Faculty Bibliography

BACKGROUND:edition of the PM staging system. METHODS:edition data. Overall survival (OS) was calculated by the Kaplan-Meier method and differences in OS assessed by the log-rank test. RESULTS:edition analyses. CONCLUSION/CONCLUSIONS:Given reproducible prognostication by Psum, size criteria will be incorporated into cT1-T3 categories in the 9th edition. Current cT4 category and all pT descriptors will be maintained, with reclassification of fissural invasion as pT2.

The International Association for the Study of Lung Cancer collaborated with the International Mesothelioma Interest Group to propose the first TNM stage classification system for diffuse pleural mesothelioma in 1995, accepted by the Union for International Cancer Control and the American Joint Committee on Cancer for the sixth and seventh edition stage classification manuals. The International Association for the Study of Lung Cancer Staging and Prognostic Factors Committee Mesothelioma Domain developed and analyzed an international registry of patients with pleural mesothelioma and updated TNM descriptors for the eighth edition of the stage classification system. To inform revisions for the forthcoming ninth edition of the TNM stage classification system, data submission was solicited for patients diagnosed between 2013 and 2022 with expanded data elements on the basis of the first project's exploratory analyses, including pleural thickness measurements, updated surgical nomenclature, and molecular markers. The resulting database consisted of a total of 3598 analyzable cases from Europe, Australia, Asia, North America, and South America, with a median age of 71 years (range: 18-99 y), 2775 (77.1%) of whom were men. With only 1310 patients (36.4%) undergoing curative-intent operations, this iteration of the database includes far more patients treated nonsurgically compared with prior. Four separate manuscripts on T, N, M, and stage groupings submitted to this journal will summarize analyses of these data and will serve collectively as the primary source of the proposed changes to the upcoming ninth edition of the pleural mesothelioma stage classification system.

Cancer diagnosis and management depend upon the extraction of complex information from microscopy images by pathologists, which requires time-consuming expert interpretation prone to human bias. Supervised deep learning approaches have proven powerful, but are inherently limited by the cost and quality of annotations used for training. Therefore, we present Histomorphological Phenotype Learning, a self-supervised methodology requiring no labels and operating via the automatic discovery of discriminatory features in image tiles. Tiles are grouped into morphologically similar clusters which constitute an atlas of histomorphological phenotypes (HP-Atlas), revealing trajectories from benign to malignant tissue via inflammatory and reactive phenotypes. These clusters have distinct features which can be identified using orthogonal methods, linking histologic, molecular and clinical phenotypes. Applied to lung cancer, we show that they align closely with patient survival, with histopathologically recognised tumor types and growth patterns, and with transcriptomic measures of immunophenotype. These properties are maintained in a multi-cancer study.

In a previous study, heart xenografts from 10-gene-edited pigs transplanted into two human decedents did not show evidence of acute-onset cellular- or antibody-mediated rejection. Here, to better understand the detailed molecular landscape following xenotransplantation, we carried out bulk and single-cell transcriptomics, lipidomics, proteomics and metabolomics on blood samples obtained from the transplanted decedents every 6 h, as well as histological and transcriptomic tissue profiling. We observed substantial early immune responses in peripheral blood mononuclear cells and xenograft tissue obtained from decedent 1 (male), associated with downstream T cell and natural killer cell activity. Longitudinal analyses indicated the presence of ischemia reperfusion injury, exacerbated by inadequate immunosuppression of T cells, consistent with previous findings of perioperative cardiac xenograft dysfunction in pig-to-nonhuman primate studies. Moreover, at 42 h after transplantation, substantial alterations in cellular metabolism and liver-damage pathways occurred, correlating with profound organ-wide physiological dysfunction. By contrast, relatively minor changes in RNA, protein, lipid and metabolism profiles were observed in decedent 2 (female) as compared to decedent 1. Overall, these multi-omics analyses delineate distinct responses to cardiac xenotransplantation in the two human decedents and reveal new insights into early molecular and immune responses after xenotransplantation. These findings may aid in the development of targeted therapeutic approaches to limit ischemia reperfusion injury-related phenotypes and improve outcomes.

INTRODUCTION/BACKGROUND:The International Association for the Study of Lung Cancer developed an international pleural mesothelioma database to improve staging. Data entered from 1995 to 2009 (training data set) were analyzed previously to evaluate supplemental prognostic factors. We evaluated these factors with new clinical data to determine whether the previous models could be improved. METHODS:Patients entered into the database from 2009 to 2019 (validation cohort) were assessed for the association between previous prognosticators and overall survival using Cox proportional hazards regression with bidirectional stepwise selection. Additional variables were analyzed and models were compared using Harrell's C-index. RESULTS:The training data set included 3101 patients and the validation cohort, 1733 patients. For the multivariable pathologic staging model applied to the training cohort, C-index was 0.68 (95% confidence interval [CI]: 0.656-0.705). For the validation data set (n = 497), C-index was 0.650 (95% CI: 0.614-0.685), and pathologic stage, histologic diagnosis, sex, adjuvant therapy, and platelet count were independently associated with survival. Adding anemia to the model increased the C-index to 0.652 (95% CI: 0.618-0.686). A basic presentation model including all parameters before staging yielded a C-index of 0.668 (95% CI: 0.641-0.695). In comparison, the European Organization for Research and Treatment of Cancer model yielded C-indices of 0.550 (95% CI: 0.511-0.589) and 0.577 (95% CI: 0.550-0.604) for pathologic staging and presentation models, respectively. CONCLUSIONS:Although significant predictors differed slightly, the International Association for the Study of Lung Cancer training model performed well in the validation set and better than the model of the European Organization for Research and Treatment of Cancer. International collaboration is critical to improve outcomes in this rare disease.