Faculty Bibliography

Thoracic SMARCA4-deficient undifferentiated tumor (SMARCA4d-UT) is an uncommon, aggressive lung neoplasm associated with smoking and characterized by loss of SMARCA4 (BRG-1) expression. Although originally considered to be a primary sarcoma, there is growing evidence that these lesions may represent transformation of conventional non-small cell carcinoma. In this study, we probe this relationship based on the clinical, histologic and molecular findings of 18 SMARCA4-deficient malignancies of the lung. Cases diagnosed as SMARCA4d-UT and SMARCA4-deficient carcinoma were retrospectively reviewed, including histologic and immunophenotypic features, and next generation sequencing studies. Of the 18 tumors, 5 were considered to represent undifferentiated SMARCA4d-UT, and 13 SMARCA4-deficient carcinomas, including 11 adenocarcinomas, 1 squamous cell carcinoma, and 1 poorly differentiated non-small cell carcinoma. All 13 carcinomas had a morphologically identifiable undifferentiated component. Survival outcomes were similar in both SMARCA4d-UT and carcinomas. Genetic alterations often seen in lung cancer were identified in 8 cases, including mutations in EGFR (in 2 SMARCA4-deficient adenocarcinomas), KRAS (1 SMARCA4d-UT and 1 SMARCA4-deficient adenocarcinoma), MAP2K1 (1 SMARCA4-deficient adenocarcinoma), and a gene fusion involving EML4::ALK (1 SMARCA4d-UT). The patient with EML4::ALK fusion was treated with alectinib with partial response. Fusions involving BRAF::CHCHD3 and FGFR1::FILIP1 were identified in 2 SMARCA4-deficient adenocarcinomas. High expression of PD-L1 (TPS >50 %) was seen in 12 cases (67 %). These finding further suggest that SMARCA4d-UT and carcinomas with SMARCA4 loss may be on the same spectrum of disease, and accurate histologic distinction between these lesions may be challenging. A unified terminology may be beneficial for appropriate diagnosis and treatment.

There is a body-wide network of interstitial spaces that includes three components: a large-scale fascial network made up of fluid-filled spaces containing collagens and other extracellular matrix components like hyaluronic acid (HA), the peri-vascular/capillary interstitium, and intercellular interstitial spaces. Staining for HA within the colon, skin, and liver has demonstrated spatial continuity of the fascial interstitium across tissue layers and between organs, while continuity of HA staining between perineurial and adventitial sheathes beyond organ boundaries confirmed that they also participate in this body-wide network. We asked whether the pulmonary interstitium comprises a continuous organ-wide network that also connects to the body-wide interstitium via routes along nerves and the vasculature. We studied archival lung lobectomy specimens containing normal tissues inclusive of all lung anatomical units from six females and three males (mean age 53+/- 16.5 years). For comparison, we also studied normal mouse lung. Multiplex immunohistochemical cocktails were used to identify: (1) HA, CD34, and vimentin - highlighting interstitium; (2) HA, CD34, and podoplanin (D2-40) - highlighting relationships between the interstitium, vasculature, and lymphatics. Sizes of extracellular APP were measured. Tissues from nine patients (six females, three males, mean age 53+/- 16.5 years) were studied. HA staining was continuous throughout the five major anatomic compartments of the lung: alveolar walls, subpleural connective tissue, centrilobular peribronchovascular compartment, interlobular septal compartment, and axial peribronchovascular of the hilum, with similar findings in murine lung tissue. Continuity with interstitial spaces of the perineurium and adventitia was confirmed. The distribution of APP corresponded to known routes of lymphatic drainage, superficial and deep. APP within perineurium and perivascular adventitia further demonstrated continuity between intra- and extrapulmonary interstitium. To conclude, all segments of the lung interstitium are connected and are linked along nerves and the vascular tree to a body-wide communication network. These findings have significant implications for understanding lung physiology and pathobiology, suggesting routes of passage for inflammatory cells and mediators, malignant cells, and infectious agents. Interstitial spaces may be important in microbiome signaling within and beyond the lung and may be a component of the lung-brain axis.

OBJECTIVES/OBJECTIVE:With the development of genomic technologies, the isolation of genomic DNA (gDNA) from clinical samples has become more important for both clinical diagnostics and research studies. Blood samples collected in PAXgene Blood RNA Tubes, which are typically used for RNA extraction, can be used for gDNA extraction, particularly in clinical studies when only such blood samples are available. METHODS:We optimized the pre-treatment of blood samples collected in PAXgene Blood RNA Tubes. For the first time, three magnetic bead-based automated platforms (QIAsymphony SP, Maxwell RSC and KingFisher Apex) were compared for gDNA extraction from these blood samples. Additionally, the effects of storage at 4 °C or freeze-thaw cycles of the blood samples on gDNA yield were investigated. High-throughput extraction in 96-well format was evaluated. RESULTS:Systematic optimization of blood sample pre-treatment shows that prolonged incubation at room temperature and/or increased centrifugation speed and time improved gDNA yield from blood samples collected in PAXgene Blood RNA Tubes. QIAsymphony SP (4.27 ± 2.19 µg) and Maxwell RSC (4.82 ± 2.96 µg) produced significantly higher gDNA yields than KingFisher Apex (1.09 ± 0.61 µg). Higher gDNA yields were obtained with shorter storage time at 4 °C or fewer freeze-thaw cycles of the blood samples. In the 96-well format extraction, gDNA yields ranged from 0.24 to 13.46 µg. CONCLUSIONS:Not all magnetic bead-based automated platforms are suitable for gDNA extraction from blood samples collected in PAXgene Blood RNA Tubes. Systematic pre-treatments optimization provides guidance for routine and high-throughput workflows, and storage conditions and freeze-thaw cycles offer practical reference for biobanking.

The suspicious for malignancy category is used by pathologists to indicate a certain degree of uncertainty but is still able to convey to the treating physician a risk stratification of the deferred diagnosis. The category of suspicious for malignancy can be used in a vast possibility of cytomorphological features and clinical scenarios. Suspicious for malignancy is often used when there is an insufficient number of neoplastic cells for the establishment of a final diagnosis, but in many situations, the number of suspicious cells may be abundant but discrepant with the clinical presentation. In addition, the pathologist must be aware of the many mimickers of malignancy that, when present, may prompt the use of the category. Therefore, there is a need for better illustrations of the use of the category, its pitfalls and suggestions on when the category of suspicious for malignancy can be upgraded for a more definite diagnosis using ancillary studies, even in scant material.

BACKGROUND AND OBJECTIVE/OBJECTIVE:The diagnosis of interstitial lung diseases (ILDs) often relies on the integration of various clinical, radiological, and histopathological data. Achieving high diagnostic accuracy in ILDs, particularly for distinguishing usual interstitial pneumonia (UIP), is challenging and requires a multidisciplinary approach. Therefore, this study aimed to develop a multimodal artificial intelligence (AI) algorithm that combines computed tomography (CT) and histopathological images to improve the accuracy and consistency of UIP diagnosis. METHODS:A dataset of CT and pathological images from 324 patients with ILD between 2009 and 2021 was collected. The CT component of the model was trained to identify 28 different radiological features. The pathological counterpart was developed in our previous study. A total of 114 samples were selected and used for testing the multimodal AI model. The performance of the multimodal AI was assessed through comparisons with expert pathologists and general pathologists. RESULTS:The developed multimodal AI demonstrated a substantial improvement in distinguishing UIP from non-UIP, achieving an AUC of 0.92. When applied by general pathologists, the diagnostic agreement rate improved significantly, with a post-model κ score of 0.737 compared to 0.273 pre-model integration. Additionally, the diagnostic consensus rate with expert pulmonary pathologists increased from κ scores of 0.278-0.53 to 0.474-0.602 post-model integration. The model also increased diagnostic confidence among general pathologists. CONCLUSION/CONCLUSIONS:Combining CT and histopathological images, the multimodal AI algorithm enhances pathologists' diagnostic accuracy, consistency, and confidence in identifying UIP, even in cases where specialised expertise is limited.

Subsolid nodules (SSNs) are increasingly encountered in chest computed tomography (CT) imaging and clinical practice, as awareness of their significance and CT utilization grows. Either part-solid or solely ground-glass in attenuation, SSNs are shown to correlate with lung adenocarcinomas and their precursors, although a differential diagnosis is to be considered that includes additional neoplastic and inflammatory etiologies. This review discusses the differential diagnosis for SSNs, imaging and clinical features, and pathology that are helpful when making management decisions that may include PET/CT, biopsy, or surgery. Potential pitfalls in nodule characterization and management will be highlighted, to aid in managing SSNs appropriately.

BACKGROUND:The diagnosis of cardiac sarcoidosis (CS) is often challenging, particularly in atypical cases. CASE SUMMARY/METHODS:This case involves a previously healthy 33-year-old woman who was found to have a biatrial mass and evidence of a diffuse inflammatory or neoplastic process on multimodality imaging. Percutaneous biopsy of the cardiac mass was performed, and histopathologic examination revealed granulomas consistent with CS. DISCUSSION/CONCLUSIONS:This case adds to the growing number of reports of CS manifesting as an intracardiac mass. TAKE-HOME MESSAGES/CONCLUSIONS:The clinical presentation of CS is highly variable, and it may rarely manifest as an intracardiac mass. The diagnosis of cardiac sarcoidosis is often challenging, particularly in patients with atypical presentations. Indeterminate cardiac masses often require direct tissue sampling because the changes in treatment and prognosis are substantial.

How tumor microenvironment shapes lung adenocarcinoma (LUAD) precancer evolution remains poorly understood. Spatial immune profiling of 114 human LUAD and LUAD precursors reveals a progressive increase of adaptive response and a relative decrease of innate immune response as LUAD precursors progress. The immune evasion features align the immune response patterns at various stages. TIM-3-high features are enriched in LUAD precancers, which decrease in later stages. Furthermore, single-cell RNA sequencing (scRNA-seq) and spatial immune and transcriptomics profiling of LUAD and LUAD precursor specimens from 5 mouse models validate high TIM-3 features in LUAD precancers. In vivo TIM-3 blockade at precancer stage, but not at advanced cancer stage, decreases tumor burden. Anti-TIM-3 treatment is associated with enhanced antigen presentation, T cell activation, and increased M1/M2 macrophage ratio. These results highlight the coordination of innate and adaptive immune response/evasion during LUAD precancer evolution and suggest TIM-3 as a potential target for LUAD precancer interception.

CONTEXT.—/UNASSIGNED:Adenocarcinomas are the most common histologic subtype of lung cancer, and exist within a widely divergent clinical, radiologic, molecular, and histologic spectrum. There is a strong association between histologic patterns and prognosis that served as the basis for a recently described grading system. As the study of molecular pathology rapidly evolves, all targetable mutations so far have been found in adenocarcinomas, thus requiring accurate diagnosis and classification for triage of molecular alterations and adequate therapy. OBJECTIVE.—/UNASSIGNED:To discuss the rationale for adenocarcinoma classifications within the 2021 5th edition of the World Health Organization, with a focus on nonmucinous tumors, including tumor grading and biopsy/cytology diagnosis. DATA SOURCES.—/UNASSIGNED:PubMed search. CONCLUSIONS.—/UNASSIGNED:A grading system for adenocarcinoma has improved prognostic impact of the classification of pulmonary adenocarcinoma. An accurate diagnosis of adenocarcinoma in small biopsy material is important for tissue triage for molecular studies and ultimately for patient management and treatment.

High-dimensional multiplexed imaging can reveal the spatial organization of tumour tissues at the molecular level. However, owing to the scale and information complexity of the imaging data, it is challenging to discover and thoroughly characterize the heterogeneity of tumour microenvironments. Here we show that self-supervised representation learning on data from imaging mass cytometry can be leveraged to distinguish morphological differences in tumour microenvironments and to precisely characterize distinct microenvironment signatures. We used self-supervised masked image modelling to train a vision transformer that directly takes high-dimensional multiplexed mass-cytometry images. In contrast with traditional spatial analyses relying on cellular segmentation, the vision transformer is segmentation-free, uses pixel-level information, and retains information on the local morphology and biomarker distribution. By applying the vision transformer to a lung-tumour dataset, we identified and validated a monocytic signature that is associated with poor prognosis.