Integrative weighted molecular network construction from transcriptomics and genome wide association data to identify shared genetic biomarkers for COPD and lung cancer

DPF3 polymorphisms increased the risk of pulmonary tuberculosis in the Northwest Chinese Han population

PURPOSE

This study aimed to investigate the association between single nucleotide polymorphisms (SNPs) in DPF3 and susceptibility to pulmonary tuberculosis (PTB) in the Northwest Chinese Han population.

METHODS

Genotyping of four DPF3 SNPs (rs10140566, rs75575287, rs202075571, and rs61986330) was performed using Agena MassARRAY from 488 PTB patients and 488 healthy controls. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using logistic regression. Multifactor dimensionality reduction (MDR) analysis was employed to investigate the effect of SNP-SNP interactions on PTB risk. The GSE54992 dataset was analyzed using R software to ascertain DPF3 expression levels.

RESULTS

Overall analysis revealed that rs202075571 (allele: OR = 1.31, p = 0.015; CC vs. TT: OR = 1.97, p = 0.049; dominant: OR = 1.33, p = 0.032) and rs61986330 (allele: OR = 1.38, p = 0.010; CA vs. CC: OR = 1.35, p = 0.044; dominant: OR = 1.40, p = 0.019) were associated with an increased PTB risk. Stratified analysis showed that rs10140566 was a PTB risk factor in females, those aged ≤40 and non-smokers, and rs202075571 was associated with PTB risk in individuals aged >40 and smokers, and rs61986330 was associated with PTB risk in males, those aged >40 and smokers. The four SNPs model demonstrated significant predictive potential for PTB risk. Furthermore, DPF3 exhibited higher expression in PTB compared to healthy controls.

CONCLUSION

DPF3 polymorphisms (rs10140566, rs202075571, and rs61986330) are associated with an increased risk of PTB, providing valuable new insights into the mechanism of PTB.

In-silico discovery of common molecular signatures for which SARS-CoV-2 infections and lung diseases stimulate each other, and drug repurposing

COVID-19 caused by SARS-CoV-2 is a global health issue. It is yet a severe risk factor to the patients, who are also suffering from one or more chronic diseases including different lung diseases. In this study, we explored common molecular signatures for which SARS-CoV-2 infections and different lung diseases stimulate each other, and associated candidate drug molecules. We identified both SARS-CoV-2 infections and different lung diseases (Asthma, Tuberculosis, Cystic Fibrosis, Pneumonia, Emphysema, Bronchitis, IPF, ILD, and COPD) causing top-ranked 11 shared genes (STAT1, TLR4, CXCL10, CCL2, JUN, DDX58, IRF7, ICAM1, MX2, IRF9 and ISG15) as the hub of the shared differentially expressed genes (hub-sDEGs). The gene ontology (GO) and pathway enrichment analyses of hub-sDEGs revealed some crucial common pathogenetic processes of SARS-CoV-2 infections and different lung diseases. The regulatory network analysis of hub-sDEGs detected top-ranked 6 TFs proteins and 6 micro RNAs as the key transcriptional and post-transcriptional regulatory factors of hub-sDEGs, respectively. Then we proposed hub-sDEGs guided top-ranked three repurposable drug molecules (Entrectinib, Imatinib, and Nilotinib), for the treatment against COVID-19 with different lung diseases. This recommendation is based on the results obtained from molecular docking analysis using the AutoDock Vina and GLIDE module of Schrödinger. The selected drug molecules were optimized through density functional theory (DFT) and observing their good chemical stability. Finally, we explored the binding stability of the highest-ranked receptor protein RELA with top-ordered three drugs (Entrectinib, Imatinib, and Nilotinib) through 100 ns molecular dynamic (MD) simulations with YASARA and Desmond module of Schrödinger and observed their consistent performance. Therefore, the findings of this study might be useful resources for the diagnosis and therapies of COVID-19 patients who are also suffering from one or more lung diseases.

From Data to Cure: A Comprehensive Exploration of Multi-omics Data Analysis for Targeted Therapies

In the dynamic landscape of targeted therapeutics, drug discovery has pivoted towards understanding underlying disease mechanisms, placing a strong emphasis on molecular perturbations and target identification. This paradigm shift, crucial for drug discovery, is underpinned by big data, a transformative force in the current era. Omics data, characterized by its heterogeneity and enormity, has ushered biological and biomedical research into the big data domain. Acknowledging the significance of integrating diverse omics data strata, known as multi-omics studies, researchers delve into the intricate interrelationships among various omics layers. This review navigates the expansive omics landscape, showcasing tailored assays for each molecular layer through genomes to metabolomes. The sheer volume of data generated necessitates sophisticated informatics techniques, with machine-learning (ML) algorithms emerging as robust tools. These datasets not only refine disease classification but also enhance diagnostics and foster the development of targeted therapeutic strategies. Through the integration of high-throughput data, the review focuses on targeting and modeling multiple disease-regulated networks, validating interactions with multiple targets, and enhancing therapeutic potential using network pharmacology approaches. Ultimately, this exploration aims to illuminate the transformative impact of multi-omics in the big data era, shaping the future of biological research.

MECOM: a bioinformatics and experimentally identified marker for the diagnosis and prognosis of lung adenocarcinoma

Objective: We aimed to explore the clinical value of MDS1 and EVI1 complex locus (MECOM) in lung adenocarcinoma (LUAD). Methods: Bioinformatics and experimental validation confirmed MECOM expression levels in LUAD. The value of MECOM was analyzed by receiver operating characteristic (ROC) curve and Cox regression analysis. Results: Serum MECOM levels were lower in LUAD and correlated with gender, TNM stage, tumor size, lymph node metastasis and distant metastasis. The ROC curve showed that the area under the curve of MECOM was 0.804 for LUAD and, of note, could reach 0.889 for advanced LUAD; specificity was up to 90%. Conclusion: MECOM may contribute to independently identifying LUAD patients, particularly in advanced stages.

Antioncogenic roles of USP9Y and DDX3Y in lung cancer: USP9Y stabilizes DDX3Y by preventing its degradation through deubiquitination

In previous studies, downregulation of USP9Y and DDX3Y in lung cancer (LC) tissues was identified, while their function in LC progression remains elusive. In our current work, we intended to elucidate the effect and mechanisms of USP9Y and DDX3Y in LC. Gene downregulation has been confirmed in our LC tissues and cells. The effect of USP9Y or DDX3Y on LC cell malignancies was analyzed by functional assay. Both USP9Y and DDX3Y overexpression showed suppressive impact on LC cell malignancies. USP9Y overexpression has also been demonstrated to inhibit tumorigenesis in vivo. Based on GEPIA database, it was found that there was a positive correlation between the levels of USP9Y and DDX3Y in LC tissues. The mRNA expression of DDX3Y was not affected by USP9Y overexpression, while its protein levels were significantly up-regulated in USP9Y overexpressed LC cells. Moreover, USP9Y interacted with DDX3Y and has been demonstrated to stabilize DDX3Y expression by preventing its degradation via deubiquitination. In conclusion, USP9Y and DDX3Y exerted antioncogenic effects on the cell proliferation potential, cell cycle process, apoptosis, and tumorigenesis of LC. USP9Y binds to DDX3Y to prevent DDX3Y degradation through deubiquitination.

Diverse targets of SMN2-directed splicing-modulating small molecule therapeutics for spinal muscular atrophy

Designing an RNA-interacting molecule that displays high therapeutic efficacy while retaining specificity within a broad concentration range remains a challenging task. Risdiplam is an FDA-approved small molecule for the treatment of spinal muscular atrophy (SMA), the leading genetic cause of infant mortality. Branaplam is another small molecule which has undergone clinical trials. The therapeutic merit of both compounds is based on their ability to restore body-wide inclusion of Survival Motor Neuron 2 (SMN2) exon 7 upon oral administration. Here we compare the transcriptome-wide off-target effects of these compounds in SMA patient cells. We captured concentration-dependent compound-specific changes, including aberrant expression of genes associated with DNA replication, cell cycle, RNA metabolism, cell signaling and metabolic pathways. Both compounds triggered massive perturbations of splicing events, inducing off-target exon inclusion, exon skipping, intron retention, intron removal and alternative splice site usage. Our results of minigenes expressed in HeLa cells provide mechanistic insights into how these molecules targeted towards a single gene produce different off-target effects. We show the advantages of combined treatments with low doses of risdiplam and branaplam. Our findings are instructive for devising better dosing regimens as well as for developing the next generation of small molecule therapeutics aimed at splicing modulation.

Rare variant burden analysis from exomes of three consanguineous families reveals LILRB1 and PRSS3 as potential key proteins in inflammatory bowel disease pathogenesis

Background

Inflammatory bowel disease (IBD) is a chronic autoimmune disorder characterized by severe inflammation and mucosal destruction of the intestine. The specific, complex molecular processes underlying IBD pathogenesis are not well understood. Therefore, this study is aimed at identifying and uncovering the role of key genetic factors in IBD.

Method

The whole exome sequences (WESs) of three consanguineous Saudi families having many siblings with IBD were analyzed to discover the causal genetic defect. Then, we used a combination of artificial intelligence approaches, such as functional enrichment analysis using immune pathways and a set of computational functional validation tools for gene expression, immune cell expression analyses, phenotype aggregation, and the system biology of innate immunity, to highlight potential IBD genes that play an important role in its pathobiology.

Results

Our findings have shown a causal group of extremely rare variants in the LILRB1 (Q53L, Y99N, W351G, D365A, and Q376H) and PRSS3 (F4L and V25I) genes in IBD-affected siblings. Findings from amino acids in conserved domains, tertiary-level structural deviations, and stability analysis have confirmed that these variants have a negative impact on structural features in the corresponding proteins. Intensive computational structural analysis shows that both genes have very high expression in the gastrointestinal tract and immune organs and are involved in a variety of innate immune system pathways. Since the innate immune system detects microbial infections, any defect in this system could lead to immune functional impairment contributing to IBD.

Conclusion

The present study proposes a novel strategy for unraveling the complex genetic architecture of IBD by integrating WES data of familial cases, with computational analysis.

Potential Biomarkers for Parkinson Disease from Functional Enrichment and Bioinformatic Analysis of Global Gene Expression Patterns of Blood and Substantia Nigra Tissues

The Parkinson disease (PD) is the second most common neurodegenerative disorder affecting the central nervous system and motor functions. The biological complexity of PD is yet to reveal potential targets for intervention or to slow the disease severity. Therefore, this study aimed to compare the fidelity of blood to substantia nigra (SN) tissue gene expression from PD patients to provide a systematic approach to predict role of the key genes of PD pathobiology. Differentially expressed genes (DEGs) from multiple microarray data sets of PD blood and SN tissue from GEO database are identified. Using the theoretical network approach and variety of bioinformatic tools, we prioritized the key genes from DEGs. A total of 540 and 1024 DEGs were identified in blood and SN tissue samples, respectively. Functional pathways closely related to PD such as ERK1 and ERK2 cascades, mitogen-activated protein kinase (MAPK) signaling, Wnt, nuclear factor-κB (NF-κB), and PI3K-Akt signaling were observed by enrichment analysis. Expression patterns of 13 DEGs were similar in both blood and SN tissues. Comprehensive network topological analysis and gene regulatory networks identified additional 10 DEGs functionally connected with molecular mechanisms of PD through the mammalian target of rapamycin (mTOR), autophagy, and AMP-activated protein kinase (AMPK) signaling pathways. Potential drug molecules were identified by chemical-protein network and drug prediction analysis. These potential candidates can be further validated in vitro/in vivo to be used as biomarkers and/or novel drug targets for the PD pathology and/or to arrest or delay the neurodegeneration over the years, respectively.

Targeting potential receptor molecules in non-small cell lung cancer (NSCLC) using in silico approaches

Introduction: Non-Small Cell Lung Cancer is the most prevalent type of cancer in lung cancer. Chemotherapy, radiation therapy, and other conventional cancer treatments have a low success rate. Thus, creating new medications is essential to halt the spread of lung cancer. Methods: In this study bioactive nature of lochnericine against Non-Small Cell Lung Cancer (NSCLC) was analyzed using various computational approaches such as quantum chemical calculations, molecular docking, and molecular dynamic simulation. Furthermore, the MTT assay shows the anti-proliferation activity of lochnericine. Results and Discussion: Using Frontier Molecular Orbital (FMO), the calculated band gap energy value associated with bioactive compounds and the molecule's potential bioactivity is confirmed. The H38 hydrogen atom and O1 oxygen atom in the molecule are effectively electrophilic, and potential nucleophilic attack sites were confirmed through analysis of the Molecular electrostatic potential surface. Furthermore, the electrons within the molecule were delocalized, which confers bioactivity on the title molecule and was authorized through Mulliken atomic charge distribution analysis. A molecular docking study revealed that lochnericine inhibits non-small cell lung cancer-associated targeted protein. The lead molecule and targeted protein complex were stable during molecular dynamics simulation studies till the simulation period. Further, lochnericine demonstrated remarkable anti-proliferative and apoptotic features against A549 lung cancer cells. The current investigation powerfully suggests that lochnericine is a potential candidate for lung cancer.

Unveiling the Metal-Dependent Aggregation Properties of the C-terminal Region of Amyloidogenic Intrinsically Disordered Protein Isoforms DPF3b and DPF3a

Double-PHD fingers 3 (DPF3) is a BAF-associated human epigenetic regulator, which is increasingly recognised as a major contributor to various pathological contexts, such as cardiac defects, cancer, and neurodegenerative diseases. Recently, we unveiled that its two isoforms (DPF3b and DPF3a) are amyloidogenic intrinsically disordered proteins. DPF3 isoforms differ from their C-terminal region (C-TERb and C-TERa), containing zinc fingers and disordered domains. Herein, we investigated the disorder aggregation properties of C-TER isoforms. In agreement with the predictions, spectroscopy highlighted a lack of a highly ordered structure, especially for C-TERa. Over a few days, both C-TERs were shown to spontaneously assemble into similar antiparallel and parallel β-sheet-rich fibrils. Altered metal homeostasis being a neurodegeneration hallmark, we also assessed the influence of divalent metal cations, namely Cu²⁺, Mg²⁺, Ni²⁺, and Zn²⁺, on the C-TER aggregation pathway. Circular dichroism revealed that metal binding does not impair the formation of β-sheets, though metal-specific tertiary structure modifications were observed. Through intrinsic and extrinsic fluorescence, we found that metal cations differently affect C-TERb and C-TERa. Cu²⁺ and Ni²⁺ have a strong inhibitory effect on the aggregation of both isoforms, whereas Mg²⁺ impedes C-TERb fibrillation and, on the contrary, enhances that of C-TERa. Upon Zn²⁺ binding, C-TERb aggregation is also hindered, and the amyloid autofluorescence of C-TERa is remarkably red-shifted. Using electron microscopy, we confirmed that the metal-induced spectral changes are related to the morphological diversity of the aggregates. While metal-treated C-TERb formed breakable and fragmented filaments, C-TERa fibrils retained their flexibility and packing properties in the presence of Mg²⁺ and Zn²⁺ cations.