Spatial heterogeneity of immune infiltration predicts the prognosis of nasopharyngeal carcinoma patients
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ABSTRACT:
SUBMITTER: Wang Y
PROVIDER: S-EPMC8555536 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundDysregulation of iron metabolism has been shown to have significant implications for cancer development. We aimed to investigate the prognostic and immunological significance of iron metabolism-related genes (IMRGs) in nasopharyngeal carcinoma (NPC).MethodsMultiple Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets were analyzed to identify key IMRGs associated with prognosis. Additionally, the immunological significance of IMRGs was explored.ResultsA novel risk model was established using the LASSO regression algorithm, incorporating three genes (TFRC, SLC39A14, and ATP6V0D1).This model categorized patients into low and high-risk groups, and Kaplan-Meier analysis revealed significantly shorter progression-free survival for the high-risk group (P < 0.0001). The prognostic model's accuracy was additionally confirmed by employing time-dependent Receiver Operating Characteristic (ROC) curves and conducting Decision Curve Analysis (DCA). High-risk patients were found to correlate with advanced clinical stages, specific tumor microenvironment subtypes, and distinct morphologies. ESTIMATE analysis demonstrated a significant inverse relationship between increased immune, stromal, and ESTIMATE scores and lowered risk score. Immune analysis indicated a negative correlation between high-risk score and the abundance of most tumor-infiltrating immune cells, including dendritic cells, CD8+ T cells, CD4+ T cells, and B cells. This correlation extended to immune checkpoint genes such as PDCD1, CTLA4, TIGIT, LAG3, and BTLA. The protein expression patterns of selected genes in clinical NPC samples were validated through immunohistochemistry.ConclusionThis study presents a prognostic model utilizing IMRGs in NPC, which could assist in assessing patient prognosis and provide insights into new therapeutic targets for NPC.
| S-EPMC11009181 | biostudies-literature
Project description:Nasopharyngeal cancer (NPC) is a malignant tumor. In a recent publication, we described the presence and distribution of CD8+ T cells in NPC and used the information to identify 'inflamed', 'immune-excluded', and 'desert' immune phenotypes, where 'inflamed' and 'immune-excluded' NPCs were correlated with CD8 T cell infiltration and survival. Arguably, more detailed and, in particular, spatially resolved data are required for patient stratification and for the identification of new treatment targets. In this study, we investigate the phenotype of CD45+ leukocytes in the previously analyzed NPC samples by applying multiplexed tissue analysis to assess the spatial distribution of cell types and to quantify selected biomarkers. A total of 47 specified regions-of-interest (ROIs) were generated based on CD45, CD8, and PanCK morphological staining. Using the GeoMx® Digital Spatial Profiler (DSP), 49 target proteins were digitally quantified from the selected ROIs of a tissue microarray consisting of 30 unique NPC biopsies. Protein targets associated with B cells (CD20), NK cells (CD56), macrophages (CD68), and regulatory T cells (PD-1, FOXP3) were most differentially expressed in CD45+ segments within 'immune-rich cancer cell islet' regions of the tumor (cf. 'surrounding stromal leukocyte' regions). In contrast, markers associated with suppressive populations of myeloid cells (CD163, B7-H3, VISTA) and T cells (CD4, LAG3, Tim-3) were expressed at a higher level in CD45+ segments in the 'surrounding stromal leukocyte' regions (cf. 'immune-rich cancer cell islet' regions). When comparing the three phenotypes, the 'inflamed' profile (cf. 'immune-excluded' and 'desert') exhibited higher expression of markers associated with B cells, NK cells, macrophages, and myeloid cells. Myeloid markers were highly expressed in the 'immune-excluded' phenotype. Granulocyte markers and immune-regulatory markers were higher in the 'desert' profile (cf. 'inflamed' and 'immune-excluded'). In conclusion, this study describes the spatial heterogeneity of the immune microenvironment in NPC and highlights immune-related biomarkers in immune phenotypes, which may aid in the stratification of patients for therapeutic purposes.
| S-EPMC10093565 | biostudies-literature
Project description:BackgroundHepatocellular carcinoma (HCC) is a global health burden with poor prognosis. Anoikis, a novel programmed cell death, has a close interaction with metastasis and progression of cancer. In this study, we aimed to construct a novel bioinformatics model for evaluating the prognosis of HCC based on anoikis-related gene signatures as well as exploring the potential mechanisms.Materials and methodsWe downloaded the RNA expression profiles and clinical data of liver hepatocellular carcinoma from TCGA database, ICGC database and GEO database. DEG analysis was performed using TCGA and verified in the GEO database. The anoikis-related risk score was developed via univariate Cox regression, LASSO Cox regression and multivariate Cox regression, which was then used to categorize patients into high- and low-risk groups. Then GO and KEGG enrichment analyses were performed to investigate the function between the two groups. CIBERSORT was used for determining the fractions of 22 immune cell types, while the ssGSEA analyses was used to estimate the differential immune cell infiltrations and related pathways. The "pRRophetic" R package was applied to predict the sensitivity of administering chemotherapeutic and targeted drugs.ResultsA total of 49 anoikis-related DEGs in HCC were detected and 3 genes (EZH2, KIF18A and NQO1) were selected out to build a prognostic model. Furthermore, GO and KEGG functional enrichment analyses indicated that the difference in overall survival between risk groups was closely related to cell cycle pathway. Notably, further analyses found the frequency of tumor mutations, immune infiltration level and expression of immune checkpoints were significantly different between the two risk groups, and the results of the immunotherapy cohort showed that patients in the high-risk group have a better immune response. Additionally, the high-risk group was found to have higher sensitivity to 5-fluorouracil, doxorubicin and gemcitabine.ConclusionThe novel signature of 3 anoikis-related genes (EZH2, KIF18A and NQO1) can predict the prognosis of patients with HCC, and provide a revealing insight into personalized treatments in HCC.
| S-EPMC10172511 | biostudies-literature
Project description:CXC ligand 17 (CXCL17) is a novel CXC chemokine whose clinical significance remains largely unknown. In the present study, we characterized the prognostic value of CXCL17 in patients with hepatocellular carcinoma (HCC) and evaluated the association of CXCL17 with immune infiltration. We examined CXCL17 expression in 227 HCC tissue specimens by immunohistochemical staining, and correlated CXCL17 expression patterns with clinicopathological features, prognosis, and immune infiltrate density (CD4 T cells, CD8 T cells, B cells, natural killer cells, neutrophils, macrophages). Kaplan-Meier survival analysis showed that both increased intratumoral CXCL17 (P = 0.015 for overall survival [OS], P = 0.003 for recurrence-free survival [RFS]) and peritumoral CXCL17 (P = 0.002 for OS, P<0.001 for RFS) were associated with shorter OS and RFS. Patients in the CXCL17low group had significantly lower 5-year recurrence rate compared with patients in the CXCL17high group (peritumoral: 53.1% vs. 77.7%, P<0.001, intratumoral: 58.6% vs. 73.0%, P = 0.001, respectively). Multivariate Cox proportional hazards analysis identified peritumoral CXCL17 as an independent prognostic factor for both OS (hazard ratio [HR] = 2.066, 95% confidence interval [CI] = 1.296-3.292, P = 0.002) and RFS (HR = 1.844, 95% CI = 1.218-2.793, P = 0.004). Moreover, CXCL17 expression was associated with more CD68 and less CD4 cell infiltration (both P<0.05). The combination of CXCL17 density and immune infiltration could be used to further classify patients into subsets with different prognosis for RFS. Our results provide the first evidence that tumor-infiltrating CXCL17+ cell density is an independent prognostic factor that predicts both OS and RFS in HCC. CXCL17 production correlated with adverse immune infiltration and might be an important target for anti-HCC therapies.
| S-EPMC4193880 | biostudies-literature
Project description:Background: With a high incidence and dismal survival rate, hepatocellular carcinoma (HCC) tops the list of the world's most frequent malignant tumors. Immunotherapy is a new approach to cancer treatment, and its effect on prolonging overall survival (OS) varies from patient to patient. For a more effective prognosis and treatment of HCC, we are committed to identifying immune infiltration-related long non-coding RNAs (IIRLs) with prognostic value in hepatocellular carcinoma. Methods: In our study, we calculated immune scores of 369 hepatocellular carcinoma samples from the Cancer Genome Atlas (TCGA) database by using an estimation algorithm, and obtained long non-coding RNAs (lncRNAs) associated with immune infiltration by using Weighted Gene Co-expression Network analysis (WGCNA). For training cohort, univariate Cox, least absolute shrinkage and selection operator (Lasso) and multivariate Cox regression analysis were used to determine prognostic IIRLs, we established a prognostic IIRLs signature. By testing cohort and entire cohort, we confirmed that the signature is practical. The prognosis of people with different clinicopathological stages and risk scores were predicted by the nomogram we constructed. In addition, Immune cell infiltration analysis and prediction of therapeutic drugs were performed. Results: 93 IIRLs were obtained by WGCNA. Furthermore, the prognostic value of these IIRLs were evaluated by using univariate Cox, Lasso and multivariate Cox analysis. Four IIRLs were used to create a signature with a prognosis. Time-related receiver operating characteristic (ROC) curve revealed that this model had an acceptable prognostic value for HCC patients. By using univariate and multivariate Cox regression analysis, this risk score has been shown to be an independent prognostic factor for HCC. The nomogram we made showed good predictions. Except for that, the treatment with immune checkpoint inhibitors (ICI) was likely to be more effective for low-risk patients. Conclusion: Based on four IIRLs, a prognostic signature was created in this research showed good accuracy in predicting OS. This study also provided valuable references for Immunotherapy of hepatocellular carcinoma.
| S-EPMC9773198 | biostudies-literature
Project description:Increasing evidence has revealed the roles of long noncoding RNAs (lncRNAs) as tumor biomarkers. Here, we introduce an immune-associated nine-lncRNA signature for predicting distant metastasis in locoregionally advanced nasopharyngeal carcinoma (LA-NPC). The nine lncRNAs are identified through microarray profiling, followed by RT-qPCR validation and selection using a machine learning method in the training cohort (n = 177). This nine-lncRNA signature classifies patients into high and low risk groups, which have significantly different distant metastasis-free survival. Validations in the Guangzhou internal (n = 177) and Guilin external (n = 150) cohorts yield similar results, confirming that the signature is an independent risk factor for distant metastasis and outperforms anatomy-based metrics in identifying patients with high metastatic risk. Integrative analyses show that this nine-lncRNA signature correlates with immune activity and lymphocyte infiltration, which is validated by digital pathology. Our results suggest that the immune-associated nine-lncRNA signature can serve as a promising biomarker for metastasis prediction in LA-NPC.
| S-EPMC9151760 | biostudies-literature
Project description:Immune infiltration of nasopharyngeal carcinoma (NPC) is closely associated with the patients' prognosis. However, previous studies have not interpreted the difference of infiltrating immune cells in NPC.We comprehensively analyzed the tumor-infiltrating immune cells present in NPC for the first time, which was based on a scientific deconvolution algorithm (CIBERSORT) and the gene expression data of GSE64634. The fractions of 22 immune cells were assessed to reveal the associations between normal samples and NPC samples.Profiles of immune infiltration vary significantly between normal samples and NPC samples, and the variation could characterize the individual differences. NPC samples contained a higher proportion for M1 macrophages, whereas memory B cells and CD4 memory resting T cells were relatively lower.Our data suggest that the differences in the infiltrating immune cells in NPC and these differences would probably facilitate patient consultation and individualized treatment.
| S-EPMC6775332 | biostudies-literature
Project description:Pentatricopeptide repeat domain 1 (PTCD1) was reported to regulate mitochondrial metabolism and oxidative phosphorylation. However, the effect and mechanism of PTCD1 in the development of bladder urothelial carcinoma (BLCA) remain unclear. The databases from The Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) were used to analyze the expression changes, clinical features, and prognostic values of PTCD1. A nomogram was built to predict the prognostic outcomes of BLCA cases. The potential genes interacting with PTCD1 were explored by Weighted Gene Coexpression Network Analysis (WGCNA). The estimation of associations between PTCD1 and tumor mutations, tumor immunities, and m6A methylations was performed. The study found that the gradual decrease of PTCD1 expression was observed with the increase of stage and grade. Low PTCD1 expression was greatly correlated with higher pathological stage, N stage, and poor prognosis in TCGA cohorts; interestingly, low-grade BLCA cases all exhibited high expression of PTCD1. HPA database analysis implied that the expression of PTCD1 protein in BLCA was lower than that in normal bladder tissue, and the protein expression of PTCD1 in high-grade BLCA was lower than that in low-grade BLCA. Multivariate Cox regression analysis indicated that PTCD1 may serve as an independent factor influencing prognosis of BLCA. Mechanistically, PTCD1 played a regulatory role in BLCA progression through multiple tumor-related pathways containing PI3K-Akt signaling, ECM-receptor interaction, oxidative phosphorylation, and extracellular matrix organization. WGCNA reported that PTCD1 had a strong positive correlation with POLR2J, ZNHT1, ATP5MF, PDAP1, BUD31, and COPS6. Besides, the mRNA expression of PTCD1 was negatively associated with immune cells' infiltrations, immune functions, and checkpoints, especially with some m6A methylation regulators in BLCA. In sum, downregulation of PTCD1 expression may be involved in the development of BLCA and remarkably correlated with poor prognosis. Meantime, it showed an influence in immune cell infiltration and may serve as an agreeable prognostic indicator in BLCA.
| S-EPMC9256401 | biostudies-literature
Project description:IntroductionHepatocellular carcinoma (HCC) is the most common malignant tumor of the liver. Identifying specific molecular markers that can predict HCC prognosis is extremely important. The protein deoxythymidylate kinase (DTYMK) has been reported to contribute to unfavorable prognosis in non-small cell lung cancer patients, but its role in the prediction of HCC patient prognosis has not been clarified.MethodsSamples from the TCGA and GEO databases were consecutively enrolled for gene expression analysis, clinicopathology analysis, immune microenvironment analysis and chemotherapeutic response prediction. The results were validated using 86 samples from the First Affiliated Hospital of Sun Yat-sen University. Cox regression analysis was used to analyze the effect of DTYMK on progression-free survival (PFS) and overall survival (OS). Functional enrichment analysis was used to describe the marker pathways that were significantly related to DTYMK. TIMER (Tumor Immune Estimation Resource), TISIDB (Tumor and Immune System Interaction DataBase) and CIBERSORT (Cell type Identification By Estimating Relative Subsets Of RNA Transcripts) were used to explore the immune microenvironment.ResultsWe found that DTYMK expression upregulation is associated with poor prognosis in HCC patients and tightly related to the pathways regulating the cell cycle and acid metabolism. Our findings revealed that hepatocellular carcinoma cell lines with high DTYMK expression were more sensitive to sorafenib and many other chemotherapeutic drugs. We also found an inhibiting effect of DTYMK on the immune microenvironment in the process of tumorigenesis.DiscussionWe found that DTYMK has potential as a new prognostic and chemotherapeutic response biomarker for HCC patients and correlates with the immune microenvironment in HCC. However, there are some deficiencies in our study. First, this is a retrospective study that may lead to selection bias. Second, the protein expression of DTYMK was investigated via immunohistochemical analysis. Finally, we did not explore the exact underlying molecular mechanisms of DTYMK in tumorigenesis in this study, which is needed to be clarified in future research.
| S-EPMC8349219 | biostudies-literature
Project description:Increasing numbers of biomarkers have been identified in various cancers. However, biomarkers associated with endometrial carcinoma (EC) remain largely to be explored. In the current research, we downloaded the RNA-seq data and corresponding clinicopathological features from the Cancer Genome Atlas (TCGA) database. We conducted an expression analysis, which resulted in RILPL2 as a novel diagnostic biomarker in EC. The dysregulation of RILPL2 in EC was also validated in multiple datasets. The correlations between clinical features and RILPL2 expression were assessed by logistic regression analysis. Then, Kaplan-Meier analysis, univariate and multivariate Cox regression analysis were performed to estimate prognostic values of RILPL2 in the TCGA cohort, which revealed that increased level of RILPL2 was remarkably associated with better prognosis and could act as an independent prognostic biomarker in patients with EC. Moreover, correlation analysis of RILPL2 and tumor-infiltrating immune cells (TIICs) indicated that RILPL2 might play a critical role in regulating immune cell infiltration in EC and is related to immune response. Besides, high methylation level was a significant cause of low RILPL2 expression in EC. Subsequently, weighted gene co-expression network analysis (WGCNA) and enrichment analysis were conducted to explore the RILPL2-involved underlying oncogenic mechanisms, and the results indicated that RILPL2 mainly regulated cell cycle. In conclusion, our findings provided evidence that downregulation of RILPL2 in EC is an indicator of adverse prognosis and RILPL2 may act as a promising target for the therapeutics of EC.
| S-EPMC8171931 | biostudies-literature