Role of CDH23 as a prognostic biomarker and its relationship with immune infiltration in acute myeloid leukemia.

BACKGROUND: Cadherin-23 (CDH23) plays an important role in intercellular adhesion and is involved in the progression of several types of cancer. However, the biological functions and effect of CDH23 expression on the prognosis of patients with acute myeloid leukemia (AML) are unexplored. Herein, we aim to characterize the role and molecular functions of CDH23 in AML. METHODS: We downloaded the transcriptomic profiles and clinical data from the Cancer Genome Atlas and Beat AML trial. The expression level of CDH23 was assessed using Gene Expression Profiling Interactive Analysis (GEPIA). Kaplan-Meier survival analysis was used to assess prognostic value of CDH23. Correlation and biological function analyses were performed using LinkedOmics and GeneMANIA. Relationship of CDH23 with immune infiltration level was determined using Tumor Immune Estimation Resource (TIMER). RESULTS: We found that the CDH23 expression was aberrantly upregulated in patients with AML and could be used as an independent risk factor of overall survival using Cox multivariate analysis. Notably, we observed a negative correlation between CDH23 expression and immune cell infiltration abundance by calculating the immune and stromal scores. In addition, functional enrichment analysis established that CDH23 plays a crucial role in tumor immunity. CONCLUSIONS: Our findings indicate that upregulated CDH23 expression corresponds to decreased overall survival of patients with AML. CDH23 may be involved in mediating tumor immune environment, and this highlights the potential of CDH23 as a therapeutic target in AML.

LCP1 triggers mTORC2/AKT activity and is pharmacologically targeted by enzastaurin in hypereosinophilia.

Hypereosinophilia (HE) is caused by a variety of disorders, ranging from parasite infections to autoimmune diseases and cancer. Only a small proportion of HE cases are clonal malignancies, and one of these, the group of eosinophilia-associated tyrosine kinase fusion-driven neoplasms, is sensitive to tyrosine kinase inhibitors, while most subtypes lack specific treatment. Eosinophil functions are highly dependent on actin polymerization, promoting priming, shape change, and infiltration of inflamed tissues. Therefore, we investigated the role of the actin-binding protein lymphocyte cytosolic protein 1 (LCP1) in malignant and nonmalignant eosinophil differentiation. We use the protein kinase C-ß (PKCß) selective inhibitor enzastaurin (Enza) to dephosphorylate and inactivate LCP1 in FIP1L1-platelet-derived growth factor receptor α (PDGFRA)-positive Eol-1 cells, and this was associated with reduced proliferation, metabolic activity, and colony formation as well as enhanced apoptosis and impaired migration. While Enza did not alter FIP1L1-PDGFRA-induced signal transducer and activator of transcription 3 (STAT3), STAT5, and ERK1/2 phosphorylation, it inhibited STAT1Tyr701 and AKTSer473 (but not AKTThr308 ) phosphorylation, and short hairpin RNA knockdown experiments confirmed that this process was mediated by LCP1 and associated mammalian target of rapamycin complex 2 (mTORC2) activity loss. Homeobox protein HoxB8 immortalized murine bone marrow cells showed impaired eosinophilic differentiation upon Enza treatment or LCP1 knockdown. Furthermore, Enza treatment of primary HE samples reduced eosinophil differentiation and survival. In conclusion, our data show that HE involves active LCP1, which interacts with mTOR and triggers mTORC2 activity, and that the PKCß inhibitor Enza as well as targeting of LCP1 may provide a novel treatment approach to hypereosinophilic disorders.

CUL4A is overexpressed in human pituitary adenomas and regulates pituitary tumor cell proliferation.

Cullin 4A (CUL4A) encodes a core subunit of an E3 ubiquitin ligase that targets proteins for ubiquitin-mediated degradation, and aberrant expression of the CUL4A is found in many tumor types. However, its roles and clinicopathologic significance in pituitary adenomas are not clear. The aim of this study was to investigate the possible role of CUL4A in pituitary tumorigenesis. Immunohistochemistry was used to examine CUL4A expression in human normal pituitaries and pituitary tumors with respect to various clinicopathologic factors in pituitary adenomas. Cell proliferation was assessed by MTT and colony formation, and migration and invasion were analyzed by Transwell and Matrigel assays after CUL4A overexpression or knockdown in pituitary tumor cells. Overexpression of CUL4A was frequently observed in pituitary adenomas compared with normal adenohypophysial tissue and significantly associated with tumor progressiveness and invasion. CUL4A overexpression in GH3 adenoma cells increased colony numbers, cell viability and cell invasion and silencing CUL4A in AtT20 adenoma cells decreased cell proliferation, migration and invasion. Mechanistically, CUL4A could modulate the expression of p53, p21, and p27 in pituitary tumor cells. In addition, high levels of CUL4A expression also significantly inversely correlated with the p53 protein level in human pituitary adenomas. Our results indicate that CUL4A enhances pituitary cell proliferation, migration and invasion and may thus contribute to pituitary tumor development and progression.

Development and validation of a combined cuproptosis and immunogenic cell death prognostic model for diffuse large B-cell lymphoma.

BACKGROUND: Diffuse large B-cell lymphoma (DLBCL) is the most common type of non-Hodgkin lymphoma worldwide with a high degree of heterogeneity. Cuproptosis and immunogenic cell death (ICD) have been considered to be vital for tumor progression. However, current understanding of cuproptosis and immunogenic cell death in DLBCL is still very limited. We aim to explore a prognostic model combining cuproptosis and immunogenic cell death in DLBCL. METHODS: Pearson's correlation analysis was utilized to acquire lncRNAs associated with cuproptosis and immunogenic cell death. Prognostic biomarker identification and model construction involved the use of univariate Cox regression, least absolute shrinkage and selection operator (LASSO) Cox regression, and multivariate Cox regression. We assessed the predictive capability of the risk model by conducting Kaplan-Meier analysis and time-dependent ROC analysis. The analysis and comparison of immune infiltration and drug sensitivity were conducted in this study. Moreover, RT-qPCR was employed to validate the expression of lncRNAs associated with cuproptosis and immunogenic cell death in DLBCL cell lines. RESULTS: We identified 4 prognosis-related lncRNAs (ANKRD10-IT1, HOXB-AS1, LINC00520 and LINC01165) that were correlated with cuproptosis and immunogenic cell death. The model was verified to have a good and independent predictive ability in the prognostic prediction of DLBCL patients. Moreover, significant difference was observed in immune infiltration and drug sensitivity between high- and low-risk groups. CONCLUSION: Our discoveries could enhance the comprehension of the role of cuproptosis and ICD in DLBCL, potentially offering novel viewpoints and knowledge for personalized and precise treatment of DLBCL individuals.

Development of macrophage-associated genes prognostic signature predicts clinical outcome and immune infiltration for sepsis.

Sepsis is a major global health problem, causing a significant burden of disease and death worldwide. Risk stratification of sepsis patients, identification of severe patients and timely initiation of treatment can effectively improve the prognosis of sepsis patients. We procured gene expression datasets for sepsis (GSE54514, GSE65682, GSE95233) from the Gene Expression Omnibus and performed normalization to mitigate batch effects. Subsequently, we applied weighted gene co-expression network analysis to categorize genes into modules that exhibit correlation with macrophage activity. To pinpoint macrophage-associated genes (MAAGs), we executed differential expression analysis and single sample gene set enrichment analysis. We then established a prognostic model derived from four MAAGs that were significantly differentially expressed. Functional enrichment analysis and immune infiltration assessments were instrumental in deciphering the biological mechanisms involved. Furthermore, we employed principal component analysis and conducted survival outcome analyses to delineate molecular subgroups within sepsis. Four novel MAAGs-CD160, CX3CR1, DENND2D, and FAM43A-were validated and used to create a prognostic model. Subgroup classification revealed distinct molecular profiles and a correlation with 28-day survival outcomes. The MAAGs risk score was developed through univariate Cox, LASSO, and multivariate Cox analyses to predict patient prognosis. Validation of the risk score upheld its prognostic significance. Functional enrichment implicated ribonucleoprotein complex biogenesis, mitochondrial matrix, and transcription coregulator activity in sepsis, with an immune infiltration analysis indicating an association between MAAGs risk score and immune cell populations. The four MAAGs exhibited strong diagnostic capabilities for sepsis. The research successfully developed a MAAG-based prognostic model for sepsis, demonstrating that such genes can significantly stratify risk and reflect immune status. Although in-depth mechanistic studies are needed, these findings propose novel targets for therapy and provide a foundation for future precise clinical sepsis management.

Cuproptosis-related lncRNA signature as a prognostic tool and therapeutic target in diffuse large B cell lymphoma.

Cuproptosis is a newly defined form of programmed cell death that relies on mitochondria respiration. Long noncoding RNAs (lncRNAs) play crucial roles in tumorigenesis and metastasis. However, whether cuproptosis-related lncRNAs are involved in the pathogenesis of diffuse large B cell lymphoma (DLBCL) remains unclear. This study aimed to identify the prognostic signatures of cuproptosis-related lncRNAs in DLBCL and investigate their potential molecular functions. RNA-Seq data and clinical information for DLBCL were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Cuproptosis-related lncRNAs were screened out through Pearson correlation analysis. Utilizing univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis, we identified seven cuproptosis-related lncRNAs and developed a risk prediction model to evaluate its prognostic value across multiple groups. GO and KEGG functional analyses, single-sample GSEA (ssGSEA), and the ESTIMATE algorithm were used to analyze the mechanisms and immune status between the different risk groups. Additionally, drug sensitivity analysis identified drugs with potential efficacy in DLBCL. Finally, the protein-protein interaction (PPI) network were constructed based on the weighted gene co-expression network analysis (WGCNA). We identified a set of seven cuproptosis-related lncRNAs including LINC00294, RNF139-AS1, LINC00654, WWC2-AS2, LINC00661, LINC01165 and LINC01398, based on which we constructed a risk model for DLBCL. The high-risk group was associated with shorter survival time than the low-risk group, and the signature-based risk score demonstrated superior prognostic ability for DLBCL patients compared to traditional clinical features. By analyzing the immune landscapes between two groups, we found that immunosuppressive cell types were significantly increased in high-risk DLBCL group. Moreover, functional enrichment analysis highlighted the association of differentially expressed genes with metabolic, inflammatory and immune-related pathways in DLBCL patients. We also found that the high-risk group showed more sensitivity to vinorelbine and pyrimethamine. A cuproptosis-related lncRNA signature was established to predict the prognosis and provide insights into potential therapeutic strategies for DLBCL patients.

Involvement of CUL4A in regulation of multidrug resistance to P-gp substrate drugs in breast cancer cells.

CUL4A encodes a core component of a cullin-based E3 ubiquitin ligase complex that regulates many critical processes such as cell cycle progression, DNA replication, DNA repair and chromatin remodeling by targeting a variety of proteins for ubiquitination and degradation. In the research described in this report we aimed to clarify whether CUL4A participates in multiple drug resistance (MDR) in breast cancer cells. We first transfected vectors carrying CUL4A and specific shCUL4A into breast cancer cells and corresponding Adr cells respectively. Using reverse transcription polymerase chain reactions and western blots, we found that overexpression of CUL4A in MCF7 and MDA-MB-468 cells up-regulated MDR1/P-gp expression on both the transcription and protein levels, which conferred multidrug resistance to P-gp substrate drugs, as determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assays. On the other hand, silencing CUL4A in MCF7/Adr and MDA-MB-468/Adr cells led to the opposite effect. Moreover, ERK1/2 in CUL4A-overexpressing cells was highly activated and after treatment with PD98059, an ERK1/2-specific inhibitor, CUL4A-induced expression of MDR1/P-gp was decreased significantly. Lastly, immunohistochemistry in breast cancer tissues showed that P-gp expression had a positive correlation with the expression of CUL4A and ERK1/2. Thus, these results implied that CUL4A and ERK1/2 participated in multi-drug resistance in breast cancer through regulation of MDR1/P-gp expression.

Prognostic Value of PIK3R4 Expression and Its Correlation with Immune Cell Infiltration in the Diffuse Large B-cell Lymphoma Microenvironment.

Background: As a regulatory unit of class III phosphoinositide 3-kinase (PI3K), PIK3R4 is an important molecule involved in several malignant tumours, but the role and molecular mechanism of PIK3R4 in diffuse large B-cell lymphoma (DLBCL) is still unclear. Methods: Multiple bioinformatics analyses were used to investigate the role and potential mechanisms of PIK3R4 in DLBCL. Quantitative real-time polymerase chain reaction (qRT‒PCR) was performed to determine the expression of PIK3R4 in 80 DLBCL patients, and the survival time of DLBCL patients grouped according to PIK3R4 mRNA expression was compared. Results: PIK3R4 is up-regulated in several malignant tumours, including DLBCL. Bioinformatics analyses revealed that PIK3R4 exhibits prognostic value in DLBCL patients, and the upregulation of this gene in DLBCL samples was subsequently validated. In the functional category, GO analysis revealed that PIK3R4-related genes are enriched in ribosomal RNA metabolic process, the DNA damage response, mitochondrial gene expression, and nucleoside metabolic process. KEGG pathway analysis showed the enrichment of PIK3R4-related genes in the ribosome, oxidative phosphorylation, proteasome, and cellular senescence pathways. More importantly, the expression of PIK3R4 in DLBCL was correlated with the immune cell content in the cancer microenvironment, CD8(+) T-cell and neutrophil infiltration and the levels of several immune checkpoint molecules, including BTN3A2, BTN3A1, PRF1, CXCL9, PDCD1, and TIGIT. Conclusion: Our study demonstrated that PIK3R4, as a novel immune microenvironment-related gene, may represent an important diagnostic, prognostic, or therapeutic biomarker in DLBCL patients.

An angiogenesis-related lncRNA signature predicts the immune microenvironment and prognosis of breast cancer.

Both angiogenesis and lncRNAs play crucial roles in the development and progression of breast cancer. Considering the unknown association of angiogenesis and lncRNAs in breast cancer, we aim to identify angiogenesis-related lncRNAs (ARLs) and explore their prognostic value. Here, based on analysis of The Cancer Genome Atlas database, the correlation between ARL and the prognosis and immune infiltration landscape of breast cancer were investigated. Eight ARLs (MAFG-DT, AC097478.1, AL357054.4, AL118556.1, SNHG10, MED14OS, OTUD6B-AS1, and CYTOR) were selected to construct the risk model as a prognostic signature. The survival rate of the patients in the high-risk group was lower than that in the low-risk group. The ARL signature was an independent prognostic predictor, and areas under the curve of 1-, 3-, and 5-year survival were 0.745, 0.695, and 0.699, respectively. The prognostic ARLs were associated with the immune infiltration landscape and could indicate the immune status, immune response, tumor mutational burden, and drug sensitivity of patients with breast cancer. Furthermore, qRT-PCR of clinical samples revealed that OTUD6B-AS1 was correlated with prognostic pathological parameters. OTUD6B-AS1 promoted breast cancer cell proliferation, wound healing, migration, invasion, and human umbilical vein endothelial cells tube formation. Mechanistically, OTUD6B-AS1 regulated EMT- and angiogenesis-related molecules. Taken together, we constructed and verified a robust signature of eight ARLs for the prediction of survival in patients with breast cancer, and the characterization of the immune infiltration landscape. Our findings suggest that OTUD6B-AS1 could be a therapeutic target for patients with breast cancer.

A Novel Fatty Acid Metabolism-Associated Risk Model for Prognosis Prediction in Acute Myeloid Leukaemia.

Acute myeloid leukaemia (AML) is the most common acute leukaemia in adults, with an unfavourable outcome and a high rate of recurrence due to its heterogeneity. Dysregulation of fatty acid metabolism plays a crucial role in the development of several tumours. However, the value of fatty acid metabolism (FAM) in the progression of AML remains unclear. In this study, we obtained RNA sequencing and corresponding clinicopathological information from the TCGA and GEO databases. Univariate Cox regression analysis and subsequent LASSO Cox regression analysis were utilized to identify prognostic FAM-related genes and develop a potential prognostic risk model. Kaplan-Meier analysis was used for prognostic significances. We also performed ROC curve to illustrate that the risk model in prognostic prediction has good performance. Moreover, significant differences in immune infiltration landscape were found between high-risk and low-risk groups using ESTIMATE and CIBERSOT algorithms. In the end, differential expressed genes (DEGs) were analyzed by gene set enrichment analysis (GSEA) to preliminarily explore the possible signaling pathways related to the prognosis of FAM and AML. The results of our study may provide potential prognostic biomarkers and therapeutic targets for AML patients, which is conducive to individualized precision therapy.

Significance of immunogenic cell death-related genes in prognosis prediction and immune microenvironment landscape of patients with cutaneous melanoma.

Cutaneous melanoma (CM) is one of the most life-threatening tumors. Although targeted therapies and immune checkpoint inhibitors have significantly improved patient outcomes over the past decades, they still have their efficacy limitations. Immunogenic cell death (ICD) induces regulated cell death through immunogenic signal secretion and exposure. Accumulated evidence suggests that the ICD process is an effective target for the treatment of a variety of tumor types, including CM. However, the research on ICD in CM is far from complete, and its clinical value has not been widely concerned. By analyzing the Cancer Genome Atlas (TCGA) database, we constructed a new risk model based on 4 ICD-related genes and validated its ability to predict the prognosis of CM patients. In addition, we comprehensively analyzed the tumor microenvironment (TME) of CM patients and showed a significant immunosuppressive TME in the high-risk group compared with the low-risk group. By Immunophenoscore (IPS), we further explored the correlation between the model and immunotherapy response. The data of Genomics of Drug Sensitivity in Cancer (GDSC) database were further extracted to analyze drug sensitivity and evaluate its correlation with the established risk model. In the end, differential expressed genes (DEGs) were analyzed by Gene Set Variation Analysis (GSVA) to preliminarily explore the possible signaling pathways related to the prognosis of ICD and CM. The results of this study provide new perspectives and insights for individualized and accurate treatment strategies for CM patients.

The prognostic marker FLVCR2 associated with tumor progression and immune infiltration for acute myeloid leukemia.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies in adults. The tumor microenvironment (TME) has a critical effect on AML occurrence, recurrence, and progression. The gene feline leukemia virus subgroup C cellular receptor family member 2 (FLVCR2) belongs to the major facilitator superfamily of transporter protein members, which is primarily involved in transporting small molecules. The potential role of FLVCR2 in the TME in AML has not been investigated. To clarify the expression and role of FLVCR2 in AML, we analyzed the Gene Expression Omnibus and The Cancer Genome Atlas databases and found that FLVCR2 mRNA expression significantly increased among patients with AML. Furthermore, based on an analysis of the Gene Expression Profiling Interactive Analysis database, FLVCR2 upregulation predicted dismal overall survival of patients with AML. Our validation analysis revealed the significant upregulation of FLVCR2 within the bone marrow of AML relative to healthy controls by western blotting and qPCR assays. Gene set enrichment analysis was conducted to explore FLVCR2's related mechanism in AML. We found that high FLVCR2 expression was related to infiltration degrees of immune cells and immune scores among AML cases, indicating that FLVCR2 possibly had a crucial effect on AML progression through the immune response. Specifically, FLVCR2 upregulation was negatively related to the immune infiltration degrees of activated natural killer cells, activated memory CD4+ T cells, activated dendritic cells, and CD8+ T cells using CIBERSORT analysis. According to the in vitro research, FLVCR2 silencing suppressed AML cell growth and promoted their apoptosis. This study provides insights into FLVCR2's effect on tumor immunity, indicating that it might serve as an independent prognostic biomarker and was related to immune infiltration within AML.

Identification of TNFAIP8 as an Immune-Related Biomarker Associated With Tumorigenesis and Prognosis in Cutaneous Melanoma Patients.

Tumor necrosis factor-α-induced protein 8 (TNFAIP8) is a member of the TIPE/TNFAIP8 family which is associated with inflammation and tumorigenesis. The potential role of TNFAIP8 in a tumor immune microenvironment in skin cutaneous melanoma (SKCM) has not yet been investigated. The TNFAIP8 expression was evaluated via gene expression profiling interactive analysis (GEPIA). We also evaluated the influence of TNFAIP8 on overall survival via GEPIA and PrognoScan. After GO and KEGG pathway analyses, the correlation between the TNFAIP8 expression level and immune cells or gene markers of the immune infiltration level was explored by R-language. The result showed the TNFAIP8 expression was significantly reduced in SKCM in comparison with normal control. In SKCM, the TNFAIP8 expression in higher levels was associated with the better overall survival. The high expression of TNFAIP8 was positively correlated with the immune score and promoted immune cell infiltration in SKCM patients. TNFAIP8 can be a positive prognosis marker or new immunotherapy target in SKCM.

The association of POLR2E rs3787016 polymorphism and cancer risk: a Chinese case-control study and meta-analysis.

How single nucleotide polymorphisms in long non-coding RNAs are involved in cancer susceptibility remains poorly understood. We hypothesized that polymerase II polypeptide E (POLR2E) rs3787016 polymorphism, identified in a genome-wide association study of prostate cancer, might be a common genetic risk factor for cancer risk. To address this issue, we here conducted a case-control study to investigate the association of POLR2E rs3787016 polymorphism with risk of liver and lung cancer (including 800 normal controls, 480 liver cancer patients, and 550 lung cancer patients), followed by a meta-analysis. The genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism and confirmed by sequencing. Although no significant association was found for rs3787016 with risk of liver or lung cancer, the further stratified analysis identified that rs3787016 contributed to liver cancer risk particularly for over than 60 years individuals who drink. Moreover, the meta-analysis demonstrated that rs3787016 was associated with overall cancer risk and prostate cancer risk. Collectively, the POLR2E rs3787016 polymorphism may be a valuable biomarker for cancer predisposition.