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Development and validation of an immune checkpoint-based signature to predict prognosis in nasopharyngeal carcinoma using computational pathology analysis.

ABSTRACT: BACKGROUND:Immunotherapy, especially immune checkpoint inhibition, has provided powerful tools against cancer. We aimed to detect the expression of common immune checkpoints and evaluate their prognostic values in nasopharyngeal carcinoma (NPC). METHODS:The expression of 9 immune checkpoints consistent with 13 features was detected in the training cohort (n?=?208) by immunohistochemistry and quantified by computational pathology. Then, the LASSO cox regression model was used to construct an immune checkpoint-based signature (ICS), which was validated in a validation cohort containing 125 patients. RESULTS:High positive expression of PD-L1 and B7-H4 was observed in tumour cells (TCs), whereas PD-L1, B7-H3, B7-H4, IDO-1, VISTA, ICOS and OX40 were highly expressed in tumour-associated immune cells (TAICs). Eight of the 13 immune features were associated with patient overall survival, and an ICS classifier consisting of 5 features (B7-H3TAIC, IDO-1TAIC, VISTATAIC, ICOSTAIC, and LAG3TAIC) was established. Patients with high-risk scores in the training cohort had shorter overall (P?

SUBMITTER: Wang YQ

PROVIDER: S-EPMC6854706 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Development and validation of an immune checkpoint-based signature to predict prognosis in nasopharyngeal carcinoma using computational pathology analysis.

Wang Ya-Qin YQ Zhang Yu Y Jiang Wei W Chen Yu-Pei YP Xu Shuo-Yu SY Liu Na N Zhao Yin Y Li Li L Lei Yuan Y Hong Xiao-Hong XH Liang Ye-Lin YL Li Jun-Yan JY Zhang Lu-Lu LL Yun Jing-Ping JP Sun Ying Y Li Ying-Qin YQ Ma Jun J

Journal for immunotherapy of cancer 20191113 1

<h4>Background</h4>Immunotherapy, especially immune checkpoint inhibition, has provided powerful tools against cancer. We aimed to detect the expression of common immune checkpoints and evaluate their prognostic values in nasopharyngeal carcinoma (NPC).<h4>Methods</h4>The expression of 9 immune checkpoints consistent with 13 features was detected in the training cohort (n = 208) by immunohistochemistry and quantified by computational pathology. Then, the LASSO cox regression model was used to co ...[more]

PMID: 31722750

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Project description:BACKGROUND:The tumor immune microenvironment has clinicopathological significance in predicting prognosis and therapeutic efficacy. We aimed to develop an immune signature to predict distant metastasis in patients with nasopharyngeal carcinoma (NPC). METHODS:Using multiplexed quantitative fluorescence, we detected 17 immune biomarkers in a primary screening cohort of 54 NPC tissues presenting with/without distant metastasis following radical therapy. The LASSO (least absolute shrinkage and selection operator) logistic regression model used statistically significant survival markers in the training cohort (n=194) to build an immune signature. The prognostic and predictive accuracy of it was validated in an external independent group of 304 patients. RESULTS:Eight statistically significant markers were identified in the screening cohort. The immune signature consisting of four immune markers (PD-L1+ CD163+, CXCR5, CD117) in intratumor was adopted to classify patients into high and low risk in the training cohort and it showed a high level of reproducibility between different batches of samples (r=0.988 for intratumor; p<0.0001). High-risk patients had shorter distant metastasis-free survival (HR 5.608, 95%?CI 2.619 to 12.006; p<0.0001) and progression-free survival (HR 2.798, 95%?CI 1.498 to 5.266; p=0·001). The C-indexes which reflected the predictive capacity in training and validation cohort were 0.703 and 0.636, respectively. Low-risk patients benefited from induction chemotherapy plus concurrent chemoradiotherapy (IC+CCRT) (HR 0.355, 95%?CI 0.147 to 0.857; p=0·021), while high-risk patients did not (HR 1.329, 95% CI 0.543 to 3.253; p=0·533). To predict the individual risk of distant metastasis, nomograms with the integration of both immune signature and clinicopathological risk factors were developed. CONCLUSIONS:The immune signature provided a reliable estimate of distant metastasis risk in patients with NPC and might be applied to identify the cohort which benefit from IC+CCRT.

Project description:Background: Hepatocellular carcinoma (HCC) is characterized by a poor prognosis and accounts for the fourth common cause of cancer-related deaths. Recently, pyroptosis has been revealed to be involved in the progression of multiple cancers. However, the role of pyroptosis in the HCC prognosis remains elusive. Methods: The clinical information and RNA-seq data of the HCC patients were collected from the TCGA-LIHC datasets, and the differential pyroptosis-related genes (PRG) were firstly explored. The univariate Cox regression and consensus clustering were applied to recognize the HCC subtypes. The prognostic PRGs were then submitted to the LASSO regression analysis to build a prognostic model in the TCGA training cohort. We further evaluated the predictive model in the TCGA test cohort and ICGC validation cohort (LIRI-JP). The accuracy of prediction was validated using the Kaplan-Meier (K-M) and receiver operating characteristic (ROC) analyses. The single-sample gene set enrichment analysis (ssGSEA) was used to determine the differential immune cell infiltrations and related pathways. Finally, the expression of the prognostic genes was validated by qRT-PCR in vivo and in vitro. Results: We identified a total of 26 differential PRGs, among which three PRGs comprising GSDME, GPX4, and SCAF11 were subsequently chosen for constructing a prognostic model. This model significantly distinguished the HCC patients with different survival years in the TCGA training, test, and ICGC validation cohorts. The risk score of this model was confirmed as an independent prognostic factor. A nomogram was generated indicating the survival years for each HCC patient. The ssGSEA demonstrated several tumor-infiltrating immune cells to be remarkably associated with the risk scores. The qRT-PCR results also showed the apparent dysregulation of PRGs in HCC. Finally, the drug sensitivity was analyzed, indicating that Lenvatinib might impact the progression of HCC via targeting GSDME, which was also validated in human Huh7 cells. Conclusion: The PRG signature comprised of GSDME, GPX4, and SCAF11 can serve as an independent prognostic factor for HCC patients, which would provide further evidence for more clinical and functional studies.

Project description:Immune checkpoint genes (ICGs), the foundation of immunotherapy, are involved in the incidence and progression of hepatocellular carcinoma (HCC). Cuproptosis is characterized by copper-induced cell death, and this novel cell death pathway has piqued the interest of researchers in recent years. It is worth noting that there is little information available in the literature to determine the relationship between cuproptosis and anti-tumor immunity. We identified 39 cuproptosis-related ICGs using ICGs co-expressed with cuproptosis-related genes. A prognostic risk signature was constructed using the Cox regression and the least absolute shrinkage and selection operator analysis methods. The signature was built using the Cancer Genome Atlas (TCGA)-Liver Hepatocellular Carcinoma database. The TCGA and International Cancer Genome Consortium cohorts were classified into two groups; the low- and high-risk groups were determined using a prognostic signature comprised of five genes. The multivariate Cox regression analysis revealed that the signature could independently predict overall survival. Furthermore, the level of immune infiltration analysis revealed the robustness of the prognostic signature-immune cell infiltration relationship observed for Tregs, macrophages, helper T cells, and naive B cells. Both groups showed significant differences in immune checkpoint expression levels. The gene enrichment analysis was used for characterization, and the results revealed that enriching various pathways such as PI3K-AKT-mTOR signaling, glycolysis, Wnt/beta-catenin signaling, and unfolded protein response could potentially influence the prognosis of patients with HCC and the level of immune infiltration. The sensitivity of the two groups of patients to various drug-targeted therapy methods and immunotherapy was analyzed. In conclusion, the findings presented here lay the foundation for developing individualized treatment methods for HCC patients. The findings also revealed that studying the cuproptosis-based pathway can aid in the prognosis of HCC patients. It is also possible that cuproptosis contributes to developing anti-tumor immunity in patients.

Dataset Information

Development and validation of an immune checkpoint-based signature to predict prognosis in nasopharyngeal carcinoma using computational pathology analysis.

Publications

Development and validation of an immune checkpoint-based signature to predict prognosis in nasopharyngeal carcinoma using computational pathology analysis.

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