Immune gene signatures for predicting durable clinical benefit of anti-PD-1 immunotherapy in patients with non-small cell lung cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE136961 | GEO | 2020/02/03
REPOSITORIES: GEO
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Project description:Immunotherapy has improved the prognosis of patients with advanced non-small cell lung
cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC.The authors retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic (ROC) curve. Among these models(RF MLP LR XGBoost), our reproduced onnx models have better performance, especially for random forest. The response variable with a value (1/0) indicates the (efficacy/inefficacy) of PD-1/PD-L1 monotherapy in patients with advanced NSCLC
2023-07-11 | BIOMD0000001074 | BioModels
Project description:Purpose: We aimed to investigate the distinct transcriptional landscape in the poor responders to concurrent chemoradiotherapy (CCRT) and to gain mechanistic insights on treatment resistance in cervical cancer. Methods: RNA sequencing was performed using archived pre-treatment tissue biopsies of patients with locally advanced cervical cancer treated with concurrent platinum-based CCRT. Transcriptome data of patients with no durable benefit (NDB; progression-free period < 3 years) and durable clinical benefit (DCB; progression-free period > 5 years) after were compared. NDB score was estimated for each patient using the differentially expressed genes between NDB and DCB patients. Three independent cohorts, including The Cancer Genome Atlas cervical cancer (TCGA-CESC) cohort, were utilized for validation of NDB score. Potential response to PD-1 blockade was estimated with Tumor Immune Dysfunction and Exclusion (TIDE) score and T-cell-inflamed gene expression profile (GEP). Results: Patients with NDB exhibited a distinct transcriptional profile compared to those with DCB such as higher signatures of extracellular matrix organization and epithelial-to-mesenchymal transition. The fraction of cancer-associated fibroblasts (CAFs) within the tumor was significantly higher in NDB than DCB patients. Higher NDB score was significantly associated with poor survival in the TCGA-CESC cohort (n = 274; P = 0.015), but only in patients that received curative aim radiotherapy (P = 0.002) and not in patients who received other treatments (P = 0.57). The transcriptomic characteristics of patients with NDB were recapitulated in patients with high NDB score in TCGA-CESC. Patients with high NDB score displayed significantly higher TIDE prediction score and lower T-cell-inflamed GEP score compared to patients with low NDB scores. Conclusion: Cervical cancer patients with poor treatment outcome following CCRT exhibited a distinct gene signature that was able to predict treatment outcomes. For poor responders, immune checkpoint inhibitors may be less effective and CAF-targeting treatments may be a promising approach.
2021-03-02 | GSE168009 | GEO
Project description:Purpose Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for individual non-small-cell lung cancer (NSCLC) patients. Most current molecular signatures for lung cancer are prognostic only and provide limited information with regard to the functional importance of the genes selected. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefit of ACT in NSCLC. Experimental Design An 18-hub-gene prognosis signature was developed through a systems biology approach using a large NSCLC dataset from the Director’s Challenge Consortium. The prognostic value of this signature was tested in NSCLC patients from UT Lung SPORE cohort and additional five public datasets. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefit in NSCLC. Results We showed that the 18-hub-gene set can robustly predict the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The refined 12-gene functional set was successfully validated in two independent datasets. The predicted benefit group showed significant improvement in survival after ACT (JBR.10 clinical trial data: hazard ratio=0.36, p=0.038; UT Lung SPORE data: hazard ratio=0.34, p=0.017), while the predicted non-benefit group showed no survival improvement. Conclusions This is the first study to integrate genetic aberration, genome-wide RNAi functional data, and mRNA expression data to identify a functional gene set that is predictive for ACT benefits. This 12-gene predictive signature has been validated in two independent NSCLC cohorts. Patients were eligible to enter the study if they underwent curative resection for NSCLC at MD Anderson Cancer Center between December 1996 and June 2007, and patients with radiation therapy were excluded from the study. All tissue samples were obtained by surgical resection from patients who had provided written informed consent. Tissues were stored at −140°C after being snap frozen in liquid nitrogen. Serial sectioning of each sample was used to histologically evaluate tumor and malignant cells content before RNA extraction. The primary tumor tissues from 176 patients were selected randomly from similar samples in the UT Lung SPORE tumor collection based on stringent, predefined quality control procedures before any data analysis, including the presence of ≥70% tumor tissue and ≥50% malignant cells in the frozen tissue used for RNA extraction. In this cohort, 133 patients are adenocarcinomas (ADCs) and 43 patients are squamous cell carcinomas (SCCs); 49 patients received ACT (mainly Carboplatin plus Taxanes) and 127 patients did not receive ACT.
2013-01-30 | E-GEOD-42127 | biostudies-arrayexpress
Project description:Purpose Prospectively identifying who will benefit from adjuvant chemotherapy (ACT) would improve clinical decisions for individual non-small-cell lung cancer (NSCLC) patients. Most current molecular signatures for lung cancer are prognostic only and provide limited information with regard to the functional importance of the genes selected. In this study, we aim to develop and validate a functional gene set that predicts the clinical benefit of ACT in NSCLC. Experimental Design An 18-hub-gene prognosis signature was developed through a systems biology approach using a large NSCLC dataset from the Director’s Challenge Consortium. The prognostic value of this signature was tested in NSCLC patients from UT Lung SPORE cohort and additional five public datasets. The 18-hub-gene set was then integrated with genome-wide functional (RNAi) data and genetic aberration data to derive a 12-gene predictive signature for ACT benefit in NSCLC. Results We showed that the 18-hub-gene set can robustly predict the prognosis of patients with adenocarcinoma in all validation datasets across four microarray platforms. The refined 12-gene functional set was successfully validated in two independent datasets. The predicted benefit group showed significant improvement in survival after ACT (JBR.10 clinical trial data: hazard ratio=0.36, p=0.038; UT Lung SPORE data: hazard ratio=0.34, p=0.017), while the predicted non-benefit group showed no survival improvement. Conclusions This is the first study to integrate genetic aberration, genome-wide RNAi functional data, and mRNA expression data to identify a functional gene set that is predictive for ACT benefits. This 12-gene predictive signature has been validated in two independent NSCLC cohorts.
2013-01-30 | GSE42127 | GEO
Project description:Immune checkpoint inhibitors (ICIs) have transformed the treatment of melanoma. However, the majority of patients have primary or acquired resistance to ICIs, limiting durable responses and patient survival. Interferon-gamma (IFNg) signaling and the expression of IFNg-stimulated genes correlate with either response or resistance to ICIs, in a context-dependent manner. While IFNg-inducible immunostimulatory genes are required for response to ICIs, chronic IFNg signaling induces the expression of immunosuppressive genes, promoting resistance to these therapies. Here, we show that high levels of ULK1 correlate with poor survival in melanoma patients and overexpression of ULK1 in melanoma cells enhances IFNg-induced expression of immunosuppressive genes, with minimal effects on the expression of immunostimulatory genes. In contrast, genetic or pharmacological inhibition of ULK1 reduces expression of IFNg-induced immunosuppressive genes. ULK1 binds IRF1 in the nuclear compartment of melanoma cells, controlling its binding to the PD-L1 promoter region. Additionally, pharmacological inhibition of ULK1 in combination with anti-PD-1 therapy further reduces melanoma tumor growth and enhances anti-tumor immune responses in vivo. Our data suggest that targeting ULK1 represses IFNg-dependent immunosuppression. These findings support the combination of ULK1 drug-targeted inhibition with ICIs for the treatment of melanoma patients to improve response rates and patient outcomes.
2023-02-02 | PXD035347 | Pride
Project description:Background: The JBR.10 trial demonstrated significant survival benefit from adjuvant cisplatin/vinorelbine (ACT) in stage IB-II NSCLC (HR 0.69, p=0.04), but stage IB patients did not derive significant benefit (HR: 0.94, p= 0.79). We hypothesized that expression profiling could identify stage-independent subgroups of patients who might benefit from adjuvant chemotherapy. Methods: Gene expression profiling was conducted on mRNA isolated from frozen JBR.10 tumor samples (either from patients under observation [OBS], or treated with ACT). The minimum gene set that selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified and this gene signature was used to classify patients into high and low risk for death after surgery, and predict ACT effect. The prognostic gene signature was additionally tested on ACT patients and publicly available microarray datasets. Results: A 15-gene signature separated OBS patients into equal high and low risk subgroups with significantly different prognoses (HR 15.02, 95% CI 5.12-44.04, p=0.0001). The signature was prognostic in both stage IB and II. It was also predictive of improved survival following ACT treatment in high-risk patients (HR 0.33, 95% CI 0.17-0.63, p=0.0005), but not in low risk patients (HR 3.67, 95% CI 1.22-11.06, p=0.0133; interaction p=0.0001). The prognostic effect of the signature was validated in two independent gene expression datasets of 169 stage I-II adenocarcinoma and 106 squamous cell carcinoma patients. Conclusions: This microarray-based 15-gene prognostic expression signature is stage and histology independent and may select early stage NSCLC patients who are most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine. Keywords: Expression profiling by microarray; prognosis prediction 90 samples
2010-09-09 | E-GEOD-14814 | biostudies-arrayexpress
Project description:Therapeutic combinations to alter solid tumor microenvironments (TME) in immunosuppressive tumors such as breast cancer are essential to improve their responses to immune checkpoint inhibitors (ICIs). Entinostat, an oral histone deacetylase inhibitor (HDACi), has been shown to improve responses to ICIs in various tumor models with immunosuppressive TMEs. The precise and comprehensive alterations to the TME induced by entinostat remain unknown. Here, we employ single-cell RNA-sequencing on HER2 overexpressing breast tumors from mice treated with entinostat and ICIs to characterize for the first time changes across all cell types within the TME. This analysis demonstrates that treatment with entinostat induces a shift from a pro-tumor to an anti-tumor TME signature characterized predominantly by changes in the myeloid cells. We confirm myeloid-derived suppressor cells (MDSCs) within entinostat-treated tumors are associated with a less suppressive G-MDSC phenotype and now demonstrate altered suppressive signaling involves the NFkB and STAT3 pathways. In addition to MDSCs, tumor-associated macrophages are epigenetically reprogrammed toward an anti-tumor M1-like phenotype likely contributing to a more sensitized TME. Overall, our in-depth analysis suggests entinostat-induced changes on multiple myeloid cell types reduce immunosuppression and increase mechanisms of an anti-tumor response that improve sensitivity to ICI. Sensitization of the TME by entinostat could ultimately broaden the population of patients with breast cancer who could derive benefit from ICIs.
2022-01-18 | GSE166321 | GEO
Project description:Purpose: The JBR.10 trial demonstrated benefit from adjuvant cisplatin/vinorelbine (ACT) in early-stage non-small-cell lung cancer (NSCLC). We hypothesized that expression profiling may identify stage-independent subgroups who might benefit from ACT. Patients and Methods: Gene expression profiling was conducted on mRNA from 133 frozen JBR.10 tumor samples (62 observation [OBS], 71 ACT). The minimum gene set that was selected for the greatest separation of good and poor prognosis patient subgroups in OBS patients was identified. The prognostic value of this gene signature was tested in four independent published microarray data sets and by quantitative reverse-transcriptase polymerase chain reaction (RT-qPCR). Results: A 15-gene signature separated OBS patients into high-risk and low-risk subgroups with significantly different survival (hazard ratio [HR], 15.02; 95% CI, 5.12 to 44.04; P .001; stage I HR, 13.31; P .001; stage II HR, 13.47; P .001). The prognostic effect was verified in the same 62 OBS patients where gene expression was assessed by qPCR. Furthermore, it was validated consistently in four separate microarray data sets (total 356 stage IB to II patients without adjuvant treatment) and additional JBR.10 OBS patients by qPCR (n 19). The signature was also predictive of improved survival after ACT in JBR.10 high-risk patients (HR, 0.33; 95% CI, 0.17 to 0.63; P .0005), but not in low-risk patients (HR, 3.67; 95% CI, 1.22 to 11.06; P = .0133; interaction P .001). Significant interaction between risk groups and ACT was verified by qPCR. Conclusion: This 15-gene expression signature is an independent prognostic marker in early-stage, completely resected NSCLC, and to our knowledge, is the first signature that has demonstrated the potential to select patients with stage IB to II NSCLC most likely to benefit from adjuvant chemotherapy with cisplatin/vinorelbine.
2010-09-09 | GSE14814 | GEO
Project description:Adaptive immune escape of tumor cells by upregulation of ligands for programmed death 1 (PD-1) has been identified as an important and targetable pathway in many cancer types. Many clinical trials have demonstrated that targeting PD-1 or its ligand PD-L1 with immune checkpoint inhibitors (ICI) can restore anti-tumor immunity and induce durable remission. In patients with non-small cell lung cancer (NSCLC), several trials have demonstrated a survival benefit with ICI in patients with metastatic and locally advanced NSCLC.Yet, most patients have primary resistance to PD-1 or PD-L1 blockade during treatment: approximately 20% of unselected patients with NSCLC achieve a partial response while 40-50% have progressive disease as best response. Understanding mechanisms of primary resistance to PD-(L)1 blockade is important in the search for potentially targetable pathways and may ultimately allow discrimination between patients that benefit from PD-(L)1 blockade and those requiring combination or other approaches. We collected PBMCs and serum samples from 35 patients with NSCLC before and during PD-1 blockade treatment with nivolumab. We analyzed differentially expressed genes in CD8+ T cells from the peripheral blood of 5 patients with partial response and 5 patients with primary progressive disease to identify mechanisms of resistance to PD-1 therapy. Cells were collected from samples taken before and after 4 weeks of treatment.
2021-03-01 | GSE111414 | GEO
Project description:Immune checkpoint inhibitors (ICIs) targeting PD-1/PD-L1 axis have made a breakthrough in the treatment of non-small cell lung cancer (NSCLC). However, a paradoxical boost in tumor growth was reported in a fraction of NSCLC patients after ICIs administration: a novel pattern of cancer progression defined “hyperprogressive disease” (HPD). Because the mechanism of HPD onset has not completely elucidated yet, this study aimed at investigating the cellular and molecular bases of this clinical phenomenon. Pre-treatment histological samples obtained from NSCLC patients were evaluated by immunohistochemistry (IHC) for immune cell infiltrate. Tissue samples from all patients with HPD showed tumor-infiltration by M2-like macrophages. To validate these findings in preclinical models, we utilized athymic nude mice that, lacking T-cells that may cloud the results, represent a suitable model to evaluate the role of macrophages in determining HPD. Immunodeficient mice were injected with human NSCLC NCI-H460 cell line, treated with anti-PD-1 antibody and tumor growth was evaluated over time. Anti-PD-1 treated H460 tumor-bearing mice showed HPD-like tumor growth as well as an increase in macrophage infiltration compared to control group. Interestingly, in these in vivo models, HPD-like growth, triggered by anti-PD-1 treatment, was dependent of anti-PD-1 antibody Fc domain. These results suggest that macrophages are the major players in HPD development and that FcR engagement on macrophages may determine a functional reprogramming of these immune cells toward a more aggressive and pro-tumorigenic phenotype, eventually inducing HPD.
2023-01-11 | GSE210547 | GEO