Tsao, Ming‐Sound

Abstract INTRODUCTION Brain metastases (BM) are the most common intracranial tumor, with a poor prognosis of 10-16 months, and lung adenocarcinoma (LUAD) is the most common source. Currently, we cannot reliably predict which patients will develop BMs clinically, so most are detected after they develop and growing to cause deficits. Here, we use tumor DNA methylomes to predict which patients are likely to develop BM through the course of disease and we use both cerebrospinal fluid (CSF) and plasma methylomes for BM liquid biopsy, enabling their early detection and treatment. METHODS DNA methylomes were acquired from 419 tumor and plasma samples from 363 LUAD and BM patients. We built DNA methylation-based models that predict BM development and that also identify BMs non-invasively from CSF and plasma in discovery data subsets. A nomogram was built that predicts BM risk using methylation scores and clinical stage together. Models were evaluated in independent validation sets. RESULTS Our model predicting BM development was accurate (Univariable Cox: HR=5.7, 95% CI=1.9-17.2), p=0.0023), independent of clinical factors (Multivariable Cox: HR=8.9, 95% CI=2.0-40.5, p=0.0046), and more predictive than cancer staging used currently clinically (AUC=0.81 versus 0.65). Our combinatorial nomogram using methylation and staging data together showed enhanced BM prediction (Univariable Cox: HR=17.2, 95% CI=4.1-71.3, p<0.0001; AUROC=0.82). Our models identifying BM through biofluid methylomes accurately distinguished BM from differential diagnoses of gliomas and lymphomas in plasma (AUROC=0.80, 95% CI=0.68-0.93) and with greater accuracy in CSF (AUROC=0.93, 95% CI=0.71-1.0). CONCLUSION Overall, we show the first approaches for robust molecular prediction of BM development and for reliable liquid biopsy of BM. This work is expected to transform cancer management by identifying high-risk lung cancer patients after initial treatment for inclusion in screening protocols using neuroimaging and liquid biopsy, to identify BM development early with less advanced disease and more optimal therapeutic outcomes.

2030 Background: Brain metastases (BM) are common and arise in 30% of lung adenocarcinoma (LUAD) patients. Patients with LUAD that develop BM have significantly poorer outcomes, with a 10-16 month median overall survival. Unfortunately, current clinical practice for BM prediction is limited and so BM are typically detected after they develop and grow to cause neurological symptoms. Once BM are detected, currently neurosurgical tumor biopsies are performed to enable BM diagnosis via neuropathological evaluation. The aims of this study were to develop DNA methylation-based models that predict LUAD BM and non-invasively detect BM in blood to enable early diagnosis and treatment. Methods: DNA methylomes were acquired from 402 tumor tissue and plasma samples in a cohort of 346 LUAD and BM patients. Machine learning models were built using DNA methylation signatures that stratify BM risk in tissue and detect BM in plasma. Models were evaluated in independent validation datasets. A predictive nomogram was developed using the BM prediction model together with clinical factors to provide composite patient-specific scores reflecting BM risk. Results: The methylation-based BM predictor accurately stratified BM risk in a univariable Cox model using validation set data (HR = 5.65, 95%CI 1.85–17.2, p = 0.0023). Model utility was independent of the predictive value of clinical factors in a multivariable Cox model using validation set data (Table 1: HR = 8.92, 95%CI 1.97–40.5, p = 0.0046). The 5-year model accuracy was 0.81 and significantly higher than a similarly built cancer stage-based model (0.65), demonstrating utility over current practice. The combinatorial clinical-methylomic predictive nomogram had enhanced utility with an accuracy of 0.82 univariable Cox HR of 17.2 (95%CI 4.13–71.3, p < 0.0001), demonstrating comprehensive patient-specificity. The plasma-based model accurately classified BM from gliomas and lymphomas (AUROC=0.80), as typical clinical differential diagnoses, in validation set data. The models were validated further in additional external data. Conclusions: DNA methylation-based modeling of BM can accurately predict LUAD patients at risk for BM development and can non-invasively detect BM that develop. Future treatment approaches may tailor initial LUAD treatment and ongoing cancer surveillance to a patient’s BM risk, allowing for the potential to prevent and treat BM early. DNA methylation-based BM prediction is independent of clinical factors in a multivariable Cox proportional hazards model. Variable HR 95% CI p Methylome risk score 8.92 1.97–40.5 0.005 Age Years 0.96 0.92–1.02 0.177 Smoking Pack-years 0.99 0.95–1.03 0.496 EGFR Mutant vs wildtype 0.92 0.25–3.34 0.895 T T2 vs T1 1.58 0.41–6.04 0.505 T3−4 vs T1 1.49 0.28–7.98 0.642 N N1 vs N0 1.05 0.31–3.58 0.943 N2−3 vs N0 1.00 0.27–3.69 0.995 M M1 vs M0 145 12.2–1730 <0.001

Context.— Mesothelioma is an uncommon tumor that can be difficult to diagnose. Objective.— To provide updated, practical guidelines for the pathologic diagnosis of mesothelioma. Data Sources.— Pathologists involved in the International Mesothelioma Interest Group and others with expertise in mesothelioma contributed to this update. Reference material includes peer-reviewed publications and textbooks. Conclusions.— There was consensus opinion regarding guidelines for (1) histomorphologic diagnosis of mesothelial tumors, including distinction of epithelioid, biphasic, and sarcomatoid mesothelioma; recognition of morphologic variants and patterns; and recognition of common morphologic pitfalls; (2) molecular pathogenesis of mesothelioma; (3) application of immunohistochemical markers to establish mesothelial lineage and distinguish mesothelioma from common morphologic differentials; (4) application of ancillary studies to distinguish benign from malignant mesothelial proliferations, including BAP1 and MTAP immunostains; novel immunomarkers such as Merlin and p53; fluorescence in situ hybridization (FISH) for homozygous deletion of CDKN2A; and novel molecular assays; (5) practical recommendations for routine reporting of mesothelioma, including grading epithelioid mesothelioma and other prognostic parameters; (6) diagnosis of mesothelioma in situ; (7) cytologic diagnosis of mesothelioma, including use of immunostains and molecular assays; and (8) features of nonmalignant peritoneal mesothelial lesions.

Abstract Objectives Numerous studies on malignant mesothelioma (MM) highlight the prognostic importance of histologic subtype, nuclear grade, and necrosis. This study compares these parameters in paired biopsy and resection specimens of pleural MM. Methods Histologic subtype, percentage of epithelioid morphology, nuclear grade, and the presence or absence of necrosis were compared in 429 paired biopsies and resection specimens of pleural MM from 19 institutions. Results Histologic subtype was concordant in 81% of cases (κ = 0.58). When compared with resection specimens, epithelioid morphology at biopsy had a positive predictive value (PPV) of 78.9% and a negative predictive value (NPV) of 93.5%; sarcomatoid morphology showed high PPV (92.9%) and NPV (99.3%), and biphasic morphology PPV was 89.7% and NPV was 79.7%. Agreement of the percentage of epithelioid morphology was fair (κ = 0.27). Nuclear grade and necrosis were concordant in 75% (κ = 0.59) and 81% (κ = 0.53) of cases, respectively. Nuclear grade showed moderate (κ = 0.53) and substantial (κ = 0.67) agreement from patients with and without neoadjuvant therapy, respectively, and necrosis showed moderate (κ = 0.47 and κ = 0.60) agreement, respectively, in the same subsets of paired specimens. Conclusions Paired biopsy-resection specimens from pleural MM show overall moderate agreement in pathologic parameters. These findings may help guide postbiopsy management and triage of patients with MM.

TPS9079 Background: Pleurectomy/Decortication (P/D) with neoadjuvant or adjuvant chemotherapy has become a common lung-sparing surgical approach for MPM. Adjuvant hemithoracic IMPRINT was developed at Memorial Sloan Kettering Cancer Center and safe in a multi-institutional phase II study, with promising survival outcomes. The National Cancer Institute (NCI) sponsored this phase III randomized cooperative group trial to test the efficacy of this lung-sparing trimodality approach for resectable MPM. Methods: Patients with newly diagnosed MPM amenable to P/D are enrolled and undergo P/D followed by adjuvant platinum/pemetrexed (preferred) or neoadjuvant chemotherapy followed by P/D. Patients are stratified by histologic subtype, resection status (R0/1 vs. R2), and center patient volume (≤10 vs. > 10 P/Ds per year). Within 8 weeks after completion of the second modality patients are randomized 1:1 to undergo hemithoracic IMPRINT vs. no further therapy. All IMPRINT contours and treatment plans will be centrally reviewed. A contouring atlas and treatment planning constraints for target structures and organs at risk including acceptable and unacceptable variations and deviations were developed. Photon and proton therapy are permitted. The primary endpoint of the study is overall survival. Secondary endpoints include local failure-free, distant-metastases-free and progression-free survival, treatment-related toxicities (CTCAE v5.0) and change in quality-of-life (EORTC QLQ-C30 mean score changes at 9 months post randomization). The target accrual is 150 patients. This study was activated on January 29, 2020. Over 20 institutions have already committed to opening the study which is open to all National Clinical Trials Network (NCTN) sites. Treatment planning guidelines and helpful hints for photon and proton therapy will be presented. Conclusions: NRG LU-006 (clinicaltrials.gov: NCT04158141 ) is open to accrual. This is the first NRG Oncology randomized phase III trial on MPM and evaluates the use of IMPRINT following lung-sparing P/D and chemotherapy. This project was supported by grants U10CA180868 (NRG Oncology Operations), U10CA180822 (NRG Oncology SDMC), U24CA180803 (IROC) from the National Cancer Institute (NCI). Clinical trial information: NCT04158141.

LBA7005 Background: In meta-analyses, platinum-based adjuvant (adj) chemotherapy (CT) in completely resected NSCLC increased cure rate by ∼5%. At BR.19 initiation, adj study results with third-generation agents were unavailable. Gefitinib, an epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor, showed activity in monotherapy trials. We report a trial of adj gefitinib versus placebo after complete resection of NSCLC. Methods: Patients (pts) with stage IB-IIIA NSCLC were stratified by sex, stage, histology, post-op radiation, and after Jan 2003, adj CT. Pts were randomized to gefitinib 250 mg or placebo daily x 2 years. Study endpoints included overall survival (OS), disease free survival (DFS), toxicity, preplanned correlative studies. Study closed prematurely in Apr. 2005. Trial committee and NCIC CTG staff remained blinded to study drug. Results: 503 pts randomized (Sep 2002-Apr 2005); median age 67, males 54%, PS 0 54%; stage IB 49%, II 38%, III 13%; adenocarcinoma 59%, squamous 28%; ever smokers 89%; adj CT 17%; lobectomy 82%. Commonest grade 3/4 toxicities = fatigue 5%, rash 4% and diarrhea 5%. grade 3+ pneumonitis in 7 (1.4%) pts and led to death in 1. Median follow-up is 4.7 yrs; median treatment time is 4.8 mos. For gefitinib versus placebo, median DFS is 4.2 yrs versus not yet reached (NYR) HR1.22 (95% C.I. 0.93-1.61), p=0.15 and median OS 5.1 yrs versus NYR HR 1.24 (95% C.I. 0.94-1.64), p=0.14. In multivariate analysis, tumor size >4cm was predictive of poor DFS (p<0.0001) and never smoking for better OS with gefitinib (p=0.02). Results for KRAS and EGFR copy are available on 350 and 348 pts respectively. KRAS mutations were neither prognostic HR 1.12 (95% C.I. 0.67-1.86), p=0.66 nor predictive of gefitinib benefit (p = 0.16) on OS. EGFRcopy whether low/high polysomy or amplification was neither prognostic (p=0.77) nor predictive of OS benefit from gefitinib. Conclusions: Adjuvant gefitinib after complete resection of early stage NSCLC did not confer DFS or OS advantage in overall population. KRAS and EGFR copy were neither prognostic nor predictive of benefit from gefitinib. EGFR mutational analysis will be presented. [Table: see text]

Context.— The diagnosis and grading of acute cellular and antibody-mediated rejection (AMR) in lung allograft biopsies is important because rejection can lead to acute graft dysfunction and/or failure and may contribute to chronic graft failure. While acute cellular rejection is well defined histologically, no reproducible specific features of AMR are currently identified. Therefore, a combination of clinical features, serology, histopathology, and immunologic findings is suggested for the diagnosis of AMR. Objective.— To describe the perspective of members of the Pulmonary Pathology Society (PPS) on the workup of lung allograft transbronchial biopsy and the diagnosis of acute cellular rejection and AMR in lung transplant. Data Sources.— Reports by the International Society for Heart and Lung Transplantation (ISHLT), experience of members of PPS who routinely review lung allograft biopsies, and search of literature database (PubMed). Conclusions.— Acute cellular rejection should be assessed and graded according to the 2007 working formulation of the ISHLT. As currently no specific features are known for AMR in lung allografts, the triple test (clinical allograft dysfunction, donor-specific antibodies, pathologic findings) should be used for its diagnosis. C4d staining might be performed when morphologic, clinical, and/or serologic features suggestive of AMR are identified.