Identification of key genes and pathways associated with classical Hodgkin lymphoma by bioinformatics analysis

Insights into the Gene Expression Profile of Classical Hodgkin Lymphoma: A Study towards Discovery of Novel Therapeutic Targets

Classical Hodgkin lymphoma (cHL) is a common B-cell cancer and a significant health concern, especially in Western and Asian countries. Despite the effectiveness of chemotherapy, many relapse cases are being reported, highlighting the need for improved treatments. This study aimed to address this issue by discovering biomarkers through the analysis of gene expression data specific to cHL. Additionally, potential anticancer inhibitors were explored to target the discovered biomarkers. This study proceeded by retrieving microarray gene expression data from cHL patients, which was then analyzed to identify significant differentially expressed genes (DEGs). Functional and network annotation of the upregulated genes revealed the active involvement of matrix metallopeptidase 12 (MMP12) and C-C motif metallopeptidase ligand 22 (CCL22) genes in the progression of cHL. Additionally, the mentioned genes were found to be actively involved in cancer-related pathways, i.e., oxidative phosphorylation, complement pathway, myc_targets_v1 pathway, TNFA signaling via NFKB, etc., and showed strong associations with other genes known to promote cancer progression. MMP12, topping the list with a logFC value of +6.6378, was selected for inhibition using docking and simulation strategies. The known anticancer compounds were docked into the active site of the MMP12 molecular structure, revealing significant binding scores of -7.7 kcal/mol and -7.6 kcal/mol for BDC_24037121 and BDC_27854277, respectively. Simulation studies of the docked complexes further supported the effective binding of the ligands, yielding MMGBSA and MMPBSA scores of -78.08 kcal/mol and -82.05 kcal/mol for MMP12-BDC_24037121 and -48.79 kcal/mol and -49.67 kcal/mol for MMP12-BDC_27854277, respectively. Our findings highlight the active role of MMP12 in the progression of cHL, with known compounds effectively inhibiting its function and potentially halting the advancement of cHL. Further exploration of downregulated genes is warranted, as associated genes may play a role in cHL. Additionally, CCL22 should be considered for further investigation due to its significant role in the progression of cHL.

Predicting the molecular mechanism-driven progression of breast cancer through comprehensive network pharmacology and molecular docking approach

Identification of key regulators is a critical step toward discovering biomarker that participate in BC. A gene expression dataset of breast cancer patients was used to construct a network identifying key regulators in breast cancer. Overexpressed genes were identified with BioXpress, and then curated genes were used to construct the BC interactome network. As a result of selecting the genes with the highest degree from the BC network and tracing them, three of them were identified as novel key regulators, since they were involved at all network levels, thus serving as the backbone. There is some evidence in the literature that these genes are associated with BC. In order to treat BC, drugs that can simultaneously interact with multiple targets are promising. When compared with single-target drugs, multi-target drugs have higher efficacy, improved safety profile, and are easier to administer. The haplotype and LD studies of the FN1 gene revealed that the identified variations rs6707530 and rs1250248 may both cause TB, and endometriosis respectively. Interethnic differences in SNP and haplotype frequencies might explain the unpredictability in association studies and may contribute to predicting the pharmacokinetics and pharmacodynamics of drugs using FN1.

Genomic crossroads between non-Hodgkin's lymphoma and common variable immunodeficiency

Common variable immunodeficiency (CVID) represents the largest group of primary immunodeficiencies that may manifest with infections, inflammation, autoimmunity, and cancer, mainly B-cell non-Hodgkin's lymphoma (NHL). Indeed, NHL may result from chronic or recurrent infections and has, therefore, been recognized as a clinical phenotype of CVID, although rare. The more one delves into the mechanisms involved in CVID and cancer, the stronger the idea that both pathologies can be a reflection of the same primer events observed from different angles. The potential effects of germline variants on specific somatic modifications in malignancies suggest that it might be possible to anticipate critical events during tumor development. In the same way, a somatic alteration in NHL could be conditioning a similar response at the transcriptional level in the shared signaling pathways with genetic germline alterations in CVID. We aimed to explore the genomic substrate shared between these entities to better characterize the CVID phenotype immunodeficiency in NHL. By means of an in-silico approach, we interrogated the large, publicly available datasets contained in cBioPortal for the presence of genes associated with genetic pathogenic variants in a panel of 50 genes recurrently altered in CVID and previously described as causative or disease-modifying. We found that 323 (25%) of the 1,309 NHL samples available for analysis harbored variants of the CVID spectrum, with the most recurrent alteration presented in NHL occurring in PIK3CD (6%) and STAT3 (4%). Pathway analysis of common gene alterations showed enrichment in inflammatory, immune surveillance, and defective DNA repair mechanisms similar to those affected in CVID, with PIK3R1 appearing as a central node in the protein interaction network. The co-occurrence of gene alterations was a frequent phenomenon. This study represents an attempt to identify common genomic grounds between CVID and NHL. Further prospective studies are required to better know the role of genetic variants associated with CVID and their reflection on the somatic pathogenic variants responsible for cancer, as well as to characterize the CVID-like phenotype in NHL, with the potential to influence early CVID detection and therapeutic management.

Statistics and network-based approaches to identify molecular mechanisms that drive the progression of breast cancer

Breast cancer (BC) is one of the most malignant tumors and the leading cause of cancer-related death in women worldwide. So, an in-depth investigation on the molecular mechanisms of BC progression is required for diagnosis, prognosis and therapies. In this study, we identified 127 common differentially expressed genes (cDEGs) between BC and control samples by analyzing five gene expression profiles with NCBI accession numbers GSE139038, GSE62931, GSE45827, GSE42568 and GSE54002, based-on two statistical methods LIMMA and SAM. Then we constructed protein-protein interaction (PPI) network of cDEGs through the STRING database and selected top-ranked 7 cDEGs (BUB1, ASPM, TTK, CCNA2, CENPF, RFC4, and CCNB1) as a set of key genes (KGs) by cytoHubba plugin in Cytoscape. Several BC-causing crucial biological processes, molecular functions, cellular components, and pathways were significantly enriched by the estimated cDEGs including at-least one KGs. The multivariate survival analysis showed that the proposed KGs have a strong prognosis power of BC. Moreover, we detected some transcriptional and post-transcriptional regulators of KGs by their regulatory network analysis. Finally, we suggested KGs-guided three repurposable candidate-drugs (Trametinib, selumetinib, and RDEA119) for BC treatment by using the GSCALite online web tool and validated them through molecular docking analysis, and found their strong binding affinities. Therefore, the findings of this study might be useful resources for BC diagnosis, prognosis and therapies.

Silencing BLNK protects against interleukin-1β-induced chondrocyte injury through the NF-κB signaling pathway

BACKGROUND

Osteoarthritis (OA) is the most common joint disease in the elderly and is characterized by the progressive degeneration of articular cartilage. It is necessary to study the molecular pathology of OA. This study aimed to explore the role and mechanism of BLNK in regulating interleukin-1β (IL-1β)-induced chondrocyte injury and OA progression.

METHODS

GSE1919 (5 normal samples and 5 OA samples) was downloaded from the Gene Expression Omnibus (GEO) database. The limma package in R software was used to identify differentially expressed genes (DEGs) between control and OA-affected cartilage. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses of the differentially expressed genes were also performed. Apoptosis was assessed by flow cytometry. An OA rat model was established, and the relative expression of BLNK was assessed by real time quantitative PCR (qRT-PCR) and immunohistochemical staining. The expression of collagen II, MMP9, p65 and p-p65 was measured by Western blot analysis. Moreover, inflammatory factors (TNF-α and IL-18) were assessed by ELISA. The NF-κB inhibitor JSH-23 was used to assess the impact of BLNK on the NF-κB signaling pathway.

RESULTS

In total, 1318 DEGs were identified between normal and OA-affected cartilage according to the criteria (P-value <0.05 and |logFC > 1|). These DEGs were mainly enriched in the NF-κB pathway. BLNK was highly expressed in OA cartilage tissue and injured chondrocytes. Silencing BLNK significantly downregulated the IL-1β-induced apoptosis of chondrocytes. Silencing BLNK partially increased collagen II expression and downregulated MMP13 expression. Moreover, silencing BLNK partially decreased TNF-α and IL-18 expression. BLNK silencing inhibited the activation of NF-κB in OA. Silencing BLNK delayed OA progression through the NF-κB signaling pathway.

CONCLUSION

Silencing BLNK delayed OA progression and IL-1β-induced chondrocyte injury by regulating the NF-κB pathway.

The role of PLCγ2 in immunological disorders, cancer, and neurodegeneration

Phosphatidylinositol-specific phospholipase Cγ2 (PLCγ2) is a critical signaling molecule activated downstream from a variety of cell surface receptors that contain an intracellular immunoreceptor tyrosine-based activation motif. These receptors recruit kinases such as Syk, BTK, and BLNK to phosphorylate and activate PLCγ2, which then generates 1D-myo-inositol 1,4,5-trisphosphate and diacylglycerol. These well-known second messengers are required for diverse membrane functionality including cellular proliferation, endocytosis, and calcium flux. As a result, PLCγ2 dysfunction is associated with a variety of diseases including cancer, neurodegeneration, and immune disorders. The diverse pathologies associated with PLCγ2 are exemplified by distinct genetic variants. Inherited mutations at this locus cause PLCγ2-associated antibody deficiency and immune dysregulation, in some cases with autoinflammation. Acquired mutations at this locus, which often arise as a result of BTK inhibition to treat chronic lymphocytic leukemia, result in constitutive downstream signaling and lymphocyte proliferation. Finally, a third group of PLCγ2 variants actually has a protective effect in a variety of neurodegenerative disorders, presumably by increased uptake and degradation of deleterious neurological aggregates. Therefore, manipulating PLCγ2 activity either up or down could have therapeutic benefit; however, we require a better understanding of the signaling pathways propagated by these variants before such clinical utility can be realized. Here, we review the signaling roles of PLCγ2 in hematopoietic cells to help understand the effect of mutations driving immune disorders and cancer and extrapolate from this to roles which may relate to protection against neurodegeneration.

[Structure and function of B-cell linker and its role in the development of B cell-related diseases]

B cell linker (BLNK) is a key linker protein of B cell receptor (BCR) signaling pathway. BLNK participates in the regulation of PLC-γactivity and the activation of Ras pathway through its typical structure and interaction network with other proteins, and is thus widely involved in the regulation of B cell proliferation, differentiation, apoptosis and signal transduction. Furthermore, it is closely related to anaphylactic diseases, multiple sclerosis, chromosomal aneuploidy, aneuglobulinemia, B lymphocytic leukemia and lymphoma. Herein we review the structure and biological function of BLNK and its role in B cell-related diseases. BLNK can cooperate with a series of effective proteins to activate BCR signaling pathway, thereby regulating the development, maturation and function of B cells. The functional mutation of BLNK can destroy the homeostasis of B cells and affect the development and maturation of B cells, which leads to the occurrence of B cell related diseases. A comprehensive understanding of the biological functions of BLNK not only provides insights into the pathogenesis of B cell-related diseases, but also inspires new ideas and helps to find breakthroughs for the treatment of these diseases with BLNK as the therapeutic target.

Identification of pathway-based recurrence-associated signatures in optimally debulked patients with serous ovarian cancer

Serous ovarian cancer (SOC) is the most common form of the histological subtype of epithelial ovarian cancer, with the worst clinical outcome. Despite improvements in surgery and chemotherapy, most patients with SOC experience recurrence within 12-18 months of first-line treatment. Current studies are unable to robustly predict the recurrence of SOC, and more accurate predictive models are urgently required. We have, therefore, developed a novel pathway-structured model to predict the recurrence of SOC. We trained the model on a set of 333 patients and validated it in 3 diversified validation datasets of 403 patients. Genes significantly associated with recurrence within each pathway were identified using a Cox proportional hazards model based on LASSO estimation in the training dataset. Next, a pathway-structured scoring matrix was obtained after computation of the prognostic score for each pathway by fitting to the Cox proportional hazards model. With the pathway-structure scoring matrix as an input, the pathway-based recurrent signatures were identified using the Cox proportional hazards model based on LASSO estimation and the significant pathway-based signatures were externally validated in 3 independent datasets. Meanwhile, our pathway-structured model was compared with a commonly used gene-based model. Our results revealed that our 12 pathway-based signatures successfully predicted the recurrence of SOC with high accuracy in the training dataset and in the 3 validation datasets. Moreover, our pathway-structured model was superior to the gene-based model in 4 datasets. The pathways selected in our study will provide new insights into the pathogenesis and clinical treatments of SOC.