Dataset Information

Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma.

ABSTRACT: Evoked from asbestos-induced inflammation, pleural mesothelioma represents a fatal diagnosis. Therapy ranges from nihilism to aggressive multimodality regimens. However, it is still unclear who ultimately benefits from which treatment. We aimed to re-challenge inflammatory-related biomarkers' prognostic value in times of modern immune-oncology and lung-sparing surgery. The biomarkers (leukocytes, hemoglobin, platelets, neutrophils, lymphocytes, monocytes, neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), platelet-lymphocyte ratio (PLR), C-reactive protein (CRP)) and clinical characteristics (age, sex, histology, therapy) of 98 PM patients were correlated to overall survival (OS). The median OS was 19.4 months. Significant OS advantages (Log-Rank) were observed in multimodal treatment vs. others (26.1 vs. 7.2 months, p < 0.001), surgery (pleurectomy/decortication) vs. no surgery (25.5 vs. 3.8 months, p < 0.001), a high hemoglobin level (cut-off 12 g/dL, 15 vs. 24.2 months, p = 0.021), a low platelet count (cut-off 280 G/L, 26.1 vs. 11.7 months, p < 0.001), and a low PLR (cut-off 194.5, 25.5 vs. 12.3 months, p = 0.023). Histology (epithelioid vs. non-epithelioid, p = 0.002), surgery (p = 0.004), CRP (cut-off 1 mg/dL, p = 0.039), and platelets (p = 0.025) were identified as independent prognostic variables for this cohort in multivariate analysis (Cox regression, covariates: age, sex, histology, stage, CRP, platelets). Our data verified the previously shown prognostic role of systemic inflammatory parameters in patients treated with lung-sparing surgery within multimodality therapy.

SUBMITTER: Iser S

PROVIDER: S-EPMC10778470 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma.

Iser Stephanie S Hintermair Sarah S Varga Alexander A Çelik Ali A Sayan Muhammet M Kankoç Aykut A Akyürek Nalan N Öğüt Betül B Bertoglio Pietro P Capozzi Enrico E Solli Piergiorgio P Ventura Luigi L Waller David D Weber Michael M Stubenberger Elisabeth E Ghanim Bahil B

Cancers 20231224 1

Evoked from asbestos-induced inflammation, pleural mesothelioma represents a fatal diagnosis. Therapy ranges from nihilism to aggressive multimodality regimens. However, it is still unclear who ultimately benefits from which treatment. We aimed to re-challenge inflammatory-related biomarkers' prognostic value in times of modern immune-oncology and lung-sparing surgery. The biomarkers (leukocytes, hemoglobin, platelets, neutrophils, lymphocytes, monocytes, neutrophil-lymphocyte ratio (NLR), lymph ...[more]

PMID: 38201520

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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.

Project description:ObjectivesPrognostic models for malignant pleural mesothelioma (MPM) are needed to prevent potentially futile outcomes. We combined MPM plasma biomarkers with validated clinical prognostic indices to determine whether stratification of risk for death in 194 patients with MPM improved.MethodsIndividuals were recruited from three different centers: a discovery cohort (83 patients with MPM) created by combining patients from two U.S. centers and a separate, independent cohort from Canada (111 patients with MPM). Univariable and multivariable analyses were performed on the initial discovery and independent cohorts separately. In the multivariable analyses, prognostic factors were adjusted for the European Organisation for Research and Treatment of Cancer (EORTC) prognostic index (PI) of mesothelioma. The prognostic significance of adding plasma biomarker data to the PI was determined by using the likelihood ratio test, comparing models with and without the addition of biomarker to the clinical PI. The predictive ability of the biomarker was then assessed formally using Harrell's C-index by applying the fitted model variables of the discovery cohort to the second, independent cohort, including and not including the biomarker with the PI.ResultsHigher levels of osteopontin and mesothelin were individually associated with worse prognosis after adjusting for the PI. In the independent cohort, incorporating either plasma osteopontin or mesothelin into the baseline predictive PI model substantively and statistically significantly improved Harrell's C-statistic. In the final prognostic model, log-osteopontin, EORTC clinical prognostic index, and hemoglobin remained as independently significant predictors and the entire prognostic model improved the optimism-corrected Harrell's C-index significantly, from 0.718 (0.67-0.77) to 0.801 (0.77-0.84).ConclusionsThese data suggest a possible role for preoperative plasma biomarkers to improve the prognostic capability of the EORTC PI of MPM.

Project description:Malignant mesothelioma is an aggressive asbestos-induced cancer, and affected patients have a median survival of approximately one year after diagnosis. It is often difficult to reach a conclusive diagnosis, and ancillary measurements of soluble biomarkers could increase diagnostic accuracy. Unfortunately, few soluble mesothelioma biomarkers are suitable for clinical application. Here we screened the effusion proteomes of mesothelioma and lung adenocarcinoma patients to identify novel soluble mesothelioma biomarkers. We performed quantitative mass-spectrometry-based proteomics using isobaric tags for quantification and used narrow-range immobilized pH gradient/high-resolution isoelectric focusing (pH 4-4.25) prior to analysis by means of nano liquid chromatography coupled to MS/MS. More than 1,300 proteins were identified in pleural effusions from patients with malignant mesothelioma (n = 6), lung adenocarcinoma (n = 6), or benign mesotheliosis (n = 7). Data are available via ProteomeXchange with identifier PXD000531. The identified proteins included a set of known mesothelioma markers and proteins that regulate hallmarks of cancer such as invasion, angiogenesis, and immune evasion, plus several new candidate proteins. Seven candidates (aldo-keto reductase 1B10, apolipoprotein C-I, galectin 1, myosin-VIIb, superoxide dismutase 2, tenascin C, and thrombospondin 1) were validated by enzyme-linked immunosorbent assays in a larger group of patients with mesothelioma (n = 37) or metastatic carcinomas (n = 25) and in effusions from patients with benign, reactive conditions (n = 16). Galectin 1 was identified as overexpressed in effusions from lung adenocarcinoma relative to mesothelioma and was validated as an excellent predictor for metastatic carcinomas against malignant mesothelioma. Galectin 1, aldo-keto reductase 1B10, and apolipoprotein C-I were all identified as potential prognostic biomarkers for malignant mesothelioma. This analysis of the effusion proteome furthers our understanding of malignant mesothelioma, identified galectin 1 as a potential diagnostic biomarker, and highlighted several possible prognostic biomarkers of this disease.

Dataset Information

Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma.

Publications

Validation of Inflammatory Prognostic Biomarkers in Pleural Mesothelioma.

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