In this study, we utilized the yeast two-hybrid system to screen for proteins interacting with USP24. Out of 250 such proteins, functional enrichment analysis using MetaCore™ indicated that 33 of them were involved in lung cancer progression. We then investigated gene expression and survival rates of these 33 proteins in lung cancer patients and cell lines through TCGA databases, Kaplan-Meier Plotter databases, and RNA-seq profile from A549/A549-T24 cells. By employing the patients' survival rate and gene expression profile of these 33 USP24-interacting proteins as gene signatures, we identified 10 potential drugs for inhibiting lung cancer progression or drug resistance via drug repurposing strategy using the Connectivity Map (CMap) database. Of these 10 drugs, six showed similar indicators in Clinical Trials, while the other four candidates (15-delta prostaglandin J2, Astemizole, Trifluoperazine, and 1,4-chrysenequinone) were chosen to evaluate their effect on re-sensitizing cytotoxicity of Taxol and Gefitinib in drug-resistant cancer cells. Experiments demonstrated that treatment with USP24-i-101 and Astemizole alone significantly inhibited drug resistance and re-sensitized the cytotoxicity of Taxol and Gefitinib in drug-resistant lung cancer cells. Notably, combination therapy with USP24-i-101and Astemizole re-sensitized the cytotoxicity of Taxol and Gefitinib in drug-resistant lung cancer, which could benefit in inhibiting drug resistance during cancer therapy.

Centromere protein A (CENPA) exhibits an increased expression level in primary human rectal cancer tissues, but its role has not been investigated.

To clarify the specific role and mechanism of CENPA in rectal cancer progression.

CENPA protein expression in rectal cancer tissues and cell lines were detected. CENPA was overexpressed and knocked down in SW837 and SW480 cells, and proliferation, invasion, apoptosis and epithelial-mesenchymal transition (EMT) marker protein levels were examined. O6-methylguanine DNA methyltransferase (MGMT) promoter methylation was assessed with methylation-specific polymerase chain reaction. Co-immunoprecipitation assay verified the interaction between MGMT and protein tyrosine phosphatase nonreceptor type 4 (PTPN4). SW837 cells with CENPA knockdown were injected subcutaneously into mice, and tumor growth was examined.

CENPA was upregulated in rectal cancer tissues and cell lines. CENPA overexpression promoted proliferation, invasion and EMT, and inhibited apoptosis in rectal cancer cells. Whereas CENPA knockdown showed the opposite results. Moreover, CENPA inhibited MGMT expression by promoting DNA methyltransferase 1-mediated MGMT promoter methylation. MGMT knockdown abolished the CENPA knockdown-mediated inhibition of rectal cancer cell progression. MGMT increased PTPN4 protein stability by inhibiting PTPN4 ubiquitination degradation via competing with ubiquitin-conjugating enzyme E2O for interacting with PTPN4. PTPN4 knockdown abolished the inhibitory effects of MGMT overexpression on rectal cancer cell progression. Moreover, CENPA knockdown inhibited xenograft tumor growth in vivo.

CENPA knockdown inhibited rectal cancer cell growth and attenuated xenograft tumor growth through regulating the MGMT/PTPN4 axis.

Nuclear pore complexes (NPCs) are the architectures entrenched in nuclear envelop of a cell that regulate the nucleo-cytoplasmic transportation of materials, such as proteins and RNAs for proper functioning of a cell. The appropriate localization of proteins and RNAs within the cell is essential for its normal functionality. For such a complex transportation of materials across the NPC, around 60 proteins are involved comprising nucleoporins, karyopherins and RAN system proteins that play a vital role in NPC's structure formation, cargo translocation across NPC, and cargoes' rapid directed transportation respectively. In various cancers, the structure and function of NPC is often exaggerated, following altered expressions of its nucleoporins and karyopherins, affecting other proteins of associated signaling pathways. Some inhibitors of karyopherins at present, have potential to regulate the altered level/expression of these karyopherin molecules.

This review summarizes the data from 1990 to 2023, mainly focusing on recent studies that illustrate the structure and function of NPC, the relationship and mechanisms of nucleoporins and karyopherins with colorectal cancer, as well as therapeutic values, in order to understand the pathology and underlying basis of colorectal cancer associated with NPC. This is the first review to our knowledge elucidating the detailed updated studies targeting colorectal cancer at NPC. The review also aims to target certain karyopherins, Nups and their possible inhibitors and activators molecules as a therapeutic strategy.

NPC structure provides understanding, how nucleoporins and karyopherins as key molecules are responsible for appropriate nucleocytoplasmic transportation. Many studies provide evidences, describing the role of disrupted nucleoporins and karyopherins not only in CRC but also in other non-hematological and hematological malignancies. At present, some inhibitors of karyopherins have therapeutic potential for CRC, however development of more potent inhibitors may provide more effective therapeutic strategies for CRC in near future.

Lactylation, a novel form of lactate-mediated protein post-translational modification (PTM), has been identified as a crucial regulator of gene expression and protein function through the modification of both histone and non-histone proteins. Liver disease is frequently characterized by a reprogramming of glucose metabolism and subsequent lactate accumulation. Recent research has implicated lactylation in a diverse array of hepatic pathologies, including liver injury, non-alcoholic fatty liver disease, liver fibrosis, and hepatocellular carcinoma. Consequently, lactylation has emerged as a pivotal regulatory mechanism in liver disease pathogenesis. This review aims to elucidate the intricate regulatory and functional mechanisms underlying lactylation, synthesize recent advancements in its role in various liver diseases, and highlight its potential as a therapeutic target for future interventions in hepatic disorders.

Cancer remains one of the most significant public health challenges worldwide. A widely recognized hallmark of cancer is the ability to sustain proliferative signaling, which is closely tied to various cell cycle processes. Centromere Protein A (CENPA), a variant of the standard histone H3, is crucial for selective chromosome segregation during the cell cycle. Despite its importance, a comprehensive pan-cancer bioinformatic analysis of CENPA has not yet been conducted.

Data on genomes, transcriptomes, and clinical information were retrieved from publicly accessible databases. We analyzed CENPA's genetic alterations, mRNA expression, functional enrichment, association with stemness, mutations, expression across cell populations and cellular locations, link to the cell cycle, impact on survival, and its relationship with the immune microenvironment. Additionally, a prognostic model for glioma patients was developed to demonstrate CENPA's potential as a biomarker. Furthermore, drugs targeting CENPA in cancer cells were identified and predicted using drug sensitivity correlations and protein-ligand docking.

CENPA exhibited low levels of gene mutation across various cancers. It was found to be overexpressed in nearly all cancer types analyzed in TCGA, relative to normal controls, and was predominantly located in the nucleus of malignant cells. CENPA showed a strong association with the cancer cell cycle, particularly as a biomarker for the G2 phase. It also emerged as a valuable diagnostic and prognostic biomarker across multiple cancer types. In glioma, CENPA demonstrated reliable prognostic potential when used alongside other prognostic factors. Additionally, CENPA was linked to the immune microenvironment. Drugs such as CD-437, 3-Cl-AHPC, Trametinib, BI-2536, and GSK461364 were predicted to target CENPA in cancer cells.

CENPA serves as a crucial biomarker for the cell cycle in cancers, offering both diagnostic and prognostic value.

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), infects approximately one-fourth of the world's population. While most infected individuals are asymptomatic, latent TB infection (LTBI) can progress to cause pulmonary TB (PTB). We recently reported an increased accumulation of mast cells (MCs) in lungs of macaques with PTB, compared with LTBI in macaques. MCs respond in vitro to Mtb exposure via degranulation and by inducing proinflammatory cytokines. In the current study, we show the dominant production of chymase by MCs in granulomas of humans and macaques with PTB. Using scRNA seq analysis, we show that MCs found in LTBI and healthy lungs in macaques are enriched in genes involved in tumor necrosis factor alpha, cholesterol and transforming growth factor beta signaling. In contrast, MCs clusters found in PTB express transcriptional signatures associated with interferon gamma, oxidative phosphorylation, and MYC signaling. Additionally, MC deficiency in the mouse model showed improved control of Mtb infection that coincided with reduced accumulation of lung myeloid cells and diminished inflammation at chronic stages. Thus, these collective results provide novel evidence for the pathological contribution of MCs during Mtb infection and may represent a novel target for host directive therapy for TB.

Histone variants are the paralogs of core histones (H2A, H2B, H3 and H4). They are stably expressed throughout the cell cycle in a replication-independent fashion and are capable of replacing canonical counterparts under different fundamental biological processes. Variants have been shown to take part in multiple processes, including DNA damage repair, transcriptional regulation and X chromosome inactivation, with some of them even specializing in lineage-specific roles like spermatogenesis. Several reports have recently identified some unprecedented variants from different histone families and exploited their prognostic value in distinct types of cancer. Among the four classes of canonical histones, the H2A family has the greatest number of variants known to date, followed by H2B, H3 and H4. In our prior review, we focused on summarizing all 19 mammalian histone H2A variants. Here in this review, we aim to complete the full summary of the roles of mammalian histone variants from the remaining histone H2B, H3, and H4 families, along with an overview of their roles in cancer biology and their prognostic value in a clinical context.

The function of glioma stem cells (GSCs) is closely related to the progression of glioblastoma multiforme (GBM). Centromere protein A (CENPA) has been confirmed to be related to the poor prognosis of GBM patients. However, whether CENPA regulates GSCs function to mediate GBM progression is still unclear. GSCs were isolated from GBM cells. The expression of CENPA and guanylate-binding protein 2 (GBP2) was examined by quantitative real-time PCR and western blot. GSCs proliferation and stemness were assessed using EdU assay and sphere formation assay. Cell ferroptosis was evaluated by detecting related factors. The interaction between CENPA and GBP2 was analyzed by ChIP assay and dual-luciferase reporter assay. Animal experiments were conducted to measure the effect of CENPA knockdown on the tumorigenicity of GSCs in vivo. CENPA was upregulated in GBM tissues and GSCs. CENPA knockdown inhibited GSCs proliferation, stemnness, and promoted ferroptosis. GBP2 was overexpressed in GBM tissues and GSCs, and CENPA enhanced GBP2 transcription by binding to its promoter region. CENPA overexpression accelerated GSCs proliferation and stemnness and suppressed ferroptosis, while GBP2 knockdown reversed these effects. Downregulation of CENPA reduced the tumorigenicity of GSCs by decreasing GBP2 expression in vivo. In conclusion, CENPA enhanced GBP2 transcription to increase its expression, thus accelerating GSCs proliferation and stemnness and repressing ferroptosis. Our findings promote a new idea for GBM treatment.

Triple-negative breast cancer (TNBC) exhibits heightened aggressiveness compared with other breast cancer (BC) subtypes, with earlier relapse, a higher risk of distant metastasis, and a worse prognosis. Transcription factors play a pivotal role in various cancers. Here, we found that factor forkhead box M1 (FOXM1) expression was significantly higher in TNBC than in other BC subtypes and normal tissues. Combining the findings of Gene Ontology (GO) enrichment analysis and a series of experiments, we found that knockdown of the FOXM1 gene attenuated the ability of TNBC cells to proliferate and metastasize both in vivo and in vitro. In addition, Spearman's test showed that FOXM1 significantly correlated with glycolysis-related genes, especially centromere protein A (CENPA) in datasets (GSE76250, GSE76124, GSE206912, and GSE103091). The effect of silencing FOXM1 on the inhibition of CENPA expression, TNBC proliferation, migration, and glycolysis could be recovered by overexpression of CENPA. According to MeRIP, the level of m6A modification on FOMX1 decreased in cells treated with cycloleucine (a m6A inhibitor) compared with that in the control group. The increase in FOXM1 expression caused by YTHDC1 overexpression could be reversed by the m6A inhibitor, which indicated that YTHDC1 enhanced FOXM1 expression depending on m6A modification. Therefore, we concluded that the YTHDC1-m6A modification/FOXM1/CENPA axis plays an important role in TNBC progression and glycolysis.

Glutamine addiction is a significant hallmark of metabolic reprogramming in tumors and is crucial to the progression of cancer. Nevertheless, the regulatory mechanisms of glutamine metabolism in endometrial cancer (EC) remains elusive. In this research, we found that elevated expression of CENPA and solute carrier family 38 member 1 (SLC38A1) were firmly associated with worse clinical stage and unfavorable outcomes in EC patients. In addition, ectopic overexpression or silencing of CENPA could either enhance or diminish glutamine metabolism and tumor progression in EC. Mechanistically, CENPA directly regulated the transcriptional activity of the target gene, SLC38A1, leading to enhanced glutamine uptake and metabolism, thereby promoting EC progression. Notably, a prognostic model utilizing the expression levels of CENPA and SLC38A1 genes independently emerged as a prognostic factor for EC. More importantly, CENPA and SLC38A1 were significantly elevated and positively correlated, as well as indicative of poor prognosis in multiple cancers. In brief, our study confirmed that CENPA is a critical transcription factor involved in glutamine metabolism and tumor progression through modulating SLC38A1. This revelation suggests that targeting CENPA could be an appealing therapeutic approach to address pan-cancer glutamine addiction.

The growing knowledge of ferroptosis has suggested the regulatory role of ferroptosis in hepatocellular carcinoma (HCC), but the pertinent molecular mechanisms remain unclear. Herein, this study investigated the mechanistic basis of ferroptosis-related genes (ferrGenes) in the growth of HCC.

Differentially expressed human ferrGenes and tumor-related transcription factors (TFs) were obtained from the The Cancer Genome Atlas (TCGA) dataset and the GTEx dataset. Spearman method-based correlation analysis were conducted to construct TF-ferrGene coexpression regulatory network. Key genes associated with prognosis were singled out with Lasso regression and multivariate Cox analysis to construct the prognostic risk model. Then the accuracy and independent prognostic ability of the model were evaluated. Expression of CENPA and STMN1 was determined in clinical HCC tissues and HCC cells, and their binding was analyzed with dual-luciferase and chromatin immunoprecipitation (ChIP) assays. Furthermore, ectopic expression and knockdown assays were performed in HCC cells to assess the effect of CENPA and STMN1 on ferroptosis and malignant phenotypes.

The prognostic risk model constructed based on the eight TF-ferrGene regulatory network-related genes accurately predicted the prognosis of HCC patients. It was strongly related to the clinical characteristics of HCC patients. Moreover, CENPA/STMN1 might be a key TF-ferrGene regulatory network in ferroptosis of HCC. CENPA and STMN1 were overexpressed in HCC tissues and cells. Additionally, CENPA facilitated STMN1 transcription by binding to STMN1 promoter, thus facilitating the malignant phenotypes and suppressing the ferroptosis of HCC cells.

Taken together, CENPA curbs the ferroptosis of HCC cells by upregulating STMN1 transcription, thereby promoting HCC growth.

The progression of prostate cancer (PCa) leads to poor prognosis. However, the molecular mechanism of PCa is still not completely clear. This study aimed to elucidate the important role of centromere protein A (CENPA) in PCa. Large numbers of bulk RNA sequencing (RNA-seq) data and in-house immunohistochemistry data were used in analysing the expression level of CENPA in PCa and metastatic PCa (MPCa). Single-cell RNA-seq data was used to explore the expression status of CENPA in different prostate subpopulations. Enrichment analysis was employed to detect the function of CENPA in PCa. Clinicopathological parameters analysis was utilised in analysing the clinical value of CENPA. The results showed that CENPA was upregulated in PCa (standardised mean difference [SMD] = 0.83, p = 0.001) and MPCa (SMD = 0.61, p = 0.029). CENPA was overexpressed in prostate cancer stem cells (CSCs) with androgen receptor (AR) negative compared to epithelial cells with AR positive. CENPA may influence the development of PCa through affecting cell cycle. Patients with nodal metastasis had higher expression level of CENPA. And patients with high CENPA expression had poor disease-free survival. Taken together, Overexpression of CENPA may influence the development of PCa by regulating cell cycle and promoting metastasis.

Coronavirus disease 2019 (COVID-19) is a global pandemic and highly contagious, posing a serious threat to human health. Colorectal cancer (CRC) is a risk factor for COVID-19 infection. Therefore, it is vital to investigate the intrinsic link between these two diseases.

In this work, bioinformatics and systems biology techniques were used to detect the mutual pathways, molecular biomarkers, and potential drugs between COVID-19 and CRC.

A total of 161 common differentially expressed genes (DEGs) were identified based on the RNA sequencing datasets of the two diseases. Functional analysis was performed using ontology keywords, and pathway analysis was also performed. The common DEGs were further utilized to create a protein-protein interaction (PPI) network and to identify hub genes and key modules. The datasets revealed transcription factors-gene interactions, co-regulatory networks with DEGs-miRNAs of common DEGs, and predicted possible drugs as well. The ten predicted drugs include troglitazone, estradiol, progesterone, calcitriol, genistein, dexamethasone, lucanthone, resveratrol, retinoic acid, phorbol 12-myristate 13-acetate, some of which have been investigated as potential CRC and COVID-19 therapies.

By clarifying the relationship between COVID-19 and CRC, we hope to provide novel clues and promising therapeutic drugs to treat these two illnesses.

The response of advanced clear cell renal cell carcinoma (ccRCC) to immunotherapy is still not durable, suggesting that the immune landscape of ccRCC still needs to be refined, especially as some molecules that have synergistic effects with immune checkpoint genes need to be explored.

The expression levels of CENPM and its relationship with clinicopathological features were explored using the ccRCC dataset from TCGA and GEO databases. Quantitative polymerase chain reaction (qPCR) analysis was performed to validate the expression of CENPM in renal cancer cell lines. Kaplan-Meier analysis, COX regression analysis and Nomogram construction were used to systematically evaluate the prognostic potential of CENPM in ccRCC. Besides, single gene correlation analysis, protein-protein interaction (PPI) network, genetic ontology (GO), kyoto encyclopedia of genes and genomes (KEGG) and gene set enrichment analysis (GSEA) were used to predict the biological behaviour of CENPM and the possible signalling pathways involved. Finally, a comprehensive analysis of the crosstalk between CENPM and immune features in the tumor microenvironment was performed based on the ssGSEA algorithm, the tumor immune dysfunction and exclusion (TIDE) algorithm, the TIMER2.0 database and the TISIDB database.

CENPM was significantly upregulated in ccRCC tissues and renal cancer cell lines and was closely associated with poor clinicopathological features and prognosis. Pathway enrichment analysis revealed that CENPM may be involved in the regulation of the cell cycle in ccRCC and may have some crosstalk with the immune microenvironment in tumors. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. The ssGSEA algorithm, CIBERSOPT algorithm suggests that CENPM is associated with suppressor immune cells in ccRCC such as regulatory T cells. Furthermore, the TISIDB database provides evidence that not only CENPM is positively associated with immune checkpoint genes such as CTLA4, PDCD1, LAG3, TIGIT, but also chemokines and receptors (such as CCL5, CXCL13, CXCR3, CXCR5) may be responsible for the malignant phenotype of CENPM in ccRCC. Meanwhile, predictions based on the TIDE algorithm support that patients with high CENPM expression have a worse response to immunotherapy.

The upregulation of CENPM in ccRCC predicts a poor clinical outcome, and this malignant phenotype may be associated with its exacerbation of the immunosuppressive state in the tumor microenvironment.

Background: Endoplasmic reticulum (ER) stress plays a pro-apoptotic role in colorectal adenocarcinoma (COAD). This study aimed to develop a novel ER-stress-related prognostic risk model for COAD and provide support for COAD cohorts with different risk score responses to immune checkpoint inhibitor therapies. Methods: TCGA-COAD and GSE39582 were included in this prospective study. Univariate and multivariate Cox analyses were performed to identify prognostic ER stress-related genes (ERSGs). Accordingly, the immune infiltration landscape and immunotherapy response in different risk groups were assessed. Finally, the expression of prognostic genes in 10 normal and 10 COAD tissue samples was verified using reverse transcription-quantitative polymerase chain reaction. Results: Eight prognostic genes were selected to establish an ERSG-based signature in the training set of the TCGA-COAD cohort. The accuracy of this was confirmed using a testing set of TCGA-COAD and GSE39582 cohorts. Gene set variation analysis indicated that differential functionality in high-low-risk groups was related to immune-related pathways. Corresponding to this, CD36, TIMP1, and PTGIS were significantly associated with 19 immune cells with distinct proportions between the different risk groups, such as central memory CD4T cells and central memory CD8T cells. Moreover, the risk score was considered effective for predicting the clinical response to immunotherapy, and the immunotherapy response was significantly and negatively correlated with the risk score of individuals with COAD. Furthermore, the immune checkpoint inhibitor treatment was less effective in the high-risk group, where the expression levels of PD-L1 and tumor immune dysfunction and exclusion scores in the high-risk group were significantly increased. Finally, the experimental results demonstrated that the expression trends of prognostic genes in clinical samples were consistent with the results from public databases. Conclusion: Our study established a novel risk signature to predict the COAD prognosis of patients and provide theoretical support for the clinical treatment of COAD.

We reconstructed a transcriptional regulatory network for adrenocortical carcinoma (ACC) using transcriptomic and clinical data from The Cancer Genome Atlas (TCGA)-ACC cohort. We investigated the association of transcriptional regulatory units (regulons) with overall survival, molecular phenotypes, and immune signatures. We annotated the ACC regulons with cancer hallmarks and assessed single sample regulon activities in the European Network for the Study of Adrenal Tumors (ENSAT) cohort. We found 369 regulons associated with overall survival and subdivided them into four clusters: RC1 and RC2, associated with good prognosis, and RC3 and RC4, associated with worse outcomes. The RC1 and RC3 regulons were highly correlated with the 'Steroid Phenotype,' while the RC2 and RC4 regulons were highly correlated with a molecular proliferation signature. We selected two regulons, NR5A1 (steroidogenic factor 1, SF-1) and CENPA (Centromeric Protein A), that were consistently associated with overall survival for further downstream analyses. The CENPA regulon was the primary regulator of MKI-67 (a marker of proliferation KI-67), while the NR5A1 regulon is a well-described transcription factor (TF) in ACC tumorigenesis. We also found that the ZBTB4 (Zinc finger and BTB domain-containing protein 4) regulon, which is negatively associated with CENPA in our transcriptional regulatory network, is also a druggable anti-tumorigenic TF. We anticipate that the ACC regulons may be used as a reference for further investigations concerning the complex molecular interactions in ACC tumors.

Hepatocellular carcinoma (HCC) is a severe cancer endangering human health. We constructed a novel glycometabolism-related risk score to predict prognosis and immunotherapy strategies in HCC patients. The HCC data sets were obtained from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, and the glycometabolism-related gene sets were obtained from the Molecular Signature Database. The least absolute contraction and selection operator (LASSO) regression model was used to construct a risk score based on glycometabolism-related genes. A simple visual nomogram model with clinical indicators was constructed and its effectiveness in calibration, accuracy, and clinical value was evaluated. We also explored the correlation between glycometabolism-related risk scores and molecular pathways, immune cells, and functions. Patients in the low-risk group responded better to anti-CTLA-4 immune checkpoint treatment and benefited from immune checkpoint inhibitor (ICI) therapy. The study found that glycometabolism-related risk score can effectively distinguish the prognosis, molecular and immune-related characteristics of HCC patients, and may provide a new strategy for individualized treatment.

Prostate cancer (PCa) is a common malignancy that poses a major threat to the health of men. Prostate-specific antigen (PSA) and its derivatives, as FDA-approved detection assays, are insufficient to serve as optimal markers for patient prognosis and clinical decision-making. It is widely acknowledged that aberrant glycolytic metabolism in PCa is related to tumor progression and acidifies the tumor microenvironment (TME). Considering the non-negligible impacts of glycolysis and immune functions on PCa, we developed a combined classifier in prostate cancer. The Glycolysis Score containing 19 genes and TME Score including three immune cells were created, using the univariate and multivariate Cox proportional hazards model, log-rank test, least absolute shrinkage and selection operator (LASSO) regression analysis and the bootstrap approach. Combining the glycolysis and immunological landscape, the Glycolysis-TME Classifier was then constructed. It was observed that the classifier was more accurate in predicting the prognosis of patients than the current biomarkers. Notably, there were significant differences in metabolic activity, signaling pathways, mutational landscape, immunotherapeutic response, and drug sensitivity among the Glycolysis^high/TME^low, Mixed group and Glycolysis^low/TME^high identified by this classifier. Overall, due to the significant prognostic value and potential therapeutic guidance of the Glycolysis-TME Classifier, we anticipate that this classifier will be clinically beneficial in the management of patients with PCa.