Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity

Malignant pleural mesothelioma (MPM) is an aggressive cancer with rising incidence and challenging clinical management. Through a large series of whole-genome sequencing data, integrated with transcriptomic and epigenomic data using multiomics factor analysis, we demonstrate that the current World Health Organization classification only accounts for up to 10% of interpatient molecular differences. Instead, the MESOMICS project paves the way for a morphomolecular classification of MPM based on four dimensions: ploidy, tumor cell morphology, adaptive immune response and CpG island methylator profile. We show that these four dimensions are complementary, capture major interpatient molecular differences and are delimited by extreme phenotypes that-in the case of the interdependent tumor cell morphology and adapted immune response-reflect tumor specialization. These findings unearth the interplay between MPM functional biology and its genomic history, and provide insights into the variations observed in the clinical behavior of patients with MPM.

Solid papillary mesothelial tumor

We report nine examples of a previously undescribed type of peritoneal circumscribed nodular mesothelial tumor characterized by nests or sheets of mesothelial cells with sharp cell borders and extremely bland, sometimes grooved, nuclei. In some cases, nests were separated by fibrous bands. All patients were women, age range 30-72 years (median 52 years). All tumors were incidental findings during surgery and grossly were either solitary nodules or a few small nodules on the peritoneal surface. Referring pathologic diagnoses included diffuse malignant mesothelioma, localized malignant mesothelioma, well-differentiated papillary mesothelioma, and adenomatoid tumor. No tumor showed BAP1 loss by immunohistochemistry nor deletion of CDKN2A by FISH. RNA-seq revealed that these tumors clustered together and were distinct from peritoneal diffuse malignant mesotheliomas. Very few mutations or translocations were found, none of them recurrent from tumor to tumor, and no tumor showed an abnormality in any of the genes typically mutated/deleted in diffuse malignant mesothelioma. Array CGH on three cases revealed two with a completely flat profile and one with a small deletion at 3q26-3q28. On follow-up (range 5-60, median 34 months), there were no deaths, no recurrences, and no evidence of metastatic disease nor local spread; one case that initially had scattered nodules on the pelvic peritoneum had the same pattern of nodules at a second look operation 2 years later. We propose the name solid papillary mesothelial tumor for these lesions. These appear to be either benign or very low-grade tumors that need to be separated from malignant mesotheliomas.

Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center

INTRODUCTION

Histologic subtypes of malignant pleural mesothelioma are a major prognostic indicator and decision denominator for all therapeutic strategies. In an ambiguous case, a rare transitional mesothelioma (TM) pattern may be diagnosed by pathologists either as epithelioid mesothelioma (EM), biphasic mesothelioma (BM), or sarcomatoid mesothelioma (SM). This study aimed to better characterize the TM subtype from a histological, immunohistochemical, and molecular standpoint. Deep learning of pathologic slides was applied to this cohort.

METHODS

A random selection of 49 representative digitalized sections from surgical biopsies of TM was reviewed by 16 panelists. We evaluated BAP1 expression and CDKN2A (p16) homozygous deletion. We conducted a comprehensive, integrated, transcriptomic analysis. An unsupervised deep learning algorithm was trained to classify tumors.

RESULTS

The 16 panelists recorded 784 diagnoses on the 49 cases. Even though a Kappa value of 0.42 is moderate, the presence of a TM component was diagnosed in 51%. In 49% of the histological evaluation, the reviewers classified the lesion as EM in 53%, SM in 33%, or BM in 14%. Median survival was 6.7 months. Loss of BAP1 observed in 44% was less frequent in TM than in EM and BM. p16 homozygous deletion was higher in TM (73%), followed by BM (63%) and SM (46%). RNA sequencing unsupervised clustering analysis revealed that TM grouped together and were closer to SM than to EM. Deep learning analysis achieved 94% accuracy for TM identification.

CONCLUSION

These results revealed that the TM pattern should be classified as non-EM or at minimum as a subgroup of the SM type.