Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma.
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ABSTRACT:
SUBMITTER: Nair NU
PROVIDER: S-EPMC9975319 | biostudies-literature | 2023 Feb
REPOSITORIES: biostudies-literature
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Genomic and transcriptomic analyses identify a prognostic gene signature and predict response to therapy in pleural and peritoneal mesothelioma.
Nair Nishanth Ulhas NU Jiang Qun Q Wei Jun Stephen JS Misra Vikram Alexander VA Morrow Betsy B Kesserwan Chimene C Hermida Leandro C LC Lee Joo Sang JS Mian Idrees I Zhang Jingli J Lebensohn Alexandra A Miettinen Markku M Sengupta Manjistha M Khan Javed J Ruppin Eytan E Hassan Raffit R
Cell reports. Medicine 20230210 2
Malignant mesothelioma is an aggressive cancer with limited treatment options and poor prognosis. A better understanding of mesothelioma genomics and transcriptomics could advance therapies. Here, we present a mesothelioma cohort of 122 patients along with their germline and tumor whole-exome and tumor RNA sequencing data as well as phenotypic and drug response information. We identify a 48-gene prognostic signature that is highly predictive of mesothelioma patient survival, including CCNB1, the ...[more]
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Project description:BackgroundMalignant pleural and peritoneal mesotheliomas are rare malignancies with unacceptable poor prognoses and limited treatment options. The genomic landscape is mainly characterised by the loss of tumour suppressor genes and mutations in DNA repair genes. Currently, data from next-generation sequencing (NGS) of mesothelioma tumours is restricted to a limited number of cases; moreover, data comparing molecular features of mesothelioma from the pleural and peritoneal origin with NGS are lacking.MethodsWe analysed 1113 pleural mesothelioma and 355 peritoneal mesothelioma samples. All tumours were sequenced with the FoundationOne® or FoundationOne®CDx assay for detection of substitutions, insertion-deletions, copy-number alterations and selected rearrangements in at least 324 cancer genes.ResultsThis analysis revealed alterations in 19 genes with an overall prevalence of at least 2%. Alterations in BAP1, CDKN2A, CDKN2B, NF2, MTAP, TP53 and SETD2 occurred with a prevalence of at least 10%. Peritoneal, compared to pleural mesothelioma, was characterised by a lower prevalence of alterations in CDKN2A, CDKN2B and MTAP. Moreover, we could define four distinct subgroups according to alterations in BAP1 and CDKN2A/B. Alterations in Hedgehog pathway-related genes (PTCH1/2 and SUFU) and Hippo pathway-related gene (NF2) as well as KRAS, EGFR, PDGFRA/B, ERBB2 and FGFR3 were detected in both cohorts.ConclusionHere, we report the molecular aberrations from the largest cohort of patients with mesothelioma. This analysis identified a proportion of patients with targetable alterations and suggests that molecular profiling can identify new treatment options for patients with mesothelioma.
| S-EPMC9681755 | biostudies-literature
Project description:Cell lines are extensively used to study cancer biology. However, the use of highly passaged commercial cell lines has to be questioned, as they do not closely resemble the originating tumor. To understand the reliability of preclinical models for Malignant pleural mesothelioma (MPM) studies, we have performed whole transcriptome and whole exome analyses of fresh frozen MPM tumors and compared them to cell lines generated from these tumors, as well as commercial cell lines and a preclinical MPM mouse model. Patient-derived cell lines were generated from digested fresh tumors and whole exome sequencing was performed on DNA isolated from formalin-fixed, paraffin-embedded (FFPE) tumor samples, corresponding patient-derived cell lines, and normal tissue. RNA sequencing libraries were prepared from 10 fresh frozen tumor samples, the 10 corresponding patient-derived cell lines, and 7 commercial cell lines. Our results identified alterations in tumor suppressor genes such as FBXW7, CDKN2A, CDKN2B, and MTAP, all known to drive MPM tumorigenesis. Patient-derived cell lines correlate to a high degree with their originating tumor. Gene expressions involved in multiple pathways such as EMT, apoptosis, myogenesis, and angiogenesis are upregulated in tumor samples when compared to patient-derived cell lines; however, they are downregulated in commercial cell lines compared to patient-derived cell lines, indicating significant differences between the two model systems. Our results show that the genome and transcriptome of tumors correlate to a higher degree with patient-derived cell lines rather than commercial cell lines. These results are of major relevance for the scientific community in regard to using cell lines as an appropriate model, resembling the pathway of interest to avoid misleading results for clinical applications.
| S-EPMC10216513 | biostudies-literature
Project description:Introduction: Dysregulated genes play a critical role in the development and progression of cancer, suggesting their potential as novel independent biomarkers for cancer diagnosis and prognosis. Prognostic model-based gene expression profiles are not widely utilized in clinical medicine. We investigated the prognostic significance of an expression profile-based gene signature for outcome prediction in patients with malignant pleural mesothelioma (MPM). Methods: The gene expression profiles of a large cohort of patients with MPM were obtained and analyzed by repurposing publicly available microarray data. A gene-based risk score model was developed with the training dataset and then validated with the TCGA-MESO (mesothelioma) dataset. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance of survival prediction. The biological function of the prognostic genes was predicted using bioinformatics analysis. Results: Three genes in the training dataset (GSE2549) were identified as significantly associated with the overall survival (OS) of patients with MPM and were combined to develop a three-gene prognostic signature to stratify patients into low-risk and high-risk groups. The MPM patients of the training dataset in the low-risk group exhibited longer OS than those in the high-risk group (HR = 0.25, 95% CI = 0.11-0.56, P < 0.001). Similar prognostic values for the three-gene signature were observed in the validated TCGA-MESO cohort (HR = 0.53 95% CI = 0.33-0.85, P = 0.008). ROC analysis also demonstrated the good performance in predicting 3-year OS in the GEO and TCGA cohorts (KM-AUC for GEO = 0.989, KM-AUC for TCGA = 0.618). The C-statistic for the 3-gene model was 0.761. Validation with TCGA-MESO confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic: 0.68). Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to MPM. Conclusions: This study has identified and validated a novel 3-gene model to reliably discriminate patients at high and low risk of death in unselected populations of patients with MPM. Further larger, prospective multi-institutional cohort studies are necessary to validate this model.
| S-EPMC6384238 | biostudies-literature
Project description:BackgroundDiffuse pleural mesothelioma (DPM) is an aggressive malignancy that, despite recent treatment advances, has unacceptably poor outcomes. Therapeutic research in DPM is inhibited by a paucity of preclinical models that faithfully recapitulate the human disease.MethodsWe established 22 patient-derived xenografts (PDX) from 22 patients with DPM and performed multi-omic analyses to deconvolute the mutational landscapes, global expression profiles, and molecular subtypes of these PDX models and compared features to those of the matched primary patient tumors. Targeted next-generation sequencing (NGS; MSK-IMPACT), immunohistochemistry, and histologic subtyping were performed on all available samples. RNA sequencing was performed on all available PDX samples. Clinical outcomes and treatment history were annotated for all patients. Platinum-doublet progression-free survival (PFS) was determined from the start of chemotherapy until radiographic/clinical progression and grouped into < or ≥ 6 months.ResultsPDX models were established from both treatment naïve and previously treated samples and were noted to closely resemble the histology, genomic landscape, and proteomic profiles of the parent tumor. After establishing the validity of the models, transcriptomic analyses demonstrated overexpression in WNT/β-catenin, hedgehog, and TGF-β signaling and a consistent suppression of immune-related signaling in PDXs derived from patients with worse clinical outcomes.ConclusionsThese data demonstrate that DPM PDX models closely resemble the genotype and phenotype of parental tumors, and identify pathways altered in DPM for future exploration in preclinical studies.
| S-EPMC9667652 | biostudies-literature
Project description:Objective: Pleural mesothelioma (PM), an uncommon yet highly aggressive malignant neoplasm, has a very poor prognosis with a median survival of less than one year after diagnosis, morbidity and mortality due to PM are on the rise year by year worldwide. Our research aims to utilize molecular characteristics and microRNAs (miRNAs) as a breakthrough in predicting the survival of PM patients, hoping to find a molecular mechanism that can predict the survival of PM patients. Methods: The miRNA expression profiles and corresponding clinical information of patients with PM were obtained from The Cancer Genome Atlas (TCGA) database, a miRNA-based prognostic signature was developed using Cox regression analysis in the training cohort, which was validated in the testing cohort and complete cohort. The association between miRNA levels and survival outcomes was determined, the miRNAs in prognostic model were experimentally validated by quantitative real-time PCR (qRT-PCR) in cell lines. Target genes of prognostic miRNAs were identified using TargetScan, miRDB, and miRTarBase databases, biological function prediction of which was accomplished by GO and KEGG analysis. Gene Expression Omnibus (GEO) database was utilized for core targets recognition, immune infiltration and survival analysis were conducted to investigate the relationship between core targets and immune cells by bioinformatics analysis. Results: This miRNA-related prognostic risk model can effectively stratify patients into high-risk and low-risk groups, and have good sensitivity and specificity to assess the prognosis of patients with PM, which can also be used as an independent prognostic factor for overall survival (OS) prediction in patients with PM, the OS for patients in high-risk group was significantly poorer compared with patients in low-risk group. Moreover, all four miRNAs (hsa-miR-181a-2-3p, hsa-miR-491-5P, hsa-miR-503-5p, and hsa-miR-3934-5p) were found to be differentially expressed in PM cell lines as compared with normal cell line, GO and KEGG analysis revealed that target genes of miRNAs in prognostic model were involved in multiple tumor-associated signaling pathways and functions in PM, core miRNA targets also correlated with immune cell infiltration, indicating their potential role in PM initiation and progression. Conclusions: A robust four-miRNA prognostic signature with great performances in prediction of the OS for PM patients was developed in our study, providing new avenues for the prognostic predication of PM.
| S-EPMC11632982 | biostudies-literature
Project description:BackgroundImmune-related genes (IRGs) play an important role in the tumor immune microenvironment and affect tumor prognosis. This study aimed to establish a prognostic signature for malignant pleural mesothelioma (MPM) patients.MethodsWe obtained the relevant data of MPM patients in The Cancer Genome Atlas (TCGA), and univariate and multivariate Cox regression were used to construct the prediction signature and verify it with the external validation dataset GSE2549. A nomogram was then constructed, and its predictive ability was evaluated and analyzed the level of immune cell infiltration in different groups in the signature.ResultsAn IRG-related prognostic signature composed of INHBA, CAT, SORT1, TNFSF13B, and BIRC5 was constructed, with patients divided into high-risk and low-risk groups according to the risk score. The survival time of overall survival (OS), progression-free survival (PFS), disease-free interval (DFI), and relapse-free survival (RFS) in low-risk groups was longer than in high-risk groups. Furthermore, the signature had high predictive performance, and the receiver operating characteristic (ROC) of 1, 2, and 3 years could reach 0.853, 0.881, and 0.914, respectively. The predictive accuracy of the signature was verified by using the independent GSE2549 dataset. The levels of activated CD4 T cells, immature dendritic cells, and type 2 T helper cells were higher in high-risk patients. The gene set enrichment analysis (GSEA) analysis showed that a high concentration and P53 signal pathways were found in high-risk groups.ConclusionsThis research developed and verified a new type of immune prognostic signature based on five IRGs, which can predict the prognosis of tumor patients and provide new ideas for individualized treatment.
| S-EPMC8908124 | biostudies-literature
Project description:We generated a comprehensive atlas of the immunologic cellular networks within human malignant pleural mesothelioma (MPM) using mass cytometry. Data-driven analyses of these high-resolution single-cell data identified 2 distinct immunologic subtypes of MPM with vastly different cellular composition, activation states, and immunologic function; mass spectrometry demonstrated differential abundance of MHC-I and -II neopeptides directly identified between these subtypes. The clinical relevance of this immunologic subtyping was investigated with a discriminatory molecular signature derived through comparison of the proteomes and transcriptomes of these 2 immunologic MPM subtypes. This molecular signature, representative of a favorable intratumoral cell network, was independently associated with improved survival in MPM and predicted response to immune checkpoint inhibitors in patients with MPM and melanoma. These data additionally suggest a potentially novel mechanism of response to checkpoint blockade: requirement for high measured abundance of neopeptides in the presence of high expression of MHC proteins specific for these neopeptides.
| S-EPMC5928857 | biostudies-literature
Project description:Immunotherapies have demonstrated limited clinical efficacy in malignant mesothelioma treatment. We conducted multiplex immunofluorescence analyses on tissue microarrays (n = 3) from patients with malignant pleural mesothelioma (MPM, n = 88) and malignant peritoneal mesothelioma (MPeM, n = 25). Our study aimed to elucidate spatial distributions of key immune cell populations and their association with lymphocyte activation gene 3 (LAG3), BRCA1-associated protein 1 (BAP1), neurofibromatosis type 2 (NF2), and methylthioadenosine phosphorylase (MTAP), with MTAP serving as a cyclin-dependent kinase inhibitor 2A/2B (CDKN2A/B) surrogate marker. Additionally, we examined the relationship between the spatial distribution of major immune cell types and prognosis and clinical characteristics of patients with malignant mesothelioma. We observed a higher degree of interaction between immune cells and tumor cells in MPM compared with MPeM. Notably, within MPM tumors, we detected a significantly increased interaction between tumor cells and CD8+ T cells in tumors with low BAP1 expression compared with those with high BAP1 expression. To support the broader research community, we have developed The Human Spatial Atlas of Malignant Mesothelioma, containing hematoxylin and eosin and multiplex immunofluorescence images with corresponding metadata.SignificanceConsidering the limited therapeutic options available to patients with malignant mesothelioma, there is substantial translational potential in understanding the correlation between the spatial architecture of the malignant mesothelioma tumor immune microenvironment and tumor biology. Our investigation reveals critical cell-cell interactions that may influence the immune response against malignant mesothelioma tumors, potentially contributing to the differential behaviors observed in MPM and MPeM. These findings represent a valuable resource for the malignant mesothelioma cancer research community.
| S-EPMC11328914 | biostudies-literature
Project description:We characterized tumor and immune microenvironment (TiME) of malignant pleural mesothelioma (MPM) using immunoproteomic approach to comprehensively understand the landscape to affect prognosis and possibly to predict response to immunotherapy. Time-of-Flight Mass Cytometry (CyTOF) was performed on the tumors of 12 MPM patients. We comprehensively analyzed TiME by developing intuitive models for visualizing single-cell data with statistical inference and performed unsupervised clustering of cell frequency. A clinically relevant protein signature through mass spectrometry and mRNA transcriptome array was tested for its ability to reflect prognosis in three independent cohorts (n=330) and to predict response to immune checkpoint inhibitor therapy in publicly available data and in 10 patients of MPM treated with anti-PD1 therapy. A systematic understanding of antitumor immunity by immunoproteomic characterization of TiME envisions significant progress in developing rational immunotherapeutic strategies in MPM.
2018-04-05 | GSE99070 | GEO
Project description:BackgroundThe L-type amino acid transporter (LAT1) exhibits significantly increased expression within tumor cells across various neoplasms. However, the clinical significance of LAT1 expression in patients with pleural mesothelioma (PM) remains unclear.MethodsEighty patients diagnosed with PM between June 2007 and August 2022, were eligible for this study. LAT1, alanine-serine-cysteine transporter 2 (ASCT2), Ki-67, and VEGFR2 were evaluated by immunohistochemistry. Inflammatory and nutritional indices were also correlated with different variables, including neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune-inflammation index (SII), prognostic nutritional index (PNI), advanced lung cancer inflammation index (ALI), and Glasgow prognostic score (GPS).ResultsLAT1 was highly expressed in 57.5 % of patients with PM. Among the 80 patients included in this study, 65 (81.3 %) received chemotherapy, either alone or followed by surgical resection, while 15 (18.7 %) opted for best supportive care. The level of LAT1 significantly correlated with cell proliferation and ASCT2. Factors such as performance status, histology, LAT1 expression, PNI, ALI, and GPS were significant prognostic indicators for progression-free survival (PFS), while Ki-67, LAT1, NLR, SII, PNI, ALI, and GPS were identified as significant predictors for overall survival (OS). LAT1 expression emerged as an independent prognostic factor for predicting PFS and OS in all patients, as well as in the subgroup of 65 patients receiving chemotherapy. Notably, high LAT1 expression proved to be a significant predictor of outcome, particularly in the subgroup with high PLR and SII.ConclusionLAT1 was a significant predictor of outcomes in patients with PM and was more predictive of worse outcomes in patients with high inflammatory and low nutritional status.
| S-EPMC11407025 | biostudies-literature