Non-small cell lung cancer (NSCLC) accounts for nearly half of all newly diagnosed patients with brain metastasis (BM), followed by melanoma and breast carcinomas. The presence of BM is associated with reduced response to several modern cancer therapies and a poor prognosis, but the underlying molecular underpinnings remain poorly understood. Here, we performed multi-modal single-nucleus RNA, T cell receptor, single-cell spatial, and whole-genome sequencing (WGS) of 44 primary NSCLC tumors (PTs) and BMs. Through combination of WGS with inferred copy-number alterations (CNAs) and gene expression snRNA-seq, we robustly identify malignant cells despite the presence of healthy cell mosaicism. We find a strong association of chromosomal instability (CIN) and brain-metastatic organotropism. Through integration with clinical information and thousands of publicly available whole-exome sequencing (WES) profiles obtained from patients with NSCLC, we validate this observation and show that CIN progressively increases from PTs to extracranial metastases (ECMs) and is the highest in BMs. Using non-negative matrix factorization, we identify recurrent transcriptional hallmarks cancer metastasis, and additionally find that cancer cells from BMs strongly enrich for a neuronal-like cell state. At single-cell resolution, we indeed identify a rare cancer cell population genomically define by very high CIN, and transcriptionally characterized by a program of epithelial-to-mesenchymal transition (EMT), neuronal-like differentiation, and loss of lineage attribution. We show in our data and external scRNA-seq data that this cell state does not ecist in healthy lungs, progressively enriches from PTs to ECMs, and is most abundant in BMs, suggesting that these cells may indeed give rise to BMs. Furthermore, through integration of snRNA/TCR-seq and spatial transcriptomics, we find distinct tumor-microenvironments across disease sites, including, nearly exclusive expansion of tissue-resident myeloid cells in PTs, while BMs are largely dominated by dense infiltration with monocyte-derived macrophages and granulocytes, impaired T cell infiltration, activation and clonal expansion. Lastly, spatial transcriptomics also recurrent, cell-type specific patterns of geographic variability in key pathways, including antigen presentation, EMT, oxidative phosphorylation, and inflammatory response and associated cellular micro-niches. Together, this work identifies cellular, genomic, and transcriptional features of NSCLC BMs and has important therapeutic implications for novel therapies, in particular immunomodulatory approaches targeting cell types/states unique to disease sites. Citation Format: Somnath Tagore, Lindsay Caprio, Amit Dipak Amin, Irving Barrera, Johannes Melms, Karan Luthria, Yiping Wang, Yohanna Georgis, Abhi Jaiswal, Galina G. Lagos, Zachary Walsh, Parin Shah, Jana Biermann, Neha Sheikh, Priyanka Ramaradj, Niroshana Anandasabapathy, Hanina Hibshoosh, Gary Schwartz, Brian Henick, Alison Taylor, Fei Chen, Benjamin Izar. Multi-modal single-cell and spatial genomics reveals genomic, adaptive and microenvironmental features of human non-small cell lung cancer brain metastasis [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 3517.
Brain metastases are the most frequent malignancies in the brain and are associated with significant morbidity and mortality. Melanoma brain metastases (MBM) occur in most patients with advanced melanoma and are challenging to treat. Our understanding of the treatment-naïve landscape of MBM is still rudimentary, and there are no site-specific molecular therapies available. To gain comprehensive insights into the niche-specific biology of MBM, we performed multi-modal profiling of fresh and frozen samples using single-cell RNA-seq, single-cell TCR-seq, single-nuclei RNA-seq, and spatial transcriptional profiling. We evolved single-nucleus RNA-seq processing methods to enable profiling of minute amounts of archival, frozen specimens and compared data quality and structure between matched fresh and frozen MBM. We curated a treatment-naïve single-transcriptome atlas of MBM, collected either fresh samples over 1 year or profiled frozen samples dating back more than 15 years, and compared these samples to extracranial melanoma metastases (ECMM). In total, we profiled 25 samples with more than 114,000 transcriptomes. We identified more than 20 different cell types, including diverse tumor-infiltrating T-cell subsets and rare dendritic cell types, and tissue-specific cell types, such as activated microglia. Tumor cells in MBM showed an increase in copy number alterations (CNAs) compared to ECMM, which we validated using an external dataset of whole exome sequencing (WES) data including both MBM and ECMM. MBM-derived tumor cells show enrichment of genes involved in neuronal development and function, and site-specific metabolic programs (e.g., oxidative phosphorylation). Comparison with an external bulk RNA-seq dataset validated enriched key genes in MBM and ECMM as putative dependencies. We recovered cell-cell interactions between tumor and brain-resident cells involved in brain development, homeostasis, and disease. Similar to ECMM, the tumor microenvironment of MBM contained CD8+ T cells across a spectrum of differentiation, exhaustion and expansion, which was associated with loss of TCF7 expression and adoption of a TOX+ cell state. CD4+ T cells included T regulatory, T helper and T follicular-helper-like expression profiles. Plasma cells showed spatially localized expansion and limited heterogeneity. Myeloid cells largely adopted pro-tumorigenic cell states, including microglia, the brain-resident myeloid cells, which showed an activation trajectory characterized by expression of SPP1 (osteopontin). Spatial transcriptional analysis revealed restricted expression of antigen presentation genes with only a subset of these locations showing a type I interferon response. In summary, this work presents a multi-modal single-cell approach to dissect and compare the landscape of treatment-naïve MBM and ECMM. Citation Format: Johannes C. Melms, Jana Biermann, Amit Dipak Amin, Yiping Wang, Somnath Tagore, Massimo Andreatta, Ajay Nair, Meri Rogava, Patricia Ho, Lindsay A. Caprio, Zachary H. Walsh, Shivem Shah, Daniel H. Vacarro, Blake Caldwell, Adrienne M. Luoma, Joseph Driver, Matthew Ingham, Suthee Rapisuwon, Jennifer Wargo, Craig L. Slinguff, Evan Z. Macosco, Fei Chen, Richard Carvajal, Michael B. Atkins, Michael A. Davies, Elham Azizi, Santiago J. Carmona, Hanina Hibshoosh, Peter D. Canoll, Jeffrey N. Bruce, Wenya L. Bi, Gary K. Schwartz, Benjamin Izar. Dissecting the ecosystem of treatment-naïve melanoma brain metastasis using multi-modal single-cell analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 984.
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