Actin-like Protein 6A Expression Correlates with Cancer Stem Cell-like Features and Poor Prognosis in Ovarian Cancer

High expression of ACTL6A leads to poor prognosis of oral squamous cell carcinoma patients through promoting malignant progression

OBJECTIVE

The aim was to research ACTL6A's role in oral squamous cell carcinoma (OSCC).

METHODS

OSCC and normal samples were obtained from patients and public databases. GSEA was performed. CIBERSORT was utilized to analyze immune landscape. Kaplan-Meier survival analysis and multivariate Cox regression analysis were conducted. After knocking down ACTL6A, we performed MTT assay, transwell assays, and flow cytometry to detect the impact of knockdown.

RESULTS

ACTL6A expressed higher in OSCC samples than normal samples. The CNV and mutation rate of TP53 was higher in ACTL6A high-expression group. TFs E2F7 and TP63 and miRNA hsa-mir-381 were significantly related to ACTL6A. ACTL6A could influence immune microenvironment of OSCC. Knockdown of ACTL6A inhibited OSCC cells' proliferation, migration, and invasion. ACTL6A was able to predict OSCC prognosis independently.

CONCLUSION

ACTL6A expressed higher in OSCC than normal samples and it could be used as an independent prognostic marker in OSCC patients.

ACTL6A: unraveling its prognostic impact and paving the way for targeted therapeutics in carcinogenesis

Introduction: Increased Actin-like 6A (ACTL6A) expression is associated with various cancers, but its comprehensive investigation across different malignancies is lacking. We aimed to analyze ACTL6A as a potential oncogene and therapeutic target using bioinformatics tools. Methods: We comprehensively analyzed ACTL6A expression profiles across human malignancies, focusing on correlations with tumor grade, stage, metastasis, and patient survival. Genetic alterations were examined, and the epigenetic landscape of ACTL6A was assessed using rigorous methods. The impact of ACTL6A on immune cell infiltration in the tumor microenvironment was evaluated, along with molecular docking studies and machine learning models. Results: Our analysis revealed elevated ACTL6A expression in various tumors, correlating with poor prognostic indicators such as tumor grade, stage, metastasis, and patient survival. Genetic mutations and epigenetic modifications were identified, along with associations with immune cell infiltration and key cellular pathways. Machine learning models demonstrated ACTL6A's potential for cancer detection. Discussion: ACTL6A emerges as a promising diagnostic and therapeutic target in cancer, with implications for prognosis and therapy. Our study provides comprehensive insights into its carcinogenic actions, highlighting its potential as both a prognostic indicator and a target for anti-cancer therapy. This integrative approach enhances our understanding of ACTL6A's role in cancer pathogenesis and treatment.

Gene amplification of chromatin remodeling factor SMARCC2 and low protein expression of ACTL6A are unfavorable factors in ovarian high‑grade serous carcinoma

Ovarian high-grade serous carcinoma (OHGSC) is the most common type of ovarian cancer worldwide. Genome sequencing has identified mutations in chromatin remodeling factors (CRFs) in gynecological cancer, such as clear cell carcinoma, endometrioid carcinoma and endometrial serous carcinoma. However, to the best of our knowledge, the association between CRFs and OHGSC remains unexplored. The present study aimed to investigate the clinicopathological and molecular characteristics of CRF dysfunction in OHGSC. CRF alterations were analyzed through numerous methods, including the analysis of public next-generation sequencing (NGS) data from 585 ovarian serous carcinoma cases from The Cancer Genome Atlas (TCGA), immunohistochemistry (IHC), and DNA copy number assays, which were performed on 203 surgically resected OHGSC samples. In the public NGS dataset, the most frequent genetic alteration was actin-like protein 6A (ACTL6A) amplification at 19.5%. Switch/sucrose non-fermentable related, matrix associated, actin dependent regulator of chromatin subfamily c member 2 (SMARCC2) amplification (3.1%) was associated with significantly decreased overall survival (OS). In addition, chromodomain-helicase-DNA-binding protein 4 (CHD4) amplification (5.7%) exhibited unfavorable outcome trends, although not statistically significant. IHC revealed the protein expression loss of ARID1A (2.5%), SMARCA2 (2.5%) and SMARCA4 (3.9%). The protein expression levels of ACTL6A, SMARCC2 and CHD4 were evaluated using H-score. Patients with low protein expression levels of ACTL6A showed a significantly decreased OS. Copy number gain or gene amplification was demonstrated in ACTL6A (66.2%) and SMARCC2 (33.5%), while shallow deletion or deep deletion was demonstrated in CHD4 (70.7%). However, there was no statistically significant difference in protein levels of these CRFs, between the different copy number alterations (CNAs). Overall, OHGSC exhibited CNAs and protein loss, indicating possible gene alterations in CRFs. Moreover, there was a significant association between the protein expression levels of ACTL6A and poor prognosis. Based on these findings, it is suggested that CRFs could serve as prognostic markers for OHGSC.

Analysis of weighted gene co-expression networks and clinical validation identify hub genes and immune cell infiltration in the endometrial cells of patients with recurrent implantation failure

Background

About 10% of individuals undergoing in vitro fertilization encounter recurrent implantation failure (RIF), which represents a worldwide social and economic concern. Nevertheless, the critical genes and genetic mechanisms underlying RIF are largely unknown.

Methods

We first obtained three comprehensive microarray datasets "GSE58144, GSE103465 and GSE111974". The differentially expressed genes (DEGs) evaluation, enrichment analysis, as well as efficient weighted gene co-expression network analysis (WGCNA), were employed for distinguishing RIF-linked hub genes, which were tested by RT-qPCR in our 30 independent samples. Next, we studied the topography of infiltration of 22 immune cell subpopulations and the association between hub genes and immune cells in RIF using the CIBERSORT algorithm. Finally, a novel ridge plot was utilized to exhibit the potential function of core genes.

Results

The enrichment of GO/KEGG pathways reveals that Herpes simplex virus 1 infection and Salmonella infection may have an important role in RIF. After WGCNA, the intersected genes with the previous DEGs were obtained using both variance and association. Notably, the subsequent nine hub genes were finally selected: ACTL6A, BECN1, SNRPD1, POLR1B, GSK3B, PPP2CA, RBBP7, PLK4, and RFC4, based on the PPI network and three different algorithms, whose expression patterns were also verified by RT-qPCR. With in-depth analysis, we speculated that key genes mentioned above might be involved in the RIF through disturbing endometrial microflora homeostasis, impairing autophagy, and inhibiting the proliferation of endometrium. Furthermore, the current study revealed the aberrant immune infiltration patterns and emphasized that uterine NK cells (uNK) and CD4+ T cells were substantially altered in RIF endometrium. Finally, the ridge plot displayed a clear and crucial association between hub genes and other genes and key pathways.

Conclusion

We first utilized WGCNA to identify the most potential nine hub genes which might be associated with RIF. Meanwhile, this study offers insights into the landscape of immune infiltration status to reveal the underlying immune pathogenesis of RIF. This may be a direction for the next study of RIF etiology. Further studies would be required to investigate the involved mechanisms.

Molecular panorama of therapy resistance in prostate cancer: a pre-clinical and bioinformatics analysis for clinical translation

Prostate cancer (PCa) is a malignant disorder of prostate gland being asymptomatic in early stages and high metastatic potential in advanced stages. The chemotherapy and surgical resection have provided favourable prognosis of PCa patients, but advanced and aggressive forms of PCa including CRPC and AVPC lack response to therapy properly, and therefore, prognosis of patients is deteriorated. At the advanced stages, PCa cells do not respond to chemotherapy and radiotherapy in a satisfactory level, and therefore, therapy resistance is emerged. Molecular profile analysis of PCa cells reveals the apoptosis suppression, pro-survival autophagy induction, and EMT induction as factors in escalating malignant of cancer cells and development of therapy resistance. The dysregulation in molecular profile of PCa including upregulation of STAT3 and PI3K/Akt, downregulation of STAT3, and aberrant expression of non-coding RNAs are determining factor for response of cancer cells to chemotherapy. Because of prevalence of drug resistance in PCa, combination therapy including co-utilization of anti-cancer drugs and nanotherapeutic approaches has been suggested in PCa therapy. As a result of increase in DNA damage repair, PCa cells induce radioresistance and RelB overexpression prevents irradiation-mediated cell death. Similar to chemotherapy, nanomaterials are promising for promoting radiosensitivity through delivery of cargo, improving accumulation in PCa cells, and targeting survival-related pathways. In respect to emergence of immunotherapy as a new tool in PCa suppression, tumour cells are able to increase PD-L1 expression and inactivate NK cells in mediating immune evasion. The bioinformatics analysis for evaluation of drug resistance-related genes has been performed.

A census of actin-associated proteins in humans

Actin filaments help in maintaining the cell structure and coordinating cellular movements and cargo transport within the cell. Actin participates in the interaction with several proteins and also with itself to form the helical filamentous actin (F-actin). Actin-binding proteins (ABPs) and actin-associated proteins (AAPs) coordinate the actin filament assembly and processing, regulate the flux between globular G-actin and F-actin in the cell, and help maintain the cellular structure and integrity. We have used protein-protein interaction data available through multiple sources (STRING, BioGRID, mentha, and a few others), functional annotation, and classical actin-binding domains to identify actin-binding and actin-associated proteins in the human proteome. Here, we report 2482 AAPs and present an analysis of their structural and sequential domains, functions, evolutionary conservation, cellular localization, abundance, and tissue-specific expression patterns. This analysis provides a base for the characterization of proteins involved in actin dynamics and turnover in the cell.