Stromal Scores Research Articles

Tertiary lymphoid structures: Associated multiple immune cells and analysis their formation in hepatocellular carcinoma.

The prognostic value of immune cells in tertiary lymphoid structures (TLSs) remains unclear in hepatocellular carcinoma (HCC). Here, 59 of 145 patients had TLSs in training set, 48 of 120 patients had TLSs in testing set. Immunohistochemistry (IHC) were used to label CD3+ T cells, CD20+ B cells, CD8+ T cells, CD208+ dendritic cells, and CD21+ follicular dendritic cells in TLSs. High CD20+, CD208+, and CD8+ cell densities were favorable prognostic factors for overall survival (OS). High CD3+, CD20+, CD208+, and CD8+ cell densities were significantly associated with reduced early recurrence. TLSs were divided into three grades (A, B, and C) based on immune cell density. Patients with grade C or B had significantly improved OS. Patients with grade C had the lowest recurrence rate, followed by those with grade B, while patients with grade A had the highest recurrence rate. The stromal, immune, and ESTIMATE scores derived from the ESTIMATE package were significantly higher and tumor purity was significantly lower in patients with TLSs. Patients with TLSs had significantly higher relative numbers of memory B cells, plasma cells, CD8+ T cells, NK cells, and dendritic cells and lower relative numbers of Treg cells, macrophages, and M2 macrophages according to the CIBERSORT assessment. Bioinformatics analysis and experiments confirmed that KLRK1 and GZMA expression are associated TLSs formation and can predict TLSs existence. Grade B and grade C were favorable prognostic factors for OS and recurrence and could represent immune-active tumors.

The development and validation of a m6A-lncRNAs based prognostic model for overall survival in lung squamous cell carcinoma.

No biomarkers have been identified for the prognosis of lung squamous cell carcinoma (LUSC). Risk models based on m6A-lncRNAs help to predict survival in some cancers. However, very few studies have reported m6A-lncRNA risk models in LUSC. We aimed to construct a prognostic model based on m6A-lncRNAs in LUSC. The clinical and RNA-sequencing information of 504 LUSC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Prognostic m6A-lncRNAs were identified by a Pearson correlation analysis and univariate Cox regression analysis. The ConsensusClusterPlus algorithm was used to cluster the prognostic m6A-lncRNAs. The overall survival (OS) and clinicopathological characteristics of the 2 clusters were compared. A gene set enrichment analysis (GSEA) analysis was performed to analyze the genes enriched in the 2 clusters. A least absolute shrinkage and selection operator (LASSO) Cox regression analysis was used to construct the risk-score model. Two hundred and forty eight patients were randomly chosen from TCGA-LUSC cohort for the training set. The receiver operating characteristic (ROC) curve analysis was used to assess the predictive ability of the model. The clinical characteristics and OS in the high- and low-risk groups were compared. The independent prognostic value of the model was tested by Cox regression analyses. Thirteen m6A-lncRNAs were identified as prognostic lncRNAs and classified into cluster A and cluster B. The OS of patients in cluster A was better than that of patients in cluster B (P<0.001). Patients in cluster B had higher expressions of immune checkpoints. Immune score, stromal score, and ESTIMATE score were higher in cluster B (P<0.001). Seven of the 13 lncRNAs were used to construct the risk-score model. Patients in the high-risk group had a worse OS. ROC curves showed a under the curve (AUC) of 0.639 in the training set and 0.624 in the validation set. A high risk was associated with cluster B, a high immune score, and stage III-IV disease. Patients in the high-risk group had increased expressions of immune checkpoints. The Cox regression analyses showed that the risk-score model had independent prognostic value for OS. The risk-score model retained its prognostic value in different subgroups. The m6A-lncRNA risk-score model is an independent prognostic factor for OS in LUSC patients. However, the risk-score model need to be further tested clinically.

Oxidative stress genes in patients with esophageal squamous cell carcinoma: construction of a novel prognostic signature and characterization of tumor microenvironment infiltration

BackgroundOxidative stress plays an important role in the progression of various types of tumors. However, its role in esophageal squamous cell carcinoma (ESCC) has seldom been explored. This study aimed to discover prognostic markers associated with oxidative stress in ESCC to improve the prediction of prognosis and help in the selection of effective immunotherapy for patients.ResultsA consensus cluster was constructed using 14 prognostic differentially expressed oxidative stress-related genes (DEOSGs) that were remarkably related to the prognosis of patients with ESCC. The infiltration levels of neutrophils, plasma cells, and activated mast cells, along with immune score, stromal score, and estimated score, were higher in cluster 1 than in cluster 2. A prognostic signature based on 10 prognostic DEOSGs was devised that could evaluate the prognosis of patients with ESCC. Calculated risk score proved to be an independent clinical prognostic factor in the training, testing, and entire sets. P53 signaling pathway was highly enriched in the high-risk group. The calculated risk score was positively related to the infiltration levels of resting mast cells, memory B cells, and activated natural killer (NK) cells and negatively associated with the infiltration levels of M1 and M2 macrophages. The relationship between clinical characteristics and risk score has not been certified. The half-maximal inhibitory concentration (IC50) values for sorafenib and gefitinib were lower for patients in the low-risk group.ConclusionOur prognostic signature based on 10 prognostic DEOSGs could predict the disease outcomes of patients with ESCC and had strong clinical value. Our study improves the understanding of oxidative stress in tumor immune microenvironment (TIME) and provides insights for developing improved and efficient immunotherapy strategies.

IL-2 Combined with IL-15 Enhanced the Expression of NKG2D Receptor on Patient Autologous NK Cells to Inhibit Wilms' Tumor via MAPK Signaling Pathway.

Objective The dysfunction of immune surveillance, a hot spot in cancer research, could lead to the occurrence and development in multicancers. However, the potential mechanisms of immunity in Wilms' tumor (WT) remain unclear on Wilms' tumor (WT). In this study, we aim to investigate the immune cell in WT and explore the underlying treatment strategy. Method We quantified stromal and immune scores by using ESTIMATE algorithm based on gene expression matrix of WT patients in TCGA and GEO databases. Different expression genes (DEGs) and functional enrichments were analyzed by R studio and DAVID tools. Flow cytometry, immunofluorescence staining, ELISA assay, and qRT-PCR were used for detecting the NK cells, cytotoxic cytokines (INF-γ, PRF, and GZMB), and NK cell receptor expression, respectively. WT patient autologous NK cells were stimulated by IL-2 and IL-15, and the cytotoxicity of NK cells against WT cell lines was detected by LDH assay. Western blot experiment was used for measuring the MAPK signaling pathway protein maker in NK cells. Results ESTIMATE indicated that WT tissue had a lower immune score than adjacent kidney tissue. Meanwhile, the low immune score group was associated with poorly outcomes. DEG functional enrichment analysis showed that NK cell-mediated cytotoxicity was significantly different in low and high immune score groups. Although few of proportion of NK cells in WT patients were increased, most of that were significantly lower than normal children. Moreover, the proportion of NK cells and the expression level of INF-γ, PRF, and GZMB in WT tissue were lower than adjacent kidney tissue. Importantly, the NKG2D expression level of NK cells was significantly lower in WT tissue. Furthermore, in vitro, compared with uncultured NK cells, IL-2 and IL-15 could effectively enhance the cytotoxicity of NK cells on killing the WT cell lines. The FACS and WB results showed that the NKG2D and p-PI3K ratio PI3K, MEK1/2, and p-ERK1/2 ratio ERK1/2 were significantly increased in IL-2 and IL15 group compared with uncultured groups. Conclusion The abnormal NK cell-mediated cytotoxicity may cause the occurrence of WT. Costimulation of WT patients autologous NK cells could effectively enhance the antitumor reaction which involved in activation of NKG2D-mediated MAPK signaling pathway.

Leucine zipper protein 2 serves as a prognostic biomarker for prostate cancer correlating with immune infiltration and epigenetic regulation

BackgroundWe sought to determine whether leucine zipper protein 2 (LUZP2) could benefit men with prostate cancer (PCa) undergoing radical radiotherapy (RT) or prostatectomy (RP). MethodsAnalysis was done on differentiating expression, clinical prognosis, co-expressed genes, immune infiltration, and epigenetic changes. All of our analyses were done using the R software (version 3.6.3) and the appropriate packages. ResultsIn terms of PCa, tumor samples expressed LUZP2 more than normal samples did. In the TCGA database and GSE116918, we found that LUZP2 was the only independent risk factor for PCa. The shared enriched pathways for patients undergoing RP or RT were cell-cell adhesion, regulation of filopodium assembly, and extracellular matrix containing collagen. With the exception of TNFRSF14, we discovered that LUZP2 was negatively correlated with 21 immune checkpoints in PCa patients receiving RT. We found a significant inverse relationship between LUZP2 expression and the tumor immune environment, which included B cells, CD4+ T cells, neutrophils, macrophages, dendritic cells, stromal score, immune score, and estimate score, in patients receiving RP or RT. Additionally, tumor purity was positively correlated with LUZP2. We found that the drug bortezomib may be susceptible to the LUZP2. DNA methylation was significantly associated with the mRNA expression of LUZP2 in PCa patients from the TCGA database, and LUZP2 methylation was positively correlated with immune cells. The proliferative activity of various PCa cells, which correlated to different stages of this disease, was also found to be significantly reduced by LUZP2 reduction, according to the results of our experimental work. ConclusionsWe proposed a relatively comprehensive understanding of the roles of LUZP2 on PCa from the fresh perspective of senescence.

APOL4, a Novel Immune-Related Prognostic Biomarker for Glioma.

Glioma is the common, most aggressive and poorest prognostic tumor type in the brain. More and more biomarkers associated with glioma treatment, prognosis, and immunity are being discovered. Here, we aimed to explore the underlying biological functions and prognostic predictive value of Apolipoprotein L4 (APOL4) in glioma. We downloaded the expression data of APOL4 and clinical information from several databases and used R software for preprocessing. The clinical significance of APOL4 in a glioma outcome was explored by the Cox regression analysis and Kaplan–Meier survival analysis. In addition, immune infiltrates and microenvironmental indicators were assessed by CIBERSORT and TIMER. GO and KEGG analyses were used to analyze the potential functions of APOL4 in gliomas. APOL4 expression was increased in glioma specimens compared to normal tissues and correlated dramatically with the WHO grade. A survival analysis showed a shorter overall survival (OS) in glioma patients with APOL4 overexpression, and a Cox regression analysis showed that APOL4 was an independent prognostic factor for the OS of glioma patients. GSEA, GO, and KEGG enrichment analyses showed remarkable enrichment in immune-related pathways. APOL4 expression was positively correlated with immune infiltration (including DC cells, neutrophils, CD8+ T cells, B cells, macrophages, CD4+ T cells, etc.) and microenvironmental parameters (including immune, stromal, and ESTIMATE scores) in gliomas. Glioma patients with a higher expression of APOL4 may be more sensitive to immune checkpoint inhibitors (ICI). In conclusion, these findings suggest that APOL4 is associated with the tumor grade and immune infiltrates; APOL4 may be a new and potential biomarker for therapeutic and prognostic evaluations that may further suggest the therapeutic efficacy of immunotherapy.

Signature construction and molecular subtype identification based on cuproptosis-related genes to predict the prognosis and immune activity of patients with hepatocellular carcinoma.

BackgroundHepatocellular carcinoma (HCC) is one of the most common malignancies in the world, with high incidence, high malignancy, and low survival rate. Cuproptosis is a novel form of cell death mediated by lipoylated TCA cycle proteins-mediated novel cell death pathway and is highly associated with mitochondrial metabolism. However, the relationship between the expression level of cuproptosis-related genes (CRGs) and the prognosis of HCC is still unclear.MethodsCombining the HCC transcriptomic data from The Cancer Genome Atlas(TCGA) and Gene Expression Omnibus (GEO) databases, we identified the differentially expressed cuproptosis-related genes (DECRGs) and obtained the prognosis-related DECRGs through univariate regression analysis.LASSO and multivariate COX regression analyses of these DECRGs yielded four genes that were used to construct the signature. Next, we use ROC curves to evaluate the performance of signatures. The tumor microenvironment, immune infiltration, tumor mutation load, half-maximum suppression concentration, and immunotherapy effects were also compared between the low-risk and high-risk groups. Finally, we analyzed the expression level, prognosis, and immune infiltration correlation on the four genes that constructed the model.ResultsFour DECRGs s were used to construct the signature. The ROC curves indicated that signature can better assess the prognosis of HCC patients. Patients were grouped according to the signature risk score. Patients in the low-risk group had a significantly longer survival time than those in the high-risk group. Furthermore, the tumor mutation burden (TMB) values were associated with the risk score and the higher-risk group had a higher proportion of TP53 mutations than the low-risk group.ESTIMATE analysis showed significant differences in stromal scores between the two groups.N6-methyladenosine (m6A) and multiple immune checkpoints were expressed at higher levels in the high-risk group. Then, we found that signature score correlated with chemotherapeutic drug sensitivity and immunotherapy efficacy in HCC patients. Finally, we further confirmed that the four DECRGs genes were associated with the prognosis of HCC through external validation.ConclusionsWe studied from the cuproptosis perspective and developed a new prognostic feature to predict the prognosis of HCC patients. This signature with good performance will help physicians to evaluate the overall prognosis of patients and may provide new ideas for clinical decision-making and treatment strategies.

A pan-cancer analysis of collagen VI family on prognosis, tumor microenvironment, and its potential therapeutic effect

BackgroundCollagen VI family (COL6A) is a major member of extracellular matrix protein. There is accumulating evidence that COL6A is involved in tumorigenesis and tumor progression. In this study, we performed a systematic analysis of COL6A in pan-cancer based on their molecular features and clinical significance.MethodsBased on updated public databases, we integrated several bioinformatics analysis methods to investigate the expression levels of COL6A as well as the relationship between their expression and patient survival, immune subtypes, tumor microenvironment, stemness scores, drug sensitivity, and DNA methylation.ResultsThe expression levels of COL6A members varied in different cancers, suggesting their expression was cancer-dependent. Among COL6A members, COL6A1/2/3 were predicted poor prognosis in specific cancers. Furthermore, COL6A1/2/3 expression levels revealed a clear correlation with immune subtypes, and COL6A1/2/3 were associated with tumor purity, that is, gene expression levels were generally higher in tumors with higher stromal scores and immune scores. COL6A1/2/3 had a significantly negative correlation with RNA stemness scores, and meanwhile they were also related to DNA stemness scores in different degrees. In addition, the expression of COL6A1/2/3 was significantly related to drug sensitivity of cancer cells. Finally, our study revealed that COL6A1/2/3 expression was mainly negatively correlated with gene methylation, and the methylation levels showed remarkable differences in various cancers.ConclusionsThese findings highlight both the similarities and differences in the molecular characteristics of COL6A members in pan-cancer, and provide comprehensive insights for further investigation into the mechanism of COL6A.

The PDGF Family Is Associated with Activated Tumor Stroma and Poor Prognosis in Ovarian Cancer.

The initiation and progression of cancer depend on the genetic alterations inherent in cancer cells, coupled with the mutual interplay of cancer cells with the surrounding tumor stroma. The platelet-derived growth factor (PDGF) family, as a mesenchymal growth factor, was involved in tumor progression by affecting the surrounding tumor stroma in some cancer types. However, the association of the PDGF family with the ovarian cancer stroma remains elusive. In our study, we first explored the expression pattern of the PDGF family using RNA expression profiles from public databases. We found that the PDGF family was highly expressed in tumor stroma compared with the corresponding epithelial components of ovarian cancer. In particular, PDGF receptors were weakly expressed in ovarian cancer tissues compared with the respective normal tissues; even in tumor mass, PDGF receptors were predominantly expressed by tumor stroma rather than ovarian cancer cells. Importantly, functional enrichment analyses and correlation analyses revealed that the PDGF family was strongly associated with activated stromal scores in ovarian cancer, including higher stromal scores, enriched pathways related to the extracellular matrix (ECM) organization and remodeling, elevated cancer-associated fibroblasts (CAFs) infiltration, and increased tumor-associated macrophages (TAMs) infiltration, especially macrophage M2. Besides, the positive correlations of the PDGF family with CAFs infiltration and macrophage M2 infiltration were observed in other various cancer types. Of note, the PDGF family was also involved in tumor progression-related pathways, such as transforming growth factor β (TGF-β) signaling, epithelial-mesenchymal transition (EMT), angiogenesis, and phosphatidylinositol 3-kinase-Akt (PI3K-Akt) signaling. Higher expressions of PDGF receptors were also observed in ovarian cancer patients with venous or lymphatic invasion. Furthermore, we uncovered the prognostic prediction of the PDGF family in ovarian cancer and constructed a PDGF family-based risk prognosis model with a hazard ratio of 1.932 (95%confidence interval (CI) = 1.27–2.95) and P value < 0.01 (AUC = 0.782, 0.752 for 1 year and 2 years, respectively). Taken together, we demonstrated that ovarian cancers with high PDGF family expression biologically exhibit malignant progression behaviors as well as poor clinical survival, which is attributed to the activated tumor stroma in ovarian cancer.

204. THE TUMOUR IMMUNE MICROENVIRONMENT IN OESOPHAGEAL ADENOCARCINOMA HAS PROGNOSTIC SIGNIFICANCE

Abstract Oesophageal adenocarcinoma (OAC) is a deadly disease with an increasing incidence globally. Treatment outcomes with traditional therapy have largely plateaued and responses to immunotherapy are modest at best, necessitating the need for better biomarker driven selection. We aimed to unravel the tumour neoantigen landscape and immune microenvironment in OAC patients to aid improved patient selection and inform novel immunotherapy trials. To characterise the tumour immune microenvironment and neoantigen landscape of OACs, we performed DNA sequencing (n = 117) and RNA sequencing (n = 115) on biopsies taken at pre-treatment endoscopy. Using expression-based computational methods we analysed transcriptomic data to profile infiltration levels of 28 immune cell populations and their functional orientation, as well as stromal signatures and immune checkpoint molecules. TCGA data was used for as a validation cohort. Tumour neoantigens were predicted using the pVAC-Seq pipeline. Using an immune based classification based on the tumour microenvironment composition, we identified three distinct phenotypes; immune-enriched (IE), heterogeneously-infiltrated (HI), and immune-cold (IC). The IE group showed improved survival compared to both HI and IC, with HI showing the worst survival. The HI-group showed no difference in stromal scores to the IE group, but showed significantly decreased adaptive-immune cell infiltration, indicating that an immunosuppressive stromal compartment may be driving outcomes for these patients. No difference was seen in total or quality neoantigen load between groups, but high correlation with antigen processing machinery is seen. Our analysis expands the knowledge of the relatively unknown tumour immune microenvironment of OAC. We have identified three immune TME-phenotypes with prognostic utility with current standard of care therapies; which may also act as potential immunotherapy biomarkers. This is being explored further in ongoing immune microenvironment research and will guide future translational studies.

Role of ARRB1 in prognosis and immunotherapy: A Pan-Cancer analysis.

Background: β-arrestin1 (ARRB1), was originally identified as a multifunctional adaptor protein. Although ARRB1 has recently been shown to also play an important role in tumor growth, metastasis, inflammation, and immunity, its relationship with distinct tumor types and the tumor immune microenvironment remains unclear. Methods: We analyzed the ARRB1 expression profile and clinical characteristics in 33 cancer types using datasets from The Cancer Genome Atlas (TCGA) database. Clinical parameters such as patient survival, tumor stage, age, and gender were used to assess the prognostic value of ARRB1. The Human Protein Atlas (HPA) database was used to explore ARRB1 protein expression data. ESTIMATE and CIBERSORT algorithms were performed to assess immune infiltration. Furthermore, putative correlations between ARRB1 and tumor-infiltrating immune cells, the signatures of T-cell subtypes, immunomodulators, the tumor mutation burden (TMB), Programmed cell death ligand 1 (PD-L1), and microsatellite instability (MSI) were also explored. Gene functional enrichment was determined using GSEA. GSE40435 and GSE13213 cohorts were used to validate the correlation of ARRB1 with KIRC and LUAD clinicopathological parameters. Finally, the relationship between ARRB1 and immunotherapeutic responses was assessed using three independent immunotherapy cohorts, namely, GSE67501, GSE168204, and IMvigor210. Results: We found that ARRB1 expression levels were lower in 17 tumor tissues than in the corresponding normal tissues. We further found that ARRB1 expression was significantly correlated with tumor stage in BRCA, ESCA, KIRC, TGCT, and THCA, while in some tumors, particularly KIRC and LUAD, ARRB1 expression was associated with better prognosis. ARRB1 expression was also positively correlated with the stromal score or the immune score in some tumors. Regarding immune cell infiltration, ARRB1 expression in DLBC was positively correlated with M1 macrophage content and negatively correlated with B-cell infiltration. Additionally, there was a broad correlation between ARRB1 expression and three classes of immunomodulators. Furthermore, high ARRB1 expression levels were significantly correlated with some tumor immune-related pathways. Finally, ARRB1 expression was significantly associated with MSI, PD-L1, and TMB in some tumors and with the efficacy of immune checkpoint inhibitors (ICIs) in melanoma. Conclusion: ARRB1 has prognostic value in malignant tumors, especially in KIRC and LUAD. At the same time, ARRB1 was closely correlated with the tumor immune microenvironment and indicators of immunotherapy efficacy, indicating its great potential as a reliable marker for predicting the efficacy of immunotherapy.

Characterization of cancer-related fibroblasts (CAF) in hepatocellular carcinoma and construction of CAF-based risk signature based on single-cell RNA-seq and bulk RNA-seq data.

BackgroundCancer-associated fibroblasts (CAFs) are involved in tumor growth, angiogenesis, metastasis, and resistance to therapy. We sought to explore the CAFs characteristics in hepatocellular carcinoma (HCC) and establish a CAF-based risk signature for predicting the prognosis of HCC patients.MethodsThe signal-cell RNA sequencing (scRNA-seq) data was obtained from the GEO database. Bulk RNA-seq data and microarray data of HCC were obtained from the TCGA and GEO databases respectively. Seurat R package was applied to process scRNA-seq data and identify CAF clusters according to the CAF markers. Differential expression analysis was performed to screen differentially expressed genes (DEGs) between normal and tumor samples in TCGA dataset. Then Pearson correlation analysis was used to determine the DEGs associated with CAF clusters, followed by the univariate Cox regression analysis to identify CAF-related prognostic genes. Lasso regression was implemented to construct a risk signature based on CAF-related prognostic genes. Finally, a nomogram model based on the risk signature and clinicopathological characteristics was developed.ResultsBased on scRNA-seq data, we identified 4 CAF clusters in HCC, 3 of which were associated with prognosis in HCC. A total of 423 genes were identified from 2811 DEGs to be significantly correlated with CAF clusters, and were narrowed down to generate a risk signature with 6 genes. These six genes were primarily connected with 39 pathways, such as angiogenesis, apoptosis, and hypoxia. Meanwhile, the risk signature was significantly associated with stromal and immune scores, as well as some immune cells. Multivariate analysis revealed that risk signature was an independent prognostic factor for HCC, and its value in predicting immunotherapeutic outcomes was confirmed. A novel nomogram integrating the stage and CAF-based risk signature was constructed, which exhibited favorable predictability and reliability in the prognosis prediction of HCC.ConclusionCAF-based risk signatures can effectively predict the prognosis of HCC, and comprehensive characterization of the CAF signature of HCC may help to interpret the response of HCC to immunotherapy and provide new strategies for cancer treatment.

Combination of Tumor Mutational Burden and DNA Damage Repair Gene Mutations with Stromal/Immune Scores Improved Prognosis Stratification in Patients with Lung Adenocarcinoma.

Background Both the tumor environment and the genomic landscape of lung cancer may shape patient responses to treatments, including immunotherapy, but their joint impacts on lung adenocarcinoma (LUAD) prognosis are underexplored. Methods RNA sequencing data and whole-exome sequencing results were downloaded from the TCGA database, and only LUAD-related data were included in this study. Based on gene expression data, the ESTIMATE algorithm was used to estimate stromal and immune scores, and CIBERSORT analysis was used for quantification of the relative abundances of immune cells. Somatic mutations were used for calculating tumor mutation burden (TMB). Specific mutations in genes involved in DNA damage repair (DDR) pathways were identified. The individual and joint associations of stromal and immune score, TMB, and DDR gene mutations with 5-year survival were analyzed by the Kaplan–Meier method and multivariate Cox model. Results LUAD patients with a high (>highest 25%) stromal or immune score had prolonged survival as compared to those with a low (<lowest 25%) score (log-rank P=0.05 and 0.035, respectively). Patients with both high stromal and immune scores had the most favorable survival. Although the survival differences between patients with high (>highest 25%) and low (<lowest 25%) TMB, or between patients with mutant- and wild-type DDR genes were not statistically significant, a survival benefit from high TMB or DDR gene mutations was observed in patients with high stromal or immune scores. Conclusion A comprehensive evaluation of transcriptomic signatures and genomic biomarkers may provide a novel avenue for improving prognosis stratification in LUAD.

Comprehensive analyses of a tumor-infiltrating lymphocytes-related gene signature regarding the prognosis and immunologic features for immunotherapy in bladder cancer on the basis of WGCNA.

Tumor-infiltrating lymphocyte (TIL) is a class of cells with important immune functions and plays a crucial role in bladder cancer (BCa). Several studies have shown the clinical significance of TIL in predicting the prognosis and immunotherapy efficacy. TIL-related gene module was screened utilizing weighted gene coexpression network analysis. We screened eight TIL-related genes utilizing univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis, and multivariate Cox regression analysis. Then, we established a TIL-related signature model containing the eight selected genes and subsequently classified all patients into two groups, that is, the high-risk as well as low-risk groups. Gene mutation status, prognosis, immune cell infiltration, immune subtypes, TME, clinical features, and immunotherapy response were assessed among different risk subgroups. The results affirmed that the TIL-related signature model was a reliable predictor of overall survival (OS) for BCa and was determined as an independent risk factor for BCa patients in two cohorts. Moreover, the risk score was substantially linked to age, tumor staging, TNM stage, and pathological grade. And there were different mutational profiles, biological pathways, immune scores, stromal scores, and immune cell infiltration in the tumor microenvironment (TME) between the two risk groups. In particular, immune checkpoint genes’ expression was remarkably different between the two risk groups, with patients belonging to the low-risk group responding better to immune checkpoint inhibition (ICI) therapy. In conclusion, our study demonstrates that the TIL-related model was a reliable signature in anticipating prognosis, immune status, and immunotherapy response, which can help in screening patients who respond to immunotherapy.

Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients.

Background: We aimed to explore the role of mitochondrial aldehyde dehydrogenase 2 (ALDH2) in prostate cancer (PCa) patients and provide insights into the tumor immune microenvironment (TME) for those patients undergoing radical radiotherapy. Methods: We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish network of competing endogenous RNAs (ceRNAs). Results: Downregulation of ADLH2 was significantly associated with higher risk of BCR-free survival (HR: 0.40, 95%CI: 0.24–0.68, p = 0.001) and metastasis-free survival (HR: 0.21, 95%CI: 0.09–0.49, p = 0.002). Additionally, ALDH2 repression contributed to significantly shorter BCR-free survival in the TCGA database (HR: 0.55, 95%CI: 0.33–0.93, p = 0.027). For immune checkpoints, patients that expressed a higher level of CD96 had a higher risk of BCR than their counterparts (HR: 1.79, 95%CI: 1.06–3.03, p = 0.032), as well as NRP1 (HR: 2.18, 95%CI: 1.29–3.69, p = 0.005). In terms of the TME parameters, the spearman analysis showed that ALDH was positively associated with B cells (r: 0.13), CD8+ T cells (r: 0.19), neutrophils (r: 0.13), and macrophages (r: 0.17). Patients with higher score of neutrophils (HR: 1.75, 95%CI: 1.03–2.95, p = 0.038), immune score (HR: 1.92, 95%CI: 1.14–3.25, p = 0.017), stromal score (HR: 2.52, 95%CI: 1.49–4.26, p = 0.001), and estimate score (HR: 1.81, 95%CI: 1.07–3.06, p = 0.028) had higher risk of BCR than their counterparts. Our ceRNA network found that PART1 might regulate the expression of ALDH via has-miR-578 and has-miR-6833-3p. Besides, PHA-793887, PI-103, and piperlongumine had better correlations with ALDH2. Conclusions: We found that ALDH2 might serve as a potential biomarker predicting biochemical recurrence for PCa patients.

Prognostic and immunotherapeutic significance of mannose receptor C type II in 33 cancers: An integrated analysis.

Background: The type 2 mannose receptor C (MRC2) is involved in tumor biological processes and plays a new role in the remodeling of the extracellular matrix turnover. Previous studies have demonstrated MRC2 expression profiling and prognostic relevance in some tumor types. However, the clinical and immunotherapeutic value of MRC2 in pan-cancers remains controversial. Our study aimed to evaluate MRC2 expression pattern, clinical characteristics and prognostic significance in 33 cancers, explore the relationship between MRC2 and immune-related characteristics, and assess the prediction of MRC2 for the immunotherapeutic response. Methods: Transcriptional and clinical data of 33 cancers were downloaded from The Cancer Genome Atlas database (TCGA) database and two independent immunotherapeutic cohorts were obtained from GSE67501 and the IMvigor210 study. Next, patients stratified by MRC2 expression levels were displayed by Kaplan-Meier plot to compare prognosis-related indexes. Meanwhile, immune infiltrates of different cancers were estimated by tumor immune estimation resources (TIMER) and CIBERSORT. The ESTIMATE algorithm was used to estimate the immune and stromal scores in tumor tissues. MRC2 expression and immunological modulators, including immune inhibitors, immune stimulators, and MHC molecules, were screened through the TISIDB portal. Gene-set enrichment analysis analyses were performed to explore the underlying biological process of MRC2 across different cancers. The immunotherapeutic response prediction was performed in two independent cohorts (GSE78220: metastatic melanoma with pembrolizumab treatment and IMvigor210: advanced urothelial cancer with atezolizumab intervention). Results: MRC2 is expressed differently in many cancers and has been shown to have potential prognostic predicting significance. MRC2 was significantly associated with immune cell infiltration, immune modulators, and immunotherapeutic markers. Notably, the immunotherapeutic response group was associated with lower MRC2 expression in metastatic melanoma and advanced urothelial carcinoma cohort. Conclusion: This study demonstrated that MRC2 could be a prognostic indicator for certain cancer and is critical for tumor immune microenvironments. MRC2 expression level may influence and predict immune checkpoint blockade response as a potential indicator.

Identification of senescence-related molecular subtypes and key genes for prostate cancer.

We identified distinct senescence-related molecular subtypes and critical genes among prostate cancer (PCa) patients undergoing radical prostatectomy (RP) or radical radiotherapy (RT). We conducted all analyses using R software and its suitable packages. Twelve genes, namely, secreted frizzled-related protein 4 (SFRP4), DNA topoisomerase II alpha (TOP2A), pleiotrophin (PTN), family with sequence similarity 107 member A (FAM107A), C-X-C motif chemokine ligand 14 (CXCL14), prostate androgen-regulated mucin-like protein 1 (PARM1), leucine zipper protein 2 (LUZP2), cluster of differentiation 38 (CD38), cartilage oligomeric matrix protein (COMP), vestigial-like family member 3 (VGLL3), apolipoprotein E (APOE), and aldehyde dehydrogenase 2 family member (ALDH2), were eventually used to subtype PCa patients from The Cancer Genome Atlas (TCGA) database and GSE116918, and the molecular subtypes showed good correlations with clinical features. In terms of the tumor immune environment (TME) analysis, compared with cluster 1, cancer-associated fibroblasts (CAFs) scored significantly higher, while endothelial cells scored lower in cluster 2 in TCGA database. There was a statistically significant correlation between both CAFs and endothelial cells with biochemical recurrence (BCR)-free survival for PCa patients undergoing RP. For the GSE116918 database, cluster 2 had significantly lower levels of CAFs and tumor purity and higher levels of stromal, immune, and Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) scores than cluster 1; in addition, patients with high levels of CAFs, stromal scores, immune scores, and ESTIMATE scores and low levels of tumor purity tended to suffer from BCR. Based on the median of differentially expressed checkpoints, high expression of CD96, hepatitis A virus cellular receptor 2 (HAVCR2), and neuropilin 1 (NRP1) in GSE116918 and high expression of CD160 and tumor necrosis factor (ligand) superfamily member 18 (TNFSF18) in TCGA database were associated with a significantly higher risk of BCR than their counterparts. In conclusion, we first constructed distinct molecular subtypes and critical genes for PCa patients undergoing RP or RT from the fresh perspective of senescence.

Unveiling the molecular features, relevant immune and clinical characteristics of SIGLEC15 in thyroid cancer.

The groundbreaking research work about SIGLEC15 has raised it as a potential promising target in cancer immunotherapy. Unfortunately, the role of SIGLEC15 in thyroid carcinoma (THCA) remains obscure. Public and home multi-omics data were collected to investigate the role of SIGLEC15 in THCA in our study. SIGLEC15 was upregulated in THCA tumor tissue compared to nontumor tissue in both mRNA and protein levels; gene set enrichment analysis (GSEA) results showed that high SIGLEC15 mRNA expression was positively correlated to many immune pathways. Results of the examination of immunological landscape characteristics displayed high SIGLEC15 mRNA expression that mainly positively correlated with a large number of cancer immunity immunomodulators and pathways. In addition, upregulation of SIGLEC15 was positively correlated with an enhanced immune score, stromal score, and estimate score. However, higher SIGLEC15 mRNA also met high immune exhausted status. The majority of CpG methylation sites negatively correlated with SIGLEC15 mRNA expression. Analysis of clinical characteristics supported increased SIGLEC15 expression that was positively correlated with more extrathyroid extension and lymph node metastasis. We observed different single nucleotide variant (SNV) and copy number variation (CNV) patterns in high and low SIGLEC15 mRNA expression subgroups; some vital DNA damage repair deficiency scores addressed a negative correlation with SIGLEC15 mRNA expression. We also found that some commonly used chemotherapy drugs might be suitable for different SIGLEC15 mRNA expression subgroups. This study highlighted the vital role of SIGLEC15 in THCA. Targeting SIGLEC15 may offer a potential novel therapeutic opportunity for THCA patients. However, the detailed exact cellular mechanisms of SIGLEC15 in THCA still needed to be elucidated by further studies.

A specific immune signature for predicting the prognosis of glioma patients with IDH1-mutation and guiding immune checkpoint blockade therapy.

Isocitrate dehydrogenase (IDH1) is frequently mutated in glioma tissues, and this mutation mediates specific tumor-promoting mechanisms in glioma cells. We aimed to identify specific immune biomarkers for IDH1-mutation (IDH1mt) glioma. The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) were used to obtain RNA sequencing data and clinical characteristics of glioma tissues, while the stromal and immune scores of TCGA glioma tissues were determined using the ESTIMATE algorithm. Differentially expressed genes (DEGs), the protein–protein interaction(PPI) network, and least absolute shrinkage and selection operator (LASSO) and Cox regression analyses were used to select hub genes associated with stroma and immune scores and the prognoses of patients and to construct the risk model. The practicability and specificity of the risk model in both IDH1mt and IDH1-wildtype (wtIDH1) gliomas in TCGA and CGGA were evaluated. Molecular mechanisms, immunological characteristics and benefits of immune checkpoint blockade therapy in glioma tissues with IDH1mt were analyzed using GSEA, immunohistochemical staining, CIBERSORT, and T-cell dysfunction and exclusion (TIDE) analysis. The overall survival rate for IDH1mt-glioma patients with high stroma/immune scores was lower than that for those with low stroma/immune scores. A total of 222 DEGs were identified in IDH1mt glioma tissues with high stroma/immune scores. Among them, 72 genes had interactions in the PPI network, while three genes, HLA-DQA2, HOXA3, and SAA2, were selected as hub genes and used to construct risk models classifying patients into high- and low-risk score groups, followed by LASSO and Cox regression analyses. This risk model showed prognostic value in IDH1mt glioma in both TCGA and CCGA; nevertheless, the model was not suitable for wtIDH1 glioma. The risk model may act as an independent prognostic factor for IDH1mt glioma. IDH1mt glioma tissues from patients with high-risk scores showed more infiltration of M1 and CD8 T cells than those from patients with low-risk scores. Moreover, TIDE analysis showed that immune checkpoint blockade(ICB) therapy was highly beneficial for IDH1mt patients with high-risk scores. The risk model showed specific potential to predict the prognosis of IDH1mt-glioma patients, as well as guide ICB, contributing to the diagnosis and therapy of IDH1mt-glioma patients.

Integrated Analysis of C16orf54 as a Potential Prognostic, Diagnostic, and Immune Marker across Pan-Cancer.

Chromosome 16 open reading frame 54 (C16orf54) is a protein coding gene, showing a biased expression in the bone marrow, lymph node, and 11 other tissues. Reports on the function of C16orf54 in the onset and development of tumours remain scarce. Clinical information and tumour expression profile data from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx) were utilized to determine the relationship between C16orf54 expression and prognosis, diagnosis, immune microenvironment, heterogeneity, and stemness across pan-cancer. The findings ascertained that C16orf54 was expressed at a low level in most cancers. Furthermore, C16orf54 could distinguish between cancer and normal tissues with high accuracy in most cancers, and the prognostic significance of low C16orf54 mRNA levels differs across cancers. C16orf54 expression was positively linked to the stromal, immune, and ESTIMATE scores. On the other hand, C16orf54 was reported to be negatively correlated with tumour purity in most cancers. Further, C16orf54 expression was positively correlated with immune cell infiltration and the expression of immune regulatory genes, including chemokines, receptors, major histocompatibility complexes, immune inhibitory, and immune stimulatory genes, in most cancers. Additionally, C16orf54 expression was significantly associated with tumour heterogeneity indicators, such as tumour mutation burden (TMB) and microsatellite instability (MSI), and was significantly correlated with DNAss and RNAss tumour stemness indicators. Moreover, Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis, as well as Gene Set Enrichment analysis (GSEA), revealed that C16orf54 expression was closely linked to the signalling pathways of immune cells and factors. The integrated analysis of C16orf54 indicates it as a potential prognostic, diagnostic, and immune marker, which could be adopted as a novel target for adjuvant immunotherapy across pan-cancer.