Identification of Gene Signature as Diagnostic and Prognostic Blood Biomarker for Early Hepatocellular Carcinoma Using Integrated Cross-Species Transcriptomic and Network Analyses

Long-Chain Acyl Coenzyme A Dehydrogenase, a Key Player in Metabolic Rewiring/Invasiveness in Experimental Tumors and Human Mesothelioma Cell Lines

Cross-species investigations of cancer invasiveness are a new approach that has already identified new biomarkers which are potentially useful for improving tumor diagnosis and prognosis in clinical medicine and veterinary science. In this study, we combined proteomic analysis of four experimental rat malignant mesothelioma (MM) tumors with analysis of ten patient-derived cell lines to identify common features associated with mitochondrial proteome rewiring. A comparison of significant abundance changes between invasive and non-invasive rat tumors gave a list of 433 proteins, including 26 proteins reported to be exclusively located in mitochondria. Next, we analyzed the differential expression of genes encoding the mitochondrial proteins of interest in five primary epithelioid and five primary sarcomatoid human MM cell lines; the most impressive increase was observed in the expression of the long-chain acyl coenzyme A dehydrogenase (ACADL). To evaluate the role of this enzyme in migration/invasiveness, two epithelioid and two sarcomatoid human MM cell lines derived from patients with the highest and lowest overall survival were studied. Interestingly, sarcomatoid vs. epithelioid cell lines were characterized by higher migration and fatty oxidation rates, in agreement with ACADL findings. These results suggest that evaluating mitochondrial proteins in MM specimens might identify tumors with higher invasiveness.

Transcriptomic data analysis coupled with copy number aberrations reveals a blood-based 17-gene signature for diagnosis and prognosis of patients with colorectal cancer

Background: Colorectal cancer (CRC) is the third most common cancer and third leading cause of cancer-associated deaths worldwide. Diagnosing CRC patients reliably at an early and curable stage is of utmost importance to reduce the risk of mortality. Methods: We identified global differentially expressed genes with copy number alterations in patients with CRC. We then identified genes that are also expressed in blood, which resulted in a blood-based gene signature. We validated the gene signature's diagnostic and prognostic potential using independent datasets of gene expression profiling from over 800 CRC patients with detailed clinical data. Functional enrichment, gene interaction networks and pathway analyses were also performed. Results: The analysis revealed a 17-gene signature that is expressed in blood and demonstrated that it has diagnostic potential. The 17-gene SVM classifier displayed 99 percent accuracy in predicting the patients with CRC. Moreover, we developed a prognostic model and defined a risk-score using 17-gene and validated that high risk score is strongly associated with poor disease outcome. The 17-gene signature predicted disease outcome independent of other clinical factors in the multivariate analysis (HR = 2.7, 95% CI = 1.3-5.3, p = 0.005). In addition, our gene network and pathway analyses revealed alterations in oxidative stress, STAT3, ERK/MAPK, interleukin and cytokine signaling pathways as well as potentially important hub genes, including BCL2, MS4A1, SLC7A11, AURKA, IL6R, TP53, NUPR1, DICER1, DUSP5, SMAD3, and CCND1. Conclusion: Our results revealed alterations in various genes and cancer-related pathways that may be essential for CRC transformation. Moreover, our study highlights diagnostic and prognostic value of our gene signature as well as its potential use as a blood biomarker as a non-invasive diagnostic method. Integrated analysis transcriptomic data coupled with copy number aberrations may provide a reliable method to identify key biological programs associated with CRC and lead to improved diagnosis and therapeutic options.

Global Transcriptional Profiling of Granulosa Cells from Polycystic Ovary Syndrome Patients: Comparative Analyses of Patients with or without History of Ovarian Hyperstimulation Syndrome Reveals Distinct Biomarkers and Pathways

Ovarian hyperstimulation syndrome (OHSS) is often a complication of polycystic ovarian syndrome (PCOS), the most frequent disorder of the endocrine system, which affects women in their reproductive years. The etiology of OHSS is multifactorial, though the factors involved are not apparent. In an attempt to unveil the molecular basis of OHSS, we conducted transcriptome analysis of total RNA extracted from granulosa cells from PCOS patients with a history of OHSS (n = 6) and compared them to those with no history of OHSS (n = 18). We identified 59 significantly dysregulated genes (48 down-regulated, 11 up-regulated) in the PCOS with OHSS group compared to the PCOS without OHSS group (p-value < 0.01, fold change >1.5). Functional, pathway and network analyses revealed genes involved in cellular development, inflammatory and immune response, cellular growth and proliferation (including DCN, VIM, LIFR, GRN, IL33, INSR, KLF2, FOXO1, VEGF, RDX, PLCL1, PAPPA, and ZFP36), and significant alterations in the PPAR, IL6, IL10, JAK/STAT and NF-κB signaling pathways. Array findings were validated using quantitative RT-PCR. To the best of our knowledge, this is the largest cohort of Saudi PCOS cases (with or without OHSS) to date that was analyzed using a transcriptomic approach. Our data demonstrate alterations in various gene networks and pathways that may be involved in the pathophysiology of OHSS. Further studies are warranted to confirm the findings.

H2AFX might be a prognostic biomarker for hepatocellular carcinoma

BACKGROUND

H2AFX can play a central role in DNA repair, replication, transcription regulation, and chromosomal stability. However, there is little research to explore the expression of H2AFX in cancers. Moreover, the correlation between the expression of H2AFX and tumor immunity, which affects the prognosis of hepatocellular carcinoma (HCC), is not clear. This article aimed to observe the correlation between H2AFX and tumor tissue infiltration biomarkers in HCC and its prognostic potential in HCC.

METHOD

Oncomine and TIMER database were used to assess the expression level of H2AFX mRNA, and GEPIA and Kaplan-Meier databases were used to evaluate its prognostic potential. The TIMER database analyzed the relationship between h2afx expression level and tumor immune cell infiltration markers in liver cancer tissues.

RESULTS

The results showed that H2AFX was overexpressed in tumor tissues than normal tissues in HCC via analysis, and its expression level was correlated with the survival rate of HCC. Moreover, the expression level of H2AFX was related to various immune biomarkers. These results show that overexpression of H2AFX would reflect the poor prognosis of HCC, and these would also reflect that the gene H2AFX can affect the infiltration of HCC immune cells and then play a role in regulating tumor immunity.

CONCLUSION

Our study showed that the gene H2AFX might be a potential poor prognostic biomarker in HCC and might be involved in the infiltration of HCC immune cells.

Integrated Analysis of Transcriptomic and Genomic Data Reveals Blood Biomarkers With Diagnostic and Prognostic Potential in Non-small Cell Lung Cancer

Background: Lung cancer is the second most common cancer and the main leading cause of cancer-associated death worldwide. Non-small cell lung cancer (NSCLC) accounts for about 85% of lung cancer diagnoses and more than 50% of all lung cancer cases are diagnosed at an advanced stage; hence have poor prognosis. Therefore, it is important to diagnose NSCLC patients reliably and as early as possible in order to reduce the risk of mortality.

Methods: We identified blood-based gene markers for early NSCLC by performing a multi-omics approach utilizing integrated analysis of global gene expression and copy number alterations of NSCLC patients using array-based techniques. We also validated the diagnostic and the prognostic potential of the gene signature using independent datasets with detailed clinical information.

Results: We identified 12 genes that are significantly expressed in NSCLC patients’ blood, at the earliest stages of the disease, and associated with a poor disease outcome. We then validated 12-gene signature’s diagnostic and prognostic value using independent datasets of gene expression profiling of over 1000 NSCLC patients. Indeed, 12-gene signature predicted disease outcome independently of other clinical factors in multivariate regression analysis (HR = 2.64, 95% CI = 1.72–4.07; p = 1.3 × 10−8). Significantly altered functions, pathways, and gene networks revealed alterations in several key genes and cancer-related pathways that may have importance for NSCLC transformation, including FAM83A, ZNF696, UBE2C, RECK, TIMM50, GEMIN7, and XPO5.

Conclusion: Our findings suggest that integrated genomic and network analyses may provide a reliable approach to identify genes that are associated with NSCLC, and lead to improved diagnosis detecting the disease in early stages in patients’ blood instead of using invasive techniques and also have prognostic potential for discriminating high-risk patients from the low-risk ones.

Identifying Potential New Gene Expression-Based Biomarkers in the Peripheral Blood Mononuclear Cells of Hepatitis B-Related Hepatocellular Carcinoma

OBJECTIVE

The analysis of the gene expression of peripheral blood mononuclear cells (PBMCs) is important to clarify the pathogenesis of hepatocellular carcinoma (HCC) and the detection of suitable biomarkers. The purpose of this investigation was to use RNA-sequencing to screen the appropriate differentially expressed genes (DEGs) in the PBMCs for the HCC.

METHODS

The comprehensive transcriptome of extracted RNA of PBMC (n = 20) from patients with chronic hepatitis B (CHB), liver cirrhosis, and early stage of HCC (5 samples per group) was carried out using RNA-sequencing. All raw RNA-sequencing data analyses were performed using conventional RNA-sequencing analysis tools. Next, gene ontology (GO) analyses were carried out to elucidate the biological processes of DEGs. Finally, relative transcript abundance of selected DEGs was verified using qRT-PCR on additional validation groups.

RESULTS

Specifically, 13, 1262, and 1450 DEGs were identified for CHB, liver cirrhosis, and HCC, when compared with the healthy controls. GO enrichment analysis indicated that HCC is closely related to the immune response. Seven DEGs (TYMP, TYROBP, CD14, TGFBI, LILRA2, GNLY, and GZMB) were common to HCC, cirrhosis, and CHB when compared to healthy controls. The data revealed that the expressions of these 7 DEGs were consistent with those from the RNA-sequencing results. Also, the expressions of 7 representative genes that had higher sensitivity were obtained by receiver operating characteristic analysis, which indicated their important diagnostic accuracy for HBV-HCC.

CONCLUSION

This study provides us with new horizons into the biological process and potential prospective clinical diagnosis and prognosis of HCC in the near future.