Naso, Julia

Prognostic stratification of pulmonary carcinoids into “typical” and “atypical” categories requires examination of large tissue volume. However, there is a need for tools that provide similar prognostic information on small biopsy samples. Ki-67 and OTP immunohistochemistry have shown promising prognostic value in studies of resected pulmonary carcinoids, but prognostic value when using biopsy/cytology specimens is unclear. Ki-67 immunohistochemistry was performed on small biopsy/cytology specimens from pulmonary carcinoid tumors (n=139), and labeling index was scored via automated image analysis of at least 500 cells. OTP immunohistochemistry was performed on 70 cases with sufficient tissue and scored as positive or negative (<20% tumor nuclei staining). Higher Ki-67 index was associated with worse disease-specific progression-free survival (ds-PFS), with 3% and 4% thresholds having similarly strong associations with ds-PFS ( P <0.001, hazard ratio ≥11). Three-year ds-PFS was 98% for patients with Ki-67 <3% and 89% for patients with Ki-67≥3% ( P =0.0006). The optimal Ki-67 threshold for prediction of typical versus atypical carcinoid histology on subsequent resection was 3.21 (AUC 0.68). Negative OTP staining approached significance with atypical carcinoid histology ( P =0.06) but not with ds-PFS ( P =0.24, hazard ratio=3.45), although sample size was limited. We propose that Ki-67 immunohistochemistry may contribute to risk stratification for carcinoid tumor patients based on small biopsy samples. Identification of a 3% hot-spot Ki-67 threshold as optimal for prediction of ds-PFS is notable as a 3% Ki-67 threshold is currently used for gastrointestinal neuroendocrine tumor stratification, allowing consideration of a unified classification system across organ systems.

Primary pulmonary salivary gland‐type tumours are rare neoplasms that are thought to arise from seromucinous glands that are located in the submucosa of large airways. These neoplasms have clinical and pathologic features that are distinct from other pulmonary neoplasms. The majority of primary pulmonary salivary gland‐type tumours are malignant, with the most common entities being mucoepidermoid carcinoma, adenoid cystic carcinoma, and epithelial‐myoepithelial carcinoma. Less commonly seen are myoepithelial carcinoma, hyalinizing clear cell carcinoma, acinic cell carcinoma, secretory carcinoma, salivary duct carcinoma, intraductal carcinoma, and polymorphous adenocarcinoma. Benign salivary gland‐type tumours of the lung include pleomorphic adenoma and sialadenoma papilliferum. Morphologic, immunophenotypic, and molecular features of these neoplasms are largely similar to salivary gland tumours elsewhere, and therefore the exclusion of metastatic disease requires clinical and radiologic correlation. However, the differential diagnostic considerations are different in the lung. The distinction of salivary gland‐type tumours from their histologic mimics is important for both prognostication and treatment decisions. Overall, salivary gland type‐tumours tend to have a more favourable outcome than other pulmonary carcinomas, although high‐grade variants exist for many of these tumour types. Recent advances in our understanding of the spectrum of salivary gland‐type tumours reported in the lung and their diversity of molecular and immunohistochemical features have helped to refine the classification of these tumours and have highlighted a few differences between salivary gland‐type tumours of the lung and those primary to other sites.

Abstract Background: Non-small cell lung cancer (NSCLC) tissue is a valuable resource for diagnosis, treatment planning, and drug development. Current 2D histopathological techniques introduce under-sampling error (i.e., a single 5 um section represents 0.5% of a 1 mm thick biopsy), interobserver variability, and fail to capture the biology contained within the entire tissue sample. We have developed a suite of technologies to stain, chemically clarify, image, visualize, and analyze entire intact NSCLC tissue samples. Methods: Human NSCLC tissue, stored frozen in OCT, was fixed in 4% paraformaldehyde, stained with nuclear (TOPRO-3) and general protein (Eosin) fluorescent dyes, and optically cleared using a modified iDISCO protocol with ethyl cinnamate as the refractive index matching solution. Whole, intact tissue samples, roughly 1-5mm3 in volume, were imaged at 2 microns/pixel resolution with an open-top light-sheet microscope (3Di, Alpenglow Biosciences). Smaller regions of interest (ROIs) with key pathologic features were reimaged at higher resolution, 0.17 microns/pixel, to reveal subnuclear features and for cell typing. Visualization was performed using Aivia software. Results: NSCLC tissue samples were successfully imaged in 3D. Low resolution images (2 microns/pixel) were obtained within 4-31 minutes, depending on the tissue volume. The 3D distribution of cancer cells, immune cells, vessels, and fibrosis varied substantially throughout the volume of the tissue. Recognizable histologic features, including nests of tumor cells surrounded by vasculature and immune cells, were readily visualized. Squamous and adenocarcinoma with its subtypes (solid, acinar, lepidic, and micropapillary) morphologies were recognizable in 2D optical sections of the 3D datasets. Imaging quality degraded in tissue deeper than 1 mm due to light scattering. Conclusion: We assessed intact NSCLC tissue samples measuring up to 5 mm3 using our custom light-sheet microscope and tissue clearing techniques. This novel method enables us to visualize key features of NSCLC such as the tumor interfaces, tertiary lymphoid structures, vessels and fibrosis in the entire tissue sample, preventing under sampling error, and potentially enabling new biologic insights. Next steps include segmentation and quantification of key tissue structures such as tumor volume, immune cell distribution, and fibrosis/immune cell exclusion. This proof-of-concept study provides motivation for further investigation into the significance of 3D tissue features in NSCLC tissue samples. Citation Format: Alexandra Alvarsson, Carl Storey, Brandy Olin Pope, Caleb Stoltzfus, Robert Vierkant, Jessica Tufariello, Aaron Bungum, Julia Naso, Cheuk Ki Chan, Eric Edell, Christopher Hartley, Janani Reisenauer, Nicholas Reder. 3D assessment of the lung cancer microenvironment using multi-resolution open-top light-sheet microscopy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6624.

AbstractBackgroundObtaining a diagnosis and treating pulmonary malignancies during the same anesthesia requires either an on‐site pathologist or a system for remotely evaluating microscopic images. Cytology specimens are challenging to remotely assess given the need to navigate through dispersed and three‐dimensional cell clusters. Remote navigation is possible using robotic telepathology, but data are limited on the ease of use of current systems, particularly for pulmonary cytology.MethodsAir dried modified Wright‐Giemsa stained slides from 26 touch preparations of transbronchial biopsies and 27 smears of endobronchial ultrasound guided fine needle aspirations were scored for ease of adequacy assessment and ease of diagnosis on robotic (rmtConnect Microscope) and non‐robotic telecytology platforms. Diagnostic classifications were compared between glass slides and the robotic and non‐robotic telecytology assessments.ResultsCompared to non‐robotic telecytology, robotic telecytology had a greater ease of adequacy assessment and non‐inferior ease of diagnosis. The median time to diagnosis using robotic telecytology was 85 s (range 28–190 s). Diagnostic categories were concordant for 76% of cases in robotic versus non‐robotic telecytology and 78% of cases in robotic telecytology versus glass slide diagnosis. Weighted Cohen's kappa scores for agreement in these comparisons were 0.84 and 0.72, respectively.ConclusionsUse of a remote‐controlled robotic microscope improved the ease of adequacy assessment compared to non‐robotic telecytology and enabled strongly concordant diagnoses to be expediently rendered. This study provides evidence that modern robotic telecytology is a feasible and user‐friendly method of remotely and potentially intraoperatively rendering adequacy assessments and diagnoses on bronchoscopic cytology specimens.

e20646 Background: Thymic carcinomas tend to be aggressive malignancies with variable patterns of immunostaining. We aimed to assess whether the outcome of patients with thymic carcinomas was associated with immunoreactivity for conventional and emerging immunohistochemical markers of thymic carcinoma versus thymoma. Methods: Scoring of CD5, CD117, EZH2, POU2F3, BAP1, and MTAP immunohistochemistry on whole slide sections was compared to overall survival (OS) and progression free survival (PFS) for 36 thymic carcinoma patients, 28 of whom had complete tumor resection and 8 of whom had incomplete tumor resection. Results: Positive CD5 staining (defined as staining in ≥50% of tumor cells) was present in 13/36 cases (36%) and was significantly associated with longer OS (P = 0.005, hazard ratio = 0.18, CI 0.03-0.63) but not PFS (P = 0.14, hazard ratio = 0.48, CI 0.16-1.26), whereas the other markers were not significantly associated with OS or PFS. Positive CD5 staining remained significantly associated with OS in squamous cell carcinoma subgroup analysis (n = 23, HR = 0.17, CI 0.03-0.65, P = 0.009), patients who did not receive neo-adjuvant treatment (n = 24, HR = 0.21, CI 0.03-0.85, P = 0.03) and after adjusting for incomplete resection (HR = 0.20, CI0.03-0.73, P = 0.01), M1 stage (HR = 0.19, CI 0.03-0.71, P = 0.01) or neoadjuvant treatment (HR = 0.19, CI 0.03-0.71, P = 0.01) in bivariate models. Positive CD5 staining was also significantly associated with age ≥60 years, absence of neoadjuvant treatment, and positive POU2F3 staining. Conclusions: CD5 staining in ≥50% of tumor cells was significantly associated with longer OS for thymic carcinoma patients. Our study supports the notion that CD5 immunohistochemistry may have utility as a prognostic marker for thymic carcinomas.

2616 Background: Non-small cell lung cancer (NSCLC) tissue is a valuable resource for diagnosis, treatment planning, and drug development. Current 2D histopathological techniques introduce under-sampling error (i.e., a single 5 µm section represents 0.5% of a 1 mm thick biopsy), interobserver variability, and failure to capture the biology contained within the entire tissue sample. We have developed a suite of technologies to stain, chemically clarify, image, visualize, and analyze entire, intact lung tissue samples. Herein, we present analysis methods for comprehensive 3D assessment of intact NSCLC tissue. Methods: Human NSCLC tissue, stored frozen in optimal cutting temperature (OCT) compound, was fixed in 4% paraformaldehyde, stained with nuclear (TOPRO-3) and general protein (Eosin) fluorescent dyes, and optically cleared using a modified iDISCO protocol with ethyl cinnamate as the refractive index matching solution. Twenty tissue samples measuring 1-5 mm3 in volume were imaged at 2 µm/pixel resolution with a hybrid open-top light-sheet microscope. Smaller regions of interest (ROIs) with interesting pathologic features were re-imaged at higher resolution, 0.17 µm/pixel. Visualization and analysis was performed using Aivia software, custom spatial analysis software and python scripts. Results: All NSCLC tissue samples were successfully imaged in 3D at both low and high resolution. Computational approaches, such as machine learning, were used to segment and classify tumor cells and lymphocytes within the high resolution ROIs. In one example we quantified a 0.0045 mm3 ROI containing 1x109 voxels. We segmented 1,474 unique objects, and classified 683 (46%) of the objects as lymphocytes and 309 (20%) of the cells as tumor cells. We found that on average the lymphocytes were within 12 µm of the nearest tumor cell. Additionally the tissue was broken into separate lymphocyte dense (58% of volume) and tumor dense regions (42% of volume). Further analysis is in progress to quantify more features, such as tertiary lymphoid structures, stromal cells, and fibrosis over the full 20 sample dataset. Conclusions: We successfully implemented 3D machine learning analysis pipelines using images from intact NSCLC tissue samples measuring up to 5 mm3. The imaging was performed using our custom hybrid open-top light-sheet microscope. This novel method enables us to identify and quantify key histological features such as tumor cells and lymphocytes within the tumor microenvironment. In addition, machine learning driven algorithms clustered cells into distinct tissue regions in 3D which enables a more precise assessment of disease state and heterogeneity. Further investigation is ongoing to link these results to patient outcomes.

Thymic carcinoma is an aggressive malignancy that can be challenging to distinguish from thymoma using histomorphology. We assessed two emerging markers for these entities, EZH2 and POU2F3, and compared them with conventional immunostains. Whole slide sections of 37 thymic carcinomas, 23 type A thymomas, 13 type B3 thymomas, and 8 micronodular thymomas with lymphoid stroma (MNTLS) were immunostained for EZH2, POU2F3, CD117, CD5, TdT, BAP1, and MTAP. POU2F3 (≥10% hotspot staining), CD117, and CD5 showed 100% specificity for thymic carcinoma versus thymoma with 51%, 86%, and 35% sensitivity, respectively, for thymic carcinoma. All POU2F3 positive cases were also positive for CD117. All thymic carcinomas showed >10% EZH2 staining. EZH2 (≥80% staining) had a sensitivity of 81% for thymic carcinoma and a specificity of 100% for thymic carcinoma versus type A thymoma and MNTLS but had poor specificity (46%) for thymic carcinoma versus B3 thymoma. Adding EZH2 to a panel of CD117, TdT, BAP1, and MTAP increased cases with informative results from 67/81 (83%) to 77/81 (95%). Overall, absent EZH2 staining may be useful for excluding thymic carcinoma, diffuse EZH2 staining may help to exclude type A thymoma and MNTLS, and ≥10% POU2F3 staining has excellent specificity for thymic carcinoma versus thymoma.

AbstractThe pathologic assessment of lung cancers provides essential guidance to the surgeon and oncologist who are considering the best treatment strategies for patients with both early and advanced‐stage disease. The management of patients with lung cancer is predicated first and foremost on access to an accurate diagnosis, even when the sample size is limited, as is often the case with use of modern, minimally invasive sampling techniques. Once the diagnosis and disease stage are established, predictive biomarker testing may be essential, particularly for those patients with nonsmall cell lung carcinoma (NSCLC) being considered for immunotherapy or genomic biomarker‐driven targeted therapy. This review will discuss the best practices for the diagnosis of NSCLC using morphology and immunohistochemistry, thus providing the surgeon with needed information to understand and critically evaluate pathology reports. Controversial and evolving topics including tumor spread through airspaces, evaluation of multiple tumors, and staging based on invasive tumor size will be addressed. Clinical genomic profiling in NSCLC is driven by published guidelines and reflects evidence based on clinical trials and regulatory approvals. In this fast‐moving space, surgeons should be aware of the critical immunohistochemical and genomic biomarkers that drive systemic therapy decisions and anticipate when such testing will be required, both to ensure adequate sampling and to advise the pathologist when tumor material will be required for biomarker analysis. The basic approaches to and sample requirements for molecular biomarker testing will be addressed. As biomarker testing moves exclusively from advanced‐stage patients into earlier stage disease, the surgeon should be aware of the relevant markers and work with the pathologist and oncologist to ensure that this information is available to facilitate timely access to therapies not just in the advanced setting, but in consideration of neoadjuvant and adjuvant care.