Papillary thyroid carcinoma with a high tumor mutation burden has a poor prognosis

BackgroundTumor mutation burden (TMB) as a prognostic marker for immunotherapy has shown prognostic value in many cancers. However, there is no systematic investigation on TMB in papillary thyroid carcinoma (PTC).MethodsBased on the somatic mutation data of 487 PTC patients from The Cancer Genome Atlas (TCGA), TMB was calculated, and we classified the samples into high-TMB (H-TMB) and low-TMB (L-TMB) groups. Bioinformatics methods were used to explore the characteristics and potential mechanism of TMB in PTC.ResultsHigh TMB predicts shorter progression-free survival (PFS) (P < 0.001). TMB was positively correlated with age, stage, tumor size, metastasis, the male sex and tall cell PTC. Compared to the L-TMB group, the H-TMB group presented with lower immune cell infiltration, a higher proportion of tumor-promoting immune cells (M0 macrophages, activated dendritic cells and monocytes) and a lower proportion of antitumor immune cells (M1 macrophages, CD8⁺ T cells and B cells). Additionally, the characteristics displayed by different TMB groups were not driven by critical driver mutations such as BRAF and RAS.ConclusionsPTC patients with high TMB have a worse prognosis. By stratifying PTC patients according to their TMB, advanced PTC patients who are candidates for immunotherapy could be selected.     

Less immune cell infiltration and worse prognosis after immunotherapy for patients with lung adenocarcinoma who harbored STK11 mutation

The STK11 mutation defined a special subtype for patients with lung adenocarcinoma. The cBioPortal data platform was applied to analyze STK11 mutation frequency and the relationship between STK11 mutation and immune prognostic markers. The TIMER database was used to analyze the relationship between STK11 mutation and immune cell infiltration. The survival difference for lung adenocarcinoma patients harbored STK11 mutation who received immunotherapy also used the cBioPortal database. The results showed that STK11 mutation co-occurrence more KRAS and KEAP1 mutation and fewer TP53 and EGFR mutation (all, P < 0.05); the patients harbored STK11 mutation had a lower expression of PDL1 (P = 0.002), higher TMB score (P = 0.002), higher proportion of males and smoking history; the patients harbored STK11 mutation had fewer immune cell infiltration including B cell (P < 0.01), CD8+ T cell (P < 0.001), CD4+ T cell (P < 0.001), Macrophage (P < 0.001), Neutrophil (P < 0.001) and Dendritic cell (P < 0.001). Importantly, we found the patients harbored STK11 mutation who received immune checkpoint inhibitors have worse overall survival (OS) with median survival only 6 months. In conclusion, our study demonstrated that STK11 mutation defined a special subtype for lung adenocarcinoma patients with different co-occurrence gene mutation, lower PDL1 expression, fewer immune cell infiltration and worse OS benefit from immune checkpoint inhibitors.     

Exploration of gene expression profiles and immune microenvironment between high and low tumor mutation burden groups in prostate cancer

BackgroundTumor mutation burden (TMB) has been established as a biomarker for response to immune therapy and prognosis in various cancers. However, the association between TMB and prognosis of prostate cancer (PCa) remains unclear. This study aimed to investigate the impact of TMB in biochemical recurrence (BCR) and the immune microenvironment in high and low TMB groups.MethodsMutation data, gene expression, clinicopathological information were downloaded from The Cancer Genome Atlas (TCGA). Mutation types and TMB values were identified. All samples were divided into high and low TMB groups with median TMB value as the cutoff point. The BCR-free survival rates, Differentially expressed genes (DEGs) and immune cells infiltrations in different TMB groups were identified.ResultsThe most common variant type and SNV were single nucleotide polymorphism and C > T. respectively. High TMB level was significantly associated with older age, positive lymph node, higher International Society of Urological Pathology (ISUP) grade, advanced stage and poor BCR-free survival. 132 DEGs were identified and involved in receptor ligand activity and hormone activity. High expression of six core genes UBE2C, PLK1, CDC20, BUB1, CDK1 and HJURP were associated with worse BCR-free survival. The analysis of immune cells infiltration revealed that the amount of activated CD4⁺ memory T cells was significantly different in high and low TMB groups.ConclusionsThe current study comprehensively described the summary of mutation and TMB related DEGs in PCa. TMB was associated with BCR-free survival and the infiltration of activated CD4⁺ memory T cells in the immune microenvironment.     

Construction of an immune-related gene signature for prediction of prognosis in patients with cervical cancer

Cervical cancer (CeCa) is becoming an intractable public health issue worldwide. Emerging evidence uncovers that the tumor progression and prognosis of patients with CeCa are tightly associated with the abundance of tumor-infiltrating immune cells. In the current study, the abundance of tumor-infiltrating immune cells in CeCa samples was assessed by using the ssGSEA, thereby generating two immune-related groups according to the immune status. A 4-gene prognostic signature (RIPOR2, DAAM2, SORBS1, and CXCL8) was next established based on the grouping and its predictive capability was validated by multiple analyses. The TIMER database was used to evaluate the association between 4 hub gene expression and immune cell infiltration. Immunophenoscore (IPS) was used to assess response to immune checkpoint inhibitors in CeCa samples. As the results, a novel grouping strategy based on immune cell infiltration was developed and validated. Based on the grouping, a 4-gene signature was identified to be an independent prognostic indicator for overall survival (OS) in CeCa patients. Among the 4 hub genes, RIPOR2 and CXCL8 expression were significantly correlated with immune cell infiltration. Besides, higher immune checkpoints expression and IPS scores were found in the 4-gene signature low-risk group, suggesting a more immunoactive status that tended to respond to immune checkpoint inhibitors. To sum up, a novel immune-related signature is established to predict CeCa patients’ prognosis and also associated with response to immune checkpoint inhibitors, which might be a promising prognostic stratification strategy and innovate therapeutic management.     

Identification of immune-related biomarkers in adrenocortical carcinoma: Immune-related biomarkers for ACC

Emerging evidence has suggested that the tumor microenvironment, including immune infiltration, plays a crucially important role in tumor progression. Nevertheless, limited studies have been conducted on this topic in adrenocortical carcinoma. The present study aimed to explore the immune-related biomarkers in adrenocortical carcinoma. CIBERSORT was used to estimate the abundances of 22 kinds of immune cells, and univariable Cox analysis was performed to find survival-related immune cells with both Overall Survival (OS) and Progression-Free Interval (PFI). DESeq2 was applied to find differentially expressed genes between adrenocortical carcinoma and normal control samples; subsequently, weighted correlation network analysis and protein-protein interaction (PPI) network analysis were conducted to identify immune-related hub genes. xCell, TISIDB, and MsigDB were searched to validate the immune associations of hub genes. Eventually, univariable Cox and Kaplan–Meier analysis were used to assess the prognostic implications of the hub gene with the GEO database. Consequently, we identified two hub immune-related genes (ERN1, CEP55), GSEA revealed that both were mainly involved in tumor progression and immune response. ROC analysis indicated that ERN1 can accurately predict the 1-, 3-, and 5-year PFI, and CEP55 had the best performance for the prediction of both OS and PFI compared with other traits. Univariable Cox and Kaplan–Meier analysis showed that both genes have a significant effect on prognosis. Furthermore, both hub genes were validated in GEO datasets. The hub genes can provide better insights into tumor microenvironment and serve as potential biomarkers for immunotherapy in adrenocortical carcinoma.     

Comprehensive analysis of a 14 immune-related gene pair signature to predict the prognosis and immune features of gastric cancer

BackgroundAs a new method for predicting tumor prognosis, the predictive effect of immune-related gene pairs (IRGPs) has been confirmed in several cancers, but there is no comprehensive analysis of the clinical significance of IRGPs in gastric cancer (GC).MethodClinical and gene expression profile data of GC patients were obtained from the GEO database. Based on the ImmPort database, differentially expressed immune-related gene (DEIRG) events were determined by a comparison of GC samples and adjacent normal samples. Cox proportional regression was used to construct an IRGP signature, and its availability was validated using three external validation datasets. In addition, we explored the association between clinical data and immune features and established a nomogram to predict outcomes in GC patients.ResultA total of 88 DEIRGs were identified in GC from the training set, which formed 3828 IRGPs. Fourteen overall survival (OS)-related IRGPs were used to construct the prognostic signature. As a result, patients in the high-risk group exhibited poorer OS compared to those in the low-risk group. In addition, the fraction of CD8+ T cells, plasma cells, CD4 memory activated T cells, and M1 macrophages was higher in the high-risk group. Expression of two immune checkpoints, CD276 and VTCN1, was significantly higher in the high-risk group as well. Based on the independent prognostic factors, a nomogram was established and showed excellent performance.ConclusionThe 14 OS-related IRGP signature was associated with OS, immune cells, and immune checkpoints in GC patients, and it could provide the basis for related immunotherapy.     

Identification and validation of an immune prognostic signature in colorectal cancer

BackgroundColorectal cancer (CRC) is one of the most common malignant neoplasms worldwide. Although the significant efficacy of immunotherapy has been shown, only limited CRC patients benefit from it. Therefore, we aimed to establish a prognostic signature based on immune-related genes (IRGs) to predict overall survival (OS) and the potential response to immunotherapy in CRC patients.MethodsGene expression profiles and clinical information of CRC patients were collected from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The prognostic signature composed of IRGs was established using univariate Cox regression and the least absolute shrinkage and selection operator (LASSO) regression analysis. CIBERSORT was used to estimate the immune cell infiltration.ResultsA total of 24 survival-related IRGs were identified from 247 differentially expressed IRGs. Then, 16 IRGs were selected to establish the prognostic signature that stratified the patients into the high-risk and low-risk groups with statistically different survival outcomes. The AUCs of the time-dependent ROC curves indicated that the signature had a strong predictive accuracy in internal and external validation sets. Multivariate cox regression analysis suggested that the signature could also act as an independent prognostic factor for OS. The low-risk group had a higher proportion of immune cell infiltration than the high-risk group, such as CD4 memory resting T cells, activated dendritic cells, and resting dendritic cells. In addition, patients in the high-risk group exhibited higher tumor mutation burden and BRAF mutation.ConclusionWe developed an immune-related prognostic signature to predict the OS and immune status in CRC patients. We believed that our signature is conducive to better stratification and more precise immunotherapy for CRC patients.     

基于生物信息数据库分析CD47对肺鳞癌免疫微环境及其免疫治疗的影响

目的 采用生物信息学方法分析基因CD47对肺鳞癌免疫微环境的影响并预测其免疫治疗响应。方法 从The Cancer Genome Atlas (TCGA)数据库下载基因CD47在肺鳞癌组织和正常组织中的测序数据并分析其表达差异。采用基因集富集分析研究CD47富集的免疫相关通路;通过肿瘤免疫数据库(Tumor Immune Estimation Resource,TIMER)和TISIDB数据库(http://cis.hku.hk/TISIDB/TISIDB)分析肺鳞癌患者中CD47基因表达情况与肿瘤微环境免疫细胞浸润的关系;同时也分析了CD47和其他免疫检查点基因PD-1、PD-L1、CTLA-4、IDO1的相关性;采用pRRophetic和TIDE算法,预测CD47基因表达与化疗药物敏感性以及免疫治疗的响应。结果 与正常组织相比,CD47在肺鳞癌组织中低表达;CD47富集了免疫相关通路如炎症反应、干扰素α反应、干扰素γ反应和JAK-STAT通路。2个数据库分析结果显示,在肺鳞癌组织中CD47表达水平与B细胞、CD8⁺T细胞、CD4⁺T细胞、巨噬细胞、中性粒细胞以及树突状细胞呈正相关性。同时CD47与其他的免疫检查点PD-1、PD-L1、CTLA-4、IDO1均呈一定的正相关性,化疗敏感性结果显示,在肺鳞癌组织中,对于舒尼替尼、达沙替尼、阿霉素、吉西他滨等化疗药物,高表达CD47组IC₅₀值低于低表达组。但对于免疫治疗,其响应率却低于低表达组。结论 CD47在肺鳞癌组织中低表达,能激活免疫相关通路,对免疫治疗响应率高,可作为肺鳞癌新型分子标志物。     

Prognostic value of tissue-infiltrating immune cells in tumor microenvironment of follicular lymphoma: A meta-analysis

BackgroundThe follicular lymphoma (FL) microenvironment is composed of follicular dendritic cells (FDCs), tumor-infiltrating CD4/CD8+ T cells (TILs), follicular regulatory T (Treg) cells, lymphoma-associated macrophages (LAMs), and immune checkpoint–related immune cells, all of which are relevant in the prognosis of FL, but their results remain controversial. Therefore, we performed this systematic review to explore the relationship between the FL microenvironment and prognosis.MethodsRelevant studies were identified from PubMed, EMBASE and the Cochrane Library. Twenty-three trials involving 3336 patients with FL were included for analysis.ResultsThis meta-analysis confirmed the unfavorable prognostic role of high CD21+/CD23+ FDC density in overall survival (OS) and progression-free survival (PFS). CD8+ or granzyme B+ TILs instead of CD4+ TILs are indicators for good OS. FoxP3+ Treg cells was not associated with prognosis, and even in subgroup analysis neither the number of cells nor the infiltration pattern had predictive value. A high degree of CD68+ macrophage infiltration was a negative prognostic factor for OS, but was associated with good prognosis in the rituximab-era subgroup. Although there was no correlation between PD1-positive immune cells and prognosis, subtypes with the follicular helper T (TFH) or exhausted T cell (TEX) phenotype tended to influence prognosis. The HR in the short time to transformation (TTT) analyses suggested that high CD68+ LAM numbers, diffuse pattern of FOXP3+ Treg cells and PD1+ cells, and high PD-L1 cell numbers are adverse factors leading to early transformation.ConclusionsMultiple tissue-infiltrating immune cells in microenvironment play critical and different roles in FL prognosis.     

Establishment and validation of an immune-based prognostic score model in glioblastoma

BackgroundImmune escape is one of the landmark features of glioblastoma (GBM). Immunotherapy is undoubtedly a revolution in the field of tumor treatment, especially the application of immune checkpoint inhibitors and CAR-T cells, which have achieved amazing results in fighting against cancer. This study aimed to establish a TP53-related immune-based score model to improve the prognostic of GBM by investigating the gene mutations and the immune landscape of GBM.MethodsData were obtained from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. Differentially expressed genes (DEGs) analysis between the TP53 mutated (TP53^MUT) and wild-type (TP53^WT) GBM patients was conducted. The CIBERSORT algorithm was applied to evaluate the proportion of immune cell types and RNA sequencing (RNA-seq) data from the TCGA and CGGA were used as discovery and validation cohorts, respectively, to build and validate an immune-related prognostic model (IPM). Genes in the IPM model were first screened by univariate Cox analysis, then filtered by the least absolute shrinkage and selection operator (LASSO) Cox regression method to eliminate collinearity among DEGs. A nomogram was finally established and evaluated by combining both the IPM and other clinical factors.ResultsPTEN was the top most mutated gene in GBM patients (118/393), followed by TP53 (116/393). 332 immune-related genes were identified and the immune response in the TP53^WT group was remarkably greater than in the TP53^MUT group. The final IPM model composed three immune-related genes: IPM risk score = (0.392 × S100A8 expression) + (0.174 × CXCL1 expression) + (0.368 × IGLL5 expression), significantly correlated with the overall survival (OS) of GBM in the stratified TP53 status subgroups and was an independent prognostic variate for GBM. By integrating the IPM and clinical characteristics, a nomogram was generated to facilitate clinical utilization, with the results suggesting that it has better predictive performance for GBM prognosis than the IPM.ConclusionsThe IPM model can identify patients at high-risk and can be combined with other clinical factors to estimate the OS of GBM patients, demonstrating that it is a promising biomarker to optimize the prognosis of GBM.     

The pattern and prognostic relevance of immune activity scores and tumor-infiltrating immune cells in metastatic clear cell renal cell carcinoma: Evidence from multiple datasets

PurposeTo investigate the immune activity scores (IAS) and tumor-infiltrating immune cells (TIIC) in metastatic clear cell renal cell carcinoma (mccRCC) patients and to explore their patterns and potential prognostic values.MethodsThe gene expression profiles and clinical information of ccRCC patients from multiple Gene Expression Omnibus (GEO) datasets and TCGA were used as study cohorts. Overall, 3 sets of 69 variables associated with tumor-immune interactions were collected from several tumor immunophenotype analysis websites. Least absolute shrinkage and selection operator (LASSO) and area under receiver operating characteristic (AUC) analyses were performed to establish and evaluate the predictive models.ResultsSeveral TIIC and IAS variables are significantly different between patients and between different sites within the same patient. The AUC of the multivariable logistic models based on IAS and the two TIIC groups is 0.705 (95%CI 0.643–0.766), 0.719 (95%CI 0.650–0.788), and 0.685 (95%CI 0.623–0.747), respectively. The AUC of the LASSO model is 0.715 (95%CI 0.652–0.777). Certain subtypes identified by the consensus clustering method show a favorable OS (log-rank, p < 0.01) in both nonmetastatic and metastatic ccRCC patients.ConclusionIAS and TIIC could vary between patients and different sites within the same patient, and distinct patterns of these variables could correlate with clinical features. Heterogeneity might exist in the biological process of metastasis. LASSO logistic regression reveals that the infiltration of two TIICs would be a predictor of metastatic ccRCC. Last, certain subtypes may have a better prognosis in both ccRCC and mccRCC patients.     

Analyses of multi-omics differences between patients with high and low PD1/PDL1 expression in lung squamous cell carcinoma

BackgroundImmunotherapy has achieved excellent results in patients with lung squamous cell carcinoma. However, in which population it can exert the greatest effect is still unknown. Some studies have suggested that its effect is related to the expression level of PD1. Analyzing the relationship between PD1 expression level and genetic differences in lung squamous cell carcinoma patients will be helpful in understanding the underlying causes of this immunotherapy effect and provide a reference for clinical practice.MethodsIn this study, we used RNA-seq, miRNA-seq, methylation array, mutation profiles, and copy number variation data from the TCGA database and RNA-seq data from the GEO database to analyze the distinctive genomic patterns associated with PD1 and PDL1 expression. RNA-seq data from 44 LUSC patients who underwent surgery at Zhongshan Hospital were also included in the study.ResultsAfter grouping LUSC patients according to the expression levels of PD1 and PDL1, we found no significant difference in survival between the two groups. However, 178 genes, including IL-21, KLRC3, and KLRC4, were significantly upregulated in both the TCGA and GEO databases in the high expression group, and there was a precise correlation between gene expression and epigenetic changes in the two groups. At the same time, the overall level of somatic mutations was not significantly different between the two groups. It is worth noting that the gene enrichment results showed that the differential pathways were mainly enriched in immune regulation, especially T cell-related immune activities.ConclusionWe found that the differences in gene expression between the two groups were related to immunity, which may affect the effectiveness of immunotherapy. We hope our results can provide a reference for further research and help in finding other targets to improve the efficacy of immunotherapy.     

Autophagy-related gene expression classification defines three molecular subtypes with distinct clinical and microenvironment cell infiltration characteristics in colon cancer

BackgroundMultiple molecular subtypes with distinct clinical outcomes in colon cancer have been identified in recent years. Nonetheless, the autophagy-related molecular subtypes as well as its mediated tumor microenvironment (TME) cell infiltration characteristics have not been fully understood.MethodsBased on the seven colon cancer cohorts with 1580 samples, we performed a comprehensive genomic analysis to explore the molecular subtypes mediated by autophagy-related genes. The single-sample gene-set enrichment analysis (ssGSEA) was used to quantify the relative abundance of each cell infiltration in the TME. Unsupervised methods were used to perform autophagy subtype clustering. Least absolute shrinkage and selection operator regression (LASSO) was used to construct autophagy characterization score (APCS) signature.ResultsWe determined three distinct autophagy-related molecular subtypes in colon cancer. The three autophagy subtypes presented significant survival differences. Microenvironment analyses revealed the heterogeneous TME immune cell infiltration characterization between three subtypes. Cluster 1 autophagy subtype was characterized by abundant innate and adaptive immune cell infiltration. This subtype exhibited an enhanced stromal activity including activated pathways of epithelial-mesenchymal transition, TGF-β and angiogenesis, and an increased infiltration of fibroblasts and endothelial cells. The expression of immune checkpoint molecules was also significantly up-regulated, which may mediate immune escape in Cluster 1 subtype. Cluster 2 subtype was characterized by relatively lower TME immune cell infiltration and enhanced DNA damage repair pathways. Cluster 3 subtype was characterized by the suppression of immunity. Patients with high APCS, with poorer survival, presented a significantly positive correlation with TME stromal activity. Low APCS, relevant to activated damage repair pathways, showed enhanced responses to anti-PD-1/PD-L1 immunotherapy. Two immunotherapy cohorts confirmed patients with low APCS exhibited prominently enhanced clinical response and treatment advantages.ConclusionsThis study may help understand the molecular characterization of autophagy-related subtypes. We demonstrated the autophagy genes in colon cancer could drive the heterogeneity of TME immune cell infiltration. Our study represented a step toward personalized immunotherapy in colon cancer.     

基于数据挖掘分析SLC22A1基因在肝细胞癌组织中的表达及其预后意义

目的探讨阳离子转运蛋白1(SLC22A1)基因在肝细胞癌中的表达情况和预后意义。方法用The Human Protein Atlas(HAP)数据库分析SLC22A1蛋白在肝细胞癌中的表达情况。利用Oncomine和GEPIA数据库分析SLC22A1基因在肝细胞癌和肝正常组织中的表达水平。利用GEPIA和Linked Omics数据库分析SLC22A1基因与肝细胞癌患者临床相关性:总生存期(OS)、无瘤生存期(DFS)、病理分期和种族。采用Metascape在线工具对SLC22A1相关基因进行功能和通路富集分析。结果 LC22A1蛋白和m RNA在肝细胞癌组织中显著低于正常组织,且与肝细胞癌预后呈正相关(P0.001)。肝细胞癌中SLC22A1基因表达水平与预后、病理分期存在显著差异性(P0.05),与种族无相关性。功能富集分析显示,SLC22A1基因通过影响小分子分解代谢过程、对异源生物刺激的反应和有机酸生物合成过程等发挥作用。通路富集分析显示,SLC22A1基因通过作用于过氧化物酶体、脂肪酸降解和精氨酸和脯氨酸代谢等通路起作用。结论细胞癌组织中SLC22A1蛋白和m RNA表达水平均显著低于肝正常组织,其表达情况与肝细胞癌预后存在显著关联,提示SLC22A1可能成为评估肝细胞癌预后的指标和研发肝细胞癌相关靶向药物的候选靶点,为肝细胞癌研究提供新研究思路。     

BICC1 as a novel prognostic biomarker in gastric cancer correlating with immune infiltrates

AimBicC family RNA-binding protein 1 (BICC1) codes an RNA-binding protein that regulates gene expression and modulates cell proliferation and apoptosis. We aim at investigating the role of BICC1 in gastric carcinogenesis.MethodsBICC1 mRNA expression in gastric cancer (GC) was examined using the Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Correlations between BICC1 expression and clinicopathological parameters were analyzed. The Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter databases were used to examine the clinical prognostic significance of BICC1 in GC. Signaling pathways related to BICC1 expression were identified by gene set enrichment analysis (GSEA).TIMER and CIBERSORT were used to analyze the correlations among BICC1, BICC1-coexpressed genes and tumor-infiltrating immune cells.ResultsBICC1 was highly expressed in GC and significantly correlated with grade (P = 0.002), TNM stage (P = 0.033), invasion depth (P = 0.001) and vital status (P = 0.009) of GC patients. High BICC1 expression correlated with poor overall survival. The GSEA results showed that cell adhesion-, tumor- and immune- related pathways were significantly enriched in samples with high BICC1 expression. BICC1 and its coexpressed genes were positively related to tumor-infiltrating immune cells and were strongly correlated with tumor-infiltrating macrophages (all r ≥ 0.582, P < 0.0001). The CIBERSORT database revealed that BICC1 correlated with M2 macrophages (P < 0.0001), regulatory T cells (P < 0.0001), resting mast cells (P < 0.0001), activated memory CD4+ T cells (P = 0.002), resting NK cells (P = 0.002), activated dendritic cells (P = 0.002), and follicular helper T cells (P = 0.016). The results from TIMER database confirmed that BICC1 is closely associated with the markers of M2 macrophages and tumor-associated macrophages (all r ≥ 0.5, P < 0.0001).ConclusionBICC1 may be a potential prognostic biomarker in GC and correlates with immune infiltrates.     

Bromodomain 4 is a potent prognostic marker associated with immune cell infiltration in breast cancer

Bromodomain 4 (BRD4), a member of the bromodomain and extra‐terminal domain protein family, has become a promising epigenetic target in cancer and inflammatory diseases; however, the detailed biological role of BRD4 in breast cancer (BRCA) remains undetermined. We analysed the BRD4 expression levels using the Oncomine and TIMER databases and evaluated the clinical impact of BRD4 on BRCA prognosis using Kaplan‐Meier plot and PrognoScan. The correlation between BRD4 and tumour‐infiltrating immune cells was investigated using TIMER. Furthermore, the correlation between BRD4 expression levels was also analysed using TIMER in addition to the GEPIA database for immune cell gene markers. BRD4 expression was significantly higher in BRCA tissues than in normal tissues, which was significantly correlated with poor overall survival (OS). Specifically, high BRD4 expression was correlated with worse OS and progression‐free survival in patients with BRCA. In addition, BRD4 expression was correlated with levels of infiltrating monocytes (CSF1R, cor = 0.204, P = 9.19e?12), tumour‐associated macrophages (CD68, cor = 0.129, P = 1.81e?05), M1/M2 macrophages and different effector T cells (including Th1/Th2/Treg) in BRCA. These findings suggest that BRD4 could be used as a prognostic biomarker for determining prognosis and immune cell infiltration levels in BRCA.     

A robust signature associated with patient prognosis and tumor immune microenvironment based on immune-related genes in lung squamous cell carcinoma

BackgroundLung squamous cell carcinoma (LUSC) is one common type of lung cancer. Immune-related genes (IRGs) are closely associated with cancer prognosis. This study aims to screen the key genes associated with LUSC and establish an immune-related prognostic model.MethodsBased on the Cancer Genome Atlas (TCGA) database, we screened the differentially expressed genes (DEGs) between LUSC and normal samples. Intersecting the DEGs with the immune-related genes (IRGs), we obtained the differentially expressed IRGs (DEIRGs). Univariate as well as multivariate Cox regression analyses were performed to identify the survival-associated IRGs and establish an immune-related prognostic model. The relationship between the prognostic model and tumor-infiltrating immune cells was analyzed by TIMER and CIBERSORT.ResultsA total of 229 DEIRGs were screened, and 14 IRGs associated with survival were identified using univariate Cox analysis. Among the 14 IRGs, six genes were selected out using Lasso and multivariate Cox analyses, and they were used to build the prognostic model. Further analysis indicated that overall survival (OS) of high-risk groups was lower than that of low-risk groups. High risk score was independently related to worse OS. Moreover, the risk score was positively correlated with several immune infiltration cells. Finally, the efficacy of the prognostic model was validated by another independent cohort GSE73403.ConclusionThe DEIRGs described in the study may have the potential to be the prognostic molecular markers for LUSC. In addition, the risk score model could predict the OS and provides more information for the immunotherapy of patients with LUSC.     

A novel immune checkpoint-related seven-gene signature for predicting prognosis and immunotherapy response in melanoma

BackgroundNew emergence of immunotherapy has significantly improved clinical outcome of melanoma patients with advanced and metastatic diseases. We aimed to develop a gene signature based on the expression of PD-1/PD-L1 signaling pathway genes to predict prognosis and immunotherapy response in melanoma patients.MethodsMelanoma samples from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO) were used as the training set and external validation sets respectively. Prognostic genes for overall survival (OS) were identified by univariate Cox regression analysis. Then a multi-gene risk signature was established with the Least Absolute Shrinkage and Selector Operation (LASSO) regression and multivariate Cox regression. The predictive and prognostic value of gene signature was evaluated by Kaplan Meier curve, Time-dependent receiver operating characteristic (ROC) curve, and area under curve (AUC). Gene set enrichment analysis (GSEA) was performed to investigate the discrepantly enriched biological processes between low-risk and high-risk group of melanoma patients.ResultsA seven-gene risk signature (BATF2, CTLA4, EGFR, HLA-DQB1, IKBKG, PIK3R2, PPP3CA) was constructed. The signature was an independent risk factor for OS (hazard ratio = 1.544, p < 0.001) and it could robustly predict OS in both training and validation sets. Besides, high risk scores indicated advanced clinical stage and no response to immunotherapy for melanoma patients. GSEA demonstrated that high risk score was intimately associated with immune response and immune regulation. In conclusion, the novel seven-gene signature could serve as a robust biomarker for prognosis and a potential indicator of immunotherapy response in melanoma.     

Identification of DRP1 as a prognostic factor correlated with immune infiltration in breast cancer

BackgroundBreast cancer (BC) is the leading cause of cancer-related mortality in women worldwide. The identification of effective markers for early diagnosis and prognosis is important for reducing mortality and ensuring that therapy for BC is effective. Dynamin-related protein-1 (DRP1) is a regulator of mitochondrial fission. However, the prognostic value of DRP1 and its association with immune infiltration in BC remain unknown.MethodsThe TCGA, Oncomine, UALCAN and HPA databases were used to examine DRP1 expression in BC. Kaplan-Meier plotter and PrognoScan were used to evaluate the association of DRP1 with the prognosis of patients with BC. The mechanism was investigated with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and the relationship between DRP1 expression and immune infiltration in BC was investigated using the TIMER database and CIBERSORT algorithm.ResultsDRP1 expression was significantly upregulated in BC compared to healthy breast tissues. In addition, elevated DRP1 expression was associated with various clinicopathological parameters. High DRP1 expression was significantly correlated with poor survival of BC patients. GO and KEGG analyses indicated that DRP1 was closely correlated with various signaling pathways and immune response. Functional analyses revealed that DRP1 was positively correlated with infiltration levels of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils, and dendritic cells. Moreover, DRP1 affected the prognosis of BC patients partially via immune infiltration.ConclusionsOur results suggest that DRP1 is a marker of poor prognosis in patients with BC and plays an important role in tumor-related immune infiltration.     

Prognostic and clinicopathological utility of programmed death-ligand 1 in malignant pleural mesothelioma: A meta-analysis

ObjectiveProgrammed death ligand 1 (PD-L1) has been reported to be connected to prognosis in individuals with malignant pleural mesothelioma (MPM), although there is no consensus based on data from previous studies. Accordingly, this quantitative meta-analysis investigated prognostic and clinicopathological utility of PD-L1 in patients with MPM.MethodsA comprehensive search of the PubMed, Web of Science, Embase, and Cochrane Library databases for articles published up to October 4, 2019 was performed. Studies using immunohistochemical techniques to detect/quantify the expression of PD-L1 in MPM tissue were enrolled in the analysis. The combined hazard ratio (HR) and corresponding 95% confidence interval (CI) was applied to assess the association between PD-L1 expression and overall survival (OS).ResultsA total of 11 studies comprising 1606 patients was included in the present meta-analysis. For OS, pooled data revealed an HR of 1.50 (95% CI 1.32–1.70; p < 0.001), suggesting that patients with PD-L1 overexpression experience inferior OS. Subgroup analysis revealed that elevated PD-L1 remained a significant prognostic indicator for worse OS, irrespective of sample size, cut-off value, ethnicity, and Newcastle-Ottawa Scale score. Moreover, PD-L1 overexpression was associated with non-epithelioid histology (odds ratio 4.30 [95% CI 1.89–9.74]; p < 0.001).ConclusionsResults of this meta-analysis show that elevated expression of PD-L1 could be a factor predicting poorer survival in patients with MPM.