A Transcriptomic Analysis of Smoking-Induced Gene Expression Alterations in Coronary Artery Disease Patients

Smoking is a well established risk factor for coronary artery disease (CAD). Despite this, there have been no previous studies investigating the effects of smoking on blood gene expression in CAD patients. This single-centre cross-sectional study was designed with clearly defined inclusion criteria to address this gap. We conducted a high-throughput approach using next generation sequencing analysis with a single-end sequencing protocol and a read length of 75-cycles. Sixty-one patients with a median age of 67 years (range: 28-88 years) were recruited, and only 44 subjects were included for further analyses. Our investigation revealed 120 differentially expressed genes (DEGs) between smokers and nonsmokers, with a fold change (FC) of ≥1.5 and a p-value < 0.05. Among these DEGs, 15 were upregulated and 105 were downregulated. Notably, when applying a more stringent adjusted FC ≥ 2.0, 31 DEGs (5 upregulated, annotated to immune response pathways, and 26 downregulated, involving oxygen and haem binding or activity, with FDR ≤ 0.03) remained statistically significant at an alpha level of <0.05. Our results illuminate the molecular mechanisms underlying CAD, fortifying existing epidemiological evidence. Of particular interest is the unexplored overexpression of RCAN3, TRAV4, and JCHAIN genes, which may hold promising implications for the involvement of these genes in CAD among smokers.

IGJ suppresses breast cancer growth and metastasis by inhibiting EMT via the NF‑κB signaling pathway

Breast cancer metastasis is the primary cause of mortality of patients with breast cancer. The present study aimed to explore the role and underlying mechanisms of IGJ in the invasion and metastasis of breast cancer. The Cancer Genome Atlas database was utilized to analyze the differential gene expression profiles in patients with breast cancer with or without metastasis; the target gene, joining chain of multimeric IgA and IgM (JCHAIN, also known as IGJ, as referred to herein), with significant expression and with prognostic value was screened. The expression levels of IGJ in human breast cancer paired tissues and cell lines were detected using reverse transcription‑quantitative PCR and western blot analysis. IGJ differential expression was detected in paired human breast cancer tissues using immunohistochemistry. The role of IGJ in breast cancer was verified using CCK‑8, invasion and migration assays, and scratch tests in vivo and in vitro. Further exploration of the role and mechanism of IGJ in breast cancer was conducted through Gene Set Enrichment Analysis, Kyoto Encyclopedia of Genes and Genomes analysis, western blot analysis and immunofluorescence experiments. Through the analysis of gene expression profiles, it was found that IGJ was poorly expressed in patients with breast cancer with metastasis compared to patients with non‑metastatic breast cancer. The overexpression of IGJ was associated with an improved distant metastasis‑free survival and overall survival (OS). COX multivariate regression analysis demonstrated that IGJ was an independent prognostic factor for the OS and relapse‑free survival of patients with breast cancer. In comparison to healthy breast cancer adjacent tissues and cell lines, IGJ was poorly expressed in breast cancer tissues and cell lines (P<0.05). Further analyses indicated that the overexpression of IGJ suppressed the proliferation, invasion and metastasis of breast cancer cells in vivo and in vitro by inhibiting the occurrence of epithelial‑to‑mesenchymal transition (EMT) and suppressing the nuclear translocation of p65. Finally, rescue experiments indicated that IGJ restricted the proliferation and metastasis of breast cancer cells by regulating the NF‑κB signaling pathway. On the whole, the present study demonstrates that IGJ suppresses the invasion and metastasis of breast cancer by inhibiting both the occurrence of EMT and the NF‑κB signaling pathway. These findings may provide novel biomarkers and potential therapeutic targets for the treatment of metastatic breast cancer.

Discovery of drug targets and therapeutic agents based on drug repositioning to treat lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is the one of the most common subtypes in lung cancer. Although various targeted therapies have been used in the clinical practice, the 5-year overall survival rate of patients is still low. Thus, it is urgent to identify new therapeutic targets and develop new drugs for the treatment of the LUAD patients.

METHODS

Survival analysis was used to identify the prognostic genes. Gene co-expression network analysis was used to identify the hub genes driving the tumor development. A profile-based drug repositioning approach was used to repurpose the potentially useful drugs for targeting the hub genes. MTT and LDH assay were used to measure the cell viability and drug cytotoxicity, respectively. Western blot was used to detect the expression of the proteins.

FINDINGS

We identified 341 consistent prognostic genes from two independent LUAD cohorts, whose high expression was associated with poor survival outcomes of patients. Among them, eight genes were identified as hub genes due to their high centrality in the key functional modules in the gene-co-expression network analysis and these genes were associated with the various hallmarks of cancer (e.g., DNA replication and cell cycle). We performed drug repositioning analysis for three of the eight genes (CDCA8, MCM6, and TTK) based on our drug repositioning approach. Finally, we repurposed five drugs for inhibiting the protein expression level of each target gene and validated the drug efficacy by performing in vitro experiments.

INTERPRETATION

We found the consensus targetable genes for the treatment of LUAD patients with different races and geographic characteristics. We also proved the feasibility of our drug repositioning approach for the development of new drugs for disease treatment.

Comprehensive gene cluster analysis of head and neck squamous cell carcinoma TCGA RNA-seq data defines B cell immunity-related genes as a robust survival predictor

BACKGROUND

The authors aimed to define novel gene expression signatures that are associated with patients' survival with head and neck squamous cell carcinoma (HNSCC).

METHODS

TCGA RNA-seq data were used for gene expression clusters extraction from 499 tumor samples by the "EPIG" method. Tumor samples were then partitioned into lower and higher than median level groups for survival relevant analysis by Kaplan-Meier estimator.

RESULTS

We found that two gene clusters (_1, _2) are favorably, while two (_3, _4) are unfavorably, associated with patients' survival with HNSCC. Notably, most genes on the top lists of cluster_2 are associated with B cells. A gene expression signature with combined genes from cluster_2 and _4 was further determined to be associated with HNSCC survival rate.

CONCLUSION

Our work strongly supported a favorable role of B cells in patients' survival with HNSCC and identified a novel coexpressed gene signature as prognostic biomarker for patients' survival with HNSCC estimation.

Prediction of Response to Sorafenib in Hepatocellular Carcinoma: A Putative Marker Panel by Multiple Reaction Monitoring-Mass Spectrometry (MRM-MS)

Sorafenib is the only standard treatment for unresectable hepatocellular carcinoma (HCC), but it provides modest survival benefits over placebo, necessitating predictive biomarkers of the response to sorafenib. Serum samples were obtained from 115 consecutive patients with HCC before sorafenib treatment and analyzed by multiple reaction monitoring-mass spectrometry (MRM-MS) and ELISA to quantify candidate biomarkers. We verified a triple-marker panel to be predictive of the response to sorafenib by MRM-MS, comprising CD5 antigen-like (CD5L), immunoglobulin J (IGJ), and galectin-3-binding protein (LGALS3BP), in HCC patients. This panel was a significant predictor (AUROC > 0.950) of the response to sorafenib treatment, having the best cut-off value (0.4) by multivariate analysis. In the training set, patients who exceeded this cut-off value had significantly better overall survival (median, 21.4 months) than those with lower values (median, 8.6 months; p = 0.001). Further, a value that was lower than this cutoff was an independent predictor of poor overall survival [hazard ratio (HR), 2.728; 95% confidence interval (CI), 1.312-5.672; p = 0.007] and remained an independent predictive factor of rapid progression (HR, 2.631; 95% CI, 1.448-4.780; p = 0.002). When applied to the independent validation set, levels of the cut-off value for triple-marker panel maintained their prognostic value for poor clinical outcomes. On the contrast, the triple-marker panel was not a prognostic factor for patients who were treated with transarterial chemoembolization (TACE). The discriminatory signature of a triple-marker panel provides new insights into targeted proteomic biomarkers for individualized sorafenib therapy.

Hexameric immunoglobulin M in humans: desired or unwanted?

Immunoglobulin M (IgM) is the first antibody produced upon infection, and is often suggested as the first line of defense of human immune system. In addition to being present on the surface of naïve B cells as a monomeric molecule, IgM is always secreted as a polymer. The most abundant IgM polymer in humans is pentamer, composed of five monomeric units, joined together by so-called joining or J chain. On the other hand, it is well known that hexameric IgM can be also found in human sera. Its presence is often related to different dissorders (Waldenström's macroglobulinemia, cold agglutinin, and recurrent urinary bacterial infections), although it is believed that small amounts of hexamer are present in normal human sera as well. Unlike pentamer, IgM hexamer contains six monomeric blocks and completely lacks J chain. Although it has been decades since its discovery, the precise function of IgM hexamer is still unknown. Since it was documented that hexamer is very potent in activating complement, it is suggested that its production in humans must be under strict control, and that it is produced in special conditions, when strong activation of complement is absolutely needed. However, the question is whether hexameric IgM is really a secret weapon or just an undesirable molecule in humans. According to structural and known functional characteristics of both pentamers and hexamers of IgM, it can be concluded that hexamers are, in addition to being maybe too reactive to be around, probably not that efficient in protecting us from bacterial and viral infections.

[An immunological study of secreted human polymeric immunoglobulins' J-peptide tissue specificity]

Contents of J-peptide of secreted human polymeric immunoglobulins may vary considerably with different pathologies, reflecting the state of the adaptive immune system. In this work assessed the content of J-peptide in various tissues of healthy people to use as a baseline for studies related to the change in the content of J-peptide in pathologies.

Changes in composition of IgM polymers in patients suffering from recurrent urinary bacterial infections after bacterial immunization treatment

IgM is the first antibody produced during the immune response to infection or immunization, and it can be secreted as pentamer (containing a small polypeptide, termed as J chain) or hexamer (lacking J chain). In this paper we have analyzed structural characteristics (by electrophoresis and immunoblot) and anti-bacterial specificity (by enzyme-linked immunosorbent assay) of IgM antibodies purified from female patients suffering from recurrent bacterial infections of lower urinary tract and therapeutically immunized with the mixture of heat-inactivated uropathogenic bacteria. We report on changes in the composition of IgM polymers in tested patients. The immunization induced the raise of the levels of hexamers in patients that did not respond to immunization (non-responders), while the IgM polymers remained on the pentameric level in immunization dependent responders. We propose that the composition of IgM polymers could influence the immunization outcome and should be taken in count regarding the treatment of recurrent bacterial infections.