Prognostic Role of Tumor Immune Microenvironment in Pleural Epithelioid Mesothelioma.

Background: Pleural mesothelioma (MPM) is an aggressive malignancy with an average patient survival of only 10 months. Interestingly, about 5%-10% of the patients survive remarkably longer. Prior studies have suggested that the tumor immune microenvironment (TIME) has potential prognostic value in MPM. We hypothesized that high-resolution single-cell spatial profiling of the TIME would make it possible to identify subpopulations of patients with long survival and identify immunophenotypes for the development of novel treatment strategies. Methods: We used multiplexed fluorescence immunohistochemistry (mfIHC) and cell-based image analysis to define spatial TIME immunophenotypes in 69 patients with epithelioid MPM (20 patients surviving ≥ 36 months). Five mfIHC panels (altogether 21 antibodies) were used to classify tumor-associated stromal cells and different immune cell populations. Prognostic associations were evaluated using univariate and multivariable Cox regression, as well as combination risk models with area under receiver operating characteristic curve (AUROC) analyses. Results: We observed that type M2 pro-tumorigenic macrophages (CD163+pSTAT1-HLA-DRA1-) were independently associated with shorter survival, whereas granzyme B+ cells and CD11c+ cells were independently associated with longer survival. CD11c+ cells were the only immunophenotype increasing the AUROC (from 0.67 to 0.84) when added to clinical factors (age, gender, clinical stage, and grade). Conclusion: High-resolution, deep profiling of TIME in MPM defined subgroups associated with both poor (M2 macrophages) and favorable (granzyme B/CD11c positivity) patient survival. CD11c positivity stood out as the most potential prognostic cell subtype adding prediction power to the clinical factors. These findings help to understand the critical determinants of TIME for risk and therapeutic stratification purposes in MPM.

High tumor cell platelet-derived growth factor receptor beta expression is associated with shorter survival in malignant pleural epithelioid mesothelioma.

Malignant pleural mesothelioma (MPM) has a rich stromal component containing mesenchymal fibroblasts. However, the properties and interplay of MPM tumor cells and their surrounding stromal fibroblasts are poorly characterized. Our objective was to spatially profile known mesenchymal markers in both tumor cells and associated fibroblasts and correlate their expression with patient survival. The primary study cohort consisted of 74 MPM patients, including 16 patients who survived at least 60 months. We analyzed location-specific tissue expression of seven fibroblast markers in clinical samples using multiplexed fluorescence immunohistochemistry (mfIHC) and digital image analysis. Effect on survival was assessed using Cox regression analyses. The outcome measurement was all-cause mortality. Univariate analysis revealed that high expression of secreted protein acidic and cysteine rich (SPARC) and fibroblast activation protein in stromal cells was associated with shorter survival. Importantly, high expression of platelet-derived growth factor receptor beta (PDGFRB) in tumor cells, but not in stromal cells, was associated with shorter survival (hazard ratio [HR] = 1.02, p < 0.001). A multivariable survival analysis adjusted for clinical parameters and stromal mfIHC markers revealed that tumor cell PDGFRB and stromal SPARC remained independently associated with survival (HR = 1.01, 95% confidence interval [CI] = 1.00-1.03 and HR = 1.05, 95% CI = 1.00-1.11, respectively). The prognostic effect of PDGFRB was validated with an artificial intelligence-based analysis method and further externally validated in another cohort of 117 MPM patients. In external validation, high tumor cell PDGFRB expression associated with shorter survival, especially in the epithelioid subtype. Our findings suggest PDGFRB and SPARC as potential markers for risk stratification and as targets for therapy.

Artificial intelligence identifies inflammation and confirms fibroblast foci as prognostic tissue biomarkers in idiopathic pulmonary fibrosis.

A large number of fibroblast foci (FF) predict mortality in idiopathic pulmonary fibrosis (IPF). Other prognostic histological markers have not been identified. Artificial intelligence (AI) offers a possibility to quantitate possible prognostic histological features in IPF. We aimed to test the use of AI in IPF lung tissue samples by quantitating FF, interstitial mononuclear inflammation, and intra-alveolar macrophages with a deep convolutional neural network (CNN). Lung tissue samples of 71 patients with IPF from the FinnishIPF registry were analyzed by an AI model developed in the Aiforia® platform. The model was trained to detect tissue, air spaces, FF, interstitial mononuclear inflammation, and intra-alveolar macrophages with 20 samples. For survival analysis, cut-point values for high and low values of histological parameters were determined with maximally selected rank statistics. Survival was analyzed using the Kaplan-Meier method. A large area of FF predicted poor prognosis in IPF (p = 0.01). High numbers of interstitial mononuclear inflammatory cells and intra-alveolar macrophages were associated with prolonged survival (p = 0.01 and p = 0.01, respectively). Of lung function values, low diffusing capacity for carbon monoxide was connected to a high density of FF (p = 0.03) and a high forced vital capacity of predicted was associated with a high intra-alveolar macrophage density (p = 0.03). The deep CNN detected histological features that are difficult to quantitate manually. Interstitial mononuclear inflammation and intra-alveolar macrophages were novel prognostic histological biomarkers in IPF. Evaluating histological features with AI provides novel information on the prognostic estimation of IPF.

Histopathological features of epithelioid malignant pleural mesotheliomas in patients with extended survival.

Diffuse malignant mesothelioma (DMM) of the pleura is a rare and aggressive disease, wherein the long-term survival (LTS) rate is low. The epithelioid subtype is the most prevalent form of DMM with the best prognosis. To study prognostic histopathologic factors associated with extended survival in epithelioid DMM, we examined 43 tumors from patients with survival more than five years (LTSs) and compared the findings with 84 tumors from a reference group (RG) with average survival. We analyzed the tumors considering previously published histopathological prognostic features and attempted to identify additional morphological features predictive of extended survival. Most of the LTS tumors presented with nuclear grade I (n = 34, 90%) and a tubulopapillary growth pattern (n = 30, 70%). One LTS tumor had necrosis. In contrast, nuclear grade II (n = 49, 61%) and solid growth pattern (n = 59, 70%) were more frequent in the RG, and necrosis was present in 16 (19%) tumors. We also evaluated the association of asbestos lung tissue fiber burden quantified from autopsy samples with histopathological features and found that elevated asbestos fiber was associated with higher nuclear grade (P < 0.001) and the presence of necrosis (P = 0.021). In univariate survival analysis, we identified the following three novel morphological features associated with survival: exophytic polypoid growth pattern, tumor density, and single mesothelium layered tubular structures. After adjustments, low nuclear grade (P < 0.001) and presence of exophytic polypoid growth (P = 0.024) were associated with prolonged survival. These results may aid in estimating DMM prognosis.

Elevated Circulating Activin A Levels in Patients With Malignant Pleural Mesothelioma Are Related to Cancer Cachexia and Reduced Response to Platinum-based Chemotherapy.

BACKGROUND: Previous preclinical studies have shown that activin A is overexpressed in malignant pleural mesothelioma (MPM), associates with cancer cachexia, and is observed in in vitro resistance to platinum-based chemotherapy. We evaluated circulating activin levels and their endogenous antagonists' follistatin/follistatin-like 3 in intrathoracic tumors. MATERIALS AND METHODS: Patients suspected of thoracic malignancy were recruited prior to surgery. Serum samples were collected from 21 patients with MPM, 59 patients with non-small-cell lung cancer (NSCLC), and 22 patients with benign lung lesions. Circulating activin/follistatin levels were measured using enzyme-linked immunosorbent assay and compared with clinicopathologic parameters. RESULTS: Circulating activin A levels were elevated in patients with MPM when compared with patients with NSCLC or benign lung lesion samples (P < .0001). Also, follistatin and follistatin-like 3 levels were the highest in MPM, although with less difference compared with activin A. Receiver operating characteristic analysis for activin A for separating NSCLC from benign lung lesion showed an area under the curve of 0.856 (95% confidence interval, 0.77-0.94). Activin A levels were higher in patients with cachexia (P < .001). In patients with MPM, activin A levels correlated positively with computed tomography-based baseline tumor size (R = 0.549; P = .010) and the change in tumor size after chemotherapy (R = 0.743; P = .0006). Patients with partial response or stable disease had lower circulating activin A levels than the ones with progressive disease (P = .028). CONCLUSION: Activin A serum level could be used as a biomarker in differentiating malignant and benign lung tumors. Circulating activin A levels were elevated in MPM and associates with cancer cachexia and reduced chemotherapy response.

Inorganic particulate matter in the lung tissue of idiopathic pulmonary fibrosis patients reflects population density and fine particle levels.

Idiopathic pulmonary fibrosis (IPF) is a chronic lung disease with a dismal prognosis and an unknown etiology. Inorganic dust is a known risk factor, and air pollution seems to affect disease progression. We aimed to investigate inorganic particulate matter in IPF lung tissue samples. Using polarizing light microscopy, we examined coal dust pigment and inorganic particulate matter in 73 lung tissue samples from the FinnishIPF registry. We scored the amount of coal dust pigment and particulate matter from 0 to 5. Using energy dispersive spectrometry with a scanning electron microscope, we conducted an elemental analysis of six IPF lung tissue samples. We compared the results to the registry data, and to the population density and air quality data. To compare categorical data, we used Fisher's exact test; we estimated the survival of the patients with Kaplan-Meier curves. We found inorganic particulate matter in all samples in varying amounts. Samples from the southern regions of Finland, where population density and fine particle levels are high, more often had particulate matter scores from 3 to 5 than samples from the northern regions (31/50, 62.0% vs. 7/23, 30.4%, p = 0.02). The highest particulate matter scores of 4 and 5 (n = 15) associated with a known exposure to inorganic dust (p = 0.004). An association between particulate matter in the lung tissue of IPF patients and exposure to air pollution may exist.

Computed tomography in the evaluation of malignant pleural mesothelioma-Association of tumor size to a sarcomatoid histology, a more advanced TNM stage and poor survival.

OBJECTIVES: Appropriate clinical staging of malignant pleural mesothelioma (MPM) is critical for correct treatment decisions. Newly revised TNM staging protocol has been released for MPM. We investigated baseline computed tomography (CT) characteristics of MPM patients, the new staging system and a simple tumor size (TS) assessment in terms of survival. MATERIALS AND METHODS: As part of our study that included all MPM patients diagnosed in Finland 2000-2012, we retrospectively reviewed 161 CT scans of MPM patients diagnosed between 2007 and 2012 in the Hospital District of Helsinki and Uusimaa. TS was estimated by using the maximal tumor thickness and grading tumor extension along the chest wall. Cox Regression models were used to identify relationships between survival, clinicopathological factors and CT-findings. RESULTS: The median length of follow-up was 9.7 months and the median survival 9.1 months. The right sided tumors tended to be more advanced at baseline and had worse prognosis in the univariate analyses. In the multivariate survival model, TS, pleural effusion along with non-epithelioid histology were predictors of poor survival. Tumor size correlated significantly with a sarcomatoid histopathological finding and several parameters linked to a more advanced TNM stage. Most patients were diagnosed with locally advanced stage, while 12 (7%) had no sign of the tumor in CT. CONCLUSION: In this study, we demonstrate a novel approach for MPM tumor size evaluation that has a strong relationship with mortality, sarcomatoid histology and TNM stage groups. TS could be used for prognostic purposes and it may be a useful method for assessing therapy responses.