Faculty Bibliography

INTRODUCTION/BACKGROUND:The International Association for the Study of Lung Cancer developed an international database to inform potential revisions in the ninth edition of the TNM classification of diffuse pleural mesothelioma (PM). This study analyzed the clinical and pathologic N categories to determine whether revisions were indicated relative to the eighth edition staging system. METHODS:Of 7338 PM cases diagnosed from 2013 to 2022 and 3598 met all inclusion criteria for planned analyses. Data on 2836 patients without metastases were included in this study. Overall survival (OS) was measured from date of diagnosis. Patients were included regardless of whether they received neoadjuvant treatment. For the pathologic N analysis, patients who underwent resection (extrapleural pneumonectomy or pleurectomy/decortication) were included. N subgroups were analyzed and OS assessed by the Kaplan-Meier method. RESULTS:The existing eighth edition N categories were performed adequately in the ninth edition data set. A median OS advantage was noted for clinical and pathologic N0 versus N1 patients: 23.2 versus 18.5 and 33.8 versus 25.0 months, respectively. Patients with resected pN0 had a 3-year OS of 48%. No difference in OS was noted for single- versus multiple-station nodal metastases. The number of nodal stations sampled at the time of resection was not associated with a difference in OS. CONCLUSIONS:Data regarding clinical and pathologic N categories corroborate those used in the eighth edition. No changes in the N categories are recommended in the ninth edition of PM staging system.

OBJECTIVE:Early-stage lung adenocarcinoma is treated with local therapy alone, although patients with grade 3 stage I lung adenocarcinoma have a 50% 5-year recurrence rate. Our objective is to determine if analysis of the tumor microenvironment can create a predictive model for recurrence. METHODS:Thirty-four patients with grade 3 stage I lung adenocarcinoma underwent surgical resection. Digital spatial profiling was used to perform genomic (n = 31) and proteomic (n = 34) analyses of pancytokeratin positive and negative tumor cells. K-means clustering was performed on the top 50 differential genes and top 20 differential proteins, with Kaplan-Meier recurrence curves based on patient clustering. External validation of high-expression genes was performed with Kaplan-Meier plotter. RESULTS:There were no significant clinicopathologic differences between patients who did (n = 14) and did not (n = 20) have recurrence. Median time to recurrence was 806 days; median follow-up with no recurrence was 2897 days. K-means clustering of pancytokeratin positive genes resulted in a model with a Kaplan-Meier curve with concordance index of 0.75. K-means clustering for pancytokeratin negative genes was less successful at differentiating recurrence (concordance index 0.6). Genes upregulated or downregulated for recurrence were externally validated using available public databases. Proteomic data did not reach statistical significance but did internally validate the genomic data described. CONCLUSIONS:Genomic difference in lung adenocarcinoma may be able to predict risk of recurrence. After further validation, stratifying patients by this risk may help guide who will benefit from adjuvant therapy.

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.