Methylation of TMEM176A, a key ERK signaling regulator, is a novel synthetic lethality marker of ATM inhibitors in human lung cancer

Epigenetic silencing ZSCAN23 promotes pancreatic cancer growth by activating Wnt signaling

Pancreatic ductal adenocarcinoma (PDAC) is the most malignant tumor. Zinc finger and SCAN domain-containing protein 23 (ZSCAN23) is a new member of the SCAN domain family. The expression regulation and biological function remain to be elucidated. In this study, we explored the epigenetic regulation and the function of ZSCAN23 in PDAC. ZSCAN23 was methylated in 60.21% (171/284) of PDAC and its expression was regulated by promoter region methylation. The expression of ZSCAN23 inhibited cell proliferation, colony formation, migration, invasion, and induced apoptosis and G1/S phase arrest. ZSCAN23 suppressed Panc10.05 cell xenograft growth in mice. Mechanistically, ZSCAN23 inhibited Wnt signaling by interacting with myosin heavy chain 9 (MYH9) in pancreatic cancer cells. ZSCAN23 is frequently methylated in PDAC and may serve as a detective marker. ZSCAN23 suppresses PDAC cell growth both in vitro and in vivo.

MS4A superfamily molecules in tumors, Alzheimer's and autoimmune diseases

MS4A (membrane-spanning 4-domain, subfamily A) molecules are categorized into tetraspanins, which possess four-transmembrane structures. To date, eighteen MS4A members have been identified in humans, whereas twenty-three different molecules have been identified in mice. MS4A proteins are selectively expressed on the surfaces of various immune cells, such as B cells (MS4A1), mast cells (MS4A2), macrophages (MS4A4A), Foxp3+CD4+ regulatory T cells (MS4A4B), and type 3 innate lymphoid cells (TMEM176A and TMEM176B). Early research confirmed that most MS4A molecules function as ion channels that regulate the transport of calcium ions. Recent studies have revealed that some MS4A proteins also function as chaperones that interact with various immune molecules, such as pattern recognition receptors and/or immunoglobulin receptors, to form immune complexes and transmit downstream signals, leading to cell activation, growth, and development. Evidence from preclinical animal models and human genetic studies suggests that the MS4A superfamily plays critical roles in the pathogenesis of various diseases, including cancer, infection, allergies, neurodegenerative diseases and autoimmune diseases. We review recent progress in this field and focus on elucidating the molecular mechanisms by which different MS4A molecules regulate the progression of tumors, Alzheimer's disease, and autoimmune diseases. Therefore, in-depth research into MS4A superfamily members may clarify their ability to act as candidate biomarkers and therapeutic targets for these diseases. Eighteen distinct members of the MS4A (membrane-spanning four-domain subfamily A) superfamily of four-transmembrane proteins have been identified in humans, whereas the MS4A genes are translated into twenty-three different molecules in mice. These proteins are selectively expressed on the surface of various immune cells, such as B cells (MS4A1), macrophages (MS4A4A), mast cells (MS4A2), Foxp3+CD4+ regulatory T cells (MS4A4B), type 3 innate lymphoid cells (TMEM176A and TMEM176B) and colonic epithelial cells (MS4A12). Functionally, most MS4A molecules function as ion channels that regulate the flow of calcium ions [Ca2+] across cell membranes. Recent studies have revealed that some MS4A proteins also act as molecular chaperones and interact with various types of immune receptors, including pattern recognition receptors (PRRs) and immunoglobulin receptors (IgRs), to form signaling complexes, thereby modulating intracellular signaling and cellular activity. Evidence from preclinical animal models and human genetic studies suggests that MS4A proteins play critical roles in various diseases (2). Therefore, we reviewed the recent progress in understanding the role of the MS4A superfamily in diseases, particularly in elucidating its function as a candidate biomarker and therapeutic target for cancer.

Methylation synthetic lethality: Exploiting selective drug targets for cancer therapy

In cancer, synthetic lethality refers to the drug-induced inactivation of one gene and the inhibition of another in cancer cells by a drug, resulting in the death of only cancer cells; however, this effect is not present in normal cells, leading to targeted killing of cancer cells. Recent intensive epigenetic research has revealed that aberrant epigenetic changes are more frequently observed than gene mutations in certain cancers. Recently, numerous studies have reported various methylation synthetic lethal combinations involving DNA damage repair genes, metabolic pathway genes, and paralogs with significant results in cellular models, some of which have already entered clinical trials with promising results. This review systematically introduces the advantages of methylation synthetic lethality and describes the lethal mechanisms of methylation synthetic lethal combinations that have recently demonstrated success in cellular models. Furthermore, we discuss the future opportunities and challenges of methylation synthetic lethality in targeted anticancer therapies.

Epigenetic silencing of BEND4, a novel DNA damage repair gene, is a synthetic lethal marker for ATM inhibitor in pancreatic cancer

Synthetic lethality is a novel model for cancer therapy. To understand the function and mechanism of BEN domain-containing protein 4 (BEND4) in pancreatic cancer, eight cell lines and a total of 492 cases of pancreatic neoplasia samples were included in this study. Methylation-specific polymerase chain reaction, CRISPR/Cas9, immunoprecipitation assay, comet assay, and xenograft mouse model were used. BEND4 is a new member of the BEN domain family. The expression of BEND4 is regulated by promoter region methylation. It is methylated in 58.1% (176/303) of pancreatic ductal adenocarcinoma (PDAC), 33.3% (14/42) of intraductal papillary mucinous neoplasm, 31.0% (13/42) of pancreatic neuroendocrine tumor, 14.3% (3/21) of mucinous cystic neoplasm, 4.3% (2/47) of solid pseudopapillary neoplasm, and 2.7% (1/37) of serous cystic neoplasm. BEND4 methylation is significantly associated with late-onset PDAC (> 50 years, P < 0.01) and tumor differentiation (P < 0.0001), and methylation of BEND4 is an independent poor prognostic marker (P < 0.01) in PDAC. Furthermore, BEND4 plays tumor-suppressive roles in vitro and in vivo. Mechanistically, BEND4 involves non-homologous end joining signaling by interacting with Ku80 and promotes DNA damage repair. Loss of BEND4 increased the sensitivity of PDAC cells to ATM inhibitor. Collectively, the present study revealed an uncharacterized tumor suppressor BEND4 and indicated that methylation of BEND4 may serve as a potential synthetic lethal marker for ATM inhibitor in PDAC treatment.

Methylation of NRIP3 Is a Synthetic Lethal Marker for Combined PI3K and ATR/ATM Inhibitors in Colorectal Cancer

INTRODUCTION

The aim of this study was to investigate the epigenetic regulation and underlying mechanism of NRIP3 in colorectal cancer (CRC).

METHODS

Eight cell lines (SW480, SW620, DKO, LOVO, HT29, HCT116, DLD1, and RKO), 187 resected margin samples from colorectal cancer tissue, 146 cases with colorectal adenomatous polyps, and 308 colorectal cancer samples were used. Methylation-specific PCR, Western blotting, RNA interference assay, and a xenograft mouse model were used.

RESULTS

NRIP3 exhibited methylation in 2.7% (5/187) of resected margin samples from colorectal cancer tissue, 32.2% (47/146) of colorectal adenomatous polyps, and 50.6% (156/308) of CRC samples, and the expression of NRIP3 was regulated by promoter region methylation. The methylation of NRIP3 was found to be significantly associated with late onset (at age 50 years or older), poor tumor differentiation, lymph node metastasis, and poor 5-year overall survival in CRC (all P < 0.05). In addition, NRIP3 methylation was an independent poor prognostic marker ( P < 0.05). NRIP3 inhibited cell proliferation, colony formation, invasion, and migration, while induced G1/S arrest. NRIP3 suppressed CRC growth by inhibiting PI3K-AKT signaling both in vitro and in vivo . Methylation of NRIP3 sensitized CRC cells to combined PI3K and ATR/ATM inhibitors.

DISCUSSION

NRIP3 was frequently methylated in both colorectal adenomatous polyps and CRC. The methylation of NRIP3 may potentially serve as an early detection, late-onset, and poor prognostic marker in CRC. NRIP3 is a potential tumor suppressor. NRIP3 methylation is a potential synthetic lethal marker for combined PI3K and ATR/ATM inhibitors.

RASSF1A promotes ATM signaling and RASSF1A methylation is a synthetic lethal marker for ATR inhibitors

Aim: The mechanism of RASSF1A in DNA damage repair remains to be further clarified for applying to synthetic lethal strategy. Materials & methods: Eight esophageal cancer cell lines, 181 cases of esophageal dysplasia and 1066 cases of primary esophageal squamous cell carcinoma (ESCC) were employed. Methylation-specific PCR, the CRISPR/Cas9 technique, immunoprecipitation assay and a xenograft mouse model were used. Results: RASSF1A was methylated in 2.21% of esophageal dysplasia and 11.73% of ESCC. RASSF1A was also involved in DNA damage repair through activating Hippo signaling. Loss of RASSF1A expression sensitized esophageal cancer cell lines to ataxia telangiectasia mutated and rad3-related (ATR) inhibitor (VE-822) both in vitro and in vivo. Conclusion: RASSF1A methylation is a synthetic lethal marker for ATR inhibitors.

Multi-omics approaches establishing histone modification based prognostic model in glioma patients and further verification of the carcinogenesis mechanism

Glioblastoma (GBM) emerges as the most common malignant brain tumor. Histone modifications, as an epigenetic regulatory mechanism of gene expression, are closely associated with malignant tumors. Gene set related to histone modification was extracted from the MSigDB database, and scored by the function of AddModuleScore. Pearson correlation analysis was utilized using the "rcorr" function of "Hmisc" R package. Genes were screened out using the LASSO Cox analysis. TCGA-GBM and CGGA_array_301 cohorts were employed for constructing model and validation. We calculated immune infiltration scores using microenvironment cell populations counter (MCPcounter), single-sample gene set enrichment analysis (ssGSEA), and xCell algorithms. U87-MG and CHG-5 cell lines were utilized to evaluate expression level of TMEM176A by western blot (WB). Transwell, EDU, colony formation analysis (CFA), and CKK-8 assays were conducted to investigate cell proliferation and migration rate. The malignant cells in GBM patients exhibited notable activation in the TGF-β and hypoxia pathway. Histone modifications were associated with adhesion and neuron development in GBM. We identified a model with five significant genes, namely NBEAL1, AEBP1, TMEM176A, FASTK, and CD81, with prognostic efficacy. Additionally, we observed increased infiltration of T cells and CD8+ T cells in the high-risk (HR) group. 5-Fluorouracil_1073 and Taselisib_1561 were predicted as potential treatment options for GBM patients, while ABT737_1910 and Wnt_C59-1622 exhibited superior response in GBM patients of the HR group. A spike in the TP53 mutation rate was observed in the HR group. TMEM176A played a role in regulating cell proliferation and migration in vitro. We presented a novel prognostic model for patients with GBM, based on histone modification-related genes. In addition, we identified the crucial role of the TMEM176A in the regulation of GBM carcinogenic phenotypes for the first time.

Illustrating the biological functions and diagnostic value of transmembrane protein family members in glioma

Background

It is well-established that patients with glioma have a poor prognosis. Although the past few decades have witnessed unprecedented medical advances, the 5-year survival remains dismally low.

Objective

This study aims to investigate the role of transmembrane protein-related genes in the development and prognosis of glioma and provide new insights into the pathogenesis of the disease

Methods

The datasets of glioma patients, including RNA sequencing data and relative clinical information, were obtained from The Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) databases. Prognostic transmembrane protein-related genes were identified by univariate Cox analysis. New disease subtypes were recognized based on the consensus clustering method, and their biological uniqueness was verified via various algorithms. The prognosis signature was constructed using the LASSO-Cox regression model, and its predictive power was validated in external datasets by receiver operating characteristic (ROC) curve analysis. An independent prognostic analysis was conducted to evaluate whether the signature could be considered a prognostic factor independent of other variables. A nomogram was constructed in conjunction with traditional clinical variables. The concordance index (C-index) and Decision Curve Analysis (DCA) were used to assess the net clinical benefit of the signature over traditional clinical variables. Seven different softwares were used to compare the differences in immune infiltration between the high- and low-risk groups to explore potential mechanisms of glioma development and prognosis. Hub genes were found using the random forest method, and their expression was based on multiple single-cell datasets.

Results

Four molecular subtypes were identified, among which the C1 group had the worst prognosis. Principal Component Analysis (PCA) results and heatmaps indicated that prognosis-related transmembrane protein genes exhibited differential expression in all four groups. Besides, the microenvironment of the four groups exhibited significant heterogeneity. The 6 gene-based signatures could predict the 1-, 2-, and 3-year overall survival (OS) of glioma patients. The signature could be used as an independent prognosis factor of glioma OS and was superior to traditional clinical variables. More immune cells were infiltrated in the high-risk group, suggesting immune escape. According to our signature, many genes were associated with the content of immune cells, which revealed that transmembrane protein-related genes might influence the development and prognosis of glioma by regulating the immune microenvironment. TMEM158 was identified as the most important gene using the random forest method. The single-cell datasets consistently showed that TMEM158 was expressed in multiple malignant cells.

Conclusion

The expression of transmembrane protein-related genes is closely related to the immune status and prognosis of glioma patients by regulating tumor progression in various ways. The interaction between transmembrane protein-related genes and immunity during glioma development lays the groundwork for future studies on the molecular mechanism and targeted therapy of glioma.

Immune checkpoints expression patterns in early-stage triple-negative breast cancer predict prognosis and remodel the tumor immune microenvironment

Background

Currently, targeting immune checkpoint molecules holds great promise for triple-negative breast cancer (TNBC). However, the expression landscape of immune checkpoint genes (ICGs) in TNBC remains largely unknown.

Method

Herein, we systematically investigated the ICGs expression patterns in 422 TNBC samples. We evaluated the ICGs molecular typing based on the ICGs expression profile and explored the associations between ICGs molecular subtypes and tumor immune characteristics, clinical significance, and response to immune checkpoint inhibitors (ICIs).

Results

Two ICGs clusters and two ICGs-related gene clusters were determined, which were involved in different survival outcomes, biological roles and infiltration levels of immune cells. We established a quantification system ICGs riskscore (named IRS) to assess the ICGs expression patterns for individuals. TNBC patients with lower IRS were characterized by increased immune cell infiltration, favorable clinical outcomes and high sensitivity to ICIs therapy. We also developed a nomogram model combining clinicopathological variables to predict overall survival in TNBC. Genomic feature analysis revealed that high IRS group presented an increased tumor mutation burden compared with the low IRS group.

Conclusion

Collectively, dissecting the ICGs expression patterns not only provides a new insight into TNBC subtypes but also deepens the understanding of ICGs in the tumor immune microenvironment.