Faculty Bibliography

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.

Approximately 30% of early-stage lung adenocarcinoma patients present with disease progression after successful surgical resection. Despite efforts of mapping the genetic landscape, there has been limited success in discovering predictive biomarkers of disease outcomes. Here we performed a systematic multi-omic assessment of 143 tumors and matched tumor-adjacent, histologically-normal lung tissue with long-term patient follow-up. Through histologic, mutational, and transcriptomic profiling of tumor and adjacent-normal tissue, we identified an inflammatory gene signature in tumor-adjacent tissue as the strongest clinical predictor of disease progression. Single-cell transcriptomic analysis demonstrated the progression-associated inflammatory signature was expressed in both immune and non-immune cells, and cell type-specific profiling in monocytes further improved outcome predictions. Additional analyses of tumor-adjacent transcriptomic data from The Cancer Genome Atlas validated the association of the inflammatory signature with worse outcomes across cancers. Collectively, our study suggests that molecular profiling of tumor-adjacent tissue can identify patients at high risk for disease progression.

With the development of genomic technologies, the isolation of genomic DNA (gDNA) from clinical samples is increasingly required for clinical diagnostics and research studies. In this study, we explored the potential of utilizing various leftover blood samples obtained from routine clinical tests as a viable source of gDNA. Using an automated method with optimized pre-treatments, we obtained gDNA from seven types of clinical leftover blood, with average yields of gDNA ranging from 3.11 ± 0.45 to 22.45 ± 4.83 μg. Additionally, we investigated the impact of storage conditions on gDNA recovery, resulting in yields of 8.62-68.08 μg when extracting gDNA from EDTA leftover blood samples stored at 4 °C for up to 13 weeks or -80 °C for up to 78 weeks. Furthermore, we successfully obtained sequenceable gDNA from both Serum Separator Tube and EDTA Tube using a 96-well format extraction, with yields ranging from 0.61 to 71.29 μg and 3.94-215.98 μg, respectively. Our findings demonstrate the feasibility of using automated high-throughput platforms for gDNA extraction from various clinical leftover blood samples with the proper pre-treatments.

We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.

Programmed death-ligand 1 (PD-L1) expression in terms of the tumor proportion score (TPS) is the main predictive biomarker approved for immunotherapy against lung nonsmall cell carcinoma. Although some studies have explored the associations between histology and PD-L1 expression in pulmonary adenocarcinoma, they have been limited in sample size and/or extent of examined histologic variables, which may have resulted in conflicting information. In this observational retrospective study, we identified primary and metastatic lung adenocarcinoma cases in the span of 5 years and tabulated the detailed histopathologic features, including pathological stage, tumor growth pattern, tumor grade, lymphovascular and pleural invasion, molecular alterations, and the associated PD-L1 expression for each case. Statistical analyses were performed to detect associations between PD-L1 and these features. Among 1658 cases, 643 were primary tumor resections, 751 were primary tumor biopsies, and 264 were metastatic site biopsies or resections. Higher TPS significantly correlated with high-grade growth patterns, grade 3 tumors, higher T and N stage, presence of lymphovascular invasion, and presence of MET and TP53 alterations, whereas lower TPS correlated with lower-grade tumors and presence of EGFR alterations. There was no difference in PD-L1 expression in matched primary and metastases, although higher TPS was observed in metastatic tumors due to the presence of high-grade patterns in these specimens. TPS showed a strong association with a histologic pattern. Higher-grade tumors had higher TPS, which is also associated with more aggressive histologic features. Tumor grade should be kept in mind when selecting cases and blocks for PD-L1 testing.

Aspirates of mediastinal neoplasms pose a unique diagnostic challenge due to the overlapping histologic characteristics of mediastinal lesions and the morphologic similarities between mediastinal neoplasms and those originating at other sites. Presented here is the first reported description of the cytomorphologic features of adenocarcinoma NOS of the thymus in aspirate and pleural effusion specimens. The morphologic similarities between thymic and metastatic adenocarcinomas and variable immunohistochemical staining patterns of thymic epithelial neoplasms underscore the importance of pathology-radiology correlation and the careful consideration of the clinical context in the interpretation of cytology specimens.

Tumor mutations can influence the surrounding microenvironment leading to suppression of anti-tumor immune responses and thereby contributing to tumor progression and failure of cancer therapies. Here we use genetically engineered lung cancer mouse models and patient samples to dissect how LKB1 mutations accelerate tumor growth by reshaping the immune microenvironment. Comprehensive immune profiling of LKB1 -mutant vs wildtype tumors revealed dramatic changes in myeloid cells, specifically enrichment of Arg1 ⁺ interstitial macrophages and SiglecF ^Hi neutrophils. We discovered a novel mechanism whereby autocrine LIF signaling in Lkb1 -mutant tumors drives tumorigenesis by reprogramming myeloid cells in the immune microenvironment. Inhibiting LIF signaling in Lkb1 -mutant tumors, via gene targeting or with a neutralizing antibody, resulted in a striking reduction in Arg1 ⁺ interstitial macrophages and SiglecF ^Hi neutrophils, expansion of antigen specific T cells, and inhibition of tumor progression. Thus, targeting LIF signaling provides a new therapeutic approach to reverse the immunosuppressive microenvironment of LKB1 -mutant tumors.

Extracellular DNase DNASE1L3 maintains tolerance to self-DNA in humans and mice, whereas the role of its homolog DNASE1 remains controversial, and the overall function of secreted DNases in immunity is unclear. We report that deletion of murine DNASE1 neither caused autoreactivity in isolation nor exacerbated lupus-like disease in DNASE1L3-deficient mice. However, combined deficiency of DNASE1 and DNASE1L3 rendered mice susceptible to bloodstream infection with Staphylococcus aureus. DNASE1/DNASE1L3 double-deficient mice mounted a normal innate response to S. aureus and did not accumulate neutrophil extracellular traps (NETs). However, their kidneys manifested severe pathology, increased bacterial burden, and biofilm-like bacterial lesions that contained bacterial DNA and excluded neutrophils. Furthermore, systemic administration of recombinant DNASE1 protein during S. aureus infection rescued the mortality of DNase-deficient mice and ameliorated the disease in wild-type mice. Thus, DNASE1 and DNASE1L3 jointly facilitate the control of bacterial infection by digesting extracellular microbial DNA in biofilms, suggesting the original evolutionary function of secreted DNases as antimicrobial agents.

Calcific aortic valve disease (CAVD) and stenosis have a complex pathogenesis, and no therapies are available that can halt or slow their progression. Several studies have shown the presence of apolipoprotein-related amyloid deposits in close proximity to calcified areas in diseased aortic valves. In this Perspective, we explore a possible relationship between amyloid deposits, calcification and the development of aortic valve stenosis. These amyloid deposits might contribute to the amplification of the inflammatory cycle in the aortic valve, including extracellular matrix remodelling and myofibroblast and osteoblast-like cell proliferation. Further investigation in this area is needed to characterize the amyloid deposits associated with CAVD, which could allow the use of antisense oligonucleotides and/or isotype gene therapies for the prevention and/or treatment of CAVD.