Genotype-Tissue Expression Database Research Articles

Novel lactylation-related signature to predict prognosis for pancreatic adenocarcinoma

BACKGROUND Lactate, previously considered a metabolic byproduct, is pivotal in cancer progression and maintaining the immunosuppressive tumor microenvironment. Further investigations confirmed that lactate is a primary regulator, introducing recently described post-translational modifications of histone and non-histone proteins, termed lysine lactylation. Pancreatic adenocarcinomas are characterized by increased glycolysis and lactate accumulation. However, our understanding of lactylation-related genes in pancreatic adenocarcinomas remains limited. AIM To construct a novel lactylation-related gene signature to predict the survival of patients with pancreatic cancer. METHODS RNA-seq and clinical data of pancreatic adenocarcinoma (PDAC) were obtained from the GTEx (Genotype-Tissue Expression) and TCGA (The Cancer Genome Atlas) databases via Xena Explorer, and GSE62452 datasets from GEO. Data on lactylation-related genes were obtained from publicly available sources. Differential expressed genes (DEGs) were acquired by using R package “DESeq2” in R. Univariate COX regression analysis, LASSO Cox and multivariate Cox regressions were produced to construct the lactylation-related prognostic model. Further analyses, including functional enrichment, ESTIMATE, and CIBERSORT, were performed to analyze immune status and treatment responses in patients with pancreatic cancer. PDAC and normal human cell lines were subjected to western blot analysis under lactic acid intervention; two PDAC cell lines with the most pronounced lactylation were selected. Subsequently, RT-PCR was employed to assess the expression of LRGs genes; SLC16A1, which showed the highest expression, was selected for further investigation. SLC16A1-mediated lactylation was analyzed by immunofluorescence, lactate production analysis, colony formation, transwell, and wound healing assays to investigate its role in promoting the proliferation and migration of PDAC cells. In vivo validation was performed using an established tumor model. RESULTS In this study, we successfully identified 10 differentially expressed lactylation-related genes (LRGs) with prognostic value. Subsequently, a lactylation-related signature was developed based on five OS-related lactylation-related genes (SLC16A1, HLA-DRB1, KCNN4, KIF23, and HPDL ) using Lasso Cox hazard regression analysis. Subsequently, we evaluated the clinical significance of the lactylation-related genes in pancreatic adenocarcinoma. A comprehensive examination of infiltrating immune cells and tumor mutation burden was conducted across different subgroups. Furthermore, we demonstrated that SLC16A1 modulates lactylation in pancreatic cancer cells through lactate transport. Both in vivo and in vitro experiments showed that decreasing SLC16A1 Level and its lactylation significantly inhibited tumor progression, indicating the potential of targeting the SLC16A1/ Lactylation-associated signaling pathway as a therapeutic strategy against pancreatic adenocarcinoma. CONCLUSION We constructed a novel lactylation-related prognostic signature to predict OS, immune status, and treatment response of patients with pancreatic adenocarcinoma, providing new strategic directions and antitumor immunotherapies.

Transcriptomic imputation of genetic risk variants uncovers novel whole-blood biomarkers of Parkinson’s disease

Blood-based gene expression signatures could potentially be used as biomarkers for PD. However, it is unclear whether genetically-regulated transcriptomic signatures can provide novel gene candidates for use as PD biomarkers. We leveraged on the Genotype-Tissue Expression (GTEx) database to impute whole-blood transcriptomic expression using summary statistics of three large-scale PD GWAS. A random forest classifier was used with the consensus whole-blood imputed gene signature (IGS) to discriminate between cases and controls. Outcome measures included Area under the Curve (AUC) of Receiver Operating Characteristic (ROC) Curve. We demonstrated that the IGS (n = 37 genes) is conserved across PD GWAS studies and brain tissues. IGS discriminated between cases and controls in an independent whole-blood RNA-sequencing study (1176 PD, 254 prodromal, and 860 healthy controls) with mean AUC and accuracy of 64.8% and 69.4% for PD cohort, and 78.8% and 74% for prodromal cohort. PATL2 was the top-performing imputed gene in both PD and prodromal PD cohorts, whose classifier performance varied with biological sex (higher performance for males and females in the PD and prodromal PD, respectively). Single-cell RNA-sequencing studies (scRNA-seq) of healthy humans and PD patients found PATL2 to be enriched in terminal effector CD8+ and cytotoxic CD4+ cells, whose proportions are both increased in PD patients. We demonstrated the utility of GWAS transcriptomic imputation in identifying novel whole-blood transcriptomic signatures which could be leveraged upon for PD biomarker derivation. We identified PATL2 as a potential biomarker in both clinical and prodromic PD.

IFI30 as a key regulator of PDL1 immunotherapy prognosis in breast cancer

BackgroundIFI30 is a lysosomal thiol reductase involved in antigen presentation and immune regulation in various cancers, including breast cancer. Despite its known involvement, the precise mechanism, function, and relationship with the PD-L1 axis and immune response remain unclear. MethodsWe conducted an extensive investigation into IFI30 mRNA expression in breast cancer utilizing data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. Furthermore, we characterized IFI30 mRNA expression across various cell types using publicly available single-cell RNA sequencing datasets, and assessed protein expression through immunohistochemistry using an in-house breast cancer tissue microarray. Functional experiments were performed to elucidate the effects of IFI30 overexpression on PD-L1 expression and inhibitory efficacy in both macrophages and breast tumor cells. ResultsOur study unveiled a marked upregulation of IFI30 expression in breast cancer tissues compared to their normal counterparts, with notable associations identified with tumor stage and prognosis. Additionally, IFI30 expression demonstrated significant correlations with various immune-related signaling pathways, encompassing peptide antigen binding, cytokine binding, and MHC class II presentation. Notably, breast cancer samples exhibiting high IFI30 expression in tumor cells displayed high PD-L1 expression on corresponding cells, alongside a diminished ratio of CD8 + T cell infiltration within the tumor microenvironment. Furthermore, ectopic knockdown of IFI30 in both tumor cells and macrophages resulted in a reduction of PD-L1 expression, while conversely, overexpression of IFI30 led to an increase in PD-L1 expression. ConclusionsThis study offers new insights into the involvement of IFI30 in breast cancer, elucidating its interplay with the PD-L1 axis and immune response dynamics. Our findings suggest that modulation of the IFI30-PD-L1 axis could serve as a promising strategy for regulating T cells infiltration in breast cancer thus treating breast cancer.

A novel TCGA-validated programmed cell-death-related signature of ovarian cancer

BackgroundOvarian cancer (OC) is a gynecological malignancy tumor with high recurrence and mortality rates. Programmed cell death (PCD) is an essential regulator in cancer metabolism, whose functions are still unknown in OC. Therefore, it is vital to determine the prognostic value and therapy response of PCD-related genes in OC.MethodsBy mining The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx) and Genecards databases, we constructed a prognostic PCD-related genes model and performed Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic (ROC) curve for its predictive ability. A nomogram was created via Cox regression. We validated our model in train and test sets. Quantitative real-time PCR (qRT-PCR) was applied to identify the expression of our model genes. Finally, we analyzed functional analysis, immune infiltration, genomic mutation, tumor mutational burden (TMB) and drug sensitivity of patients in low- and high-risk group based on median scores.ResultsA ten-PCD-related gene signature including protein phosphatase 1 regulatory subunit 15 A (PPP1R15A), 8-oxoguanine-DNA glycosylase (OGG1), HECT and RLD domain containing E3 ubiquitin protein ligase family member 1 (HERC1), Caspase-2.(CASP2), Caspase activity and apoptosis inhibitor 1(CAAP1), RB transcriptional corepressor 1(RB1), Z-DNA binding protein 1 (ZBP1), CD3-epsilon (CD3E), Clathrin heavy chain like 1(CLTCL1), and CCAAT/enhancer-binding protein beta (CEBPB) was constructed. Risk score performed well with good area under curve (AUC) (AUC3 − year =0.728, AUC5 − year = 0.730). The nomogram based on risk score has good performance in predicting the prognosis of OC patients (AUC1 − year =0.781, AUC3 − year =0.759, AUC5 − year = 0.670). Kyoto encyclopedia of genes and genomes (KEGG) analysis showed that the erythroblastic leukemia viral oncogene homolog (ERBB) signaling pathway and focal adhesion were enriched in the high-risk group. Meanwhile, patients with high-risk scores had worse OS. In addition, patients with low-risk scores had higher immune-infiltrating cells and enhanced expression of checkpoints, programmed cell death 1 ligand 1 (PD-L1), indoleamine 2,3-dioxygenase 1 (IDO-1) and lymphocyte activation gene-3 (LAG3), and were more sensitive to A.443,654, GDC.0449, paclitaxel, gefitinib and cisplatin. Finally, qRT-PCR confirmed RB1, CAAP1, ZBP1, CEBPB and CLTCL1 over-expressed, while PPP1R15A, OGG1, CASP2, CD3E and HERC1 under-expressed in OC cell lines.ConclusionOur model could precisely predict the prognosis, immune status and drug sensitivity of OC patients.

Correlation between the RNA Expression and the DNA Methylation of Estrogen Receptor Genes in Normal and Malignant Human Tissues.

Estrogen plays a multifaceted function in humans via interacting with the estrogen receptors ERα, ERβ, and G protein-coupled estrogen receptor 1 (GPER1). Previous research has predominantly concentrated on elucidating the signaling route of estrogen. However, the comprehensive understanding of the expression profile and control of these estrogen receptors in various human tissues is not well known. In the present study, the RNA levels of estrogen receptors in various normal and malignant human tissues were retrieved from the human protein atlas, the cancer genome atlas (TCGA), and the genotype-tissue expression (GTEx) databases for analyzing the expression profile of estrogen receptors through gene expression profiling interactive analysis (GEPIA). The status of DNA methylation of estrogen receptor genes from TCGA were analyzed through the software Wanderer and cBioPortal. The MethSurv tool was utilized to estimate the relevance between specific cytosine-guanine (CG) methylation and tumor survival. The expression profile analysis revealed that ERα, ERβ, and GPER1 have unique expression patterns in diverse tissues and malignancies. The interesting results were the higher expression of ERβ RNA in the male testis than in females and the positive association between the RNA level of ERα and the androgen receptor in different human normal tissues. Especially, the significant changes in GPER1 expression in multiple malignancies showed a consistent decrease with no exception, which indicates the role of GPER1 in common tumor inhibition. The finding on the expression profile provides clues for exploring novel potential physiological and pathophysiological functions of estrogen. The DNA methylation analysis manifested that the expression of GPER1 and ERα showed a substantial correlation with the methylation of specific CG sites in the cis-regulating region of the gene. However, no such association was observed for ERβ. When comparing tumor tissues to normal tissues, the DNA methylation of certain CG sites of estrogen receptors showed a correlation with tumor survival but did not always correlate with the expression of that gene or with the expression of DNA methyltransferases. We proposed that the variation in DNA methylation at different CG sites in estrogen receptor genes had other functions beyond its regulatory role in its gene expression, and this might be associated with the progression and therapy efficiency of the tumor based on the modulation of the chromatin configuration.

Identification of fibronectin type III domain containing 3B as a potential prognostic and therapeutic target for pancreatic cancer: a preliminary analysis

BackgroundFibronectin type III domain containing 3B (FNDC3B), a member of the fibronectin type III domain-containing protein family, has been indicated in various malignancies. However, the precise role of FNDC3B in the progression of pancreatic cancer (PC) still remains to be elucidated.MethodsIn this study, we integrated data from the National Center for Biotechnology Information, the Cancer Genome Atlas, Genotype-Tissue Expression database, and Gene Expression Omnibus datasets to analyze FNDC3B expression and its association with various clinicopathological parameters. Subsequently, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, along with Gene Set Enrichment Analysis (GSEA), single sample Gene Set Enrichment Analysis (ssGSEA) and estimate analysis were recruited to delve into the biological function and immune infiltration based on FNDC3B expression. Additionally, the prognostic estimation was conducted using Cox analysis and Kaplan–Meier analysis. Subsequently, a nomogram was constructed according to the result of Cox analysis to enhance the prognostic ability of FNDC3B. Finally, the preliminary biological function of FNDC3B in PC cells was explored.ResultsThe study demonstrated a significantly higher expression of FNDC3B in tumor tissues compared to normal pancreatic tissues, and this expression was significantly associated with various clinicopathological parameters. GSEA revealed the involvement of FNDC3B in biological processes and signaling pathways related to integrin signaling pathway and cell adhesion. Additionally, ssGSEA analysis indicated a positive correlation between FNDC3B expression and infiltration of Th2 cells and neutrophils, while showing a negative correlation with plasmacytoid dendritic cells and Th17 cells infiltration. Kaplan–Meier analysis further supported that high FNDC3B expression in PC patients was linked to shorter overall survival, disease-specific survival, and progression-free interval. However, although univariate analysis demonstrated a significant correlation between FNDC3B expression and prognosis in PC patients, this association did not hold true in multivariate analysis. Finally, our findings highlight the crucial role of FNDC3B expression in regulating proliferation, migration, and invasion abilities of PC cells.ConclusionDespite limitations, the findings of this study underscored the potential of FNDC3B as a prognostic biomarker and its pivotal role in driving the progression of PC, particularly in orchestrating immune responses.

ERH Impacts Patient Prognosis and Tumor Immune Microenvironment: A Pan-Cancer Analysis.

The enhancer of rudimentary homolog (ERH) has been shown to play significant roles in tumorigenesis and progression. However, few systematic pan-cancer analyses about ERH have been described. From the tumor immune estimation resource web server2.0 (TIMER2.0), the Genotype-Tissue Expression database (GTEx) and the Gene Expression Profile Interactive Analysis version 2 (GEPIA2) databases, we explored the expression profiles and prognostic significance of ERH in 33 cancers. The Clinical Proteomic Tumor Analysis Consortium (CPTAC) and the Human Protein Atlas (HPA) databases were further used to examine the differential expression of ERH at the protein level. The genetic alteration profile was obtained from the cBioPortal. The correlation between ERH expression and the quantities of immune infiltrating cells was examined by the TIMER tool. Spearman's correlation test was conducted to analyze the association between ERH expression status and a number of prognostic indicators, including immune checkpoints, TMB, MSI, immune neoantigen, MMR genes, and DNA methyltransferases. ProteinProtein Interaction analyses were performed in the String and GeneMANIA databases, and enrichment analysis and predicted signaling pathways were identified through GO and KEGG. To make our results convincing, we validated them in six datasets in the Gene Expression Omnibus (GEO) database. In addition, we verified the expression of ERH between gastric cancer tissues and adjacent normal tissues by RT-qPCR. ERH expression was elevated in numerous tumors, and it was not associated with the patient's prognosis. Furthermore, the quantities of immune infiltrating cells and immune checkpoint genes were remarkably associated with ERH. TMB and MSI were related to ERH expression in 14 and 15 cancer types, respectively. Moreover, the expression of ERH was strongly associated with MMR defects in multiple cancer types, and almost all tumors showed coexpression of ERH and four DNA methyltransferases. The results of GO and KEGG analysis confirmed that ERH potentially impacts several important signaling pathways. Both the GEO datasets and the RT-qPCR experiment validated our previous analysis. Our pan-cancer analysis demonstrated the characterization of ERH in multiple tumors. ERH may be a valuable novel biological indicator for assessing immunotherapy efficacy and prognosis in various malignancies.

Pan-cancer prognostic model and immune microenvironment analysis of natural killer cell-related genes.

Natural killer (NK) cells play a significant role in antitumor immunity and are closely related to tumor prognosis and recurrence. NK cell-based tumor immunotherapy, including immune checkpoint inhibition and CAR-engineered NK cells, is a promising area of research. However, there is a need for better NK cell-related models and associated biomarkers. The sequences of NK cell-related genes were obtained from the published NK cell CRISPR/Cas9 library data, and the common genes were selected as NK cell-related genes. The RNA sequencing (RNA-seq) and clinical data of 32 solid tumors from The Cancer Genome Atlas (TCGA) were downloaded from the UCSC Xena database, and the RNA-seq data of normal samples were downloaded from the Genotype-Tissue Expression (GTEx) database. The differentially expressed NK cell-related genes (DENKGs) between the tumor and normal samples were analyzed. The DENKGs related to the prognosis of solid tumors were selected via univariate Cox analysis, and 32 kinds of solid tumor prognostic models were constructed using least absolute shrinkage and selection operator (LASSO) and multivariate Cox analysis. Survival, receiver operating characteristic (ROC), and independent prognostic analyses were employed to test the effectiveness of the model, along with a nomogram model and prediction curve. Differences in the immune pathways and microenvironment cells were analyzed between the high- and low-risk groups identified by the model. We constructed a pan-cancer prognostic model with 63 NK cell-related genes and further identified DEPDC1 and ASPM as potentially offering new directions in tumor research by literature screening. In this study, 63 prognostic solid tumor markers were investigated using NK cell-related genes, and for the first time, a pan-cancer prognostic model was constructed to analyze their role in the immune microenvironment, which may contribute new insights into tumor research.

Prognostic value and immunological role of MMRN1: a rising star in cancer

Background Multimerin 1 (MMRN1) is a factor V binding protein, which can support platelet adhesion and thrombus formation. In recent years, the role of MMRN1 in cancer has begun to attract attention. But systematic studies in this area are lacking. Therefore, we used bioinformatics methods to analyze MMRN1 in tumors to reveal the possible role of MMRN1. Methods Using the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database, we obtained relevant data for analyzing MMRN1. Using Gene Expression Profiling Interactive Analysis (GEPIA), Human Protein Atlas (HPA), TCGA, GeneMANIA, and cBioPortal, we explored the potential role of MMRN1 in different types of tumors. Tumor Immune System Interactions and Drug Bank (TISIDB) and Sangerbox were used to analyze the correlation between MMRN1 and tumor immunity. Gene set cancer analysis (GSCA) and UALCAN were used to analyze the methylation of MMRN1. GSCA was also used to analyze the drug sensitivity of MMRN1. Results MMRN1 is down-regulated in most cancer types and is closely related to the prognosis of cancer patients. Interestingly, in most tumors, MMRN1 is positively correlated with immune -related genes. In addition, we observed different levels of methylation and mutations in different types of tumors. Drug sensitivity analysis found that MMRN1 was negatively correlated with several drugs, including GW-2580 and TL-1-85, suggesting that it can be used to develop potential anticancer therapies. Conclusion Our analysis demonstrated a significant relationship between MMRN1 and prognosis, tumor immunity, and drug sensitivity of several tumors. As a rising star in cancer, it needs further research.

The KIR2DL family serves as prognostic biomarkers and correlates with immune infiltrates in acute myeloid leukaemia.

Acute myeloid leukaemia (AML) is a prevalent haematological malignancy in which various immune and stromal cells in the bone marrow microenvironment have instrumental roles and substantially influence its progression. KIR2DL is a member of the immunoglobulin-like receptor family and a natural killer (NK) cell surface-specific receptor. However, its impact on immune infiltration regarding AML has not been addressed. We aimed to explore molecular markers associated with the immune microenvironment and prognosis of AML with a particular focus on KIR2DL family members. Analysis of data from The Cancer Genome Atlas and Genotype-Tissue Expression databases revealed that KIR2DL1, KIR2DL3 and KIR2DL4 expression were significantly upregulated in AML and associated with decreased overall survival (OS). Moreover, univariate Cox analysis implicated KIR2DL genes as independent prognostic markers of OS. Functional enrichment analysis revealed that KIR2DL genes were associated with immune cells, the immune microenvironment and NK cell-mediated cytotoxicity. Additionally, immune infiltration analyses revealed that KIR2DL upregulation was associated with stronger immune infiltration. Finally, we performed drug sensitivity profiling of KIR2DL genes using the Cellminer database. Collectively, our findings suggest that KIR2DL1, KIR2DL3 and KIR2DL4 have critical roles in AML and may represent novel biomarker genes for disease prognosis and immune infiltration.

Novel indel variation of LTBP4 gene associates with risk of sudden cardiac death in Chinese populations with coronary artery disease

The objective of this study is to investigate whether common genetic variants of the LTBP4 gene are linked to the susceptibility of sudden cardiac death in individuals who have atherosclerotic coronary artery disease (SCD-CAD) in Chinese populations. A total of 208 SCD-CAD cases and 638 controls were included in the analysis, and logistic regression was employed to assess the association between a 4-bp insertion/deletion polymorphism (rs34005443) within LTBP4 and the susceptibility to SCD-CAD among Chinese individuals. Logistic regression analysis demonstrated a notable association between the insertion allele of rs34005443 and an escalated susceptibility to SCD-CAD [odds ratio (OR) = 1.434; 95 % confidence interval:1.14–1.80; P = 1.79 × 10−3]. Genotype-phenotype correlation analysis was performed using Genotype-Tissue expression (GTEx) database and further validated by human myocardium using qPCR. Correlation analysis revealed that LTBP4 expression level was lower in samples with the insertion allele. Furthermore, the dual-luciferase activity assays indicated that rs34005443 may play a regulatory role. Additionally, we predicted 30 transcription factors that are likely to bind to rs34005443 and its highly linked genetic variants via 3DSNP database. Subsequent GO and KEGG analysis indicated that these transcription factors have a significant function in regulating gene expression. Finally, PPI network analysis suggested a tight connection between LTBP4 proteins and TGFβs, highlighting these genes as potential hub genes in the context of SCD-CAD. In summary, our study revealed that rs34005443 might contribute to SCD-CAD susceptibility by regulating LTBP4 expression. These findings revealed that this indel could be a potentially functional marker for molecular diagnosis and risk stratification of SCD-CAD.

Bioinformatics analysis highlights CCNB1 as a potential prognostic biomarker and an anti-kidney renal papillary cell carcinoma drug target.

Kidney renal papillary cell carcinoma (KIRP) is a common urinary tumor that causes lymph node invasion. Once metastatic, the prognosis is poor and there is a lack of effective early diagnostic markers for this tumor. The expression of CCNB1 in KIRP tumor tissues was significantly higher than that in normal tissues in The Cancer Genome Atlas database with or without the genotype-tissue expression database, and a consistent result was obtained in 32 paired tissues. In addition, CCNB1 expression increased remarkably with the progression of the T and M stages. Moreover, using the online HPA database, we verified that the immunohistochemical scores of CCNB1 in KIRP were higher than those in the normal kidney tissues. The higher expression group of CCNB1 showed a worse prognosis in KIRP. Moreover, the receiver operating characteristic curve, univariate and multivariate analyses, and construction of the column diagram further illustrated that CCNB1 was an independent prognostic factor for KIRP. Meanwhile, CCNB1 could better predict the 1- and 3-year survival rates of KIRP. Six genes were significantly and positively co-expressed with CCNB1. We also found that the CCNB1 high-expression group was enriched in the ECM_RECEPTOR_INTERACTION and FOCAL_ADHESION pathways. Finally, drug sensitivity analysis combined with molecular docking identified 5 targeting drugs with the strongest binding activity to CCNB1. CCNB1 is a potential and reliable biomarker for KIRP diagnosis and can be used to predict the survival of patients with KIRP. The 5 selected drugs targeting CCNB1 may provide new hopes for patients with KIRP metastasis.

Lactate dehydrogenase A is implicated in the pathogenesis of B-cell lymphoma through regulation of the FER signaling pathway.

Lactate dehydrogenase A (LDHA) is highly expressed in various tumors. However, the role of LDHA in the pathogenesis of B-cell lymphoma remains unclear. Analysis of data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases revealed an elevated LDHA expression in diffuse large B-cell lymphoma (DLBC) tissues compared with normal tissues. Similarly, our results demonstrated a significant increase in LDHA expression in tumor tissues from the patients with B-cell lymphoma compared with those with lymphadenitis. To further elucidate potential roles of LDHA in B-cell lymphoma pathogenesis, we silenced LDHA in the Raji cells (a B-cell lymphoma cell line) using shRNA techniques. Silencing LDHA led to reduced mitochondrial membrane integrity, adenosine triphosphate (ATP) production, glycolytic activity, cell viability and invasion. Notably, LDHA knockdown substantially suppressed in vivo growth of Raji cells and extended survival in mice bearing lymphoma (Raji cells). Moreover, proteomic analysis identified feline sarcoma-related protein (FER) as a differential protein positively associated with LDHA expression. Treatment with E260, a FER inhibitor, significantly reduced the metabolism, proliferation and invasion of Raji cells. In summary, our findings highlight that LDHA plays multiple roles in B-cell lymphoma pathogenesis via FER pathways, establishing LDHA/FER may as a potential therapeutic target.

AMPKα2 promotes tumor immune escape by inducing CD8+ T-cell exhaustion and CD4+ Treg cell formation in liver hepatocellular carcinoma

BackgroundAdenosine monophosphate-activated protein kinase (AMPK) is associated with the development of liver hepatocellular carcinoma (LIHC). AMPKα2, an α2 subunit of AMPK, is encoded by PRKAA2, and functions as the catalytic core of AMPK. However, the role of AMPKα2 in the LIHC tumor immune environment is unclear.MethodsRNA-seq data were obtained from the Cancer Genome Atlas and Genotype-Tissue Expression databases. Using the single-cell RNA-sequencing dataset for LIHC obtained from the China National Genebank Database, the communication between malignant cells and T cells in response to different PRKAA2 expression patterns was evaluated. In addition, the association between PRKAA2 expression and T-cell evolution during tumor progression was explored using Pseudotime analysis, and the role of PRKAA2 in metabolic reprogramming was explored using the R “scMetabolis” package. Functional experiments were performed in LIHC HepG2 cells.ResultsAMPK subunits were expressed in tissue-specific and substrate-specific patterns. PRKAA2 was highly expressed in LIHC tissues and was associated with poor patient prognosis. Tumors with high PRKAA2 expression displayed an immune cold phenotype. High PRKAA2 expression significantly promoted LIHC immune escape. This result is supported by the following evidence: 1) the inhibition of major histocompatibility complex class I (MHC-I) expression through the regulation of interferon-gamma activity in malignant cells; 2) the promotion of CD8+ T-cell exhaustion and the formation of CD4+ Treg cells in T cells; 3) altered interactions between malignant cells and T cells in the tumor immune environment; and 4) induction of metabolic reprogramming in malignant cells.ConclusionsOur study indicate that PRKAA2 may contribute to LIHC progression by promoting metabolic reprogramming and tumor immune escape through theoretical analysis, which offers a theoretical foundation for developing PRKAA2-based strategies for personalized LIHC treatment.

CDK16 as a potential prognostic biomarker correlated with an immunosuppressive tumor microenvironment and benefits in enhancing the effectiveness of immunotherapy in human cancers.

Cyclin-Dependent Kinase 16 (CDK16) plays significant biological roles in various diseases. Nonetheless, its function in different cancer types and its relationship with the Tumor Immune Microenvironment (TIME) are still not well-understood. We analyzed the expression profile, genetic alterations, clinical features, and prognostic value of CDK16 in pan-cancer using data from The Cancer Genome Atlas, Genotype-Tissue Expression databases, and in vitro experiments. Additionally, the TIMER2 and ImmuCellAI databases were utilized to assess the correlation between CDK16 expression and immune cell infiltration levels. Finally, we examined the correlation between CDK16 and the response to immunotherapy using collected immunotherapy data. CDK16 is notably overexpressed in pan-cancer and is a risk factor for poor prognosis in various cancers. Our findings reveal that CDK16 regulates not only cell cycle-related functions to promote cell proliferation but also the autoimmunity-related functions of the innate and adaptive immune systems, along with other immune-related signaling pathways. Moreover, CDK16 overexpression contributes to an immunosuppressive tumor microenvironment, extensively suppressing immune-related features such as the expression of immune-related genes and pathways, as well as the count of immune-infiltrating cells. Our analysis indicated that individuals with low CDK16 expression showed higher response rates to immune checkpoint inhibitors and longer overall survival compared to those with high CDK16 expression. This study establishes CDK16 as a potential biomarker for predicting poor prognosis in a wide range of cancers. Its role in shaping the immunosuppressive tumor microenvironment and influencing the efficacy of immunotherapy highlights the urgent need for developing targeted therapies against CDK16, offering new avenues for cancer treatment and management.

Exploratory study of cold hypersensitivity in Japanese women: genetic associations and somatic symptom burden

Temperature perception is essential for humans to discern the environment and maintain homeostasis. However, some individuals experience cold hypersensitivity, characterized by a subjective feeling of coldness despite ambient environmental temperatures being normal, the underlying mechanisms of which are unknown. In this study, we aimed to investigate the relationship between subjective cold symptoms and somatic burden or single nucleotide polymorphisms to understand the causes of cold hypersensitivity. We conducted an online questionnaire survey [comprising 30 questions, including past medical history, subjective symptoms of cold hypersensitivity, and the Somatic Symptom Scale-8 (SSS-8)]. Respondents were 1200 Japanese adult female volunteers (age: 20–59 years), recruited between April 21 and May 25, 2022, who were customers of MYCODE, a personal genome service in Japan. Among the 1111 participants, 599 (54%) reported cold hypersensitivity. Higher cold hypersensitivity severity was positively associated with the SSS-8 scores. Additionally, a genome-wide association study for cold hypersensitivity was conducted using array-based genomic data obtained from genetic testing. We identified 11 lead variants showing suggestive associations (P < 1 × 10–5) with cold hypersensitivity, some of which showed a reasonable change in expression in specific tissues in the Genotype-Tissue Expression database. The study findings shed light on the underlying causes of cold hypersensitivity.

Calreticulin, a potential coregulator of immune checkpoints and biomarker associated with tumor microenvironment and clinical prognostic significance in breast invasive carcinoma.

As a promising immune checkpoint of immunogenic cell death (ICD) and multifunctional calcium-binding molecular chaperone, calreticulin (CALR) has been attracting increasing attention. CALR mainly locates in cellular endoplasmic reticulum and significantly affects cell proliferation, invasion, induction of apoptosis, and angiogenesis in breast invasive carcinoma (BRCA). CALR overexpression might be correlated with a worse outcome. Nonetheless, it remains obscure how CALR correlates with immune infiltration and survival prognosis of BRCA. In this study, we investigated CALR expression utilizing RNAseq data from the cancer genome atlas (TCGA) and genotype-tissue expression (GTEx) database. The prognostic value of CALR was analyzed using clinical survival data. Enrichment analysis was conducted using the R package "clusterProfiler." We downloaded the immune cell infiltration score of TCGA samples from published articles and online databases and performed a correlation analysis between immune cell infiltration levels and CALR expression. We further assessed the association between CALR and immunomodulators. Moreover, we also evaluated the expression of CALR in 100 formalin-fixed and paraffin-embedded breast cancer and adjacent normal breast tissue specimens. Our results found that CALR was highly expressed in BRCA, and CALR expression levels differed in pathological stages, T stages, and N stages. Besides, these results suggested that CALR overexpression may have adverse effects on the progression-free interval (PFI) and disease-free interval (DFI), which may be related to tumor proliferation, invasion, and metastasis, leading to tumor deterioration. Meanwhile, immune cell infiltration analysis revealed a correlation between the expression of CALR and the number of neutrophils and dendritic cells, suggesting that CALR was highly correlated with many immunomodulators in BRCA. Our results provide potential biomarkers of CALR in BRCA. CALR may interact synergistically with other immunomodulators to regulate the immune microenvironment, which could be utilized to develop new immunotherapy drugs.

Comprehensive analysis of PSME3: from pan-cancer analysis to experimental validation.

PSME3 plays a significant role in tumor progression. However, the prognostic value of PSME3 in pan-cancer and its involvement in tumor immunity remain unclear. We conducted a comprehensive study utilizing extensive RNA sequencing data from the TCGA (The Cancer Genome Atlas) and GTEx (Genotype-Tissue Expression) databases. Our research revealed abnormal expression levels of PSME3 in various cancer types and unveiled a correlation between high PSME3 expression and adverse clinical outcomes, especially in cancers like liver cancer (LIHC) and lung adenocarcinoma (LUAD). Functional enrichment analysis highlighted multiple biological functions of PSME3, including its involvement in protein degradation, immune responses, and stem cell regulation. Moreover, PSME3 showed associations with immune infiltration and immune cells in the tumor microenvironment, indicating its potential role in shaping the cancer immune landscape. The study also unveiled connections between PSME3 and immune checkpoint expression, with experimental validation demonstrating that PSME3 positively regulates CD276. This suggests that PSME3 could be a potential therapeutic target in immunotherapy. Additionally, we predicted sensitive drugs targeting PSME3. Finally, we confirmed in both single-factor Cox and multiple-factor Cox regression analyses that PSME3 is an independent prognostic factor. We also conducted preliminary validations of the impact of PSME3 on cell proliferation and wound healing in liver cancer. In summary, our study reveals the multifaceted role of PSME3 in cancer biology, immune regulation, and clinical outcomes, providing crucial insights for personalized cancer treatment strategies and the development of immunotherapy.

STIM2 is involved in the regulation of apoptosis and the cell cycle in normal and malignant monocytic cells.

Calcium is a ubiquitous messenger that regulates a wide range of cellular functions, but its involvement in the pathophysiology of acute myeloid leukemia (AML) is not widely investigated. Here, we identified, from an analysis of The Cancer Genome Atlas and genotype-tissue expression databases, stromal interaction molecule 2 (STIM2) as being highly expressed in AML with monocytic differentiation and negatively correlated with overall survival. This was confirmed on a validation cohort of 407 AML patients. We then investigated the role of STIM2 in cell proliferation, differentiation, and survival in two leukemic cell lines with monocytic potential and in normal hematopoietic stem cells. STIM2 expression increased at the RNA and protein levels upon monocyte differentiation. Phenotypically, STIM2 knockdown drastically inhibited cell proliferation and induced genomic stress with DNA double-strand breaks, as shown by increased levels of phosphorylate histone H2AXγ (p-H2AXγ), followed by activation of the cellular tumor antigen p53 pathway, decreased expression of cell cycle regulators such as cyclin-dependent kinase 1 (CDK1)-cyclin B1 and M-phase inducer phosphatase 3 (CDC25c), and a decreased apoptosis threshold with a low antiapoptotic/proapoptotic protein ratio. Our study reports STIM2 as a new actor regulating genomic stability and p53 response in terms of cell cycle and apoptosis of human normal and malignant monocytic cells.

Clinical relevance of ORCs in predicting prognosis and immunotherapy outcomes: A pan-cancer analysis

BackgroundThe origin recognition complex (ORC) consists of six subunits and mediates DNA replication by binding to its origin. Recent studies show that ORCs are closely related to various biological processes in tumors. However, a comprehensive study of ORCs in pan-cancer has not been conducted. ResultsA systematic evaluation of the expression, mutation, and prognostic significance of ORCs was conducted across cancer types using data from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The single-sample Gene Set Enrichment Analysis (ssGSEA) was performed using R package “Gene Set Variation Analysis (GSVA)” to evaluate ORC score. ORC score was significantly elevated in most cancers and linked with an inferior prognosis. It was positively related to the G2/M checkpoint and DNA repair pathways. An elevated ORC score also correlated with tumor mutation burden (TMB)/ microsatellite instability (MSI). A prognosis analysis suggested that high ORC scores were associated with heightened immunotherapeutic sensitivity. ConclusionsOur research elucidates the genomic changes associated with and clinical relevance of ORCs in cancer and provides unique insights for future investigation of ORCs in immunotherapy.