High expression of EMP1 predicts a poor prognosis and correlates with immune infiltrates in bladder urothelial carcinoma

Epithelial membrane protein 1 in human cancer: a potential diagnostic biomarker and therapeutic target

Epithelial membrane protein 1 (EMP1) is a member of the small hydrophobic membrane protein subfamily. EMP1 is aberrantly expressed in various tumor tissues and governs multiple cellular behaviors (e.g., proliferation, differentiation, and migration). The resultant regulation of the cancer pathway is responsible for the metastasis of cancer cells and determines the risk of malignant tumor progression. This review provides an updated overview of EMP1 as either an oncogene or a tumor suppressor contingent on the cancer type and summarizes its upstream regulators and downstream target genes. This systematic review summarizes our current understanding of the role of EMP1 in malignant tumor development, including critical functional mechanisms and implications for its potential use as the biomarker and therapeutic target.

Construction and validation of a prognostic model of angiogenesis-related genes in multiple myeloma

BACKGROUND

Angiogenesis is associated with tumour growth, infiltration, and metastasis. This study aimed to detect the mechanisms of angiogenesis-related genes (ARGs) in multiple myeloma (MM) and to construct a new prognostic model.

METHODS

MM research foundation (MMRF)-CoMMpass cohort, GSE47552, GSE57317, and ARGs were sourced from public databases. Differentially expressed genes (DEGs) in the tumour and control cohorts in GSE47552 were determined through differential expression analysis and were enriched with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Weighted gene coexpression network analysis (WGCNA) was applied to derive modules linked to the ARG scores and obtain module genes in GSE47552. Differentially expressed ARGs (DE-ARGs) were selected for subsequent analyses by overlapping DEGs and module genes. Furthermore, prognostic genes were selected using univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses. Depending on the prognostic genes, a risk model was constructed, and risk scores were determined. Moreover, MM samples from MMRF-CoMMpass were sorted into high- and low-risk teams on account of the median risk score. Additionally, correlations among clinical characteristics, gene set variation analysis (GSVA), gene set enrichment analysis (GSEA), immune analysis, immunotherapy predictions and the mRNA‒miRNA‒lncRNA network were carried out.

RESULTS

A total of 898 DEGs, 211 module genes, 24 DE-ARGs and three prognostic genes (AKAP12, C11orf80 and EMP1) were selected for this study. Enrichment analysis revealed that the DEGs were related to 86 GO terms, such as 'cytoplasmic translation', and 41 KEGG pathways, such as 'small cell lung cancer'. A prognostic gene-based risk model was created in MMRF-CoMMpass and confirmed with the GSE57317 dataset. Moreover, a nomogram was established on the basis of independent prognostic factors that have proven to be good predictors. In addition, the immune cell infiltration results suggested that memory B cells were enriched in the high-risk group and that immature B cells were enriched in the low-risk group. Finally, the mRNA‒miRNA‒lncRNA network demonstrated that hsa-miR-508-5p was tightly associated with EMP1 and AKAP12. RT‒qPCR was used to validate the expression of the genes associated with prognosis.

CONCLUSION

A new prognostic model of MM associated with ARGs was created and validated, providing a new perspective for exploring the connection between ARGs and MM.

Integrating single-cell RNA-seq to identify fibroblast-based molecular subtypes for predicting prognosis and therapeutic response in bladder cancer

BACKGROUND

Bladder cancer (BLCA) is a highly aggressive and heterogeneous disease, posing challenges for diagnosis and treatment. Cancer immunotherapy has recently emerged as a promising option for patients with advanced and drug-resistant cancers. Fibroblasts, a significant component of the tumor microenvironment, play a crucial role in tumor progression, but their precise function in BLCA remains uncertain.

METHODS

Single-cell RNA sequencing (scRNA-seq) data for BLCA were obtained from the Gene Expression Omnibus database. The R package "Seurat" was used for processing scRNA-seq data, with uniform manifold approximation and projection (UMAP) for downscaling and cluster identification. The FindAllMarkers function identified marker genes for each cluster. Differentially expressed genes influencing overall survival (OS) of BLCA patients were identified using the limma package. Differences in clinicopathological characteristics, immune microenvironment, immune checkpoints, and chemotherapeutic drug sensitivity between high- and low-risk groups were investigated. RT-qPCR and immunohistochemistry validated the expression of prognostic genes.

RESULTS

Fibroblast marker genes identified three molecular subtypes in the testing set. A prognostic signature comprising ten genes stratified BLCA patients into high- and low-score groups. This signature was validated in one internal and two external validation sets. High-score patients exhibited increased immune cell infiltration, elevated chemokine expression, and enhanced immune checkpoint expression but had poorer OS and a reduced response to immunotherapy. Six sensitive anti-tumor drugs were identified for the high-score group. RT-qPCR and immunohistochemistry showed that CERCAM, TM4SF1, FN1, ANXA1, and LOX were highly expressed, while EMP1, HEYL, FBN1, and SLC2A3 were downregulated in BLCA.

CONCLUSION

A novel fibroblast marker gene-based signature was established, providing robust predictions of survival and immunotherapeutic response in BLCA patients.

Comprehensive analysis of the relationship between ubiquitin-specific protease 21 (USP21) and prognosis, tumor microenvironment infiltration, and therapy response in colorectal cancer

BACKGROUND

Ubiquitin-specific proteases family is crucial to host immunity against pathogens. However, the correlations between USP21 and immunosurveillance and immunotherapy for colorectal cancer (CRC) have not been reported.

METHODS

The differential expression of USP21 between CRC tissues and normal tissues was analyzed using multiple public databases. Validation was carried out in clinical samples through qRT-PCR and IHC. The correlation between USP21 and the prognosis, as well as clinical pathological characteristics of CRC patients, was investigated. Moreover, cell models were established to assess the influence of USP21 on CRC growth and progression, employing CCK-8 assays, colony formation assays, and wound-healing assays. Subsequently, gene set variation analysis (GSVA) was used to explore the potential biological functions of USP21 in CRC. The study also examined the impact of USP21 on cytokine levels and immune cell infiltration in the tumor microenvironment (TME). Finally, the effect of USP21 on the response to immunotherapy and chemotherapy in CRC was analyzed.

RESULTS

The expression of USP21 was significantly upregulated in CRC. High USP21 is correlated with poor prognosis in CRC patients and facilitates the proliferation and migration capacities of CRC cells. GSVA indicated an association between low USP21 and immune activation. Moreover, low USP21 was linked to an immune-activated TME, characterized by high immune cell infiltration. Importantly, CRC with low USP21 exhibited higher tumor mutational burden, high PD-L1 expression, and better responsiveness to immunotherapy and chemotherapeutic drugs.

CONCLUSION

This study revealed the role of USP21 in TME, response to therapy, and clinical prognosis in CRC, which provided novel insights for the therapeutic application in CRC.

EMP1 correlated with cancer progression and immune characteristics in pan-cancer and ovarian cancer

This study examines the prognostic role and immunological relevance of EMP1 (epithelial membrane protein-1) in a pan-cancer analysis, with a focus on ovarian cancer. Utilizing data from TCGA, CCLE, and GTEx databases, we assessed EMP1 mRNA expression and its correlation with tumor progression, prognosis, and immune microenvironment across various cancers. Our results indicate that EMP1 expression is significantly associated with poor prognosis in multiple cancer types, including ovarian, bladder, testicular, pancreatic, breast, brain, and uveal melanoma. Immune-related analyses reveal a positive correlation between EMP1 and immune cell infiltration, particularly neutrophils, macrophages, and dendritic cells, as well as high expression of immune checkpoint such as CD274, HAVCR2, IL10, PDCD1LG2, and TGFB1 in most tumors. In vivo experiments confirm that EMP1 promotes ovarian cancer cell proliferation, metastasis, and invasion. In conclusion, EMP1 emerges as a potential prognostic biomarker and therapeutic target in various cancers, particularly ovarian cancer, due to its influence on tumor progression and immune cell dynamics. Further research is warranted to elucidate the precise mechanisms of EMP1 in cancer biology and to translate these findings into clinical applications.

Multi-cohort validation of Ascore: an anoikis-based prognostic signature for predicting disease progression and immunotherapy response in bladder cancer

Bladder cancer ranks as the 10th most common cancer worldwide, with deteriorating prognosis as the disease advances. While immune checkpoint inhibitors (ICIs) have shown promise in clinical therapy in both operable and advanced bladder cancer, identifying patients who will respond is challenging. Anoikis, a specialized form of cell death that occurs when cells detach from the extracellular matrix, is closely linked to tumor progression. Here, we aimed to explore the anoikis-based biomarkers for bladder cancer prognosis and immunotherapeutic decisions. Through consensus clustering, we categorized patients from the TCGA-BLCA cohort into two clusters based on anoikis-related genes (ARGs). Significant differences in survival outcome, clinical features, tumor immune environment (TIME), and potential ICIs response were observed between clusters. We then formulated a four-gene signature, termed "Ascore", to encapsulate this gene expression pattern. The Ascore was found to be closely associated with survival outcome and served as an independent prognosticator in both the TCGA-BLCA cohort and the IMvigor210 cohort. It also demonstrated superior predictive capacity (AUC = 0.717) for bladder cancer immunotherapy response compared to biomarkers like TMB and PD-L1. Finally, we evaluated Ascore's independent prognostic performance as a non-invasive biomarker in our clinical cohort (Gulou-Cohort1) using circulating tumor cells detection, achieving an AUC of 0.803. Another clinical cohort (Gulou-Cohort2) consisted of 40 patients undergoing neoadjuvant anti-PD-1 treatment was also examined. Immunohistochemistry of Ascore in these patients revealed its correlation with the pathological response to bladder cancer immunotherapy (P = 0.004). Impressively, Ascore (AUC = 0.913) surpassed PD-L1 (AUC = 0.662) in forecasting immunotherapy response and indicated better net benefit. In conclusion, our study introduces Ascore as a novel, robust prognostic biomarker for bladder cancer, offering a new tool for enhancing immunotherapy decisions and contributing to the tailored treatment approaches in this field.

A comprehensive meta-analysis of transcriptome data to identify signature genes associated with pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) has a five-year survival rate of less than 5%. Absence of symptoms at primary tumor stages, as well as high aggressiveness of the tumor can lead to high mortality in cancer patients. Most patients are recognized at the advanced or metastatic stage without surgical symptom, because of the lack of reliable early diagnostic biomarkers. The objective of this work was to identify potential cancer biomarkers by integrating transcriptome data.

METHODS

Several transcriptomic datasets comprising of 11 microarrays were retrieved from the GEO database. After pre-processing, a meta-analysis was applied to identify differentially expressed genes (DEGs) between tumor and nontumor samples for datasets. Next, co-expression analysis, functional enrichment and survival analyses were used to determine the functional properties of DEGs and identify potential prognostic biomarkers. In addition, some regulatory factors involved in PDAC including transcription factors (TFs), protein kinases (PKs), and miRNAs were identified.

RESULTS

After applying meta-analysis, 1074 DEGs including 539 down- and 535 up-regulated genes were identified. Pathway enrichment analyzes using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) revealed that DEGs were significantly enriched in the HIF-1 signaling pathway and focal adhesion. The results also showed that some of the DEGs were assigned to TFs that belonged to 23 conserved families. Sixty-four PKs were identified among the DEGs that showed the CAMK family was the most abundant group. Moreover, investigation of corresponding upstream regions of DEGs identified 11 conserved sequence motifs. Furthermore, weighted gene co-expression network analysis (WGCNA) identified 8 modules, more of them were significantly enriched in Ras signaling, p53 signaling, MAPK signaling pathways. In addition, several hubs in modules were identified, including EMP1, EVL, ELP5, DEF8, MTERF4, GLUP1, CAPN1, IGF1R, HSD17B14, TOM1L2 and RAB11FIP3. According to survival analysis, it was identified that the expression levels of two genes, EMP1 and RAB11FIP3 are related to prognosis.

CONCLUSION

We identified several genes critical for PDAC based on meta-analysis and system biology approach. These genes may serve as potential targets for the treatment and prognosis of PDAC.

Novel potential urinary biomarkers for effective diagnosis and prognostic evaluation of high-grade bladder cancer

Background

High-grade bladder cancer (HGBC) has a higher malignant potential, recurrence and progression rate compared to low-grade phenotype. Its early symptoms are often vague, making non-invasive diagnosis using urinary biomarkers a promising approach.

Methods

The gene expression data from urine samples of patients with HGBC was extracted from the GSE68020 dataset. The clinical information and gene expression data in tumor tissues of HGBC patients were obtained from The Cancer Genome Atlas (TCGA) database. Multivariate Cox analysis was used to predict the optimal risk model. The protein-protein interaction (PPI) analysis was performed via the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized using Cytoscape. Overall survival (OS) was evaluated in the Gene Expression Profiling Interactive Analysis (GEPIA) online platform. Competing endogenous RNA (ceRNA) network was also visualized using Cytoscape. The expression levels of specific genes were assessed through quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). Moreover, co-expressed genes and potential biological functions related to specific genes were explored based on the Cancer Cell Line Encyclopedia (CCLE) database.

Results

A total of 560 differentially expressed genes (DEGs) were identified when comparing the urine sediment samples from HGBC patients with the benign ones. Using these urinary DEGs and the clinical information of HGBC patients, we developed an optimal risk model consisting of eight genes to predict the patient outcome. By integrating the node degree values in the PPI network with the expression changes in both urine and tissue samples, eighteen hub genes were selected out. Among them, DKC1 and SNRPG had the most prominent comprehensive values, and EFTUD2, LOR and EBNA1BP2 were relevant to a worse OS in bladder cancer patients. The ceRNA network of hub genes indicated that DKC1 may be directly regulated by miR-150 in HGBC. The upregulation of both SNRPG and DKC1 were detected in HGBC cells, which were also observed in various tumor tissues and malignant cell lines, displaying high correlations with other hub genes.

Conclusions

Our study may provide theoretical basis for the development of effective non-invasive detection and treatment strategies, and further research is necessary to explore the clinical applications of these findings.

Expression of EMP 1, 2, and 3 in Adrenal Cortical Neoplasm and Pheochromocytoma

The purpose of this study is to investigate the expression of the epithelial membrane proteins (EMP) 1, 2, and 3 in adrenal gland neoplasm and to explore the broader implications of this. Tissue microarrays were constructed for 132 cases of adrenal cortical neoplasms (ACN) (adrenal cortical adenoma (115 cases), and carcinoma (17 cases)) and 189 cases of pheochromocytoma. Immunohistochemical staining was performed to identify EMP 1, 2, and 3, and was compared with clinicopathological parameters. The H-score of EMP 3 (p < 0.001) was higher in pheochromocytoma when compared to that of ACN, and the H-score of EMP 1 (p < 0.001) and EMP 3 (p < 0.001) was higher in adrenal cortical carcinomas when compared to that of adrenal cortical adenomas. A higher EMP 1 H-score was observed in pheochromocytomas with a GAPP score ≥3 (p = 0.018). In univariate analysis, high levels of EMP 1 and EMP 3 expression in ACN were associated with shorter overall survival (p = 0.001). Differences were observed in the expression of EMPs between ACN and pheochromocytoma. EMPs are associated with malignant tumor biology in adrenal cortical neoplasm and pheochromocytoma, suggesting the role of a prognostic and/or predictive factor for EMPs in adrenal tumor.

Key Molecules in Bladder Cancer Affect Patient Prognosis and Immunotherapy Efficacy: Further Exploration for CNTN1 and EMP1

PURPOSE

Immunotherapy has been widely used in bladder cancer (BCa) in recent years and has significantly improved the prognosis of patients with BCa. However, further identification of immunotherapy-sensitive individuals to improve the efficacy of immunotherapy remains an important unmet need.

MATERIALS AND METHODS

The key genes were screened and identified from Gene Expression Omnibus database and The Cancer Genome Atlas database to construct the risk prediction function (risk scores). Real-time polymerase chain reaction, immunohistochemistry, and IMvigor210 data sets were used to verify the roles of key molecules and efficacy of risk scores. The biologic function of CNTN1 and EMP1 was further explored through cell proliferation experiments.

RESULTS

Five key genes, CNTN1, MAP1A, EMP1, MFAP5, and PTGIS, which were significantly related to the prognosis and immune checkpoint molecules of patients, were screened out. CNTN1 and EMP1 were further experimentally confirmed for their significant tumor-promoting effects. Besides, the constructed risk scores on the basis of these five key genes can accurately predict the prognosis and immunotherapy efficacy of patients with BCa. Interestingly, the high-risk patients identified by the risk scores have significantly worse prognosis and immunotherapy effects than low-risk patients.

CONCLUSION

The key genes we screened can affect the prognosis of BCa, tumor microenvironment immune infiltration, and the efficacy of immunotherapy. The risk scores tool we constructed will contribute to the development of individualized treatment for BCa.

Establishment of a prognostic model related to tregs and natural killer cells infiltration in bladder cancer

BACKGROUND

Regulatory T cells (Tregs) and natural killer (NK) cells play an essential role in the development of bladder urothelial carcinoma (BUC).

AIM

To construct a prognosis-related model to judge the prognosis of patients with bladder cancer, meanwhile, predict the sensitivity of patients to chemotherapy and immunotherapy.

METHODS

Bladder cancer information data was obtained from The Cancer Genome Atlas and GSE32894. The CIBERSORT was used to calculate the immune score of each sample. Weighted gene co-expression network analysis was used to find genes that will have the same or similar expression patterns. Subsequently, multivariate cox regression and lasso regression was used to further screen prognosis-related genes. The prrophetic package was used to predict phenotype from gene expression data, drug sensitivity of external cell line and predict clinical data.

RESULTS

The stage and risk scores are independent prognostic factors in patients with BUC. Mutations in FGFR3 lead to an increase in Tregs percolation and affect the prognosis of the tumor, and additionally, EMP1, TCHH and CNTNAP3B in the model are mainly positively correlated with the expression of immune checkpoints, while CMTM8, SORT1 and IQSEC1 are negatively correlated with immune checkpoints and the high-risk group had higher sensitivity to chemotherapy drugs.

CONCLUSION

Prognosis-related models of bladder tumor patients, based on Treg and NK cell percolation in tumor tissue. In addition to judging the prognosis of patients with bladder cancer, it can also predict the sensitivity of patients to chemotherapy and immunotherapy. At the same time, patients were divided into high and low risk groups based on this model, and differences in genetic mutations were found between the high and low risk groups.

A prognostic model for bladder cancer based on cytoskeleton-related genes

BACKGROUND

A typical cancerous growth in the urinary tract, bladder cancer (BLCA) has a dismal survival rate and a poor chance of being cured. The cytoskeleton has been shown to be tightly related to tumor invasion and metastasis. Nevertheless, the expression of genes associated with the cytoskeleton and their prognostic significance in BLCA remain unknown.

METHODS

In our study, we performed differential expression analysis of cytoskeleton-related genes between BLCA versus normal bladder tissues. According to the outcomes of this analysis of differentially expressed genes, all BLCA cases doing nonnegative matrix decomposition clustering analysis be classified into different molecular subtypes and were subjected to Immune cell infiltration analysis. We then constructed a cytoskeleton-associated gene prediction model for BLCA, and performed risk score independent prognostic analysis and receiver operating characteristic curve analyses to evaluate and validate the prognostic value of the model. Furthermore, enrichment analysis, clinical correlation analysis of prognostic models, and immune cell correlation analysis were carried out.

RESULTS

We identified 546 differentially expressed genes that are linked to the cytoskeleton, including 314 up-regulated genes and 232 down-regulated genes. All BLCA cases doing nonnegative matrix decomposition clustering analysis could be classified into 2 molecular subtypes, and we observed differences (P < .05) in C1 and C2 immune scores about 9 cell types. Next, we obtained 129 significantly expressed cytoskeleton-related genes. A final optimized model was constructed consisting of 11 cytoskeleton-related genes. Survival curves and risk assessment predicted the prognostic risk in both groups of patients with BLCA. Survival curves and receiver operating characteristic curves were used to evaluate and validate the prognostic value of the model. Significant enrichment pathways for cytoskeleton-associated genes in bladder cancer samples were explored by Gene set enrichment analysis enrichment analysis. After we obtained the risk scores, a clinical correlation analysis was performed to examine which clinical traits were related to the risk scores. Finally, we demonstrated a correlation between different immune cells.

CONCLUSION

Cytoskeleton-related genes have an important predictive value for BLCA, and the prognostic model we constructed may enable personalized treatment of BLCA.

Unraveling the structures, functions and mechanisms of epithelial membrane protein family in human cancers

Peripheral myelin protein 22 (PMP22) and epithelial membrane proteins (EMP-1, -2, and -3) belong to a small hydrophobic membrane protein subfamily, with four transmembrane structures. PMP22 and EMPs are widely expressed in various tissues and play important roles in cell growth, differentiation, programmed cell death, and metastasis. PMP22 presents its highest expression in the peripheral nerve and participates in normal physiological and pathological processes of the peripheral nervous system. The progress of molecular genetics has shown that the genetic changes of the PMP22 gene, including duplication, deletion, and point mutation, are behind various hereditary peripheral neuropathies. EMPs have different expression patterns in diverse tissues and are closely related to the risk of malignant tumor progression. In this review, we focus on the four members in this protein family which are related to disease pathogenesis and discuss gene mutations and post-translational modification of them. Further research into the interactions between structural alterations and function of PMP22 and EMPs will help understand their normal physiological function and role in diseases and might contribute to developing novel therapeutic tools.

Comprehensive FGFR3 alteration-related transcriptomic characterization is involved in immune infiltration and correlated with prognosis and immunotherapy response of bladder cancer

Background

Bladder cancer (BC) threatens the health of human beings worldwide because of its high recurrence rate and mortality. As an actionable biomarker, fibroblast growth factor receptor 3 (FGFR3) alterations have been revealed as a vital biomarker and associated with favorable outcomes in BC. However, the comprehensive relationship between the FGFR3 alteration associated gene expression profile and the prognosis of BC remains ambiguous.

Materials and Methods

Genomic alteration profile, gene expression data, and related clinical information of BC patients were downloaded from The Cancer Genomics database (TCGA), as a training cohort. Subsequently, the Weighted Gene Co-expression Network Analysis (WGCNA) was conducted to identify the hub modules correlated with FGFR3 alteration. The univariate, multivariate, and least absolute shrinkage and selection operator (LASSO) Cox regression analyses were used to obtain an FGFR3 alteration-related gene (FARG) prognostic signature and FARG-based nomogram. The receiver operating characteristic (ROC) curve analysis was used for evaluation of the ability of prognosis prediction. The FARG signature was validated in four independent datasets, namely, GSE13507, GSE31684, GSE32548, and GSE48075, from Gene Expression Omnibus (GEO). Then, clinical feature association analysis, functional enrichment, genomic alteration enrichment, and tumor environment analysis were conducted to reveal differential clinical and molecular characterizations in different risk groups. Lastly, the treatment response was evaluated in the immunotherapy-related dataset of the IMvigor210 cohort and the frontline chemotherapy dataset of GSE48276, and the chemo-drug sensitivity was estimated via Genomics of Drug Sensitivity in Cancer (GDSC).

Results

There were a total of eleven genes (CERCAM, TPST1, OSBPL10, EMP1, CYTH3, NCRNA00201, PCDH10, GAP43, COLQ, DGKB, and SETBP1) identified in the FARG signature, which divided BC patients from the TCGA cohort into high- and low-risk groups. The Kaplan–Meier curve analysis demonstrated that BC patients in the low-risk group have superior overall survival (OS) than those in the high-risk group (median OS: 27.06 months vs. 104.65 months, p < 0.0001). Moreover, the FARG signature not only showed a good performance in prognosis prediction, but also could distinguish patients with different neoplasm disease stages, notably whether patients presented with muscle invasive phenotype. Compared to clinicopathological features, the FARG signature was found to be the only independent prognostic factor, and subsequently, a FARG-based prognostic nomogram was constructed with better ability of prognosis prediction, indicated by area under ROC curve (AUC) values for 1-, 3-, and 5-year OS of 0.69, 0.71, and 0.79, respectively. Underlying the FARG signature, multiple kinds of metabolism- and immune-related signaling pathways were enriched. Genomic alteration enrichment further identified that FGFR3 alterations, especially c.746C>G (p.Ser249Cys), were more prevalent in the low-risk group. Additionally, FARG score was positively correlated with ESTIMATE and TIDE scores, and the low-risk group had abundant enrichment of plasma B cells, CD8+ T cells, CD4+ naive T cells, and helper follicular T cells, implying that patients in the low-risk group were likely to make significant responses to immunotherapy, which was further supported by the analysis in the IMvigor210 cohort as there was a significantly higher response rate among patients with lower FARG scores. The analysis of the GDSC database finally demonstrated that low-risk samples were more sensitive to methotrexate and tipifarnib, whereas those in the high-risk group had higher sensitivities in cisplatin, docetaxel, and paclitaxel, instead.

Conclusion

The novel established FARG signature based on a comprehensive FGFR3 alteration-related transcriptomic profile performed well in prognosis prediction and was also correlated with immunotherapy and chemotherapy treatment responses, which had great potential in future clinical applications.

A Novel Type I Interferon Primed Dendritic Cell Subpopulation in TREX1 Mutant Chilblain Lupus Patients

Heterozygous TREX1 mutations are associated with monogenic familial chilblain lupus and represent a risk factor for developing systemic lupus erythematosus. These interferonopathies originate from chronic type I interferon stimulation due to sensing of inadequately accumulating nucleic acids. We here analysed the composition of dendritic cell (DC) subsets, central stimulators of immune responses, in patients with TREX1 deficiency. We performed single-cell RNA-sequencing of peripheral blood DCs and monocytes from two patients with familial chilblain lupus and heterozygous mutations in TREX1 and from controls. Type I interferon pathway genes were strongly upregulated in patients. Cell frequencies of the myeloid and plasmacytoid DC and of monocyte populations in patients and controls were similar, but we describe a novel DC subpopulation highly enriched in patients: a myeloid DC CD1C⁺ subpopulation characterized by the expression of LMNA, EMP1 and a type I interferon- stimulated gene profile. The presence of this defined subpopulation was confirmed in a second cohort of patients and controls by flow cytometry, also revealing that an increased percentage of patient's cells in the subcluster express costimulatory molecules. We identified a novel type I interferon responsive myeloid DC subpopulation, that might be important for the perpetuation of TREX1-induced chilblain lupus and other type I interferonopathies.

Three Prognostic Biomarkers Correlate with Immune Checkpoint Blockade Response in Bladder Urothelial Carcinoma

Aim

We aim to develop a signature that could accurately predict prognosis and evaluate the response to immune checkpoint blockade (ICB) in bladder urothelial carcinoma (BLCA).

Methods

Based on comprehensive analysis of public database, we identified prognosis-related hub genes and investigated their predictive values for the ICB response in BLCA.

Results

Among 69 common DEGs, three genes (AURKA, BIRC5, and CKS1B) were associated with poor prognosis, and which were related to histological subtypes, TP53 mutation status, and the C2 (IFN-gamma dominant) subtype. Three genes and their related risk model can effectively predict the response of immunotherapy. Their related drugs were identified through analysis of drug bank database.

Conclusions

Three genes could predict prognosis and evaluate the response to ICB in BLCA.

A novel 6-gene signature derived from tumor-infiltrating T cells and neutrophils predicts survival of bladder urothelial carcinoma

Intratumoral immune cells were reported to be associated with prognosis of bladder urothelial carcinoma (BUC). However, the role of immune cells related genes in BUC prognosis is less well defined. In the study, we analyzed data retrieved from the Cancer Genome Atlas database and found higher neutrophils and lower T cells infiltration in BUC tumor tissues were significantly correlated with patients’ worse prognosis. Additionally, the expression levels of 164 genes were significantly correlated with T cells and neutrophils proportions. A Cox proportional-hazards model integrating 6 genes expression (EMP1, RASGRP4, HSPA1L, AHNAK, SLC1A6, and PRSS8) was identified. The 6-gene signature outperformed other clinical factors in risk prediction and was an independent prognostic factor for BUC. The findings were further conformed in three Gene Expression Omnibus datasets (n=331) and Jiangsu Province Hospital cohort (n = 46). Gene set enrichment analysis revealed that the model was highly involved in some immune-related pathways. A comprehensive nomogram combining the model and other clinical parameters was finally constructed to facilitate clinical application. In conclusion, a T cell and neutrophil-associated 6-gene prognostic model was identified for the survival prediction of BUC patients.

Prognostic Relevance of Expression of EMP1, CASP1, and NLRP3 Genes in Pediatric B-Lineage Acute Lymphoblastic Leukemia

Glucocorticoid (GC), such as prednisolone, is an essential component of multidrug chemotherapy regimen for pediatric acute lymphoblastic leukemia (ALL). Resistance to GC in leukemia cells is associated with disease progression and poor prognosis. Despite the extensive use of GC for many years, molecular mechanisms underlying its resistance in ALL have not been fully uncovered. Recent studies have shown a potential role of EMP1, CASP1, and NLRP3 genes in prednisolone response. In this study on 148 pediatric B-ALL patients, we studied these three genes to assess their association with prednisolone response measured by day 8 blast count after 7 days of induction therapy with prednisolone. Intriguingly, ALL samples exhibited higher expression of EMP1 along with a low expression of CASP1 and NLRP3 compared to disease free normal bone marrow collected from patients with solid tumors. Among the three analyzed genes, only EMP1 was found to be overexpressed in prednisolone poor responders (p=0.015). Further, a comparison of gene expression between cytogenetic subtypes revealed higher expression of EMP1 in BCR-ABL subtype. Expression of EMP1 in multiple gene expression datasets was used for gene set enrichment analysis, which revealed TNF-α, IL-2-STAT5 signaling, inflammatory responses and hypoxia as the major positively associated pathways and E2F targets as negatively associated pathways. Interestingly, the clinical remission rate was higher in CASP1 high patients (p=0.048). In univariate survival analysis, higher EMP1 expression was associated with poor prognostic measures while higher expression of NLRP3 and CASP1 was associated with better prognostic measures in our data. Further, multivariate analysis revealed an independent association of high CASP1 and NLRP3 with a better prognosis. This study strengthens the available evidence that mRNA expression of EMP1, CASP1, and NLRP3 may serve as potential biomarkers for risk stratification of pediatric B-ALL patients.

Identification of four methylation-driven genes as candidate biomarkers for monitoring single-walled carbon nanotube-induced malignant transformation of the lung

Long-term exposure to carbon nanotubes (CNTs) has been reported to induce malignant transformation. This study aimed to screen candidate biomarkers for monitoring occupational workers to prevent the development of lung cancer. mRNA (GSE56104) and methylation (GSE153246) profiles of lung epithelial BEAS-2B cells exposed to malignant transformation dose of single-walled CNTs or control medium were downloaded from Gene Expression Omnibus database. A total of 1513 differentially expressed genes (DEGs) and 912 differentially methylated genes (DMGs) were identified using LIMMA method. The weighted correlation network analysis identified blue and turquoise modules were associated with malignant transformation of BEAS-2B cells, 124 DMGs of which were overlapped with DEGs. The mRNA and methylation levels of four methylation-driven DEGs were validated in both lung adenocarcinoma (LUAD) and squamous cell carcinomas (LUSC) of The Cancer Genome Atlas dataset and they were associated with overall survival of LUAD patients. Downregulation of PXMP4 and MCOLN2, while upregulation of MET was confirmed in both LUSC and LUAD via Human Protein Atlas analysis. PXMP4 and MET protein levels were also supported in the proteomic analysis of LUAD. Receiver operating characteristic (ROC) curve analysis showed the combination of four genes may be the optimal biomarker for predicting lung cancer, with the area under ROC curve >0.9. Function analysis revealed BARX2 may interact with CCND1 to regulate cell cycle; MET and PXMP4/MCOLN2 may positively correlate with CCR5/IL-6 or GATA3/HLA-DPB1/HLA-DPA1 to involve immune regulation. In conclusion, these four methylation-driven genes may be candidate prognostic and diagnostic biomarkers for single-walled CNT-related lung cancer.