine, glycine, CDP-Choline, glyceraldehyde 3-phosphate, β-alanine, and histidine) with potential to distinguish GH and HP.

CONCLUSION

The differential expression of miRNAs, their target genes, altered metabolites and metabolic pathways in GH patients were identified for the first time in our study. Further, the altered miRNAs and metabolites were integrated to build their inter-connectivity network. The findings obtained from our study may be used as a valuable source to further unravel the molecular pathways associated with GH and also for the evaluation of prognostic markers.

Hepatitis B Virus Modulated Transcriptional Regulatory Map of Hepatic Cellular MicroRNAs

Hepatitis B virus (HBV) is an enveloped, hepatotropic, noncytopathic virus with a partially double-stranded DNA genome. It infects hepatocytes and is associated with progression to liver fibrosis and cirrhosis, culminating in hepatocellular carcinoma (HCC), accounting for 55% of total HCC cases. MicroRNAs (miRNAs) regulated by HBV play an important role in these pathologies. Mapping the miRNAs responsive to HBV and HBV-specific proteins, including HBV X protein (HBx) that harbor the majority of HBV-human protein interactions, could aid accelerate the diagnostics and therapeutics innovation against the infection and associated diseases. With this in mind, we used a unique annotation strategy whereby we first amassed 362 mature HBV responsive-human Differentially Expressed miRNAs (HBV-hDEmiRs). The core experimentally-validated messenger RNA targets of the HBV-hDEmiRs were mostly associated with viral infections and hepatic inflammation processes. Moreover, our annotation strategy enabled the characterization of HBx-dependent/independent HBV-hDEmiRs as a tool for evaluation of the impact of HBx as a therapeutic target. Bioinformatics analysis of the HBV-human protein-protein interactome revealed new insights into the transcriptional regulatory network of the HBV-hDEmiRs. We performed a comparative analysis of data on miRNAs gathered from HBV infected cell line studies and from tissue studies of fibrosis, cirrhosis, and HCC. Accordingly, we propose hsa-miR-15a-5p that is downregulated by multiple HBV proteins, including HBx, as a potential biomarker of HBV infection, and its progression to HCC. In all, this study underscores (1) the complexity of miRNA regulation in response to HBV infection and its progression into other liver pathologies and (2) provides a regulatory map of HBV-hDEmiRs and the underlying mechanisms modulating their expression through a cross talk between HBV viral proteins and human transcription factors.