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Coactivator-associated arginine methyltransferase 1 (CARM1) promotes the development and metastasis of estrogen receptor alpha (ER α)-positive breast cancer. The function of CARM1 in triple-negative breast cancer (TNBC) is still unclear and requires further exploration. Here, we report that CARM1 promotes proliferation, epithelial–mesenchymal transition, and stemness in TNBC. CARM1 is upregulated in multiple cancers and its expression correlates with breast cancer progression. Genome-wide analysis of CARM1 showed that CARM1 is recruited by hypoxia-inducible factor-1 subunit alpha (HIF1A) and occupy the promoters of CDK4 , Cyclin D1 , β -Catenin , HIF1A , MALAT1 , and SIX1 critically involved in cell cycle, HIF-1 signaling pathway, Wnt signaling pathway, VEGF signaling pathway, thereby modulating the proliferation and invasion of TNBC cells. We demonstrated that CARM1 is physically associated with and directly interacts with HIF1A. Moreover, we found that ellagic acid, an inhibitor of CARM1, can suppress the proliferation and invasion of TNBC by directly inhibiting CDK4 expression. Our research has determined the molecular basis of CARM1 carcinogenesis in TNBC and its effective natural inhibitor, which may provide new ideas and drugs for cancer therapy. [ABSTRACT FROM AUTHOR]

Background: RNA N6-methyladenosine (m6A) modification is primarily regulated by m6A regulators, which play significant epigenetic regulatory roles in tumorigenesis, tumor development, and tumor immune microenvironment. However, the correlation between m6A regulators and immune cell infiltration in breast cancer remains unclear. Methods: In this study, m6A modification patterns were evaluated based on 31 m6A modification regulators. m6A clusters were determined by consensus clustering. Immune landscape and immune cell infiltration subgroups were characterized by m6A clusters. Key module and hub genes related to m6A regulators and immune infiltration cells were identified by WGCNA. LASSO algorithm was applied to select prognostic signatures. Multivariate Cox regression analysis was applied to assess the prognostic value of gene signatures. Results: Two distinct m6A clusters were determined based on the expression of 31 m6A modification regulators and characterized by two tumor immune microenvironment (TIME) immune cell infiltration subgroups. Further, a total of 1971 differentially expressed genes between breast cancer patients and healthy controls were screened, nine modules associated with clinical characteristics of breast cancer patients were identified. Later, one key module and 13 hub genes correlated with m6A regulators and immune infiltration cells were identified. LASSO Cox regression analysis selected and constructed a ten-gene prognostic model to build a risk score system for individual breast cancer patient prognosis. The performance of the ten-gene-based risk score system was further validated in an independent dataset with an AUC of 0.659. Conclusions: This study revealed that m6A modification regulators played a significant role in the TIME regulation of breast cancer. The hub ten gene-based risk score system is valuable in predicting the prognosis of breast cancer patients, which may provide potential significance for breast cancer diagnosis, prognosis, and immunotherapy in the future. [ABSTRACT FROM AUTHOR]

Objectives: The study aims to analyze the expression of N6-methyladenosine (m6A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ. Materials and Methods: RNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N6-methyladenosine (m6A)-modified genes in READ were downloaded from the "m6Avar" database. Differentially expressed m6A-modified genes in READ stratified by different clinicopathological characteristics were identified using the "limma" package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using "STRING" and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the "rbsurv" package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8. Results: We screened 974 differentially expressed m6A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m6A-modified genes were positively correlated with that of m6A demethylase FTO and ALKBH5. Conclusion: This study identified potential m6A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is an aggressive primary intestinal malignancy with the third-highest incidence and second-highest mortality among all cancer types worldwide. Transcription factors (TFs) regulate cell development and differentiation owing to their ability to recognize specific DNA sequences upstream of genes. Numerous studies have demonstrated a strong correlation between TFs, the etiology of tumors, and therapeutic approaches. Here, we aimed to explore prognosis-related TFs and comprehend their carcinogenic mechanisms, thereby offering novel insights into the diagnosis and management of CRC., Materials and Methods: Differentially expressed TFs between CRC and normal tissues were identified leveraging The Cancer Genome Atlas database, Weighted correlation network analysis and Cox regression analysis were performed to identify prognosis-related TFs. The cellular functions of hub TF zinc finger E-box binding homeobox 1 ( ZEB1 ) were determined using by 5-ethynyl-2'-deoxyuridine and cell invasion assays in CRC cells. RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes enrichment, and gene set enrichment analyses were used to identify the cellular processes in which ZEB1 participates. Immunoaffinity purification, silver staining mass spectrometry, and a chromatin immunoprecipitation assay were conducted to search for proteins that might interact with ZEB1 and the target genes they jointly regulate., Results: Thirteen central TFs related to prognosis were identified through bioinformatics analysis techniques. Among these TFs, ZEB1 emerged as the TF most closely associated with CRC, as determined through a combination of regulatory network diagrams, survival curves, and phenotype analyses. ZEB1 promotes CRC cell growth by recruiting the NuRD(MTA1) complex, and the ZEB1/NuRD(MTA1) complex transcriptionally represses glycolysis-associated tumor suppressor genes., Conclusion: Our study not only identified a hub biomarker related to CRC prognosis but also revealed the specific molecular mechanisms through which ZEB1 affects cancer progression. These insights provide crucial evidence for the diagnosis of CRC and potential treatment opportunities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Gao, Hao, Zhang, Huo, Hu, Ma, Yu, Teng, Wang, Yang, Huang and Wang.)

Background: Cancers arise from genetic and epigenetic abnormalities that affect oncogenes and tumor suppressor genes, compounded by gene mutations. The N6-methyladenosine (m 6 A) RNA modification, regulated by methylation regulators, has been implicated in tumor proliferation, differentiation, tumorigenesis, invasion, and metastasis. However, the role of m 6 A modification patterns in the tumor microenvironment of gastric cancer (GC) remains poorly understood., Materials and Methods: In this study, we analyzed m 6 A modification patterns in 267 GC samples utilizing 31 m 6 A regulators. Using consensus clustering, we identified two unique subgroups of GC. Patients with GC were segregated into high- and low-infiltration cohorts to evaluate the infiltration proportions of the five prognostically significant immune cell types. Leveraging the differential genes in GC, we identified a "green" module via Weighted Gene Co-expression Network Analysis. A risk prediction model was established using the LASSO regression method., Results: The "green" module was connected to both the m 6 A RNA methylation cluster and immune infiltration patterns. Based on "Module Membership" and "Gene Significance", 37 hub genes were identified, and a risk prediction model incorporating nine hub genes was established. Furthermore, methylated RNA immunoprecipitation and RNA Immunoprecipitation assays revealed that YTHDF1 elevated the expression of DNMT3B, which synergistically promoted the initiation and development of GC. We elucidated the molecular mechanism underlying the regulation of DNMT3B by YTHDF1 and explored the crosstalk between m 6 A and 5mC modification., Conclusion: m 6 A RNA methylation regulators are instrumental in malignant progression and the dynamics of tumor microenvironment infiltration of GC. Assessing m 6 A modification patterns and tumor microenvironment infiltration characteristics in patients with GC holds promise as a valuable prognostic biomarker., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer LS declared a shared affiliation with the author YW to the handling editor at the time of review., (Copyright © 2024 Huo, Zhang, Zhang, Wang, Hu, Ma, Wang, Yuan, Qin, Teng, Yu, Huang and Wang.)

Introduction: Recent research has confirmed the critical role that epigenetic factors play in regulating the immune response. Nonetheless, what role m 6 A methylation modification might play in the immune response of non-small cell lung cancer (NSCLC) remains vague., Methods: Herein, the gene expression, copy number variations (CNVs), and somatic mutations of 31 m 6 A regulators in NSCLC and adjacent control samples from the GEO and TCGA databases were comprehensively explored. Using consensus clustering, m 6 A modification patterns were identified. Correlations between m 6 A modification patterns and immune cell infiltration traits in the tumor immune microenvironment (TME) were systematically analyzed. Differentially expressed genes were verified and screened by random forest and cox regression analysis by comparing different m 6 A modification patterns. Based on the retained gene panel, a risk model was built, and m 6 Ascore for each sample was calculated. The function of m 6 Ascore in NSCLC prognosis, tumor somatic mutations, and chemotherapy/immunotherapy response prediction were evaluated., Results: Consensus clustering classified all NSCLC samples into two m 6 A clusters (m 6 A_clusterA and m 6 A_clusterB) according to the expression levels of 25 m 6 A regulator genes. Hierarchical clustering further divides the NSCLC samples into two m 6 A gene clusters: m 6 AgeneclusterA and m 6 AgeneclusterB. A panel of 83 genes was screened from the 194 differentially expressed genes between m 6 A gene clusters. Based on this, a risk score model was established. m 6 A modification clusters, m 6 A gene clusters, and m 6 Ascore calculated from the risk model were able to predict tumor stages, immune cell infiltration, clinical prognosis, and tumor somatic mutations. NSCLC patients with high m 6 Ascore have poor drug resistance to chemotherapy drugs (Cisplatin and Gemcitabine) and exhibit considerable therapeutic benefits and favorable clinical responses to anti-PD1 or anti-CTLA4 immunotherapy., Discussion: In conclusion, methylation modification patterns mediated by the m 6 A regulators in individuals play a non-negligible role in prognosis prediction and immunotherapy response, which will facilitate personalized treatment and immunotherapeutic strategies for NSCLC patients in the future., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The reviewer YZ declared a shared affiliation, with no collaboration, with the authors BY, HQ, JZ, MZ, YY, and YW to the handling editor at the time of review., (Copyright © 2022 Yuan, Qin, Zhang, Zhang, Yang, Teng, Yu, Huang and Wang.)

Objectives: The study aims to analyze the expression of N 6 -methyladenosine (m 6 A)-modified genes in rectum adenocarcinoma (READ) and identify reliable prognostic biomarkers to predict the prognosis of READ., Materials and Methods: RNA sequence data of READ and corresponding clinical survival data were obtained from The Cancer Genome Atlas (TCGA) database. N 6 -methyladenosine (m 6 A)-modified genes in READ were downloaded from the "m6Avar" database. Differentially expressed m 6 A-modified genes in READ stratified by different clinicopathological characteristics were identified using the "limma" package in R. Protein-protein interaction (PPI) network and co-expression analysis of differentially expressed genes (DEGs) were performed using "STRING" and Cytoscape, respectively. Principal component analysis (PCA) was done using R. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were used to functionally annotate the differentially expressed genes in different subgroups. Univariate Cox regression analyses were conducted to identify the powerful independent prognostic factors in READ associated with overall survival (OS). A robust likelihood-based survival model was built using the "rbsurv" package to screen for survival-associated signature genes. The Support Vector Machine (SVM) was used to predict the prognosis of READ through the risk score of survival-associated signature genes. Correlation analysis were carried out using GraphPad prism 8., Results: We screened 974 differentially expressed m 6 A-modified genes among four types of READ samples. Two READ subgroups (group 1 and group 2) were identified by K means clustering according to the expression of DEGs. The two subgroups were significantly different in overall survival and pathological stages. Next, 118 differentially expressed genes between the two subgroups were screened and the expression of 112 genes was found to be related to the prognosis of READ. Next, a panel of 10 survival-associated signature genes including adamtsl1, csmd2, fam13c, fam184a, klhl4, olfml2b, pdzd4, sec14l5, setbp1, tmem132b was constructed. The signature performed very well for prognosis prediction, time-dependent receiver-operating characteristic (ROC) analysis displaying an area under the curve (AUC) of 0.863, 0.8721, and 0.8752 for 3-year survival rate, prognostic status, and pathological stage prediction, respectively. Correlation analysis showed that the expression levels of the 10 m 6 A-modified genes were positively correlated with that of m 6 A demethylase FTO and ALKBH5., Conclusion: This study identified potential m 6 A-modified genes that may be involved in the pathophysiology of READ and constructed a novel gene expression panel for READ risk stratification and prognosis prediction., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Huang, Li, Wang, Zhou, Yin, Yang, Wang, Teng, Feng and Yu.)

The downstream of tyrosine kinase 7 (DOK7) is an adaptor protein mediating signalling transduction between receptors and intracellular downstream molecules. Reduced expression of DOK7 has been observed in breast cancer. The present study aimed to investigate the role played by DOK7 in lung cancer. The expression of DOK7 at both mRNA and protein levels was evaluated in human lung cancer. A reduced expression of DOK7 transcripts was seen in lung cancers compared with normal lung tissues. Kaplan-Meier analyses showed that the reduced expression of DOK7 was associated with poorer overall survival and progression-free survival of patients with lung cancer. A further western blot analysis revealed a predominant expression of DOK7 isoform 1 (DOK7V1) in normal lung tissues, which was reduced in lung cancer. Forced overexpression of DOK7V1 in lung cancer cell lines, A549 and H3122 resulted in a decrease of in vitro cell proliferation and migration, while adhesion to extracellular matrix was enhanced following the expression. In conclusion, DOK7 was reduced in lung cancer and reduced DOK7 expression was associated with poorer survival. DOK7 isoform 1 plays an inhibitory role on the proliferation and migration of lung cancer cells in which Akt pathway may be involved.

The oncogenic role of ectopic expression of Na+/H+ exchanger regulatory factor 1 (NHERF1) was recently suggested in colorectal cancer, where it was implicated in playing a role in the tumor hypoxia microenvironment. Here we showed that a high level expression of NHERF1 was found in colorectal cancer tissues and that the expression of NHERF1 was positively correlated with VEGFR2 expression. The prognostic value of VEGFR2 expression in colorectal cancer relied on the expression of NHERF1. The up-regulation of NHERF1 induced by the exposure to hypoxia in colon cancer cells depended on the activation of VEGFR2 signaling. NHERF1 in turn inhibited the activation of VEGFR2 signaling which could be regulated by the interaction between NHERF1 and VEGFR2, resulting in the reduction of migration and invasion of colon cancer cells. These results suggest a dynamic interplay between NHERF1 and VEGFR2 signaling in colorectal cancer, which could explain the contribution of NHERF1 to the regulation of tumor cell responses to the hypoxia microenvironment.

Background: The mitochondrial protein translocase of inner mitochondrial membrane 17 homolog A (TIMM17A) has been identified as a biomarker of breast cancer. The present study aimed to investigate the biological role of TIMM17A in human breast cancer cells., Materials and Methods: Anti-TIMM17A transgenes were stably transfected into MDA MB-231 and MCF-7 breast cancer cell lines. The impact of TIMM17A knock-down on cell migration and invasion were evaluated using the respective cell models., Results: Reducing the expression of TIMM17A in breast cancer cells resulted in reduction of cell migration using electric cell-substrate impedance sensing. It was also found that reduction of TIMM17A expression resulted in reduction of cell invasion compared to vector control., Conclusion: TIMM17A has a profound impact on the cellular function of breast cancer cells. A decrease of TIMM17A expression is associated with the reduction of the aggressiveness of breast cancer cells. TIMM17A, therefore, has potential in prognosis and treatment of breast cancer., (Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.)

Background/aim: The ribosomal S6 protein kinase (RSK) family is an important effector of extracellular signal-regulated kinase/mitogen-activated protein kinase (ERK/MAPK) that could influence tumour metastasis by phosphorylating proteins in both the nuclear and cytoplasmic compartments. Aberrant expression of RSK is evident in certain malignancies but the role played by RSK in breast cancer is still not clear. This study aimed to examine the expression of RSK in human breast cancer specimens and its role to breast cancer metastasis., Materials and Methods: The expression of RSK1 to -3 were separately examined in human breast cancer tissues (normal, n=33; cancer, n=112) using quantitative real-time polymerase chain reaction (Q-PCR) and immunohistochemistry. Migration and adhesion of breast cancer cells treated with the RSK inhibitor SL0101 were investigated by electric cell impedance sensing (ECIS). The effect on growth and invasion of RSK1-3 was then investigated using in vitro models., Results: The clinical data and immunohistochemistry revealed that expression of RSK1 and RSK3 were less in tumour tissues than normal. mRNA expression of RSK2 was negatively correlated with grade, TNM staging, and survival rate. SL0101 inhibited adhesion of the MCF-7 and MDA-231 breast cancer cell lines. SL0101 suppressed MDA-231 invasion and the alternate RSK inhibitor BRD7389 inhibited the invasion of MCF-7 and MDA-231 cells., Conclusion: RSK1 and 3 but not RSK2 are down-regulated in breast tumour and are associated with disease progression. RSK may be a key component in the progression and metastasis of breast cancer., (Copyright© 2016 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.)

Background: Metastasis associated gene-1 (MTA1), was initially discovered in aggressive human cancer cell lines and has been subsequently associated with the invasiveness and metastatic potential of cancer cells., Materials and Methods: In the present study, we evaluated the expression levels of MTA1 in a cohort of human pituitary tumors (n=95) and examined the relationship between MTA1 expression and the pathological, clinical and aggressiveness of these tumors., Results: MTA1 was expressed at significantly higher levels in large tumors and in those with higher tumor grade. It was also observed that tumors that had invaded the suprasellar bones and tumors that destructed the sella had significantly higher levels than those without bone involvement (p<005). Although there did not appear to exist any relationship between MTA1 and cystic lesions in the tumors, endocrine-active tumors, namely those secreting prolactin, growth hormone, Follicle Stimulating Hormone (FSH) and Luteinizing Hormone (LH) had significantly lower MTA1 transcript levels than inactive tumors., Conclusion: MTA1 is associated with the aggressive nature of pituitary tumors and may be a potential therapeutic target in this tumor type., (Copyright© 2015, International Institute of Anticancer Research (Dr. John G. Delinasios), All rights reserved.)