Corrigendum to "Construction of a novel immune response prediction signature to predict the efficacy of immune checkpoint inhibitors in clear cell renal cell carcinoma patients" Heliyon 9(6), (May 25, 2023).
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ABSTRACT:
SUBMITTER: Yao J
PROVIDER: S-EPMC10404658 | biostudies-literature | 2023 Aug
REPOSITORIES: biostudies-literature
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Corrigendum to "Construction of a novel immune response prediction signature to predict the efficacy of immune checkpoint inhibitors in clear cell renal cell carcinoma patients" Heliyon 9(6), (May 25, 2023).
Yao Jiannan J Liang Ziwei Z Duan Ling L Ge Yang Y Liu Jian J An Guangyu G
Heliyon 20230723 8
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Project description:BackgroundImmune checkpoint inhibitor (ICI) treatment has enhanced survival outcomes in clear cell renal cell carcinoma (ccRCC) patients. Nevertheless, the effectiveness of immunotherapy in ccRCC patients is restricted and we intended to develop and characterize an immune response prediction signature (IRPS) to forecast the efficacy of immunotherapy.MethodsRNA-seq expression profile and clinicopathologic characteristics of 539 kidney cancer and 72 patients with normal specimens, were downloaded from the Cancer Genome Atlas (TCGA) database, while the Gene Expression Omnibus (GEO) database was used as the validation set, which included 24 ccRCC samples. Utilization of the TCGA data and immune genes databases (ImmPort and the InnateDB), we explored through Weighted Gene Co-expression Network Analysis (WGCNA), along with Least Absolute Shrinkage and Selection Operator method (LASSO), and constructed an IRPS for kidney cancer patients. GSEA and CIBERSORT were performed to declare the molecular and immunologic mechanism underlying the predictive value of IRPS. The Human Protein Atlas (HPA) was deployed to verify the protein expressions of IRPS genes. Tumor immune dysfunction and exclusion (TIDE) score and immunophenoscore (IPS) were computed to determine the risk of immune escape and value the discrimination of IRPS. A ccRCC cohort with anti-PD-1 therapy was obtained as an external validation data set to verify the predictive value of IRPS.ResultsWe constructed a 10 gene signature related to the prognosis and immune response of ccRCC patients. Considering the IRPS risk score, patients were split into high and low risk groups. Patients with high risk in the TCGA cohort tended towards advanced tumor stage and grade with poor prognosis (p < 0.001), which was validated in GEO database (p = 0.004). High-risk group tumors were related with lower PD-L1 expression, higher TMB, higher MSIsensor score, lower IPS, higher TIDE score, and enriched Treg cells, which might be the potential mechanism of immune dysfunction and exclusion. Patients in the IRPS low risk group had better PFS (HR:0.73; 95% CI: 0.54-1.0; P = 0.047).ConclusionA novel biomarker of IRPS was constructed to predict the benefit of immunotherapy, which might lead to more individualized prognoses and tailored therapy for kidney cancer patients.
| S-EPMC10360603 | biostudies-literature
Project description:Background Limited treatment strategies are available for squamous-cell lung cancer (SQLC) patients. Few studies have addressed whether immune-related genes (IRGs) or the tumor immune microenvironment can predict the prognosis for SQLC patients. Our study aimed to construct a signature predict prognosis for SQLC patients based on IRGs. Methods We constructed and validated a signature from SQLC patients in The Cancer Genome Atlas (TCGA) using bioinformatics analysis. The underlying mechanisms of the signature were also explored with immune cells and mutation profiles. Results A total of 464 eligible SQLC patients from TCGA dataset were enrolled and were randomly divided into the training cohort (n = 232) and the testing cohort (n = 232). Eight differentially expressed IRGs were identified and applied to construct the immune signature in the training cohort. The signature showed a significant difference in overall survival (OS) between low-risk and high-risk cohorts (P < 0.001), with an area under the curve of 0.76. The predictive capability was verified with the testing and total cohorts. Multivariate analysis revealed that the 8-IRG signature served as an independent prognostic factor for OS in SQLC patients. Naive B cells, resting memory CD4 T cells, follicular helper T cells, and M2 macrophages were found to significantly associate with OS. There was no statistical difference in terms of tumor mutational burden between the high-risk and low-risk cohorts. Conclusion Our study constructed and validated an 8-IRG signature prognostic model that predicts clinical outcomes for SQLC patients. However, this signature model needs further validation with a larger number of patients.
| S-EPMC7533590 | biostudies-literature
Project description:BackgroundClear cell renal cell carcinoma (ccRCC) is the most prevalent subtype of renal tumors and is associated with a unfavorable prognosis. Disulfidptosis is a recently identified form of cell death mediated by disulfide bonds. Numerous studies have highlighted the significance of immune checkpoint genes (ICGs) in ccRCC. Nevertheless, the involvement of disulfidptosis-related immune checkpoint genes (DRICGs) in ccRCC remains poorly understood.MethodsThe mRNA expression profiles and clinicopathological data of ccRCC patients were obtained from The Cancer Genome Atlas and Gene Expression Omnibus (GEO) databases. The associations between disulfidptosis-related genes (DRGs) and immune checkpoint genes (ICGs) were assessed to identify DRICGs. Cox regression analysis and least absolute shrinkage and selection operator (LASSO) analysis were conducted to construct a risk signature.ResultsA total of 39 differentially expressed immune-related candidate genes were identified. A prognostic signature was constructed utilizing nine DRICGs (CD276, CD80, CD86, HLA-E, LAG3, PDCD1LG2, PVR, TIGIT, and TNFRSF4) and validated using GEO data. The risk model functioned as an independent prognostic indicator for ccRCC, while the associated nomogram provided a reliable scoring system for ccRCC. Gene set enrichment analysis indicated enrichment of phospholipase D, antigen processing and presentation, and ascorbate and aldarate metabolism-related signaling pathways in the high-risk group. Furthermore, the DRICGs exhibited correlations with the infiltration of various immune cells. It is noteworthy that patients with ccRCC categorized into distinct risk groups based on this model displayed varying sensitivities to potential therapeutic agents.ConclusionsThe novel DRICG-based risk signature is a reliable indicator for the prognosis of ccRCC patients. Moreover, it also aids in drug selection and correlates with the tumour immune microenvironment in ccRCC.
| S-EPMC11192710 | biostudies-literature
Project description: Not available
| S-EPMC10622984 | biostudies-literature
Project description:AimThe action of immune checkpoint inhibition (ICI) largely depends on antibody-dependent cellular phagocytosis (ADCP). We thus aim to develop ADCP-based ccRCC risk stratification as both prognostic and therapeutic markers of ICI.MethodGenomic data from multiple public datasets (TCGA, etc.) were integrated. A cancer-intrinsic ADCP gene set for ccRCC tailored from a recent report was constructed based on the association with prognosis, immune infiltrates, and response to ICI. Therapeutic potential was profiled using genome-drug sensitivity datasets.ResultsADCP genes were selected from a recent CRISPR/Cas9 screen report. Following a four-module panel based on clinical traits, we generated a six-gene signature (ARPC3, PHF19, FKBP11, MS4A14, KDELR3, and CD1C), which showed a strong correlation with advanced grade and stage and worsened prognosis, with a nomogram showing predictive efficacies of 0.911, 0.845, and 0.867 (AUC) at 1, 3, and 5 years, respectively. Signatures were further dichotomized, and groups with a higher risk score showed a positive correlation with tumor mutation burden, higher expressions of inhibitory checkpoint molecules, and increased antitumor immune infiltrates and were enriched for antitumor immune pathways. The high risk-score group showed better response to ICI and could benefit from TKIs of axitinib, tivozanib, or sorafenib, preferentially in combination, whereas sunitinib and pazopanib would better fit the low risk-score group.ConclusionHere we showed a six-gene ADCP signature that correlated with prognosis and immune modulation in ccRCC. The signature-based risk stratification was associated with response to both ICI and tyrosine kinase inhibition in ccRCC.
| S-EPMC9148997 | biostudies-literature
Project description:BackgroundKidney renal clear cell carcinoma (KIRC) lacks effective prognostic biomarkers and the role and mechanism of N6-methyladenosine (m6A) modification of long noncoding RNAs (lncRNAs) in KIRC remain unclear.MethodsWe extracted standard mRNA-sequencing and clinical data from the TCGA database. The prognostic risk model was obtained by Lasso regression and Cox regression. We randomly divided the samples into training and test sets, each taking half of the cases. Based on Lasso regression and Cox regression for training set, the prognostic risk signature was constructed; risk scores were calculated with the R package "glmnet." Based on the median value of the prognostic risk score, risk scores were calculated for each patient and we divided all KIRC samples into high-risk and low-risk groups. Then, high- and low-risk subtypes were established and their prognosis, clinical features, and immune infiltration microenvironment were evaluated in test set and the entire sampled data set. The reliability of the prognostic model was confirmed by receiver operating characteristic curve analysis.ResultsWe found 28 prognostic m6A-related lncRNAs and established a m6A-related lncRNAs prognostic signature. Risk score=AC015813.1∗(0.0086)+EMX2OS∗(-0.0101)+LINC00173∗(0.0309)+PWAR5∗(-0.0146)+SNHG1∗(0.0043). The signature showed a better predictive ability than other clinical indicators, including tumor node metastasis classification (TNM), histological, and pathological stages. In the high-risk group, M0 macrophages, CD8+ T cells, and regulatory T cells had significantly higher scores. Contrarily, in the low-risk group, activated dendritic cells, M1 macrophages, mast resting cells, and monocytes had significantly higher scores. In the high-risk group, LSECtin was overexpressed. In the low-risk group, PD-L1 was overexpressed. Moreover, high-risk patients may benefit more from AZ628.ConclusionsIn conclusion, prognosis prediction of patients with KIRC and new insights for immunotherapy are provided by the m6A-related lncRNA prognostic signature.
| S-EPMC9536954 | biostudies-literature
Project description:Necroptosis is a new type of programmed cell death and involves the occurrence and development of various cancers. Moreover, the aberrantly expressed lncRNA can also affect tumorigenesis, migration, and invasion. However, there are few types of research on the necroptosis-related lncRNA (NRL), especially in kidney renal clear cell carcinoma (KIRC). In this study, we analyzed the sequencing data obtained from the TGCA-KIRC dataset, then applied the LASSO and COX analysis to identify 6 NRLs (AC124854.1, AL117336.1, DLGAP1-AS2, EPB41L4A-DT, HOXA-AS2, and LINC02100) to construct a risk model. Patients suffering from KIRC were divided into high- and low-risk groups according to the risk score, and the patients in the low-risk group had a longer OS. This signature can be used as an indicator to predict the prognosis of KIRC independent of other clinicopathological features. In addition, the gene set enrichment analysis showed that some tumor and immune-associated pathways were more enriched in a high-risk group. We also found significant differences between the high and low-risk groups in the infiltrating immune cells, immune functions, and expression of immune checkpoint molecules. Finally, we use the "pRRophetic" package to complete the drug sensitivity prediction, and the risk score could reflect patients' response to 8 small molecule compounds. In general, NRLs divided KIRC into two subtypes with different risk scores. Furthermore, this signature based on the 6 NRLs could provide a promising method to predict the prognosis and immune response of KIRC patients. To some extent, our findings helped give a reference for further research between NRLs and KIRC and find more effective therapeutic drugs for KIRC.
| S-EPMC9818734 | biostudies-literature
Project description:Emerging evidence has uncovered that tumor-infiltrating immune cells (TIICs) play significant roles in regulating the tumorigenesis and progression of clear cell renal cell carcinoma (ccRCC). However, the exact composition of TIICs and their prognostic values in ccRCC have not been well defined. A total of 534 ccRCC samples with survival information and TIIC data from The Cancer Genome Atlas (TCGA) dataset were included in our research. The ImmuCellAI tool was employed to estimate the abundance of 24 TIICs and further survival analysis explored the prognostic values of TIICs in ccRCC. In addition, the expression levels of immunosuppressive molecules (PDL1, PD1, LAG3, and CTLA4) in the high- and low-risk groups were explored. Various subtypes of TIICs had distinct infiltrating features and most TIICs exhibited dysregulated abundance between normal and tumor tissues. Moreover, specific kinds of TIICs had encouraging prognostic values in ccRCC. Further analysis constructed a 4-TIICs signature to evaluate the prognosis of ccRCC patients. Cox regression analyses confirmed the independent prognostic role of the signature in ccRCC. Moreover, immunosuppressive molecules, including PD1, LAG3, and CTLA4, were significantly upregulated in the high-risk group and predicted poor prognosis. However, PDL1 was not changed between high- and low-risk groups and could not predict poor prognosis. To sum up, our research explored the landscape of TIICs in ccRCC and established a novel 4-TIIC prognostic signature, which could effectively predict the prognosis for patients with ccRCC. Based on this signature, we also concluded that PDL1 may not predict prognosis in ccRCC.
| S-EPMC9606472 | biostudies-literature
Project description:BackgroundRecent studies have demonstrated that long non-coding RNAs (lncRNAs) are involved in regulating tumor cell ferroptosis. However, prognostic signatures based on ferroptosis-related lncRNAs (FRLs) and their relationship to the immune microenvironment have not been comprehensively explored in clear cell renal cell carcinoma (ccRCC).MethodsIn the present study, the expression profiles of ccRCC were acquired from The Cancer Genome Atlas (TCGA) database; 459 patient specimens and 69 adjacent normal tissues were randomly separated into training or validation cohorts at a 7:3 ratio. We identified 7 FRLs that constitute a prognostic signature according to the differential analysis, correlation analysis, univariate regression, and least absolute shrinkage and selection operator (LASSO) Cox analysis. To identify the independence of risk score as a prognostic factor, univariate and multivariate regression analyses were also performed. Furthermore, CIBERSORT was conducted to analyze the immune infiltration of patients in the high-risk and low-risk groups. Subsequently, the differential expression of immune checkpoint and m6A genes was analyzed in the two risk groups.ResultsA 7-FRLs prognostic signature of ccRCC was developed to distinguish patients into high-risk and low-risk groups with significant survival differences. This signature has great prognostic performance, with the area under the curve (AUC) for 1, 3, and 5 years of 0.713, 0.700, 0.726 in the training set and 0.727, 0.667, and 0.736 in the testing set, respectively. Moreover, this signature was significantly associated with immune infiltration. Correlation analysis showed that risk score was positively correlated with regulatory T cells (Tregs), activated CD4 memory T cells, CD8 T cells and follicular helper T cells, whereas it was inversely correlated with monocytes and M2 macrophages. In addition, the expression of fourteen immune checkpoint genes and nine m6A-related genes varied significantly between the two risk groups.ConclusionWe established a novel FRLs-based prognostic signature for patients with ccRCC, containing seven lncRNAs with precise predictive performance. The FRLs prognostic signature may play a significant role in antitumor immunity and provide a promising idea for individualized targeted therapy for patients with ccRCC.
| S-EPMC9758795 | biostudies-literature
Project description:BackgroundIn the past decade, immunotherapy has been widely used in the treatment of various tumors, such as PD-1/PD-L1 inhibitors. Although clear cell renal cell carcinoma (ccRCC) has been shown to be sensitive to immunotherapy, it is effective only in several cases, which brings great obstacles to anti-tumor therapy for patients. Lawson et al. have successfully identified 182 "core cancer innate immune escape genes" whose deletion makes cancer cells more sensitive or resistant to T-cell attack.MethodsIn this research, we sought to explore genes closely associated with ccRCC among the 182 core cancer innate immune escape genes. We used online databases to screen mutated genes in ccRCC, and then used ConsensusClusterPlus to cluster clinical samples to analyze differences in clinical prognosis and immune components between the two subgroups. In addition, the immune escape score was calculated using lasso cox regression, and a stable tumor immune escape-related nomogram was established to predict the overall survival of patients.ResultsHigher immune escape score was significantly correlated with shorter survival time. Meanwhile, through the validation of the external cohort and the correlation analysis of the immune microenvironment, we proved that IFNAR1 is the key gene regulating immune escape in ccRCC, and we also found that the function of IFNAR1 in promoting immune activation is achieved by facilitating the infiltration of CD4+ T cells and CD8+ T cells. IFNAR1 regulates the malignant behavior of ccRCC by inhibiting the proliferation and migration properties.ConclusionsIFNAR1 may become a key biomarker for evaluating the efficacy of ccRCC immunotherapy and may also be a potential target for immunotherapy.
| S-EPMC9818644 | biostudies-literature