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Tumor-Infiltrating Immune Cell Signature Predicts the Prognosis and Chemosensitivity of Patients With Pancreatic Ductal Adenocarcinoma.

ABSTRACT: Objective:Tumor-infiltrating immune cells might add a predictive value for the prognostic stratification of patients with pancreatic ductal adenocarcinoma (PDAC) and chemotherapy response. We aimed to develop a prognostic model based on the tumor-infiltrating immune cell signature to improve the prediction of survival and chemotherapy benefits of patients with PDAC. Methods:The abundance of tumor-infiltrating immune cells for 661 patients with PDAC from four different cohorts with survival data was collected in the training cohorts. Cox regression analysis and meta-analysis of immune cells were conducted to generate the tumor immune cell score (TICS) for prognostic stratification. Other two independent cohorts including 188 patients were then used to validate the model. Those patients who underwent chemotherapy were used to further analyze the value of TICS for predicting the chemotherapy response. Furthermore, the difference in the somatic mutations and immune-related molecules between the TICS subgroups was analyzed. Results:6 out of 28 immune cells were found to be significantly associated with PDAC prognosis in the training cohorts (all P < 0.05). The developed TICS could significantly predict the PDAC survival and chemotherapy benefit both in the training and the external validation cohorts (log-rank test, P < 0.05). Significant differences were found in different TICS subgroups in terms of the immune characteristics, checkpoint genes, and tumor mutational burden. Functional and pathway analyses further proved that the TICS was significantly related to the tumor immunity response in patients with PDAC. Conclusion:TICS might be used to predict PDAC patients with a better survival and greater chemotherapy benefit.

SUBMITTER: Gao Y

PROVIDER: S-EPMC7545319 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Tumor-Infiltrating Immune Cell Signature Predicts the Prognosis and Chemosensitivity of Patients With Pancreatic Ductal Adenocarcinoma.

Gao Yuzhen Y Chen Shipeng S Vafaei Somayeh S Zhong Xiaoli X

Frontiers in oncology 20200925

<h4>Objective</h4>Tumor-infiltrating immune cells might add a predictive value for the prognostic stratification of patients with pancreatic ductal adenocarcinoma (PDAC) and chemotherapy response. We aimed to develop a prognostic model based on the tumor-infiltrating immune cell signature to improve the prediction of survival and chemotherapy benefits of patients with PDAC.<h4>Methods</h4>The abundance of tumor-infiltrating immune cells for 661 patients with PDAC from four different cohorts with ...[more]

PMID: 33102222

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Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) has persisted as one of the worst prognostic tumors with a 5-year survival rate of lower than 6%. Although many studies have investigated PDAC, new biomarkers are required to ensure early diagnosis and predict the prognosis of PDAC.MethodsIn this study, we used bioinformatics methods to evaluate differences in the expression of solute carrier (SLC) family genes in tumors and non-tumors. A Kaplan-Meier analysis, least absolute shrinkage and selection operator (LASSO) analysis, and multivariate Cox proportional hazards regression analysis were used to evaluate the relationship between SLC genes and prognosis using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. The prognostic signature was constructed depending on the risk score to assess the impact of multiple genes on the prognosis, receiver operating characteristic (ROC) curves and forest plot was constructed to assess the ability to predict the prognosis and effects of clinical variables in both high- and low-risk groups. Tumor-infiltrating immune cells were evaluated using Cell-type Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) in both high- and low-risk groups.ResultsIn 32 SLC genes, 9 were significantly associated with the OS after LASSO analysis. SLC19A3 (P=0.007), SLC25A39 (P=0.027), SLC39A11 (P=0.043) were significantly associated with prognosis and included into the prognostic model. CIBERSORT demonstrated that memory B cells (P=0.004), naive B cells (P=0.007), CD8 T cells (P=0.003), activated memory CD4 T cells (P=0.004), and activated NK cells (P=0.019) were significantly higher in the low-risk group. Gene set enrichment analysis (GSEA) showed that potential molecular mechanisms enriched in MYC and p53 signaling pathways.ConclusionsSLC19A3, SLC25A35, and SLC39A11 were significantly relative to the prognosis of PDAC and changed the tumor microenvironment, as well as the MYC and p53 signaling pathways. The SLC19A3 gene may represent a new tumor suppressor in PDAC.

Project description:PurposePancreatic ductal adenocarcinoma (PDAC) is one of the highest fatality rate cancers with poor survival rates. The tumor microenvironment (TME) is vital for tumor immune responses, leading to resistance to chemotherapy and poor prognosis of PDAC patients. This study aimed to provide a comprehensive evaluation of the immune genes and microenvironment in PDAC that might help in predicting prognosis and guiding clinical treatments.MethodsWe developed a prognosis-associated immune signature (i.e., PAIS) based on immune-associated genes to predict the overall survival of patients with PDAC. The clinical significance and immune landscapes of the signature were comprehensively analyzed.ResultsOwing to gene expression profiles from TCGA database, functional enrichment analysis revealed a significant difference in the immune response between PDAC and normal pancreas. Using transcriptome data analysis of a training set, we identified an immune signature represented by 5 genes (ESR2, IDO1, IL20RB, PPP3CA, and PLAU) related to the overall survival of patients with PDAC, significantly. This training set was well-validated in a test set. Our results indicated a clear association between a high-risk score and a very poor prognosis. Stratification analysis and multivariate Cox regression analysis revealed that PAIS was an important prognostic factor. We also found that the risk score was positively correlated with the inflammatory response, antigen-presenting process, and expression level of some immunosuppressive checkpoint molecules (e.g., CD73, PD-L1, CD80, and B7-H3). These results suggested that high-risk patients had a suppressed immune response. However, they could respond better to chemotherapy. In addition, PAIS was positively correlated with the infiltration of M2 macrophages in PDAC.ConclusionsThis study highlighted the relationship between the immune response and prognosis in PDAC and developed a clinically feasible signature that might serve as a powerful prognostic tool and help further optimize the cancer therapy paradigm.

Project description:BackgroundThe immune response in the tumor microenvironment (TME) plays a crucial role in cancer progression and recurrence. We aimed to develop an immune-related gene (IRG) signature to improve prognostic predictive power and reveal the immune infiltration characteristics of pancreatic ductal adenocarcinoma (PDAC).MethodsThe Cancer Genome Atlas (TCGA) PDAC was used to construct a prognostic model as a training cohort. The International Cancer Genome Consortium (ICGC) and the Gene Expression Omnibus (GEO) databases were set as validation datasets. Prognostic genes were screened by using univariate Cox regression. Then, a novel optimal prognostic model was developed by using least absolute shrinkage and selection operator (LASSO) Cox regression. Cell type identification by estimating the relative subsets of RNA transcripts (CIBERSORT) and estimation of stromal and immune cells in malignant tumors using expression data (ESTIMATE) algorithms were used to characterize tumor immune infiltrating patterns. The tumor immune dysfunction and exclusion (TIDE) algorithm was used to predict immunotherapy responsiveness.ResultsA prognostic signature based on five IRGs (MET, ERAP2, IL20RB, EREG, and SHC2) was constructed in TCGA-PDAC and comprehensively validated in ICGC and GEO cohorts. Multivariate Cox regression analysis demonstrated that this signature had an independent prognostic value. The area under the curve (AUC) values of the receiver operating characteristic (ROC) curve at 1, 3, and 5 years of survival were 0.724, 0.702, and 0.776, respectively. We further demonstrated that our signature has better prognostic performance than recently published ones and is superior to traditional clinical factors such as grade and tumor node metastasis classification (TNM) stage in predicting survival. Moreover, we found higher abundance of CD8+ T cells and lower M2-like macrophages in the low-risk group of TCGA-PDAC, and predicted a higher proportion of immunotherapeutic responders in the low-risk group.ConclusionsWe constructed an optimal prognostic model which had independent prognostic value and was comprehensively validated in external PDAC databases. Additionally, this five-genes signature could predict immune infiltration characteristics. Moreover, the signature helped stratify PDAC patients who might be more responsive to immunotherapy.

Project description:A six-gene signature predicts survival of patients with localized pancreatic ductal adenocarcinoma Pancreatic ductal adenocarcinoma (PDAC), comprising over 90% of all pancreatic cancers, remains a lethal disease with an estimated 232,000 new cases, 227,000 deaths per year worldwide, and a less than 5% five-year survival rate. Currently the standard of care for the 20% of patients with localized disease is surgery followed by chemotherapy, and in some cases radiation. Unfortunately despite the use of adjuvant therapy, median survival remains at best 23 months. It is important to note however, that up to 27% of patients with resected PDAC can survive for five years. However, in these studies examining actual long-term survivors, only two have found that adjuvant therapy was associated with improved survival. In addition, randomized controlled trials of gemcitabine-based chemotherapy demonstrate an improvement in median survival of at best 3 months. One possible conclusion from these studies is that tumor biology dictates outcome and that our current adjuvant therapy has only a modest impact on altering a patient's course.Hypothesizing that the dismal outcome of patients with localized disease is due to the presence of micrometastasic disease, current clinical investigation has focused on preoperative or neoadjuvant therapy. This approach, where patients who cannot tolerate the stress of therapy or develop metastatic disease during treatment are spared surgery, has demonstrated an overall survival of 34 months in this highly selected patient population. Therefore the ability to select patients who would most benefit from a neoadjuvant approach may be important. One way to do this is to define a prognostic gene signature that can identify patients with more aggressive tumor biology upfront. reference x sample The 30 Nebraska and UNC samples were not analyzed with clinical data so it is not provided. One of the PE samples is missing some clinical data.

Dataset Information

Tumor-Infiltrating Immune Cell Signature Predicts the Prognosis and Chemosensitivity of Patients With Pancreatic Ductal Adenocarcinoma.

Publications

Tumor-Infiltrating Immune Cell Signature Predicts the Prognosis and Chemosensitivity of Patients With Pancreatic Ductal Adenocarcinoma.

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