Abstract 1594: Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition

The inherent plasticity of tumor cells provides a mechanism of resistance to many molecularly targeted therapies, exemplified by adeno-to-neuroendocrine lineage transitions seen in prostate and lung cancer. Here we investigate the root cause of this lineage plasticity in a primary murine prostate organoid model that mirrors the lineage transition seen in patients. These cells lose luminal identity within weeks following deletion of Trp53 and Rb1, ultimately acquiring an Ar-negative, Syp+ phenotype after orthotopic in vivo transplantation. We performed single-cell transcriptomic analysis of a time-course experiment on the prostate organoid following Trp53 and Rb1 deletion. Critical to this study, we developed SEACells, a method that enumerates distinct, highly granular cell states, allowing for robust transcriptomic quantification. Leveraging the SEACell platform, we developed several graph-based computational approaches based on Markov absorption, diffusion maps, and attributed stochastic block models to quantify dynamic changes in plasticity. These quantitative models independently confirmed rapid collapse of cell-type fidelity in the form of a mixed luminal-basal phenotype following tumor suppressor gene deletion. These methods compute metrics for plasticity that we correlated to candidate driver gene programs. Among the strongest plasticity correlates, Jak-Stat and Fgfr signaling stood out as gene programs activated early in the time-course prior to any corresponding morphological changes. We further developed a regression-based approach to nominate ligand-receptor interactions that activate downstream Jak-Stat signaling, which identified Fgf-Fgfr interactions that were functionally validated with growth factor addition and pharmacological inhibition. Most strikingly, genetic or pharmacologic inhibition of Jak1/2 in combination with Fgfr blockade not only reversed the plastic state and restored organoids to their wild-type morphology, but also re-sensitized drug-resistant cells to antiandrogen therapy in models with residual AR expression. We additionally confirm early activation of Jak/Stat transcriptional programs in an Rb1/Trp53/Pten-deleted genetically engineered mouse model undergoing substantial cell-type diversification under plasticity in the context of the tumor microenvironment. Collectively, we show that lineage plasticity initiates quickly as a largely cell-autonomous process that is further increased in the in vivo setting, and through newly developed computational approaches, we identify a pharmacological strategy that restores lineage identity using clinical grade inhibitors.

Citation Format: Joseph M. Chan, Wouter R. Karthaus, Manu Setty, Jillian R. Love, Samir Zaidi, Jimmy Zhao, Zi-ning Choo, Sitara Persad, Justin LaClair, Kayla E. Lawrence, Ojasvi Chaudhary, Ignas Masilionis, Linas Mazutis, Ronan Chaligne, Dana Pe'er, Charles Sawyers. Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition [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 1594.

Abstract 2200: Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling

Lineage plasticity is a well-established mechanism of resistance to targeted therapies in lung and prostate cancer, where tumors transition from adenocarcinoma to small-cell or neuroendocrine carcinoma. Single-cell analysis of a cohort of late stage castration-resistant human prostate cancers (CRPC) revealed a greater degree of plasticity than previously appreciated, with multiple distinct neuroendocrine (NEPC), mesenchymal (EMT-like), and other subpopulations detected within single biopsies. To explore the steps responsible for initiation of this process, we utilized two genetically engineered mouse models of prostate cancer that recapitulate progression from adenocarcinoma to neuroendocrine disease. Time course studies reveal expansion of stem-like luminal epithelial cells (Sca1+, Psca+, called L2) that, based on trajectories, gave rise to at least 4 distinct subpopulations, NEPC (Ascl1+), POU2F3 (Pou2f3+), TFF3 (Tff3+) and EMT-like (Vim+, Ncam1+). Such populations are also seen in human prostate and small cell lung cancers. Furthermore, transformed L2-like cells express stem-like and gastrointestinal endoderm-like transcriptional programs, indicative of reemerging developmental plasticity programs, as well as elevated Jak/Stat, interferon, and FGF pathways. Strikingly pharmacologic inhibition of Jak/Stat and FGFR results in reversal of plasticity states and subsequent sensitivity to androgen receptor inhibitors (ARSIs). In sum, while the magnitude of multilineage heterogeneity, both within and across patients, raises considerable treatment challenges, the identification of highly plastic luminal cells as the likely source of this heterogeneity provides a target for more focused therapeutic intervention.

Citation Format: Samir Zaidi, Jimmy Zhao, Joseph Chan, Roudier Martine, Kristine Wadosky, Anuradha Gopalan, Wouter Karthaus, Philip Watson, Lawrence True, Peter Nelson, Howard Scher, Michael Morris, Michael Haffner, David Goodrich, Dana Pe'er, Charles Sawyers. Multilineage plasticity in prostate cancer through expansion of stem-like luminal epithelial cells with elevated inflammatory signaling [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 2200.

Cell type and gene expression deconvolution with BayesPrism enables Bayesian integrative analysis across bulk and single-cell RNA sequencing in oncology

Inferring single-cell compositions and their contributions to global gene expression changes from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we develop Bayesian cell proportion reconstruction inferred using statistical marginalization (BayesPrism), a Bayesian method to predict cellular composition and gene expression in individual cell types from bulk RNA-seq, using patient-derived, scRNA-seq as prior information. We conduct integrative analyses in primary glioblastoma, head and neck squamous cell carcinoma and skin cutaneous melanoma to correlate cell type composition with clinical outcomes across tumor types, and explore spatial heterogeneity in malignant and nonmalignant cell states. We refine current cancer subtypes using gene expression annotation after exclusion of confounding nonmalignant cells. Finally, we identify genes whose expression in malignant cells correlates with macrophage infiltration, T cells, fibroblasts and endothelial cells across multiple tumor types. Our work introduces a new lens to accurately infer cellular composition and expression in large cohorts of bulk RNA-seq data.

Spatial CRISPR genomics identifies regulators of the tumor microenvironment

While CRISPR screens are helping uncover genes regulating many cell-intrinsic processes, existing approaches are suboptimal for identifying extracellular gene functions, particularly in the tissue context. Here, we developed an approach for spatial functional genomics called Perturb-map. We applied Perturb-map to knock out dozens of genes in parallel in a mouse model of lung cancer and simultaneously assessed how each knockout influenced tumor growth, histopathology, and immune composition. Moreover, we paired Perturb-map and spatial transcriptomics for unbiased analysis of CRISPR-edited tumors. We found that in Tgfbr2 knockout tumors, the tumor microenvironment (TME) was converted to a fibro-mucinous state, and T cells excluded, concomitant with upregulated TGFβ and TGFβ-mediated fibroblast activation, indicating that TGFβ-receptor loss on cancer cells increased TGFβ bioavailability and its immunosuppressive effects on the TME. These studies establish Perturb-map for functional genomics within the tissue at single-cell resolution with spatial architecture preserved and provide insight into how TGFβ responsiveness of cancer cells can affect the TME.

MITI minimum information guidelines for highly multiplexed tissue images

The imminent release of tissue atlases combining multi-channel microscopy with single cell sequencing and other omics data from normal and diseased specimens creates an urgent need for data and metadata standards that guide data deposition, curation and release. We describe a Minimum Information about highly multiplexed Tissue Imaging (MITI) standard that applies best practices developed for genomics and other microscopy data to highly multiplexed tissue images and traditional histology.

CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for single-cell fate mapping in diverse scenarios, including regeneration, reprogramming and disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, taking into account the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in velocity vectors. On pancreas development data, CellRank automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. Applied to lineage-traced cellular reprogramming data, predicted fate probabilities correctly recover reprogramming outcomes. CellRank also predicts a new dedifferentiation trajectory during postinjury lung regeneration, including previously unknown intermediate cell states, which we confirm experimentally.

CellRank infers directed cell state transitions and cell fates incorporating RNA velocity information into a graph based Markov process.

Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy

To elucidate mechanisms by which T cells eliminate leukemia, we study donor lymphocyte infusion (DLI), an established immunotherapy for relapsed leukemia. We model T cell dynamics by integrating longitudinal, multimodal data from 94,517 bone marrow-derived single T cell transcriptomes in addition to chromatin accessibility and single T cell receptor sequencing from patients undergoing DLI. We find that responsive tumors are defined by enrichment of late-differentiated T cells before DLI and rapid, durable expansion of early differentiated T cells after treatment, highly similar to "terminal" and "precursor" exhausted subsets, respectively. Resistance, in contrast, is defined by heterogeneous T cell dysfunction. Surprisingly, early differentiated T cells in responders mainly originate from pre-existing and novel clonotypes recruited to the leukemic microenvironment, rather than the infusion. Our work provides a paradigm for analyzing longitudinal single-cell profiling of scenarios beyond adoptive cell therapy and introduces Symphony, a Bayesian approach to infer regulatory circuitry underlying T cell subsets, with broad relevance to exhaustion antagonists across cancers.

Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively). To define the heterogeneity of tumors and their associated microenvironments across subtypes, we sequenced 155,098 transcriptomes from 21 human biospecimens, including 54,523 SCLC transcriptomes. We observe greater tumor diversity in SCLC than lung adenocarcinoma, driven by canonical, intermediate, and admixed subtypes. We discover a PLCG2-high SCLC phenotype with stem-like, pro-metastatic features that recurs across subtypes and predicts worse overall survival. SCLC exhibits greater immune sequestration and less immune infiltration than lung adenocarcinoma, and SCLC-N shows less immune infiltrate and greater T cell dysfunction than SCLC-A. We identify a profibrotic, immunosuppressive monocyte/macrophage population in SCLC tumors that is particularly associated with the recurrent, PLCG2-high subpopulation.

Tumor heterogeneity

Tumor heterogeneity was traditionally considered in the genetic terms, but it has now been broadened into many more facets. These facets represent a challenge in our understanding of cancer etiology but also provide opportunity for us to understand prognosis and therapy response.

A unified atlas of CD8 T cell dysfunctional states in cancer and infection

CD8 T cells play an essential role in defense against viral and bacterial infections and in tumor immunity. Deciphering T cell loss of functionality is complicated by the conspicuous heterogeneity of CD8 T cell states described across experimental and clinical settings. By carrying out a unified analysis of over 300 assay for transposase-accessible chromatin sequencing (ATAC-seq) and RNA sequencing (RNA-seq) experiments from 12 studies of CD8 T cells in cancer and infection, we defined a shared differentiation trajectory toward dysfunction and its underlying transcriptional drivers and revealed a universal early bifurcation of functional and dysfunctional T cell states across models. Experimental dissection of acute and chronic viral infection using single-cell ATAC (scATAC)-seq and allele-specific single-cell RNA (scRNA)-seq identified state-specific drivers and captured the emergence of similar TCF1+ progenitor-like populations at an early branch point, at which functional and dysfunctional T cells diverge. Our atlas of CD8 T cell states will facilitate mechanistic studies of T cell immunity and translational efforts.

Signatures of plasticity and immunosuppression in a single-cell atlas of human small cell lung cancer

8509

Background: Small cell lung cancer (SCLC) is an aggressive malignancy that includes subtypes defined by differential expression of ASCL1, NEUROD1, and POU2F3 (SCLC-A, -N, and -P, respectively), which are associated with distinct therapeutic vulnerabilities. The emerging consensus on SCLC subtypes has led to new questions, such as whether subtypes are associated with different disease stages, metastatic potential, or immune microenvironments; whether there is plasticity between subtypes; and whether novel SCLC phenotypes exist. Single cell RNA sequencing (scRNA-seq) offers a unique opportunity to address these questions by dissecting intratumoral transcriptional heterogeneity and the surrounding tumor microenvironment (TME). However, efforts to apply this technology to human SCLC tumors have been limited, as these tumors are infrequently resected. Methods: We have optimized protocols to process both surgical resections and biopsies to construct the first single-cell atlas of SCLC patient tumors (N = 21), with comparative lung adenocarcinoma (LUAD) and normal lung data. We leverage computational methods including diffusion maps and non-negative matrix factorization to perform a deep annotation of SCLC phenotypes and the surrounding immune TME. We perform validation experiments using flow cytometry, Vectra, and immunohistochemistry in independent SCLC cohorts, as well as genetic manipulation in preclinical SCLC models. Results: Our data reveals substantial transcriptional heterogeneity in SCLC both within and across tumors and confirms a pro-metastatic gene program in SCLC-N subtype characterized by epithelial-mesenchymal transformation and axonogenesis. Beyond known subtypes, we discover a PLCG2-high tumor cell population with stem-like, pro-metastatic features that recurs across subtypes and predicts significantly worse overall survival. Manipulation of PLCG2 expression in cells confirms correlation with key metastatic markers. Treatment and subtype are associated with substantial phenotypic changes in the SCLC immune microenvironment, with greater T-cell dysfunction in SCLC-N than SCLC-A. Moreover, the recurrent, PLCG2-high subclone is associated with exhausted CD8+ T-cells and a pro-fibrotic, immunosuppressive monocyte/macrophage population, suggesting possible tumor-immune coordination to promote metastasis. Conclusions: This atlas of SCLC illustrates how canonical subtypes and a novel PLCG2-high recurrent tumor subclone enlist diverse gene programs to create tumor heterogeneity and facilitate metastasis in a profoundly immunosuppressed TME. Our dataset provides further insight into tumor and immune biology in SCLC at single-cell resolution, with potential implications for design of novel targeted therapies and immunotherapeutic approaches.

Abstract LT008: Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy

Immune therapies have transformed the cancer therapeutic landscape but fail to benefit most patients. To elucidate the underlying mechanisms by which T cells mediate elimination of leukemia, we generated a high-resolution map of longitudinal T cell dynamics within the same tumor microenvironment (TME; bone marrow) during response or resistance to donor lymphocyte infusion (DLI), a widely used immunotherapy for relapsed leukemia. We analyzed 87,939 bone marrow-derived single T cell transcriptomes, along with chromatin accessibility and single T cell receptor clonality profiles, by developing novel machine learning tools for integrating longitudinal and multimodal data. We found that pre-treatment enrichment and post-treatment rapid, durable expansion of ‘terminal’ (TEX) and ‘precursor’ (TPEX) exhausted subsets, respectively, defined DLI response. In contrast to the common, shared pathways marking DLI response, a heterogeneous pattern of T cell dysfunction marked DLI resistance. Unexpectedly, TPEX cells that expanded in responders did not arise from the infusion product but instead from both pre-existing and novel clonotypes recruited to the TME. Further, we introduce a Bayesian method, Symphony, to define the T cell regulatory circuitry and master regulators underlying TEX and TPEX subsets that may be broadly relevant to other exhaustion antagonists across cancers. In conclusion, our data implicate the hierarchy of both TEX and TPEX subsets for immunotherapeutic responses in leukemia, extending the scope of their relevance beyond checkpoint blockade to adoptive cellular therapy. Moreover, our results provocatively suggest that immunologic ‘help’ from DLI, rather than direct transfer of anti-leukemic T cells, drove leukemic remission. Finally, we provide a general analysis paradigm for exploiting temporal single-cell genomic profiling for deep understanding of how immune therapies differentially shape the evolutionary trajectories of the TME in accordance with clinical outcome.

Citation Format: Pavan Bachireddy, Elham Azizi, Cassandra Burdziak, Vinhkhang Nguyen, Christina Ennis, Zi- Ning Choo, Shuqiang Li, Kenneth Livak, Donna Neuberg, Robert Soiffer, Jerome Ritz, Edwin Alyea, Dana Pe'er, Catherine Wu. Mapping the evolution of T cell states during response and resistance to adoptive cellular therapy [abstract]. In: Proceedings of the AACR Virtual Special Conference on the Evolving Tumor Microenvironment in Cancer Progression: Mechanisms and Emerging Therapeutic Opportunities; in association with the Tumor Microenvironment (TME) Working Group; 2021 Jan 11-12. Philadelphia (PA): AACR; Cancer Res 2021;81(5 Suppl):Abstract nr LT008.

A gene-environment-induced epigenetic program initiates tumorigenesis

Tissue damage increases the risk of cancer through poorly understood mechanisms1. In mouse models of pancreatic cancer, pancreatitis associated with tissue injury collaborates with activating mutations in the Kras oncogene to markedly accelerate the formation of early neoplastic lesions and, ultimately, adenocarcinoma2,3. Here, by integrating genomics, single-cell chromatin assays and spatiotemporally controlled functional perturbations in autochthonous mouse models, we show that the combination of Kras mutation and tissue damage promotes a unique chromatin state in the pancreatic epithelium that distinguishes neoplastic transformation from normal regeneration and is selected for throughout malignant evolution. This cancer-associated epigenetic state emerges within 48 hours of pancreatic injury, and involves an 'acinar-to-neoplasia' chromatin switch that contributes to the early dysregulation of genes that define human pancreatic cancer. Among the factors that are most rapidly activated after tissue damage in the pre-malignant pancreatic epithelium is the alarmin cytokine interleukin 33, which recapitulates the effects of injury in cooperating with mutant Kras to unleash the epigenetic remodelling program of early neoplasia and neoplastic transformation. Collectively, our study demonstrates how gene-environment interactions can rapidly produce gene-regulatory programs that dictate early neoplastic commitment, and provides a molecular framework for understanding the interplay between genetic and environmental cues in the initiation of cancer.

A Single-Cell Atlas of the Human Healthy Airways

Rationale: The respiratory tract constitutes an elaborate line of defense that is based on a unique cellular ecosystem.Objectives: We aimed to investigate cell population distributions and transcriptional changes along the airways by using single-cell RNA profiling.Methods: We have explored the cellular heterogeneity of the human airway epithelium in 10 healthy living volunteers by single-cell RNA profiling. A total of 77,969 cells were collected at 35 distinct locations, from the nose to the 12th division of the airway tree.Measurements and Main Results: The resulting atlas is composed of a high percentage of epithelial cells (89.1%) but also immune (6.2%) and stromal (4.7%) cells with distinct cellular proportions in different regions of the airways. It reveals differential gene expression between identical cell types (suprabasal, secretory, and multiciliated cells) from the nose (MUC4, PI3, SIX3) and tracheobronchial (SCGB1A1, TFF3) airways. By contrast, cell-type-specific gene expression is stable across all tracheobronchial samples. Our atlas improves the description of ionocytes, pulmonary neuroendocrine cells, and brush cells and identifies a related population of NREP-positive cells. We also report the association of KRT13 with dividing cells that are reminiscent of previously described mouse "hillock" cells and with squamous cells expressing SCEL and SPRR1A/B.Conclusions: Robust characterization of a single-cell cohort in healthy airways establishes a valuable resource for future investigations. The precise description of the continuum existing from the nasal epithelium to successive divisions of the airways and the stable gene expression profile of these regions better defines conditions under which relevant tracheobronchial proxies of human respiratory diseases can be developed.

Frontiers in cancer immunotherapy-a symposium report

Cancer immunotherapy has dramatically changed the approach to cancer treatment. The aim of targeting the immune system to recognize and destroy cancer cells has afforded many patients the prospect of achieving deep, long-term remission and potential cures. However, many challenges remain for achieving the goal of effective immunotherapy for all cancer patients. Checkpoint inhibitors have been able to achieve long-term responses in a minority of patients, yet improving response rates with combination therapies increases the possibility of toxicity. Chimeric antigen receptor T cells have demonstrated high response rates in hematological cancers, although most patients experience relapse. In addition, some cancers are notoriously immunologically "cold" and typically are not effective targets for immunotherapy. Overcoming these obstacles will require new strategies to improve upon the efficacy of current agents, identify biomarkers to select appropriate therapies, and discover new modalities to expand the accessibility of immunotherapy to additional tumor types and patient populations.

Single-Cell Transcriptomics Reveals Early Emergence of Liver Parenchymal and Non-parenchymal Cell Lineages

The cellular complexity and scale of the early liver have constrained analyses examining its emergence during organogenesis. To circumvent these issues, we analyzed 45,334 single-cell transcriptomes from embryonic day (E)7.5, when endoderm progenitors are specified, to E10.5 liver, when liver parenchymal and non-parenchymal cell lineages emerge. Our data detail divergence of vascular and sinusoidal endothelia, including a distinct transcriptional profile for sinusoidal endothelial specification by E8.75. We characterize two distinct mesothelial cell types as well as early hepatic stellate cells and reveal distinct spatiotemporal distributions for these populations. We capture transcriptional profiles for hepatoblast specification and migration, including the emergence of a hepatomesenchymal cell type and evidence for hepatoblast collective cell migration. Further, we identify cell-cell interactions during the organization of the primitive sinusoid. This study provides a comprehensive atlas of liver lineage establishment from the endoderm and mesoderm through to the organization of the primitive sinusoid at single-cell resolution.

Abstract 5722: Acquired stemness by luminal cells

Rare cell types in the prostate are reported to have stem cell properties based on organ regeneration potential following castration. Here, we use single cell RNA-seq (scRNA-Seq) to characterize these populations from the murine and human prostate in hormonally intact and androgen deprived conditions. Prostate cells from hormonally intact mice partitioned into one large subset of basal epithelial cells, another large subset of luminal epithelial cells, which we designate luminal 1 and two rare luminal populations: luminal 2 and luminal 3. Luminal cells that persist following castration display enhanced organoid regeneration potential, particularly within 1-2 days of androgen addback, and contribute equipotently to prostatic regeneration as revealed by lineage tracing. This regeneration is mediated, in part, through the orchestrated expression of Nrg2, Igf1, Fgf10 and Rspo3 by distinct populations of androgen-responsive mesenchymal and smooth muscle cells. Thus, luminal cells that persist post-castration undergo a cell state change that primes a proliferative response to microenvironment signals, analogous to other models of tissue injury such as liver damage.

Citation Format: Wouter Karthaus, Matan Hofree, Danielle Choi, Eliot L. Linton, Mesruh Turkekul, Alborz Bejnood, Brett Carver, Anuhandra Gopalan, Vincent Laudone, Moshe Biton, Ojasvi Chaudhary, Ignas Masilionis, Linas Mazutis, Dana Pe'er, Aviv Regev, Charles Sawyers. Acquired stemness by luminal cells [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5722.

Cancer cells deploy lipocalin-2 to collect limiting iron in leptomeningeal metastasis

The tumor microenvironment plays a critical regulatory role in cancer progression, especially in central nervous system metastases. Cancer cells within the cerebrospinal fluid (CSF)-filled leptomeninges face substantial microenvironmental challenges, including inflammation and sparse micronutrients. To investigate the mechanism by which cancer cells in these leptomeningeal metastases (LM) overcome these constraints, we subjected CSF from five patients with LM to single-cell RNA sequencing. We found that cancer cells, but not macrophages, within the CSF express the iron-binding protein lipocalin-2 (LCN2) and its receptor SCL22A17. These macrophages generate inflammatory cytokines that induce cancer cell LCN2 expression but do not generate LCN2 themselves. In mouse models of LM, cancer cell growth is supported by the LCN2/SLC22A17 system and is inhibited by iron chelation therapy. Thus, cancer cells appear to survive in the CSF by outcompeting macrophages for iron.

Publisher Correction: Lineage plasticity in cancer: a shared pathway of therapeutic resistance

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Tumor Analyses Reveal Squamous Transformation and Off-Target Alterations As Early Resistance Mechanisms to First-line Osimertinib in EGFR-Mutant Lung Cancer

PURPOSE

Patterns of resistance to first-line osimertinib are not well-established and have primarily been evaluated using plasma assays, which cannot detect histologic transformation and have differential sensitivity for copy number changes and chromosomal rearrangements.

EXPERIMENTAL DESIGN

To characterize mechanisms of resistance to osimertinib, patients with metastatic EGFR-mutant lung cancers who received osimertinib at Memorial Sloan Kettering Cancer Center and had next-generation sequencing performed on tumor tissue before osimertinib initiation and after progression were identified.

RESULTS

Among 62 patients who met eligibility criteria, histologic transformation, primarily squamous transformation, was identified in 15% of first-line osimertinib cases and 14% of later-line cases. Nineteen percent (5/27) of patients treated with first-line osimertinib had off-target genetic resistance (2 MET amplification, 1 KRAS mutation, 1 RET fusion, and 1 BRAF fusion) whereas 4% (1/27) had an acquired EGFR mutation (EGFR G724S). Patients with squamous transformation exhibited considerable genomic complexity; acquired PIK3CA mutation, chromosome 3q amplification, and FGF amplification were all seen. Patients with transformation had shorter time on osimertinib and shorter survival compared with patients with on-target resistance. Initial EGFR sensitizing mutation, time on osimertinib treatment, and line of therapy also influenced resistance mechanism that emerged. The compound mutation EGFR S768 + V769L and the mutation MET H1094Y were identified and validated as resistance mechanisms with potential treatment options.

CONCLUSIONS

Histologic transformation and other off-target molecular alterations are frequent early emerging resistance mechanisms to osimertinib and are associated with poor clinical outcomes.See related commentary by Piotrowska and Hata, p. 2441.

Regenerative potential of prostate luminal cells revealed by single-cell analysis

Androgen deprivation is the cornerstone of prostate cancer treatment. It results in involution of the normal gland to ~90% of its original size because of the loss of luminal cells. The prostate regenerates when androgen is restored, a process postulated to involve stem cells. Using single-cell RNA sequencing, we identified a rare luminal population in the mouse prostate that expresses stemlike genes (Sca1 ⁺ and Psca ⁺) and a large population of differentiated cells (Nkx3.1 ⁺, Pbsn ⁺). In organoids and in mice, both populations contribute equally to prostate regeneration, partly through androgen-driven expression of growth factors (Nrg2, Rspo3) by mesenchymal cells acting in a paracrine fashion on luminal cells. Analysis of human prostate tissue revealed similar differentiated and stemlike luminal subpopulations that likewise acquire enhanced regenerative potential after androgen ablation. We propose that prostate regeneration is driven by nearly all persisting luminal cells, not just by rare stem cells.

The Human Tumor Atlas Network: Charting Tumor Transitions across Space and Time at Single-Cell Resolution

Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous large-scale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.