T cell subtype profiling measures exhaustion and predicts anti-PD-1 response.
Ontology highlight
ABSTRACT:
SUBMITTER: Schillebeeckx I
PROVIDER: S-EPMC8789795 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Immune checkpoint blockade is revolutionizing therapy for advanced cancer, but many patients do not respond to treatment. The identification of robust biomarkers that predict clinical response to specific checkpoint inhibitors is critical in order to stratify patients and to rationally select combinations in the context of an expanding array of therapeutic options.We performed multiparameter flow cytometry on freshly isolated metastatic melanoma samples from 2 cohorts of 20 patients each prior to treatment and correlated the subsequent clinical response with the tumor immune phenotype.Increasing fractions of programmed cell death 1 high/cytotoxic T lymphocyte-associated protein 4 high (PD-1hiCTLA-4hi) cells within the tumor-infiltrating CD8+ T cell subset strongly correlated with response to therapy (RR) and progression-free survival (PFS). Functional analysis of these cells revealed a partially exhausted T cell phenotype. Assessment of metastatic lesions during anti-PD-1 therapy demonstrated a release of T cell exhaustion, as measured by an accumulation of highly activated CD8+ T cells within tumors, with no effect on Tregs.Our data suggest that the relative abundance of partially exhausted tumor-infiltrating CD8+ T cells predicts response to anti-PD-1 therapy. This information can be used to appropriately select patients with a high likelihood of achieving a clinical response to PD-1 pathway inhibition.This work was funded by a generous gift provided by Inga-Lill and David Amoroso as well as a generous gift provided by Stephen Juelsgaard and Lori Cook.
| S-EPMC5004965 | biostudies-literature
Project description:IntroductionMany studies have focused on the role of programmed death receptor ligand 1 (PD-L1) expression in predicting immunotherapy outcomes. Limited clinical data are available regarding the role of programmed death receptor 1 (PD-1; the PD-L1 receptor) expressing tumor-infiltrating lymphocytes (TILs) in PD-1/PD-L1 antibody responsiveness. However, preclinical studies demonstrate that TILs expressing PD-1 contribute to tumor immune evasion.MethodsThis study analyzed the association between TIL-PD-1 status and outcome after immune checkpoint blockade (ICB) therapy. We evaluated 123 patients with various solid tumors treated with monoclonal antibodies targeting the PD-1/PD-L1 signaling axis. Additionally, 8706 solid tumor specimens were assessed for TIL-PD-1 and tumor mutational burden (TMB) status.ResultsThe presence of PD-1-expressing TILs in tumors was associated with increased median progression-free survival (7.0 vs 1.9 months; p = 0.006) and overall survival (18.1 vs 8.0 months; p = 0.04) after treatment with ICB. TIL-PD-1-positive patients had an objective response rate (ORR) of 41% (95% CI, 24-61; N = 12/29) compared with 17% (95% CI, 4-43; N = 3/17) for TIL-PD-1-negative patients (p = 0.18). Analyzed as continuous variables, TIL-PD-1 and TMB showed a weak correlation in 8706 solid tumor samples (Pearson r = 0.074); when analyzed as categorical variables (cutoffs: TIL-PD-1 ≥ 1% and TMB ≥ 10 mutations/Mb), the two variables are correlated (p < 0.0001). TIL-PD-1-positive status is also associated with enrichment of pathologic variants within several genes, most notably TP53 (adjusted p < 0.05).ConclusionTIL-PD-1 positivity in tumors (≥ 1%) is associated with significantly longer progression-free and overall survival after ICB. ClinicalTrials.gov ID: NCT02478931.
| S-EPMC9714418 | biostudies-literature
Project description:Tumor extracellular matrix has been associated with drug resistance and immune suppression. Here, proteomic and RNA profiling reveal increased collagen levels in lung tumors resistant to PD-1/PD-L1 blockade. Additionally, elevated collagen correlates with decreased total CD8+ T cells and increased exhausted CD8+ T cell subpopulations in murine and human lung tumors. Collagen-induced T cell exhaustion occurs through the receptor LAIR1, which is upregulated following CD18 interaction with collagen, and induces T cell exhaustion through SHP-1. Reduction in tumor collagen deposition through LOXL2 suppression increases T cell infiltration, diminishes exhausted T cells, and abrogates resistance to anti-PD-L1. Abrogating LAIR1 immunosuppression through LAIR2 overexpression or SHP-1 inhibition sensitizes resistant lung tumors to anti-PD-1. Clinically, increased collagen, LAIR1, and TIM-3 expression in melanoma patients treated with PD-1 blockade predict poorer survival and response. Our study identifies collagen and LAIR1 as potential markers for immunotherapy resistance and validates multiple promising therapeutic combinations.
| S-EPMC7481212 | biostudies-literature
Project description:Tuberous sclerosis complex (TSC) is an incurable multisystem disease characterized by mTORC1-hyperactive tumors. TSC1/2 mutations also occur in other neoplastic disorders, including lymphangioleiomyomatosis (LAM) and bladder cancer. Whether TSC-associated tumors will respond to immunotherapy is unknown. We report here that the programmed death 1 coinhibitory receptor (PD-1) is upregulated on T cells in renal angiomyolipomas (AML) and pulmonary lymphangioleiomyomatosis (LAM). In C57BL/6J mice injected with syngeneic TSC2-deficient cells, anti-PD-1 alone decreased 105K tumor growth by 67% (P < 0.0001); the combination of PD-1 and CTLA-4 blockade was even more effective in suppressing tumor growth. Anti-PD-1 induced complete rejection of TSC2-deficient 105K tumors in 37% of mice (P < 0.05). Double blockade of PD-1 and CTLA-4 induced rejection in 62% of mice (P < 0.01). TSC2 reexpression in TSC2-deficient TMKOC cells enhanced antitumor immunity by increasing T cell infiltration and production of IFN-?/TNF-? by T cells, suggesting that TSC2 and mTORC1 play specific roles in the induction of antitumor immunity. Finally, 1 month of anti-PD-1 blockade reduced renal tumor burden by 53% (P < 0.01) in genetically engineered Tsc2+/- mice. Taken together, these data demonstrate for the first time to our knowledge that checkpoint blockade may have clinical efficacy for TSC and LAM, and possibly other benign tumor syndromes, potentially yielding complete and durable clinical responses.
| S-EPMC5931128 | biostudies-literature
Project description:Recent years have witnessed the groundbreaking success of immune checkpoint blockage (ICB) in metastasized malignant melanoma. However, biomarkers predicting the response to ICB are still urgently needed. In the present study, we investigated CTLA4 promoter methylation (mCTLA4) in 470 malignant melanoma patients from The Cancer Genome Atlas (non-ICB cohort) and in 50 individuals with metastasized malignant melanomas under PD-1/CTLA-4-targeted immunotherapy (ICB cohort). mCTLA4 levels were quantified using the Infinium HumanMethylation450 BeadChip (non-ICB cohort) and methylation-specific quantitative real-time PCR in DNA formalin-fixed and paraffin-embedded tissues (ICB cohort). Methylation levels were associated with molecular and clinicopathological variables and analyzed with respect to response (irRECIST) and overall survival. CTLA-4 mRNA and mCTLA4 showed a significant inverse correlation (non-ICB cohort: Spearman's ? = -0.416, P < 0.001). In ICB-treated melanoma patients, low mCTLA4 was further strongly correlated with response to therapy (P = 0.009, ANOVA) and overall survival (hazard ratio = 2.06 [95% CI: 1.29-3.29], P = 0.003). Our data strongly support the assumption that mCTLA4 predicts response to both anti-PD-1 and anti-CTLA-4 targeted ICB in melanoma and provides paramount information for the selection of patients likely to respond to ICB.
| S-EPMC6124533 | biostudies-literature
Project description:Immune-checkpoint blockades (ICBs) have been routinely implemented to treat metastatic urothelial cancer (mUC), whereas robust biomarkers are urgently warranted. Herein, we explored latent promising biomarkers based on 348 pretreatment mUC samples from IMvigor210. Methods: The genome, transcriptome, immunome, and metabolome were systemically analyzed using the external TCGA dataset for validation. Kaplan-Meier and ROC curve analyses were performed to estimate the predictive capacity of M1-macrophage infiltration. Chi-square/Spearman/Mann Whitney U test are used to determine its correlation to genetic, biochemical, and clinicopathological parameters. Results: M1 frequency is a robust biomarker for predicting the prognosis and response to ICBs, which is non-inferior to tumor mutation burden (TMB) or tumor neoantigen burden (TNB), and exceeds CD8 T cells, T cell inflamed gene expression profile (GEP), and PD-L1 expression. Moreover, M1 infiltration is associated with immune phenotypes (AUC = 0.785) and is negatively correlated with immune exclusion. Additionally, transcriptomic analysis showed immune activation in the high-M1 subgroup, whereas it showed steroid and drug metabolism reprograming in the M1-deficient subset, which characterized the limited sensitivity to ICB therapy. Notably, investigation of the corresponding intrinsic genomic profiles highlighted the significance of TP53 and FGFR alterations. Conclusions: M1 infiltration is a robust biomarker for immunotherapeutic response and immunophenotype determination in an mUC setting. Innate immunity activation involving macrophage polarization remodeling and anti-FGFR mutations may be promising strategies for synergy with anti-PD-L1 treatments and may help prolong the clinical survival of patients with mUC.
| S-EPMC7295060 | biostudies-literature
Project description:Despite the utilization of anti-PD-1 therapy in gastric cancer (GC), the absence of a reliable predictive biomarker continues to pose a challenge. In this study, we utilized bioinformatic analysis and immunohistochemistry to develop a prediction model for activated CD4+ memory T cells, considering both mRNA and protein levels. An elevation of activated CD4+ memory T cells in GC was noted, which exhibited a strong association with the patients' overall survival. By utilizing WGCNA and DEG analysis, we discovered that BATF2, MYB, and CD36 are genes that exhibit differential expression and are linked to activated CD4+ memory T cells. Afterwards, a forecast model was built utilizing Stepwise regression and immunohistochemistry relying on the three genes. The model's high-risk score showed significant associations with a suppressive immune microenvironment. Moreover, our model exhibited encouraging prognostic value and superior performance in predicting response to immune checkpoint blockade therapy compared with the conventional CD8+PD-L1 model. In terms of mechanism, CD36 could function as a receptor upstream that identifies Helicobacter pylori and fatty acids. This recognition then results in the reduction of the BATF2-MYB protein complex and subsequent alterations in the transcription of genes associated with classical T cell activation. As a result, the activation state of CD4+ memory T cells is ultimately suppressed. The CD36-BATF2/MYB signature serves as a robust predictor of anti-PD-1 immunotherapy response in GC.
| S-EPMC10535701 | biostudies-literature
Project description:Immune checkpoint blockade has revolutionized cancer therapy. In particular, inhibition of programmed cell death protein 1 (PD-1) is effective for the treatment of metastatic melanoma and other cancers. Despite a dramatic increase in progression-free survival, a large proportion of patients do not show durable response. Therefore, predictive biomarkers of clinical response are urgently needed. Here, we employed high-dimensional single cell mass cytometry and a bioinformatics pipeline for the in-depth characterization of the immune cell subsets in the peripheral blood of metastatic melanoma patients before and after anti-PD-1 immunotherapy. During therapy, we observed a clear treatment response to immunotherapy in the T cell compartment. However, prior to commending therapy a strong predictor of progression free and overall survival in response to anti-PD-1 immunotherapy was the frequency of CD14+CD16-HLA-DRhi monocytes. We could confirm this by conventional flow cytometry in an independent validation cohort and propose this as a novel predictive biomarker for therapy decisions in the clinic. In order to determine whether there are cell intrinsic changes in the monocyte signature, we performed RNA sequencing on sorted CD14+CD16-HLA-DRhi cells from HD, NR and R at baseline. Representative samples (n=4, each) of responders/non responders/ and healthy donors were selected from archival samples stored in the dermatology biobank according to the same clinical criteria used in the discovery and validation cohorts for CyTOF and FACS analysis. CD14+CD16-HLA-DRhiLin- (CD3, CD4, CD19, CD45RO) monocytes were sorted from frozen PBMC form blood samples from HD, R and NR at baseline.
2017-12-20 | E-MTAB-6214 | biostudies-arrayexpress
Project description:A large proportion of anti-tumor immunity research is focused on major histocompatibility complex class I (MHC-I) molecules and CD8+ T cells. Despite mounting evidence has shown that CD4+ T cells play a major role in anti-tumor immunity, the role of the MHC-II molecules in tumor immunotherapy has not been thoroughly researched and reported. In this study, we defined a MHC-II signature for the first time by calculating the enrichment score of MHC-II protein binding pathway with a single sample gene set enrichment analysis (ssGSEA) algorithm. To evaluate and validate the predictive value of the MHC class II (MHC-II) signature, we collected the transcriptome, mutation data and matched clinical data of bladder cancer patients from IMvigor210, The Cancer Genome Atlas (TCGA) databases and Gene Expression Omnibus (GEO) databases. Comprehensive analyses of immunome, transcriptome, metabolome, genome and drugome were performed in order to determine the association of MHC-II signature and tumor immunotherapy. We identified that MHC-II signature is an independent and favorable predictor of immune response and the prognosis of bladder cancer treated with immune checkpoint inhibitors (ICIs), one that may be superior to tumor mutation burden. MHC-II signature was significantly associated with increased immune cell infiltration and levels of immune-related gene expression signatures. Additionally, transcriptomic analysis showed immune activation in the high-MHC-II signature subgroup, whereas it showed fatty acid metabolism and glucuronidation in the low-MHC-II signature subgroup. Moreover, exploration of corresponding genomic profiles highlighted the significance of tumor protein p53 (TP53) and fibroblast growth factor receptor 3 (FGFR3) alterations. Our results also allowed for the identification of candidate compounds for combined immunotherapy treatment that may be beneficial for patients with bladder cancer and a high MHC-II signature. In conclusion, this study provides a new perspective on MHC-II signature, as an independent and favorable predictor of immune response and prognosis of bladder cancer treated with ICIs.
| S-EPMC8873787 | biostudies-literature
Project description:The biomarkers for the pathological response of neoadjuvant chemotherapy plus anti-programmed cell death protein-1/programmed cell death-ligand 1 (PD-1/PD-L1) (CAPD) are unclear in non-small cell lung cancer (NSCLC). Two hundred and eleven patients with stage Ib-IIIa NSCLC undergoing CAPD prior to surgical resection were enrolled, and 11 immune cell subsets in peripheral blood were prospectively analyzed using multicolor flow cytometry. Immune cell subtypes were selected by recursive feature elimination and least absolute shrinkage and selection operator methods. The support vector machine (SVM) was used to build a model. Multivariate analysis for major pathological response (MPR) was also performed. Finally, five immune cell subtypes were identified and an SVM based on liquid immune profiling (LIP-SVM) was developed. The LIP-SVM model achieved high accuracies in discovery and validation sets (AUC = 0.886, 95% CI: 0.823-0.949, P < 0.001; AUC = 0.874, 95% CI: 0.791-0.958, P < 0.001, respectively). Multivariate analysis revealed that age, radiological response, and LIP-SVM were independent factors for MPR in the two sets (each P < 0.05). The integration of LIP-SVM, clinical factors, and radiological response showed significantly high accuracies for predicting MPR in discovery and validation sets (AUC = 0.951, 95% CI: 0.916-0.986, P < 0.001; AUC = 0.943, 95% CI: 0.912-0.993, P < 0.001, respectively). Based on immune cell profiling of peripheral blood, our study developed a predictive model for the MPR of patients with NSCLC undergoing CAPD treatment that can potentially guide clinical therapy.
| S-EPMC8797141 | biostudies-literature