Faculty Bibliography

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.

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.

BACKGROUND/UNASSIGNED:Immune microenvironment plays a critical role in cancer from onset to relapse. Machine learning (ML) algorithm can facilitate the analysis of lab and clinical data to predict lung cancer recurrence. Prompt detection and intervention are crucial for long-term survival in lung cancer relapse. Our study aimed to evaluate the clinical and genomic prognosticators for lung cancer recurrence by comparing the predictive accuracy of four ML models. METHODS/UNASSIGNED:A total of 41 early-stage lung cancer patients who underwent surgery between June 2007 and October 2014 at New York University Langone Medical Center were included (with recurrence, n=16; without recurrence, n=25). All patients had tumor tissue and buffy coat collected at the time of resection. The CIBERSORT algorithm quantified tumor-infiltrating immune cells (TIICs). Protein-protein interaction (PPI) network and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted to unearth potential molecular drivers of tumor progression. The data was split into training (75%) and validation sets (25%). Ensemble linear kernel support vector machine (SVM) ML models were developed using optimized clinical and genomic features to predict tumor recurrence. RESULTS/UNASSIGNED:emerged as prominent hub genes. Prediction models integrating clinicopathological prognostic factors, tumor gene expression (45 genes), and buffy coat gene expression (47 genes) yielded varying receiver operating characteristic (ROC)-area under the curves (AUCs): 62.7%, 65.4%, and 59.7% in the training set, 58.3%, 83.3%, and 75.0% in the validation set, respectively. Notably, merging gene expression with clinical data in a linear SVM model led to a significant accuracy boost, with an AUC of 92.0% in training and 91.7% in validation. CONCLUSIONS/UNASSIGNED:Using ML algorithm, immune gene expression data from tumor tissue and buffy coat may enhance the precision of lung cancer recurrence prediction.

BACKGROUND:Cross-species immunological incompatibilities have hampered pig-to-human xenotransplantation, but porcine genome engineering recently enabled the first successful experiments. However, little is known about the immune response after the transplantation of pig kidneys to human recipients. We aimed to precisely characterise the early immune responses to the xenotransplantation using a multimodal deep phenotyping approach. METHODS:We did a complete phenotyping of two pig kidney xenografts transplanted to decedent humans. We used a multimodal strategy combining morphological evaluation, immunophenotyping (IgM, IgG, C4d, CD68, CD15, NKp46, CD3, CD20, and von Willebrand factor), gene expression profiling, and whole-transcriptome digital spatial profiling and cell deconvolution. Xenografts before implantation, wild-type pig kidney autografts, as well as wild-type, non-transplanted pig kidneys with and without ischaemia-reperfusion were used as controls. FINDINGS:cells. Both xenografts showed increased expression of genes biologically related to a humoral response, including monocyte and macrophage activation, natural killer cell burden, endothelial activation, complement activation, and T-cell development. Whole-transcriptome digital spatial profiling showed that antibody-mediated injury was mainly located in the glomeruli of the xenografts, with significant enrichment of transcripts associated with monocytes, macrophages, neutrophils, and natural killer cells. This phenotype was not observed in control pig kidney autografts or in ischaemia-reperfusion models. INTERPRETATION:Despite favourable short-term outcomes and absence of hyperacute injuries, our findings suggest that antibody-mediated rejection in pig-to-human kidney xenografts might be occurring. Our results suggest specific therapeutic targets towards the humoral arm of rejection to improve xenotransplantation results. FUNDING:OrganX and MSD Avenir.

Asbestos is the main cause of malignant mesothelioma. Previous studies have linked asbestos-induced mesothelioma to the release of HMGB1 from the nucleus to the cytoplasm, and from the cytoplasm to the extracellular space. In the cytoplasm, HMGB1 induces autophagy impairing asbestos-induced cell death. Extracellularly, HMGB1 stimulates the secretion of TNFα. Jointly, these two cytokines kick-start a chronic inflammatory process that over time promotes mesothelioma development. Whether the main source of extracellular HMGB1 were the mesothelial cells, the inflammatory cells, or both was unsolved. This information is critical to identify the targets and design preventive/therapeutic strategies to interfere with asbestos-induced mesothelioma. To address this issue, we developed the conditional mesothelial HMGB1-knockout (Hmgb1

Genetically modified xenografts are one of the most promising solutions to the discrepancy between the numbers of available human organs for transplantation and potential recipients. To date, a porcine heart has been implanted into only one human recipient. Here, using 10-gene-edited pigs, we transplanted porcine hearts into two brain-dead human recipients and monitored xenograft function, hemodynamics and systemic responses over the course of 66 hours. Although both xenografts demonstrated excellent cardiac function immediately after transplantation and continued to function for the duration of the study, cardiac function declined postoperatively in one case, attributed to a size mismatch between the donor pig and the recipient. For both hearts, we confirmed transgene expression and found no evidence of cellular or antibody-mediated rejection, as assessed using histology, flow cytometry and a cytotoxic crossmatch assay. Moreover, we found no evidence of zoonotic transmission from the donor pigs to the human recipients. While substantial additional work will be needed to advance this technology to human trials, these results indicate that pig-to-human heart xenotransplantation can be performed successfully without hyperacute rejection or zoonosis.

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.

BACKGROUND/UNASSIGNED:Evidence suggests that patients critically ill with COVID-19 have a dysregulated host immune response that contributes to end-organ damage. Extracorporeal membrane oxygenation (ECMO) has been used in this population with varying degrees of success. This study was performed to evaluate the impact of ECMO on the host immunotranscriptomic response in these patients. METHODS/UNASSIGNED:Eleven patients critically ill with COVID-19 requiring ECMO underwent an analysis of cytokines and immunotranscriptomic pathways before ECMO (T1), after ECMO for 24 hours (T2), and 2 hours after ECMO decannulation (T3). A Multiplex Human Cytokine panel was used to identify cytokine changes, and immunotranscriptomic changes in peripheral leukocytes were evaluated by PAXgene and NanoString nCounter. RESULTS/UNASSIGNED:, which code for binding ligands for the activation of toll-like receptors 2 and 4. Reactome analyses of differential gene expression demonstrated an impact on many of the body's most important immune inflammatory pathways. CONCLUSIONS/UNASSIGNED:These findings suggest a temporal impact of ECMO on the host immunotranscriptomic response in patients critically ill with COVID-19.

BACKGROUND:The increased detection of small-sized peripheral non-small-cell lung cancer (NSCLC) has renewed interest in sublobar resection in lieu of lobectomy. METHODS:We conducted a multicenter, noninferiority, phase 3 trial in which patients with NSCLC clinically staged as T1aN0 (tumor size, ≤2 cm) were randomly assigned to undergo sublobar resection or lobar resection after intraoperative confirmation of node-negative disease. The primary end point was disease-free survival, defined as the time between randomization and disease recurrence or death from any cause. Secondary end points were overall survival, locoregional and systemic recurrence, and pulmonary functions. RESULTS:From June 2007 through March 2017, a total of 697 patients were assigned to undergo sublobar resection (340 patients) or lobar resection (357 patients). After a median follow-up of 7 years, sublobar resection was noninferior to lobar resection for disease-free survival (hazard ratio for disease recurrence or death, 1.01; 90% confidence interval [CI], 0.83 to 1.24). In addition, overall survival after sublobar resection was similar to that after lobar resection (hazard ratio for death, 0.95; 95% CI, 0.72 to 1.26). The 5-year disease-free survival was 63.6% (95% CI, 57.9 to 68.8) after sublobar resection and 64.1% (95% CI, 58.5 to 69.0) after lobar resection. The 5-year overall survival was 80.3% (95% CI, 75.5 to 84.3) after sublobar resection and 78.9% (95% CI, 74.1 to 82.9) after lobar resection. No substantial difference was seen between the two groups in the incidence of locoregional or distant recurrence. At 6 months postoperatively, a between-group difference of 2 percentage points was measured in the median percentage of predicted forced expiratory volume in 1 second, favoring the sublobar-resection group. CONCLUSIONS:In patients with peripheral NSCLC with a tumor size of 2 cm or less and pathologically confirmed node-negative disease in the hilar and mediastinal lymph nodes, sublobar resection was not inferior to lobectomy with respect to disease-free survival. Overall survival was similar with the two procedures. (Funded by the National Cancer Institute and others; CALGB 140503 ClinicalTrials.gov number, NCT00499330.).