Identification of hub genes in peripheral blood mononuclear cells for the diagnosis of hepatocellular carcinoma using a weighted gene co-expression network analysis

Predictive three-biomarker panel in peripheral blood mononuclear cells for detecting hepatocellular carcinoma

Hepatocellular carcinoma (HCC) ranks among the most prevalent cancers and accounts for a significant proportion of cancer-associated deaths worldwide. This disease, marked by multifaceted etiology, often poses diagnostic challenges. Finding a reliable and non-invasive diagnostic method seems to be necessary. In this study, we analyzed the gene expression profiles of 20 HCC patients, 12 individuals with chronic hepatitis, and 15 healthy controls. Enrichment analysis revealed that platelet aggregation, secretory granule lumen, and G-protein-coupled purinergic nucleotide receptor activity were common biological processes, cellular components, and molecular function in HCC and chronic hepatitis B (CHB) compared to healthy controls, respectively. Furthermore, pathway analysis demonstrated that "estrogen response" was involved in the pathogenesis of HCC and CHB conditions, while, "apoptosis" and "coagulation" pathways were specific for HCC. Employing computational feature selection and logistic regression classification, we identified candidate genes pivotal for diagnostic panel development and evaluated the performance of these panels. Subsequent machine learning evaluations assessed these panels' performance in an independent cohort. Remarkably, a 3-marker panel, comprising RANSE2, TNF-α, and MAP3K7, demonstrated the best performance in qRT-PCR-validated experimental data, achieving 98.4% accuracy and an area under the curve of 1. Our findings highlight this panel's promising potential as a non-invasive approach not only for detecting HCC but also for distinguishing HCC from CHB patients.

Imaging and AI based chromatin biomarkers for diagnosis and therapy evaluation from liquid biopsies

Multiple genomic and proteomic studies have suggested that peripheral blood mononuclear cells (PBMCs) respond to tumor secretomes and thus could provide possible avenues for tumor prognosis and treatment evaluation. We hypothesized that the chromatin organization of PBMCs obtained from liquid biopsies, which integrates secretome signals with gene expression programs, provides efficient biomarkers to characterize tumor signals and the efficacy of proton therapy in tumor patients. Here, we show that chromatin imaging of PBMCs combined with machine learning methods provides such robust and predictive chromatin biomarkers. We show that such chromatin biomarkers enable the classification of 10 healthy and 10 pan-tumor patients. Furthermore, we extended our pipeline to assess the tumor types and states of 30 tumor patients undergoing (proton) radiation therapy. We show that our pipeline can thereby accurately distinguish between three tumor groups with up to 89% accuracy and enables the monitoring of the treatment effects. Collectively, we show the potential of chromatin biomarkers for cancer diagnostics and therapy evaluation.

SPARC: a potential target for functional nanomaterials and drugs

Secreted protein acidic and rich in cysteine (SPARC), also termed osteonectin or BM-40, is a matricellular protein which regulates cell adhesion, extracellular matrix production, growth factor activity, and cell cycle. Although SPARC does not perform a structural function, it, however, modulates interactions between cells and the surrounding extracellular matrix due to its anti-proliferative and anti-adhesion properties. The overexpression of SPARC at sites, including injury, regeneration, obesity, cancer, and inflammation, reveals its application as a prospective target and therapeutic indicator in the treatment and assessment of disease. This article comprehensively summarizes the mechanism of SPARC overexpression in inflammation and tumors as well as the latest research progress of functional nanomaterials in the therapy of rheumatoid arthritis and tumors by manipulating SPARC as a new target. This article provides ideas for using functional nanomaterials to treat inflammatory diseases through the SPARC target. The purpose of this article is to provide a reference for ongoing disease research based on SPARC-targeted therapy.

Upregulation of TMEM40 is associated with the malignant behavior and promotes tumor progression in cervical cancer

OBJECTIVE

Recent studies indicated that transmembrane protein 40 (TMEM40) is associated with several types of cancers but is not clear in cervical cancer (CC). The study aimed to examine the role of TMEM40 in CC and related mechanisms.

METHODS

The expression of TMEM40 in CC tissues and cell lines was studied with western blot and real-time quantitative RT-PCR. The effect of TMEM40 on proliferation was evaluated by CCK-8, EdU and colony formation assay. The migration, invasion, cell cycle and apoptosis of CC cells were studied with wound healing, transwell assays and flow cytometry. Tumor growth was evaluated in vivo using a xenogenous subcutaneously implant model.

RESULTS

The results revealed that the TMEM40 elevation in CC tissues and cell lines was closely correlated with tumor size and lymph node metastasis in clinical patients. Upregulation of TMEM40 with OE-TMEM40 vector promoted the invasion, migration and proliferation, inhibited the apoptosis and led to distinct S cell cycle arrest in CC cell lines. Silencing TMEM40 with shRNA inhibited the invasion, migration and proliferation, promoted apoptosis and led to a G0/G1 cell cycle arrest in CC cell lines. Silence of TMEM40 downregulated the expression of c-MYC, Cyclin D1, matrix metalloproteinase-1 (MMP-1) and matrix metalloproteinase-9 (MMP-9), but in contrast, activated p53 and several apoptosis related proteins such as p53, Caspase-3, Caspase-9 and PARP1. In addition, TMEM40 silencing dramatically decreased tumor growth in mice models.

CONCLUSION

The present study demonstrates that TMEM40 upregulation can be a potential prognostic biomarker and contribute to CC development.

Exploring the immunological role and prognostic potential of PPM1M in pan-cancer

BACKGROUND

PPM1M is a member of the metal-dependent protein phosphatase family, and its role in the immunization process has not been studied in depth. In this study, we investigated the role of PPM1M in pan-cancer.

METHODS

Samples of cancer and normal tissues were obtained from the cancer genome atlas and genotype-tissue expression. Kaplan-Meier survival curves and Cox regression were used to analyze the effect of PPM1M on prognosis. Functional and pathway enrichment analyses were performed using the R package "clusterProfiler" to explore the role of PPM1M. The Sanger Box database was used to analyze the relationship between PPM1M and tumor immune checkpoint, tumor mutational burden, and microsatellite instability. The Tumor Immune Estimation Resource 2 database and CIBERSORT method were used to analyze the relationship between PPM1M and tumor-infiltrating immune cells. Finally, the cBioPortal database was used to analyze the genomic variation in PPM1M.

RESULTS

Among the variety of tumors, the expression of PPM1M was higher in normal tissues than in cancerous tissues. The expression of PPM1M is closely associated with patient prognosis, tumor immune checkpoint, tumor mutational burden, and microsatellite instability. PPM1M is closely associated with the infiltration of immune cells into the tumor microenvironment. In addition, PPM1M is involved in the regulation of several immune-related pathways.

CONCLUSION

In pan-cancer, PPM1M affects patient prognosis and may be a potential immunological biomarker. Furthermore, PPM1M may be a potential therapeutic target in tumor immunology.

Identification of pyroptosis‑related genes in neuropathic pain based on bioinformatics analysis

Pyroptosis is defined as inflammation-induced programmed cell death. However, gene expression levels related to pyroptosis and their role in neuropathic pain (NP) remain unclear. The present study aimed to develop and validate an NP-predictive signature based on the genes associated with pyroptosis. Gene expression level profiles were downloaded from the Gene Expression Omnibus database. Weighted gene co-expression network analysis was used to identify the pyroptotic genes most highly associated with NP. NP-related pyroptosis gene signature was constructed using multivariate logistic regression. A rat model of neuropathic pain was established through chronic constriction injury to analyse the inflammatory infiltration and myelin damage around the sciatic nerve, and examine the expression levels of macrophage markers S100 calcium-binding protein β (S100β) and ionized calcium-binding adapter molecule 1 (Iba-1). Finally, flow cytometry analysis was used to examine the lipopolysaccharide (LPS)-induced cell death ratio of RSC96 cells (Schwann cells), while the expression levels of LPS-induced pyroptosis-related genes in RSC96 cells were measured via reverse transcription-quantitative PCR. The results demonstrated that pyroptosis-related genes (gasdermin D, NLR family pyrin domain containing 3, neuronal apoptosis inhibitory protein and NLR family CARD domain containing 4) were identified to increase the risk of NP. NP-related pyroptosis signatures were constructed based on these four genes. Moreover, the high-risk group had a higher level of macrophage infiltration compared with the low-risk group, as determined by the CIBERSORT algorithm. H&E staining results showed that the myelin structure of the sciatic nerve tissue of chronic constriction injury (CCI) rats was destroyed and inflammatory cells infiltrated around neurons. The results of immunohistochemistry showed that compared with in the sham group, the expression levels of Iba-1 and sS100β in the sciatic nerve of the CCI group were increased. Furthermore, the expression levels of cell death and pyroptosis-related genes in Schwann cells induced by LPS were increased compared with in the control group. In conclusion, an NP-related pyroptosis gene signature was constructed based on four pyroptosis-related genes and it was found that the expression of pyroptosis-related genes was upregulated in the early steps of the neuroinflammatory process in RSC96 cells.

C8B in Complement and Coagulation Cascades Signaling Pathway is a predictor for Survival in HBV-Related Hepatocellular Carcinoma Patients

OBJECTIVE

The role of the complement and coagulation cascades signaling pathway in the pathogenesis of cancers remains uncertain. This study aimed to investigate the associations between enriched differentially expressed genes (DEGs) in this pathway and hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients.

MATERIALS AND METHODS

Clinical and gene expression data of the Gene Expression Omnibus (GEO) series profile GSE14520 were downloaded. The "Limma" package was used to screen the DEGs and the "clusterProfiler" package was used to identify the complement and coagulation cascades pathway and enriched significant genes. Cox regression analysis, the Kaplan-Meier method, and the nomogram model were used to address the correlations between significantly enriched DEGs in the complement and coagulation cascades pathway and HCC survival.

RESULTS

A total of 220 HBV-related HCC patients were enrolled in this study. The complement and coagulation cascades pathway was significantly enriched by 37 DEGs (p-value < 0.05 and adjusted p-value < 0.05). Complement 8 beta chain (C8B) expression levels had protective effects on overall survival (OS) and recurrence-free survival (RFS) in HBV-related HCC patients. High levels of C8B contributed to favorable OS and RFS in this population (both p < 0.01), even after adjustment of clinicopathological characteristics including tumor node metastasis (TNM) staging, Barcelona Clinic liver cancer (BCLC) staging, gender, and fibrinogen beta chain (FGB) expression (all p < 0.05).

CONCLUSION

C8B in the complement and coagulation cascades signaling pathway serves as a predictive candidate for survival in HBV-related HCC patients.