Faculty Bibliography

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.

Lung adenocarcinoma staging and grading were recently updated to reflect the link between histologic growth patterns and outcomes. The lepidic growth pattern is regarded as "in-situ," whereas all other patterns are regarded as invasive, though with stratification. Solid, micropapillary, and complex glandular patterns are associated with worse prognosis than papillary and acinar patterns. These recent changes have improved prognostic stratification. However, multiple pitfalls exist in measuring invasive size and in classifying lung adenocarcinoma growth patterns. Awareness of these limitations and recommended practices will help the pathology community achieve consistent prognostic performance and potentially contribute to improved patient management.

KRAS^G12C inhibitors (adagrasib and sotorasib) have shown clinical promise in targeting KRAS^G12C-mutated lung cancers; however, most patients eventually develop resistance. In lung patients with adenocarcinoma with KRAS^G12C and STK11/LKB1 co-mutations, we find an enrichment of the squamous cell carcinoma gene signature in pre-treatment biopsies correlates with a poor response to adagrasib. Studies of Lkb1-deficient KRAS^G12C and Kras^G12D lung cancer mouse models and organoids treated with KRAS inhibitors reveal tumors invoke a lineage plasticity program, adeno-to-squamous transition (AST), that enables resistance to KRAS inhibition. Transcriptomic and epigenomic analyses reveal ΔNp63 drives AST and modulates response to KRAS inhibition. We identify an intermediate high-plastic cell state marked by expression of an AST plasticity signature and Krt6a. Notably, expression of the AST plasticity signature and KRT6A at baseline correlates with poor adagrasib responses. These data indicate the role of AST in KRAS inhibitor resistance and provide predictive biomarkers for KRAS-targeted therapies in lung cancer.

INTRODUCTION/BACKGROUND:Pathologists are staging thymic epithelial tumors (TET) according to the 8th UICC/AJCC TNM system. Within the French RYTHMIC network, dedicated to TET, agreement on pathologic tumor stage (pT) among the pathology panelists was difficult. The aim of our study was to determine the interobserver reproducibility of pT at an international level, to explore the source of discrepancies and potential interventions to address these. METHODS:An international panel of pathologists was recruited through the International Thymic Malignancy Interest Group (ITMIG). The study focused on invasion of mediastinal pleura, pericardium, and lung. From a cohort of cases identified as challenging within the RYTHMIC network, we chose a series of test and validation cases (n = 5 and 10, respectively). RESULTS:Reproducibility of the pT stage was also challenging at an international level as none of the 15 cases was classified as the same pT stage by all ITMIG pathologists. The agreement rose from slight (κ = 0.13) to moderate (κ = 0.48) between test and validation series. Discussion among the expert pathologists pinpointed two major reasons underlying discrepancies: 1) Thymomas growing with their "capsule" and adhering to the pleurae, pericardium, or lung were often misinterpreted as invading these structures. 2) Recognition of the mediastinal pleura was identified as challenging. CONCLUSION/CONCLUSIONS:Our study underlines that the evaluation of the pT stage of TET is problematic and needs to be addressed in more detail in an upcoming TNM classification. The publication of histopathologic images of landmarks, including ancillary tests could improve reproducibility for future TNM classifications.

Advancements in the classification of lung adenocarcinoma have resulted in significant changes in pathological reporting. The eighth edition of the tumour-node-metastasis (TNM) staging guidelines calls for the use of invasive size in staging in place of total tumour size. This shift improves prognostic stratification and requires a more nuanced approach to tumour measurements in challenging situations. Similarly, the adoption of new grading criteria based on the predominant and highest-grade pattern proposed by the International Association for the Study of Lung Cancer (IASLC) shows improved prognostication, and therefore clinical utility, relative to previous grading systems. Spread through airspaces (STAS) is a form of tumour invasion involving tumour cells spreading through the airspaces, which has been highly researched in recent years. This review discusses updates in pathological T staging, adenocarcinoma grading and STAS and illustrates the utility and limitations of current concepts in lung adenocarcinoma.

Recent statistics on lung cancer, including the steady decline of advanced diseases and the dramatically increasing detection of early-stage diseases and indeterminate pulmonary nodules, mark the significance of a comprehensive understanding of early lung carcinogenesis. Lung adenocarcinoma (ADC) is the most common histologic subtype of lung cancer, and atypical adenomatous hyperplasia is the only recognized preneoplasia to ADC, which may progress to adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) and eventually to invasive ADC. Although molecular evolution during early lung carcinogenesis has been explored in recent years, the progress has been significantly hindered, largely due to insufficient materials from ADC precursors. Here, we employed state-of-the-art deep learning and artificial intelligence techniques to robustly segment and recognize cells on routinely used hematoxylin and eosin histopathology images and extracted 9 biology-relevant pathomic features to decode lung preneoplasia evolution. We analyzed 3 distinct cohorts (Japan, China, and United States) covering 98 patients, 162 slides, and 669 regions of interest, including 143 normal, 129 atypical adenomatous hyperplasia, 94 AIS, 98 MIA, and 205 ADC. Extracted pathomic features revealed progressive increase of atypical epithelial cells and progressive decrease of lymphocytic cells from normal to AAH, AIS, MIA, and ADC, consistent with the results from tissue-consuming and expensive molecular/immune profiling. Furthermore, pathomics analysis manifested progressively increasing cellular intratumor heterogeneity along with the evolution from normal lung to invasive ADC. These findings demonstrated the feasibility and substantial potential of pathomics in studying lung cancer carcinogenesis directly from the low-cost routine hematoxylin and eosin staining.

AIMS/OBJECTIVE:Thymic epithelial tumours (TET), including thymomas and thymic carcinomas and thymic neuroendocrine neoplasms, are malignant neoplasms that can be associated with morbidity and mortality. Recently, an updated version of the World Health Organization (WHO) Classification of Thoracic Tumours 5th Edition, 2021 has been released, which included various changes to the classification of these neoplasms. In addition, in 2017 the Union for International Cancer Control (UICC) / American Joint Committee on Cancer (AJCC) published the 8th Edition Staging Manual which, for the first time, includes a TNM staging that is applicable to thymomas, thymic carcinomas, and thymic neuroendocrine neoplasms. METHODS AND RESULTS/RESULTS:To standardize reporting of resected TET and thymic neuroendocrine neoplasms the accrediting bodies updated their reporting protocols. The International Collaboration on Cancer Reporting (ICCR), which represents a collaboration between various National Associations of Pathology, updated its 2017 histopathology reporting guide on TET and thymic neuroendocrine neoplasms accordingly. This report will highlight important changes in the reporting of TET and thymic neuroendocrine neoplasms based on the 2021 WHO, emphasize the 2017 TNM staging, and also comment on the rigour and various uncertainties for the pathologist when trying to follow that staging. CONCLUSION/CONCLUSIONS:The ICCR dataset provides a comprehensive, standardized template for reporting of resected TET and thymic neuroendocrine neoplasms.

Lung cancer treatment has benefited greatly through advancements in immunotherapies. However, immunotherapy often fails in patients with specific mutations like KEAP1, which are frequently found in lung adenocarcinoma. We established an antigenic lung cancer model and used it to explore how Keap1 mutations remodel the tumor immune microenvironment. Using single-cell technology and depletion studies, we demonstrate that Keap1-mutant tumors diminish dendritic cell and T cell responses driving immunotherapy resistance. This observation was corroborated in patient samples. CRISPR-Cas9-mediated gene targeting revealed that hyperactivation of the NRF2 antioxidant pathway is responsible for diminished immune responses in Keap1-mutant tumors. Importantly, we demonstrate that combining glutaminase inhibition with immune checkpoint blockade can reverse immunosuppression, making Keap1-mutant tumors susceptible to immunotherapy. Our study provides new insight into the role of KEAP1 mutations in immune evasion, paving the way for novel immune-based therapeutic strategies for KEAP1-mutant cancers.