RAC1 as a potential pan-cancer diagnostic, prognostic, and immunological biomarker

Background

Ras-related C3 botulinum toxin substrate 1 (RAC1) is an important member of the Rho GTPase family involved in tumorigenesis. However, its role and potential clinical utility across cancer entities in solid tumors is unknown.

Methods

We analyzed data from various databases, including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project, cBioPortal, Tumor Immune Estimation Resource 2 (TIMER2), and published articles. A prognostic nomogram for liver hepatocellular carcinoma (LIHC) patients was developed based on RAC1-guanosine triphosphate (GTP) gene expression levels, which were validated using immunohistochemistry (IHC).

Results

In this study, RAC1 was highly expressed in most cancers and correlated with prognosis and pathological stages. Furthermore, significant associations were observed between RAC1 and DNA methylation, immune cell infiltration, immune-related genes, tumor mutational burden, and microsatellite instability in most tumors. As a use case, we employed gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) to analyze the biologic importance of RAC1 expression and established a prognostic nomogram based on tumor stage and RAC1 expression, which can better predict the overall survival rate of patients with LIHC better than tumor stage alone. The gene expression results were validated with IHC, which confirmed a higher expression of the RAC1-GTP protein in LIHC compared to paracancerous tissues.

Conclusions

This extensive solid tumor analysis provides sound evidence that RAC1 can serve as both as an immunotherapy target and as a diagnostic and prognostic biomarker.

Effect of urokinase-type plasminogen activator combined with clinical stage and Barcelona Clinic Liver Cancer stage on the prognosis of patients with hepatocellular carcinoma

Background

The aim of this investigation is to evaluate the association and potential mechanism between plasminogen activator urokinase (PLAU) and the prognosis of patients with liver hepatocellular carcinoma (LIHC).

Methods

We verified PLAU expression and its correlation with LIHC patients' prognosis in The Cancer Genome Atlas (TCGA) database. The interaction network for protein-gene was established in the GeneMania database and the STRING database, and the association between PLAU and immune cells was assessed in Tumor Immune Estimation Resource (TIMER) and TCGA databases. The potential physiological mechanism was elucidated by the Gene Set Enrichment Analysis (GSEA) enrichment assessment. Finally, the individual clinical data of 100 LIHC patients were retrospectively evaluated to further analyze the clinical value of PLAU.

Results

The PLAU expression in LIHC tissues was greater than in paracancerous tissues, and LIHC patients with low PLAU expression had better disease-specific survival (DSS), overall survival (OS), and progression free interval (PFI) than those with high PLAU expression. In the TIMER database, the PLAU expression was positively associated with six kinds of infiltrating immune cells: CD4⁺ T, neutrophils, CD8⁺ T, macrophages, B, and dendritic cells, while GSEA enrichment analysis indicated PLAU may impact the biological activities of LIHC by taking part in MAPK and JAK_STAT signaling pathways, angiogenesis, and P53. There were statistically significant differences in T-stage and Edmondson grading between the two groups of patients with high and low expression of PLAU (P<0.05). The tumor progression rates were 88% (44/50) and 92% (46/50) respectively in the low and high PLAU groups, with early recurrence rates of 60% (30/50) and 72% (36/50), and median PFS of 29.5 and 23 months, respectively. The COX regression analysis showed PLAU expression and CS and Barcelona Clinic Liver Cancer (BCLC) stages were independent prognostic factors affecting tumor progression in LIHC patients.

Conclusions

The decreased expression of PLAU can prolong the DSS, OS, and PFI in LIHC patients, and can be utilized as a novel predictive index. PLAU combined with CS staging and BCLC staging has good clinical value in the early screening and prognosis of LIHC. These results reveal an efficient approach for developing anticancer strategies against LIHC.

A novel prognostic biomarker: GINS3 is correlated with methylation and immune escape in liver hepatocellular carcinoma

Background

Liver cancer remains one of the tricky malignancies nowadays. GINS complex subunit 3 (GINS3), part of the GINS tetrameric complex, is significantly upregulated in many cancers, including liver hepatocellular carcinoma (LIHC). With the development of liver cancer treatment, immune and molecular targeted therapy gradually becomes a promising treatment. However, the key target for liver cancer is still indistinct. Herein, the underneath mechanism of GINS3 was investigated to verify its role as a biomarker in LIHC.

Methods

Genomic expression, genetic alteration, and methylation analyses were obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), The University of Alabama at Birmingham CANcer (UALCN), and Human Protein Atlas (HPA), cBioPortal, and MethSurv databases. Subsequently, the diagnostic and prognostic role of GINS3 in LIHC were analyzed based on data from receiver operating characteristic (ROC), Kaplan-Meier plotter (KM-plotter), and univariate and multivariate cox regression analyses. The functional analyses were conducted with GeneMANIA and STRING databases, gene-gene, and protein-protein interaction (PPI) networks, Gene Ontology (GO) term, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Tumor Immune Estimation Resource (TIMER), Tumor-Immune System Interaction Database (TISIDB), and Gene Expression Profiling Interactive Analysis (GEPIA) were utilized to explore the internal connection with the immune escape.

Results

Through the analyses of genomic expression, GINS3 was significantly upregulated in LIHC and positively correlated with higher T classification. ROC analysis indicated GINS3 as a potential biomarker in the diagnosis of LIHC. KM-plotter, univariate and multivariate cox regression analyses both associated GINS3 with poor prognosis in LIHC patients. GINS3 genetic alteration, gene-gene interaction, PPI networks, and enrichment analysis further revealed that GINS3 played a pivotal role in the progression of LIHC. Furthermore, hypermethylation of GINS3 at different cytosine-guanine (CpG) sites was correlated with better or worse overall survival (OS) in LIHC and GINS3 was also closely correlated with m6A modification. Moreover, results supported that GINS3 could influence the tumor microenvironment and relate to the immune checkpoints.

Conclusions

Taken together, comprehensive analyses from this study supported GINS3 as a novel targeted biomarker in LIHC.

Prognostic value and immunological role of BAIAP2L2 in liver hepatocellular carcinoma: A pan-cancer analysis

BACKGROUND

In recent years, the role of BAI1-associated protein 2-like 2 (BAIAP2L2) in the prognosis and immune microenvironment of various cancers has attracted increasing attention. However, its clinical value and immune infiltration in liver hepatocellular carcinoma (LIHC) remain unclear.

OBJECTIVE

To investigate the prognostic value of BAIAP2L2 and its correlation with immune infiltration in LIHC, we conducted corresponding data mining.

METHODS

In this study, The Cancer Genome Atlas, GTEx, StarBase, UALCAN, TIMER, GEPIA, Human Protein Atlas, Kaplan-Meier Plotter, cBioPortal, LinkedOmics, STRING and BioGPS databases were used to analyze BAIAP2L2 in cancers. Logistic regression and Cox regression were performed to analyze the correlation between clinical features and BAIAP2L2 expression in LIHC. In addition, the diagnostic and prognostic values of BAIAP2L2 in LIHC were determined by receiver operating characteristic (ROC) curves and nomograms. Single-sample gene set enrichment analysis (ssGSEA), BioGPS and TIMER were used to analyze the correlation between BAIAP2L2 and immune infiltration. More importantly, quantitative real-time polymerase chain reaction was used to verify BAIAP2L2 expression in a liver cancer cell line and a normal cell line. Visualization of data was mostly achieved using R language, version 3.6.3.

RESULTS

High BAIAP2L2 levels indicated poor overall survival (OS) and disease-free survival (DFS) of patients with LIHC. Abnormally increased expression of BAIAP2L2 in LIHC may be the result of both genetic alterations and lower DNA methylation levels. Furthermore, Cox regression analysis showed that high BAIAP2L2 expression was an independent risk factor for OS and DFS in patients with liver cancer. ROC curves and nomograms also confirmed the diagnostic and prognostic values of BAIAP2L2 in LIHC. Additionally, a PPI network of BAIAP2L2 was established and results implyed that BAIAP2L2 interacts with MTSS1, AMPH, FCHO1, SYT9, PDK2, MTSS1L, PM20D1, CHST4 and PALM3. ssGSEA showed that BAIAP2L2 was associated with T cells and natural killer cells. Simultaneously, the TIMER database showed that the expression of BAIAP2L2 in LIHC was positively correlated with tumor infiltrating cells, including B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells.

CONCLUSIONS

Through pan-cancer analysis, prognostic and immunological value of BAIAP2L2 in LIHC was identified. This is the first report on the potential of BAIAP2L2 as a prognostic biomarker and its correlation with immune infiltration in LIHC.

Tumor mutation burden associated with miRNA-gene interaction outcome mediates the survival of patients with liver hepatocellular carcinoma

Tumor mutation burden (TMB) is associated with immunogenic responses and the survival of cancer patients. This study demonstrates how TMB levels impact the immune-related cells, genes, and miRNAs, and how miRNA/gene interactions respond to variations in the survival rate of patients with liver hepatocellular carcinoma (LIHC). LIHC patients were divided into two groups, either a low TMB (< median) or a high TMB (≥ median) group. We found that high TMB plays a positive role in immune-mediated infiltration, generating more CD4 T-cells and memory B cells. Among the 21 immune genes that altered significantly, only C9orf24 and CYP1A1 were expected to up-regulate in LIHC patients with high TMB. A total of 19 miRNAs, which regulate various functional pathways, were significantly altered in patients with LIHC. One of the miRNA/gene pair, hsa-miR-33a/ALDH1A3 was significantly associated with the survival rate of LIHC patients. Our results suggest that LIHC patients with high TMB can be treated more effectively with immunotherapy.

Identification of cancer stem cell characteristics in liver hepatocellular carcinoma by WGCNA analysis of transcriptome stemness index

Cancer stem cells (CSCs) are characterized by self-renewal and -differential potential as compared to common cancer cells and play an important role in the development and therapeutic resistance of liver hepatocellular carcinoma (LIHC). However, the specific pathogenesis of LIHC stem cells is still unclear, and the genes involved in the stemness of LIHC stem cells are currently unknown. In this study, we investigated novel biomarkers associated with LIHC and explored the expression characteristics of stem cell-related genes in LIHC. We found that mRNA expression-based stemness index (mRNAsi) was significantly overexpressed in liver cancer tissues. Further, mRNAsi expression in LIHC increased with the tumor pathological grade, with grade 4 tumors harboring the greatest stem cell features. Upon establishing mRNAsi scores based on mRNA expression of every gene, we found an association with poor overall survival in LIHC. Moreover, modules of interest were determined based on weighted gene co-expression network analysis (WGCNA) inclusion criteria, and three significant modules (red, green, and brown) and 21 key genes (DCN, ECM1, HAND2, PTGIS, SFRP1, SRPX, COLEC10, GRP182, ADAMTS7, CD200, CDH11, COL8A1, FAP, LZTS1, MAP1B, NAV1, NOTCH3, OLFML2A, PRR16, TMEM119, and VCAN) were identified. Functional analysis of these 21 genes demonstrated their enrichment in pathways involved in angiogenesis, negative regulation of DNA-binding transcription factor activity, apoptosis, and autophagy. Causal relationship with proteins indicated that the Wnt, Notch, and Hypoxia pathways are closely related to LIHC tumorigenesis. To our knowledge, this is the first report of a novel CSC biomarker, mRNAsi, to predict the prognosis of LIHC. Further, we identified 21 key genes through mRNA expression network analysis, which could be potential therapeutic targets to inhibit the stemness of cancer cells in LIHC.

A profiling analysis on the receptor ACE2 expression reveals the potential risk of different type of cancers vulnerable to SARS-CoV-2 infection

Background

The new coronavirus pneumonia (NCP) is now causing a severe public health emergency. The novel coronavirus 2019 (2019-nCoV) infected individuals by binding human angiotensin converting enzyme II (ACE2) receptor. ACE2 is widely expressed in multiple organs including respiratory, cardiovascular, digestive and urinary systems in healthy individuals. These tissues with high expression level of ACE2 seemed to be more vulnerable to SARS-CoV-2 infection. Recently, it has been reported that patients with tumors were likely to be more susceptible to SARS-CoV-2 infection and indicated poor prognosis.

Methods

The tissue atlas database and the blood atlas were used to analyze the distribution of ACE2 in human tissues or organs of cancers and normal samples. Starbase dataset was applied to predict the prognosis of cancers according to expression level of ACE2.

Results

In this study, we demonstrated a landscape profiling analysis on expression level of ACE2 in pan-cancers and showed the risky of different type of cancers to SARS-CoV-2 according to the expression level of ACE2. In addition, we found that ACE2 was both differential expression and related to the prognosis only in liver hepatocellular carcinoma (LIHC). Relative high expression of ACE2 indicated a favorable prognosis in LIHC, but they might be more susceptible to SARS-CoV-2.

Conclusions

We indeed emphasized that LIHC patients with high expression level of ACE2 should be more cautious of the virus infection. Our study might provide a potential clue for preventing infection of SARS-CoV-2 in cancers.