Aberrant ARMCX1 Expression Is an Independent Predictor of Poor Prognosis in Gastric Cancer

Development and validation of cancer-associated fibroblasts-related gene landscape in prognosis and immune microenvironment of bladder cancer

Backgrounds

Bladder cancer (BLCA) is one of the most prevalent cancers of the genitourinary system, the clinical outcomes of patients with BLCA are bad, and the morbidity rate is high. One of the key components of the tumor microenvironment (TME) is cancer-associated fibroblasts (CAFs) which are critically involved in BLCA tumorigenesis. Previous studies have shown the involvement of CAFs in tumor growth, cancer progression, immune evasion, angiogenesis, and chemoresistance in several cancers such as breast, colon, pancreatic, ovarian, and prostate cancers. However, only a few studies have shown the role of CAFs in the occurrence and development of BLCA.

Methods

We have retrieved and merged the data on RNA-sequencing of patients with BLCA from databases including "the Cancer Genome Atlas" and "Gene Expression Omnibus." Next, we compared the differences in CAFs-related genes (CRGs) expression between normal and BLCA tissues. Based on CRGs expression, we randomly divided patients into two groups. Next, we determined the correlation between CAFs subtypes and differentially expressed CRGs (DECRGs) between the two subtypes. Furthermore, the "Gene Ontology" and "Kyoto Encyclopedia of Genes and Genomes pathway" enrichment analyses were conducted to determine the functional characteristics between the DECRGs and clinicopathology.

Results

We identified five genes (POF1B, ARMCX1, ALDOC, C19orf33, and KRT13) using multivariate COX regression and "Least Absolute Shrinkage and Selection Operator (LASSO) COX regression analysis" for developing a prognostic model and calculating the CRGs-risk score. The TME, mutation, CSC index, and drug sensitivity were also analyzed.

Conclusion

We constructed a novel five- CRGs prognostic model, which sheds light on the roles of CAFs in BLCA.

Gene dysregulation in acute HIV-1 infection – early transcriptomic analysis reveals the crucial biological functions affected

Introduction

Transcriptomic analyses from early human immunodeficiency virus (HIV) infection have the potential to reveal how HIV causes widespread and lasting damage to biological functions, especially in the immune system. Previous studies have been limited by difficulties in obtaining early specimens.

Methods

A hospital symptom-based screening approach was applied in a rural Mozambican setting to enrol patients with suspected acute HIV infection (Fiebig stage I-IV). Blood samples were collected from all those recruited, so that acute cases and contemporaneously recruited, uninfected controls were included. PBMC were isolated and sequenced using RNA-seq. Sample cellular composition was estimated from gene expression data. Differential gene expression analysis was completed, and correlations were determined between viral load and differential gene expression. Biological implications were examined using Cytoscape, gene set enrichment analysis, and enrichment mapping.

Results

Twenty-nine HIV infected subjects one month from presentation and 46 uninfected controls were included in this study. Subjects with acute HIV infection demonstrated profound gene dysregulation, with 6131 (almost 13% of the genome mapped in this study) significantly differentially expressed. Viral load was correlated with 1.6% of dysregulated genes, in particular, highly upregulated genes involved in key cell cycle functions, were correlated with viremia. The most profoundly upregulated biological functions related to cell cycle regulation, in particular, CDCA7 may drive aberrant cell division, promoted by overexpressed E2F family proteins. Also upregulated were DNA repair and replication, microtubule and spindle organization, and immune activation and response. The interferome of acute HIV was characterized by broad activation of interferon-stimulated genes with antiviral functions, most notably IFI27 and OTOF. BCL2 downregulation alongside upregulation of several apoptotic trigger genes and downstream effectors may contribute to cycle arrest and apoptosis. Transmembrane protein 155 (TMEM155) was consistently highly overexpressed during acute infection, with roles hitherto unknown.

Discussion

Our study contributes to a better understanding of the mechanisms of early HIV-induced immune damage. These findings have the potential to lead to new earlier interventions that improve outcomes.

Exploration of hub genes, lipid metabolism, and the immune microenvironment in stomach carcinoma and cholangiocarcinoma

Background

Gastric cancer (GC) is the 5th most common cause of cancer in the world and the 3rd largest cause of cancer-related death. It is usually associated with a variety of cancers, of which cholangiocarcinoma (CCA) combined with GC accounts for about 1.6%. This study sought to examine the hub genes and role of lipid metabolism in the development and diagnosis of GC and CCA.

Methods

To screen potential hub genes, The Cancer Genome Atlas (TCGA) data sets, including the GC (STAD, dataset of GC) and CCA (CHOL, dataset of CCA) data sets, were used to conduct a differentially expressed gene (DEG) analysis and an enrichment analysis of the DEGs. A weighted-gene co-expression network analysis (WGCNA) was conducted to identify the significant gene module and then find the hub genes in the module. To verify the 4 hub genes, we conducted a differentiation analysis of the 4 genes in GC and CCA and found that there were differences. A survival analysis of the hub genes was performed and mutations were mapped. Additionally, tumor immune microenvironment (TIME) and immune analyses were performed to evaluate how lipid metabolism affects the development of GC with CCA.

Results

The principal component analysis showed that both GC and CCA had distinct up-regulated and down-regulated genes, which are involved in a variety of metabolic processes. Upon WGCNA, the turquoise and blue modules were meaningful, and the hub genes were identified from these 2 modules. Four hub genes were identified: amyloid beta precursor protein binding family B member 1 (APBB1), Homo sapiens armadillo repeat containing X-linked 1 (ARMCX1), DAZ interacting zinc finger protein 1 (DZIP1), and methionine sulfoxide reductase B3 (MSRB3). In survival analysis, increased expression of the 4 hub genes was associated with inferior survival outcomes, with variations in all 4 genes. Additionally, we demonstrated that genes related to lipid metabolism had an effect on immune function.

Conclusions

APBB1, ARMCX1, DZIP1, and MSRB3 affect the development of GC and CCA and can be used as biomarkers. The expression of lipid metabolism genes is related to the TIME of patients with GC and CCA.