Faculty Bibliography

PURPOSE/OBJECTIVE:Necrosis quantification in the neoadjuvant setting using pathology slide review is the most important validated prognostic marker in conventional osteosarcoma. Herein, we explored three deep learning strategies on histology samples to predict outcome for OSA in the neoadjuvant setting. EXPERIMENTAL DESIGN/METHODS:Our study relies on a training cohort from New York University (New York, NY) and an external cohort from Charles university (Prague, Czechia). We trained and validated the performance of a supervised approach that integrates neural network predictions of necrosis/tumor content, and compared predicted overall survival (OS) using Kaplan-Meier curves. Furthermore, we explored morphology-based supervised and self-supervised approaches to determine whether intrinsic histomorphological features could serve as a potential marker for OS in the setting of neoadjuvant. RESULTS:Excellent correlation between the trained network and the pathologists was obtained for the quantification of necrosis content (R2=0.899, r=0.949, p < 0.0001). OS prediction cutoffs were consistent between pathologists and the neural network (22% and 30% of necrosis, respectively). Morphology-based supervised approach predicted OS with p-value=0.0028, HR=2.43 [1.10-5.38]. The self-supervised approach corroborated the findings with clusters enriched in necrosis, fibroblastic stroma, and osteoblastic morphology associating with better OS (lg2HR; -2.366; -1.164; -1.175; 95% CI=[-2.996; -0.514]). Viable/partially viable tumor and fat necrosis were associated with worse OS (lg2HR;1.287;0.822;0.828; 95% CI=[0.38-1.974]). CONCLUSIONS:Neural networks can be used to automatically estimate the necrosis to tumor ratio, a quantitative metric predictive of survival. Furthermore, we identified alternate histomorphological biomarkers specific to the necrotic and tumor regions themselves which can be used as predictors.

BACKGROUND:Risk of early-stage lung adenocarcinoma (LUAD) recurrence after surgical resection is significant, and post-recurrence median survival is approximately two years. Currently there are no commercially available biomarkers that predict recurrence. Here, we investigated whether microbial and host genomic signatures in the lung can predict recurrence. METHODS:In 91 early-stage (Stage IA/IB) LUAD-patients with extensive follow-up, we used 16s rRNA gene sequencing and host RNA-sequencing to map the microbial and host transcriptomic landscape in tumor and adjacent unaffected lung samples. RESULTS:23 out of 91 subjects had tumor recurrence over 5-year period. In tumor samples, LUAD recurrence was associated with enrichment with Dialister, Prevotella, while in unaffected lung, recurrence was associated with enrichment with Sphyngomonas and Alloiococcus. The strengths of the associations between microbial and host genomic signatures with LUAD recurrence were greater in adjacent unaffected lung samples than in the primary tumor. Among microbial-host features in the unaffected lung samples associated with recurrence, enrichment with Stenotrophomonas geniculata and Chryseobacterium were positively correlated with upregulation of IL-2, IL-3, IL-17, EGFR, HIF-1 signaling pathways among the host transcriptome. In tumor samples, enrichment with Veillonellaceae Dialister, Ruminococcacea, Haemophilus Influenza, and Neisseria were positively correlated with upregulation of IL-1, IL-6, IL17, IFN, and Tryptophan metabolism pathways. CONCLUSIONS:Overall, modeling suggested that a combined microbial/transcriptome approach using unaffected lung samples had the best biomarker performance (AUC=0.83). IMPACT/CONCLUSIONS:This study suggests that LUAD recurrence is associated with distinct pathophysiological mechanisms of microbial-host interactions in the unaffected lung rather than those present in the resected tumor.

Diverse cellular insults converge on activation of the heat shock factor 1 (HSF1), which regulates the proteotoxic stress response to maintain protein homoeostasis. HSF1 regulates numerous gene programmes beyond the proteotoxic stress response in a cell-type- and context-specific manner to promote malignancy. However, the role(s) of HSF1 in immune populations of the tumour microenvironment remain elusive. Here, we leverage an in vivo model of HSF1 activation and single-cell transcriptomic tumour profiling to show that augmented HSF1 activity in natural killer (NK) cells impairs cytotoxicity, cytokine production and subsequent anti-tumour immunity. Mechanistically, HSF1 directly binds and regulates the expression of key mediators of NK cell effector function. This work demonstrates that HSF1 regulates the immune response under the stress conditions of the tumour microenvironment. These findings have important implications for enhancing the efficacy of adoptive NK cell therapies and for designing combinatorial strategies including modulators of NK cell-mediated tumour killing.

The traditional view of cancer emphasizes a genes-first process. Novel cancer traits arise by genetic mutations that spread to drive phenotypic change. However, recent data support a phenotypes-first process in which nonheritable cellular variability creates novel traits that later become heritably stabilized by genetic and epigenetic changes. Single-cell measurements reinforce the idea that phenotypes lead genotypes, showing how cancer evolution follows normal developmental plasticity and creates novel traits by recombining parts of different cellular developmental programs. In parallel, studies in evolutionary biology also support a phenotypes-first process driven by developmental plasticity and developmental recombination. These advances in cancer research and evolutionary biology mutually reinforce a revolution in our understanding of how cells and organisms evolve novel traits in response to environmental challenges.

Partitioning of repressive from actively transcribed chromatin in mammalian cells fosters cell-type-specific gene expression patterns. While this partitioning is reconstructed during differentiation, the chromatin occupancy of the key insulator, CCCTC-binding factor (CTCF), is unchanged at the developmentally important Hox clusters. Thus, dynamic changes in chromatin boundaries must entail other activities. Given its requirement for chromatin loop formation, we examined cohesin-based chromatin occupancy without known insulators, CTCF and Myc-associated zinc-finger protein (MAZ), and identified a family of zinc-finger proteins (ZNFs), some of which exhibit tissue-specific expression. Two such ZNFs foster chromatin boundaries at the Hox clusters that are distinct from each other and from MAZ. PATZ1 was critical to the thoracolumbar boundary in differentiating motor neurons and mouse skeleton, while ZNF263 contributed to cervicothoracic boundaries. We propose that these insulating activities act with cohesin, alone or combinatorially, with or without CTCF, to implement precise positional identity and cell fate during development.

As efforts to study the mechanisms of melanoma metastasis and novel therapeutic approaches multiply, researchers need accurate, high-throughput methods to evaluate the effects on tumor burden resulting from specific interventions. We show that automated quantification of tumor content from whole slide images is a compelling solution to assess in vivo experiments. In order to increase the outflow of data collection from preclinical studies, we assembled a large dataset with annotations and trained a deep neural network for the quantitative analysis of melanoma tumor content on histopathological sections of murine models. After assessing its performance in segmenting these images, the tool obtained consistent results with an orthogonal method (bioluminescence) of measuring metastasis in an experimental setting. This AI-based algorithm, made freely available to academic laboratories through a web-interface called MetFinder, promises to become an asset for melanoma researchers and pathologists interested in accurate, quantitative assessment of metastasis burden.

Innate inflammation promotes tumor development, although the role of innate inflammatory cytokines in established human tumors is unclear. Herein, we report clinical and translational results from a phase Ib trial testing whether IL1β blockade in human pancreatic cancer would alleviate myeloid immunosuppression and reveal antitumor T-cell responses to PD1 blockade. Patients with treatment-naïve advanced pancreatic ductal adenocarcinoma (n = 10) were treated with canakinumab, a high-affinity monoclonal human antiinterleukin-1β (IL1β), the PD1 blocking antibody spartalizumab, and gemcitabine/n(ab)paclitaxel. Analysis of paired peripheral blood from patients in the trial versus patients receiving multiagent chemotherapy showed a modest increase in HLA-DR+CD38+ activated CD8+ T cells and a decrease in circulating monocytic myeloid-derived suppressor cells (MDSC) by flow cytometry for patients in the trial but not in controls. Similarly, we used patient serum to differentiate monocytic MDSCs in vitro and showed that functional inhibition of T-cell proliferation was reduced when using on-treatment serum samples from patients in the trial but not when using serum from patients treated with chemotherapy alone. Within the tumor, we observed few changes in suppressive myeloid-cell populations or activated T cells as assessed by single-cell transcriptional profiling or multiplex immunofluorescence, although increases in CD8+ T cells suggest that improvements in the tumor immune microenvironment might be revealed by a larger study. Overall, the data indicate that exposure to PD1 and IL1β blockade induced a modest reactivation of peripheral CD8+ T cells and decreased circulating monocytic MDSCs; however, these changes did not lead to similarly uniform alterations in the tumor microenvironment.

OBJECTIVE:Early-stage lung adenocarcinoma is treated with local therapy alone, although patients with grade 3 stage I lung adenocarcinoma have a 50% 5-year recurrence rate. Our objective is to determine if analysis of the tumor microenvironment can create a predictive model for recurrence. METHODS:Thirty-four patients with grade 3 stage I lung adenocarcinoma underwent surgical resection. Digital spatial profiling was used to perform genomic (n = 31) and proteomic (n = 34) analyses of pancytokeratin positive and negative tumor cells. K-means clustering was performed on the top 50 differential genes and top 20 differential proteins, with Kaplan-Meier recurrence curves based on patient clustering. External validation of high-expression genes was performed with Kaplan-Meier plotter. RESULTS:There were no significant clinicopathologic differences between patients who did (n = 14) and did not (n = 20) have recurrence. Median time to recurrence was 806 days; median follow-up with no recurrence was 2897 days. K-means clustering of pancytokeratin positive genes resulted in a model with a Kaplan-Meier curve with concordance index of 0.75. K-means clustering for pancytokeratin negative genes was less successful at differentiating recurrence (concordance index 0.6). Genes upregulated or downregulated for recurrence were externally validated using available public databases. Proteomic data did not reach statistical significance but did internally validate the genomic data described. CONCLUSIONS:Genomic difference in lung adenocarcinoma may be able to predict risk of recurrence. After further validation, stratifying patients by this risk may help guide who will benefit from adjuvant therapy.

Relapsed pediatric B-cell acute lymphoblastic leukemia (B-ALL) remains one of the leading causes of cancer mortality in children. We performed Hi-C, ATAC-seq, and RNA-seq on 12 matched diagnosis/relapse pediatric leukemia specimens to uncover dynamic structural variants (SVs) and 3D chromatin rewiring that may contribute to relapse. While translocations are assumed to occur early in leukemogenesis and be maintained throughout progression, we discovered novel, dynamic translocations and confirmed several fusion transcripts, suggesting functional and therapeutic relevance. Genome-wide chromatin remodeling was observed at all organizational levels: A/B compartments, TAD interactivity, and chromatin loops, including some loci shared by 25% of patients. Shared changes were found to drive the expression of genes/pathways previously implicated in resistance as well as novel therapeutic candidates, two of which (ATXN1 and MN1) we functionally validated. Overall, these results demonstrate chromatin reorganization under the selective pressure of therapy and offer the potential for discovery of novel therapeutic interventions.

The integration of extrinsic signaling with cell-intrinsic transcription factors can direct progenitor cells to differentiate into distinct cell fates. In the developing Drosophila eye, differentiation of photoreceptors R1-R7 requires EGFR signaling mediated by the transcription factor Pointed, and our single-cell RNA-Seq analysis shows that the same photoreceptors require the eye-specific transcription factor Glass. We find that ectopic expression of Glass and activation of EGFR signaling synergistically induce neuronal gene expression in the wing disc in a Pointed-dependent manner. Targeted DamID reveals that Glass and Pointed share many binding sites in the genome of developing photoreceptors. Comparison with transcriptomic data shows that Pointed and Glass induce photoreceptor differentiation through intermediate transcription factors, including the redundant homologs Scratch and Scrape, as well as directly activating neuronal effector genes. Our data reveal synergistic activation of a multi-layered transcriptional network as the mechanism by which EGFR signaling induces neuronal identity in Glass-expressing cells.