Analysis of immune-related signatures of lung adenocarcinoma identified two distinct subtypes: implications for immune checkpoint blockade therapy.
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ABSTRACT:
SUBMITTER: Wang Q
PROVIDER: S-EPMC7066911 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundOropharyngeal cancer (OPC) exhibits diverse immunological properties; however, their implications for immunotherapy are unknown.MethodsWe analysed 37 surgically resected and nine recurrent or metastatic anti-programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1)-treated OPC tumours. OPCs were classified into immune-rich (IR), mesenchymal (MS) and xenobiotic (XB) subtypes based on RNA-sequencing data.ResultsAll IR type tumours were human papillomavirus (HPV) positive, most XB types were HPV negative, and MS types showed mixed HPV status. The IR type showed an enriched T cell exhaustion signature with PD-1+ CD8+ T cells and type I macrophages infiltrating the tumour nest on multiplex immunohistochemistry. The MS type showed an exclusion of CD8+ T cells from the tumour nest and high MS and tumour growth factor-β signatures. The XB type showed scant CD8+ T cell infiltration and focal CD73 expression. The IR type was associated with a favourable response signature during anti-PD-1/PD-L1 therapy and showed a high APOBEC mutation signature, whereas the MS and XB types showed resistance signature upregulation. Among anti-PD-1/PD-L1-treated OPC patients, the IR type showed a favourable clinical response (3/4 patients), whereas the XB type showed early progression (3/3 patients).ConclusionOur analysis classified OPCs into three subtypes with distinct immune microenvironments that are potentially related to the response to anti-PD-1/PD-L1 therapy.
| S-EPMC7251088 | biostudies-literature
Project description:BackgroundDespite the acknowledged predictive value of KRAS in immune checkpoint inhibitor (ICI) responses, the heterogeneous behavior of its mutations in this sphere remains largely unexplored. As of now, no studies have definitively categorized KRAS subtype variations as independent prognostic indicators for ICI responses in lung cancer patients.MethodsWe analyzed a cohort of 103 patients, all harboring different KRAS mutation subtypes, and complemented this data with information from TCGA and GEO databases. Our research focused on delineating the relationships between KRAS mutation subtypes and factors like immunotherapy markers and immune cell composition, in addition to examining survival rates, drug sensitivity, and PD-L1 responses corresponding to distinct KRAS subtypes.ResultsWe found that the G12V and G12D subtypes demonstrated elevated expressions of immunotherapy markers, implying a potentially enhanced benefit from immunotherapy. Significant variations were identified in the distribution of naive B cells, activated CD4+ memory T cells, and regulatory T cells (Tregs) across different KRAS mutant subtypes. A notable difference was observed in the Tumor Mutation Burden (TMB) levels across the four KRAS subtypes, with the G12D subtype displaying the lowest TMB level. Furthermore, G12C subtype showcased the worst prognosis in terms of progression-free intervals (PFI), in stark contrast to the more favorable outcomes associated with the G12A subtype.ConclusionOur study reveals that KRAS mutations exhibit considerable variability in predicting outcomes for LUAD patients undergoing ICI treatment. Thus, the evaluation of KRAS as a biomarker for ICIs necessitates recognizing the potential diversity inherent in KRAS mutations.
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Project description:Lung cancer is the most common cause of cancer deaths worldwide, and lung adenocarcinoma (LUAD) is the most common histological subtype. However, the prognostic and predictive outcomes differ because of this cancer type heterogeneity. LUAD subtypes were identified on the basis of the immunogenomic profiling of 29 immune signatures. We named three LUAD subtypes: Immunity High, Immunity Medium, and Immunity Low. The Immunity High subtype was characterized by immune activation, e.g., increased immune scores, elevated stromal scores and the highest infiltration of CD8+ T cells, and decreased tumor purities. Activated expressions of human leukocyte antigen (HLA) genes, immune checkpoint molecules, and T helper 1 (Th1)/interferon-gamma (IFN?) gene signature were also observed in the Immunity High subtype. N 6-methyladenosine (m6A) RNA methylation, associated with cancer initiation and progression, was reduced in the Immunity High subtype. Functional and signaling pathway enrichment analysis further showed that differentially expressed genes between the Immunity High subtype and the other subtypes mainly participated in immune response and some cancer-associated pathways. In addition, the Immunity High subtype exhibited more sensitivity to immunotherapy and chemotherapy. Finally, candidate compounds that aimed at LUAD subtype differentiation were identified. Comprehensively characterizing the LUAD subtypes based on immune signatures may help to provide potential strategies for LUAD treatment.
| S-EPMC7183104 | biostudies-literature
Project description:BackgroundBrain tumor ranks as the most devastating cancer type. The complex tumor immune microenvironment prevents brain tumor from receiving therapeutic benefits. The purpose of this study was to stratify brain tumors based on their distinct immune infiltration signatures to facilitate better clinical decision making and prognosis prediction.MethodsWe developed a deep learning model to characterize immune infiltration from transcriptome. The developed model was applied to distill expression signatures of transcriptome of brain tumor samples. We performed molecular subtyping with the extracted expression signatures to unveil brain tumor subtypes. Computational methods, including gene set enrichment analysis, Kaplan-Meier survival and multivariate Cox regression analyses, were employed.ResultsWe identified two distinctive subtypes (i.e. C1/2) of brain tumor featured by distinct immune infiltration signatures. The C1 subtype is characterized by protective immune infiltration signatures, including high infiltration of CD8+ T cells and activation of CX3CL1. The C2 subtype has an extensive infiltration of tumor-associated macrophages and microglia, and was enriched with immune suppressive, wound-healing, and angiogenic signatures. The C1 subtype had significantly better prognosis as compared with C2 (Log-rank test, HR: 2.5, 95% CI: 2.2 - 2.7; P = 8.2e-78). This difference remained statistically significant (multivariate Cox model, HR: 2.2, 95% CI: 1.7 - 2.9; P = 3.7e-10) by taking into account age, gender, recurrent/secondary status at sampling time, tumor grade, histology, radio-chemotherapy, IDH mutation, MGMT methylation, and co-deletion of 1p and 19q. This finding was validated in six datasets. The C2 subtype of glioblastoma patients with IDH mutation has poor survival analogous to those without IDH mutation (Log-rank test, adjusted P = 0.8), while C1 has favorable prognosis as compared with glioblastoma of C2 subtype with IDH mutation (Log-rank test, adjusted P = 1.2e-3) or without IDH mutation (Log-rank test, adjusted P = 1.3e-6).ConclusionsWe identified two distinctive subtypes of brain tumor with different immune infiltration signatures, which might be helpful as an independent prognosticator for brain tumor.
| S-EPMC8554158 | biostudies-literature
Project description:The magnitude of the immune response is closely associated with clinical outcome in patients with cancer. However, finding potential therapeutic targets for lung cancer in the immune system remains challenging. Here, we constructed a vital immune-prognosis genes (VIPGs) based cluster of lung adenocarcinoma (LUAD) from IMMPORT databases and The Cancer Genome Atlas. A transcription factor regulatory network for the VIPGs was also established. The tumor microenvironment of LUAD was analyzed using the ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data) algorithm and single-sample Gene Set Enrichment Analysis. The immune checkpoints and genomic alterations were explored in the different immune clusters. We identified 15 VIPGs for patients with LUAD and clustered the patients into low-immunity and high-immunity subtypes. The immune score, stromal score and ESTIMATE score were significantly higher in the high-immunity subtype, whereas tumor purity was higher in the low-immunity subtype. In addition, the immune checkpoints cytotoxic T lymphocyte associate protein-4(CTLA4), programmed cell death protein-1 and programmed death-ligand were elevated in the low-immunity subtype. The genomic results also showed that the tumor mutation burden was higher in the high-immunity subtype. Finally, Gene Set Enrichment Analysis showed that several immune-related gene sets, including interleukin-2/STAT5 signaling, inflammatory response, interleukin-6/Janus kinase(JAK)/signal transducer and activator of transcription 3 (STAT3) signaling, interferon-gamma response and allograft rejection, were elevated in the high-immunity subtype. Finally, high-immunity patients exhibited greater overall and disease-specific survival outcome compared with low-immunity patients (log rank P = 0.013 and P = 0.0097). Altogether, here we have identified 15 immune-prognosis genes and a potential immune subtype for patients with LUAD, which may provide new insights into the prognosis and treatment of LUAD.
| S-EPMC7459417 | biostudies-literature
Project description:BackgroundEndometriosis (EMs) is a chronic inflammatory condition that is highly heterogeneous. Current clinical staging fails to accurately predict drug responses and prognosis. In this study, we aimed to reveal the heterogeneity of ectopic lesions and investigate the possible underlying mechanisms using transcriptomic data and clinical information.MethodsThe EMs microarray dataset GSE141549 was obtained from the Gene Expression Omnibus database. Unsupervised hierarchical clustering was performed to identify EMs subtypes, which was followed by the functional enrichment analysis and estimation of immune infiltrates. Subtype-associated gene signatures were identified and further validated in other independent datasets, including GSE25628, E-MTAB-694, and GSE23339. Additionally, tissue microarrays (TMAs) were generated from premenopausal patients with EMs to investigate the potential clinical implications of the two identified subtypes.ResultsThe unsupervised clustering analysis revealed that ectopic EMs lesions can be classified into two distinct subtypes: stroma-enriched (S1) and immune-enriched (S2). The functional analysis revealed that S1 correlated with fibroblast activation and extracellular matrix remodeling in the ectopic milieu, whereas S2 was characterized by the upregulation of immune pathways and a higher positive correlation with the immunotherapy response. Moreover, we identified a subtype signature composed of FHL1 and SORBS1, and constructed a subtype diagnostic model. Based on the cohort data from the TMAs, we found that S2 was strongly associated with the failure of/intolerance to hormone therapy.ConclusionsThis study identified two distinct subtypes that are varyingly associated with hormone resistance, stroma-immunity, and molecular features, thereby highlighting the importance of this stromal-immune heterogeneity in identifying EMs subtypes and providing novel insights into future personalized hormone-free therapy in EMs.
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Project description:BackgroundIn recent years, glioblastoma multiforme (GBM) has been a concern of many researchers, as it is one of the main drivers of cancer-related deaths worldwide. GBM in general usually does not responding well to immunotherapy due to its unique microenvironment.MethodsTo uncover any further informative immune-related prognostic signatures, we explored the immune-related distinction in the genetic or epigenetic features of the three types (expression profile, somatic mutation, and DNA methylation). Twenty eight immune-related hub genes were identified by Weighted Gene Co-Expression Network Analysis (WGCNA). The findings showed that three genes (IL1R1, TNFSF12, and VDR) were identified to construct an immune-related prognostic model (IRPM) by lasso regression. Then, we used three hub genes to construct an IRPM for GBM and clarify the immunity, mutation, and methylation characteristics.ResultsSurvival analysis of patients undergoing anti-program cell death protein 1 (anti-PD-1) therapy showed that overall survival was superior in the low-risk group than in the high-risk group. The high-risk group had an association with epithelial-mesenchymal transition (EMT), high immune cell infiltration, immune activation, a low mutation number, and high methylation, while the low-risk group was adverse status.ConclusionsIn conclusion, IRPM is a promising tool to distinguish the prognosis of patients and molecular and immune characteristics in GBM, and the IRPM risk score can be used to predict patient sensitivity to checkpoint inhibitor blockade therapy. Thus, three immune-related signatures will guide us in improving treatment strategies and developing objective diagnostic tools.
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Project description:Despite significant strides in the identification and characterization of potential therapeutic targets for medulloblastoma, the role of the immune system and its interplay with the tumor microenvironment within these tumors are poorly understood. To address this, we adapted two syngeneic animal models of human Sonic Hedgehog (SHH)-driven and group 3 medulloblastoma for preclinical evaluation in immunocompetent C57BL/6 mice.Multicolor flow cytometric analyses were used to phenotype and characterize immune infiltrating cells within established cerebellar tumors. We observed significantly higher percentages of dendritic cells, infiltrating lymphocytes, myeloid-derived suppressor cells, and tumor-associated macrophages in murine SHH model tumors compared with group 3 tumors. However, murine group 3 tumors had higher percentages of CD8(+) PD-1(+) T cells within the CD3 population. PD-1 blockade conferred superior antitumor efficacy in animals bearing intracranial group 3 tumors compared with SHH group tumors, indicating that immunologic differences within the tumor microenvironment can be leveraged as potential targets to mediate antitumor efficacy. Further analysis of anti-PD-1 monoclonal antibody localization revealed binding to PD-1(+) peripheral T cells, but not tumor infiltrating lymphocytes within the brain tumor microenvironment. Peripheral PD-1 blockade additionally resulted in a marked increase in CD3(+) T cells within the tumor microenvironment.This is the first immunologic characterization of preclinical models of molecular subtypes of medulloblastoma and demonstration that response to immune checkpoint blockade differs across subtype classification. Our findings also suggest that effective anti-PD-1 blockade does not require that systemically administered antibodies penetrate the brain tumor microenvironment.
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Project description:The most prevalent histological type of non-small cell lung cancer (NSCLC) is adenocarcinoma. The WHO classifies this tumor into subtypes according to the predominant growth pattern such as lepidic, acinar, papillary, solid or micropapillary, each harboring specific molecular features. NSCLC adenocarcinoma heterogeneity is discussed to be a reason for therapy failure using targeted therapy or immune checkpoint inhibitors. For successful therapy of immune checkpoint inhibitors the expression and distribution of the involved immune checkpoint proteins is essential. Therefore, we aimed to investigate the distribution of five prominent immune checkpoint proteins in regard of the histological growth patterns of lung adenocarcinoma. We performed immunohistochemical staining of 84 tumor segments from 22 resected tumor samples to evaluate the expression of PD-L1, PD-1, Nectin-2, PVR, and TIGIT in distinct growth patterns of lung adenocarcinoma. We determined a distinct heterogeneity between and within different tumor segments regarding morphological growth patterns. Furthermore, expression of immune checkpoint proteins varied between different growth pattern areas as well as within one distinct growth pattern. Expression of PVR was significantly higher in solid compared to acinar growth pattern (p= 0.00736). Of note, we detected TIGIT not only on tumor infiltrating lymphocytes but also on tumor cells, whereas non-neoplastic lung tissue was consistently TIGIT-negative. The immune checkpoint protein distribution in histologic subtypes of pulmonary adenocarcinoma displays an considerable intra- and intertumoral heterogeneity implying the requirement of either a multiregion or an adjusted analysis when determining the expression status of PD-1:PD-L1 and the TIGIT:PVR/Nectin-2 checkpoint proteins as predictive markers.
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Project description:Despite the success of standard front-line chemotherapy, 20% of classical Hodgkin lymphoma (cHL) patients still relapse or have refractory disease (r/r), and a subset of them die due to disease progression. There is a critical lack of predictive factors for early identification of those r/r patients who may benefit from new therapeutic strategies. This study aimed to evaluate the dynamic expression of 586 immune-related genes in a cohort of 42 cHL patients including 30 r/r cHL after first-line chemotherapy. Gene expression profiling (GEP) using NanoString technology identified a 19-gene immune signature at diagnosis predictive of cHL relapse, but dependent on histological subtypes. Genes related to tumor survival were found upregulated while genes related to B-lineage were downregulated at diagnosis in r/r nodular sclerosis cHL. In contrast to the mixed-cellularity subtype, comparative GEP analyses between paired diagnosis/relapse biopsies of nodular sclerosis cHL showed 118 differentially expressed genes, supporting an immune contexture switch at relapse with upregulation of immunosuppressive cytokines, such as LGALS1 and TGFB1, and downregulation of the T-cell co-stimulatory receptor ICOS. These results indicate that the predictive value of immune signature in cHL is strongly influenced by histological subtype which should be considered when assessing new immunotherapy target strategies.
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