ABSTRACT
Small-cell lung cancer (SCLC) is the most fatal form of lung cancer. Intratumoral heterogeneity, marked by neuroendocrine (NE) and non-neuroendocrine (non-NE) cell states, defines SCLC, but the cell-extrinsic drivers of SCLC plasticity are poorly understood. To map the landscape of SCLC tumor microenvironment (TME), we apply spatially resolved transcriptomics and quantitative mass spectrometry-based proteomics to metastatic SCLC tumors obtained via rapid autopsy. The phenotype and overall composition of non-malignant cells in the TME exhibit substantial variability, closely mirroring the tumor phenotype, suggesting TME-driven reprogramming of NE cell states. We identify cancer-associated fibroblasts (CAFs) as a crucial element of SCLC TME heterogeneity, contributing to immune exclusion, and predicting exceptionally poor prognosis. Our work provides a comprehensive map of SCLC tumor and TME ecosystems, emphasizing their pivotal role in SCLC's adaptable nature, opening possibilities for reprogramming the TME-tumor communications that shape SCLC tumor states.
Subject(s)
Lung Neoplasms , Small Cell Lung Carcinoma , Tumor Microenvironment , Humans , Small Cell Lung Carcinoma/pathology , Small Cell Lung Carcinoma/genetics , Small Cell Lung Carcinoma/metabolism , Lung Neoplasms/pathology , Lung Neoplasms/metabolism , Cancer-Associated Fibroblasts/metabolism , Cancer-Associated Fibroblasts/pathology , Neuroendocrine Tumors/pathology , Neuroendocrine Tumors/genetics , Neuroendocrine Tumors/metabolism , Neuroendocrine Cells/pathology , Neuroendocrine Cells/metabolism , Female , Male , PrognosisABSTRACT
Natural killer (NK) cells function by eliminating virus-infected or tumor cells. Here we identified an NK-lineage-biased progenitor population, referred to as early NK progenitors (ENKPs), which developed into NK cells independently of common precursors for innate lymphoid cells (ILCPs). ENKP-derived NK cells (ENKP_NK cells) and ILCP-derived NK cells (ILCP_NK cells) were transcriptionally different. We devised combinations of surface markers that identified highly enriched ENKP_NK and ILCP_NK cell populations in wild-type mice. Furthermore, Ly49H+ NK cells that responded to mouse cytomegalovirus infection primarily developed from ENKPs, whereas ILCP_NK cells were better IFNγ producers after infection with Salmonella and herpes simplex virus. Human CD56dim and CD56bright NK cells were transcriptionally similar to ENKP_NK cells and ILCP_NK cells, respectively. Our findings establish the existence of two pathways of NK cell development that generate functionally distinct NK cell subsets in mice and further suggest these pathways may be conserved in humans.
Subject(s)
Cell Differentiation , Killer Cells, Natural , Killer Cells, Natural/immunology , Animals , Mice , Humans , Cell Differentiation/immunology , Mice, Inbred C57BL , Immunity, Innate , CD56 Antigen/metabolism , Muromegalovirus/immunology , Cell Lineage/immunology , Interferon-gamma/metabolism , Interferon-gamma/immunology , Lymphoid Progenitor Cells/metabolism , Lymphoid Progenitor Cells/cytology , Lymphoid Progenitor Cells/immunology , Mice, Knockout , Cells, CulturedABSTRACT
Thymic epithelial cells (TEC) control T cell development and play essential roles in establishing self-tolerance. By using Foxn1-Cre-driven ablation of Klf6 gene in TEC, we identified Klf6 as a critical factor in TEC development. Klf6 deficiency resulted in a hypoplastic thymus-evident from fetal stages into adulthood-in which a dramatic increase in the frequency of apoptotic TEC was observed. Among cortical TEC (cTEC), a previously unreported cTEC population expressing the transcription factor Sox10 was relatively expanded. Within medullary TEC (mTEC), mTEC I and Tuft-like mTEC IV were disproportionately decreased. Klf6 deficiency altered chromatin accessibility and affected TEC chromatin configuration. Consistent with these defects, naïve conventional T cells and invariant natural killer T cells were reduced in the spleen. Late stages of T cell receptor-dependent selection of thymocytes were affected, and mice exhibited autoimmunity. Thus, Klf6 has a prosurvival role and affects the development of specific TEC subsets contributing to thymic function.
Subject(s)
Gene Expression Regulation , Thymocytes , Animals , Mice , Cell Differentiation/genetics , Chromatin/metabolism , Epithelial Cells/metabolism , Mice, Inbred C57BL , Thymocytes/metabolism , Thymus Gland/metabolismABSTRACT
Importance: Patients with relapsed small cell lung cancer (SCLC), a high replication stress tumor, have poor prognoses and few therapeutic options. A phase 2 study showed antitumor activity with the addition of the ataxia telangiectasia and Rad3-related kinase inhibitor berzosertib to topotecan. Objective: To investigate whether the addition of berzosertib to topotecan improves clinical outcomes for patients with relapsed SCLC. Design, Setting, and Participants: Between December 1, 2019, and December 31, 2022, this open-label phase 2 randomized clinical trial recruited 60 patients with SCLC and relapse after 1 or more prior therapies from 16 US cancer centers. Patients previously treated with topotecan were not eligible. Interventions: Eligible patients were randomly assigned to receive topotecan alone (group 1), 1.25 mg/m2 intravenously on days 1 through 5, or with berzosertib (group 2), 210 mg/m2 intravenously on days 2 and 5, in 21-day cycles. Randomization was stratified by tumor sensitivity to first-line platinum-based chemotherapy. Main Outcomes and Measures: The primary end point was progression-free survival (PFS) in the intention-to-treat population. Secondary end points included overall survival (OS) in the overall population and among patients with platinum-sensitive or platinum-resistant tumors. The PFS and OS for each treatment group were estimated using the Kaplan-Meier method. The log-rank test was used to compare PFS and OS between the 2 groups, and Cox proportional hazards models were used to estimate the treatment hazard ratios (HRs) and the corresponding 2-sided 95% CI. Results: Of 60 patients (median [range] age, 59 [34-79] years; 33 [55%] male) included in this study, 20 were randomly assigned to receive topotecan alone and 40 to receive a combination of topotecan with berzosertib. After a median (IQR) follow-up of 21.3 (18.1-28.3) months, there was no difference in PFS between the 2 groups (median, 3.0 [95% CI, 1.2-5.1] months for group 1 vs 3.9 [95% CI, 2.8-4.6] months for group 2; HR, 0.80 [95% CI, 0.46-1.41]; P = .44). Overall survival was significantly longer with the combination therapy (5.4 [95% CI, 3.2-6.8] months vs 8.9 [95% CI, 4.8-11.4] months; HR, 0.53 [95% CI, 0.29-0.96], P = .03). Adverse event profiles were similar between the 2 groups (eg, grade 3 or 4 thrombocytopenia, 11 of 20 [55%] vs 20 of 40 [50%], and any grade nausea, 9 of 20 [45%] vs 14 of 40 [35%]). Conclusions and Relevance: In this randomized clinical trial, treatment with berzosertib plus topotecan did not improve PFS compared with topotecan therapy alone among patients with relapsed SCLC. However, the combination treatment significantly improved OS. Trial Registration: ClinicalTrials.gov Identifier: NCT03896503.
Subject(s)
Lung Neoplasms , Small Cell Lung Carcinoma , Humans , Male , Middle Aged , Female , Small Cell Lung Carcinoma/pathology , Topotecan/adverse effects , Lung Neoplasms/pathology , Antineoplastic Combined Chemotherapy Protocols/adverse effects , RecurrenceABSTRACT
PURPOSE: Despite promising preclinical studies, toxicities have precluded combinations of chemotherapy and DNA damage response (DDR) inhibitors. We hypothesized that tumor-targeted chemotherapy delivery might enable clinical translation of such combinations. PATIENTS AND METHODS: In a phase I trial, we combined sacituzumab govitecan, antibody-drug conjugate (ADC) that delivers topoisomerase-1 inhibitor SN-38 to tumors expressing Trop-2, with ataxia telangiectasia and Rad3-related (ATR) inhibitor berzosertib. Twelve patients were enrolled across three dose levels. RESULTS: Treatment was well tolerated, with improved safety over conventional chemotherapy-based combinations, allowing escalation to the highest dose. No dose-limiting toxicities or clinically relevant ≥grade 4 adverse events occurred. Tumor regressions were observed in 2 patients with neuroendocrine prostate cancer, and a patient with small cell lung cancer transformed from EGFR-mutant non-small cell lung cancer. CONCLUSIONS: ADC-based delivery of cytotoxic payloads represents a new paradigm to increase efficacy of DDR inhibitors. See related commentary by Berg and Choudhury, p. 3557.
Subject(s)
Carcinoma, Non-Small-Cell Lung , Immunoconjugates , Lung Neoplasms , Male , Humans , Carcinoma, Non-Small-Cell Lung/drug therapy , Lung Neoplasms/drug therapy , Camptothecin/adverse effects , Camptothecin/administration & dosage , Immunoconjugates/adverse effects , Immunoconjugates/administration & dosageABSTRACT
Dietary components and metabolites have a profound impact on immunity and inflammation. Here, we investigated how sensing of cholesterol metabolite oxysterols by γδ T cells impacts their tissue residency and function. We show that dermal IL-17-producing γδ T (Tγδ17) cells essential for skin-barrier homeostasis require oxysterols sensing through G protein receptor 183 (GPR183) for their development and inflammatory responses. Single-cell transcriptomics and murine reporter strains revealed that GPR183 on developing γδ thymocytes is needed for their maturation by sensing medullary thymic epithelial-cell-derived oxysterols. In the skin, basal keratinocytes expressing the oxysterol enzyme cholesterol 25-hydroxylase (CH25H) maintain dermal Tγδ17 cells. Diet-driven increases in oxysterols exacerbate Tγδ17-cell-mediated psoriatic inflammation, dependent on GPR183 on γδ T cells. Hence, cholesterol-derived oxysterols control spatially distinct but biologically linked processes of thymic education and peripheral function of dermal T cells, implicating diet as a focal parameter of dermal Tγδ17 cells.
Subject(s)
Cholesterol, Dietary , Oxysterols , Humans , Animals , Mice , Oxysterols/metabolism , Skin/metabolism , Inflammation , GTP-Binding Proteins/metabolism , Receptors, Antigen, T-Cell, gamma-delta/metabolism , Receptors, G-Protein-Coupled/metabolismABSTRACT
Complex age-associated phenotypes are caused, in part, by an interaction between an individual's genotype and age. The mechanisms governing such interactions are however not entirely understood. Here, we provide a novel transcriptional mechanism-based framework-SNiPage, to investigate such interactions, whereby a transcription factor (TF) whose expression changes with age (age-associated TF), binds to a polymorphic regulatory element in an allele-dependent fashion, rendering the target gene's expression dependent on both, the age and the genotype. Applying SNiPage to GTEx, we detected ~637 significant TF-SNP-Gene triplets on average across 25 tissues, where the TF binds to a regulatory SNP in the gene's promoter or putative enhancer and potentially regulates its expression in an age- and allele-dependent fashion. The detected SNPs are enriched for epigenomic marks indicative of regulatory activity, exhibit allele-specific chromatin accessibility, and spatial proximity to their putative gene targets. Furthermore, the TF-SNP interaction-dependent target genes have established links to aging and to age-associated diseases. In six hypertension-implicated tissues, detected interactions significantly inform hypertension state of an individual. Lastly, the age-interacting SNPs exhibit a greater proximity to the reported phenotype/diseases-associated SNPs than eSNPs identified in an interaction-independent fashion. Overall, we present a novel mechanism-based model, and a novel framework SNiPage, to identify functionally relevant SNP-age interactions in transcriptional control and illustrate their potential utility in understanding complex age-associated phenotypes.
Subject(s)
Aging/genetics , Gene Expression Regulation , Models, Biological , Phenotype , Polymorphism, Single Nucleotide , Transcription, Genetic , Algorithms , Alleles , Humans , Transcription Factors/metabolismABSTRACT
Interactions between thymic epithelial cells (TEC) and developing thymocytes are essential for T cell development, but molecular insights on TEC and thymus homeostasis are still lacking. Here we identify distinct transcriptional programs of TEC that account for their age-specific properties, including proliferation rates, engraftability and function. Further analyses identify Myc as a regulator of fetal thymus development to support the rapid increase of thymus size during fetal life. Enforced Myc expression in TEC induces the prolonged maintenance of a fetal-specific transcriptional program, which in turn extends the growth phase of the thymus and enhances thymic output; meanwhile, inducible expression of Myc in adult TEC similarly promotes thymic growth. Mechanistically, this Myc function is associated with enhanced ribosomal biogenesis in TEC. Our study thus identifies age-specific transcriptional programs in TEC, and establishes that Myc controls thymus size.
Subject(s)
Epithelial Cells/metabolism , Oncogene Protein p55(v-myc)/metabolism , Thymus Gland/embryology , Transcription, Genetic , Animals , Epithelial Cells/cytology , Female , Gene Expression Regulation, Developmental , Humans , Male , Mice , Mice, Transgenic , Oncogene Protein p55(v-myc)/genetics , Organ Size , Organogenesis , Thymus Gland/metabolismABSTRACT
Alternative splicing contributes to phenotypic diversity at multiple biological scales, and its dysregulation is implicated in both ageing and age-associated diseases in human. Cross-tissue variability in splicing further complicates its links to age-associated phenotypes and elucidating these links requires a comprehensive map of age-associated splicing changes across multiple tissues. Here, we generate such a map by analyzing ~8500 RNA-seq samples across 48 tissues in 544 individuals. Employing a stringent model controlling for multiple confounders, we identify 49,869 tissue-specific age-associated splicing events of 7 distinct types. We find that genome-wide splicing profile is a better predictor of biological age than the gene and transcript expression profiles, and furthermore, age-associated splicing provides additional independent contribution to age-associated complex diseases. We show that the age-associated splicing changes may be explained, in part, by concomitant age-associated changes of the upstream splicing factors. Finally, we show that our splicing-based model of age can successfully predict the relative ages of cells in 8 of the 10 paired longitudinal data as well as in 2 sets of cell passage data. Our study presents the first systematic investigation of age-associated splicing changes across tissues, and further strengthening the links between age-associated splicing and age-associated diseases.
Subject(s)
Aging/genetics , Gene Expression Profiling/methods , RNA/metabolism , Alternative Splicing , Female , Genetic Predisposition to Disease , Humans , Male , Organ Specificity , RNA Splicing , Sequence Analysis, RNAABSTRACT
Mammalian gene expression is often regulated by distal enhancers. However, little is known about higher order functional organization of enhancers. Using â¼100 K P300-bound regions as candidate enhancers, we investigated their correlated activity across 72 cell types based on DNAse hypersensitivity. We found widespread correlated activity between enhancers, which decreases with increasing inter-enhancer genomic distance. We found that correlated enhancers tend to share common transcription factor (TF) binding motifs, and several chromatin modification enzymes preferentially interact with these TFs. Presence of shared motifs in enhancer pairs can predict correlated activity with 73% accuracy. Also, genes near correlated enhancers exhibit correlated expression and share common function. Correlated enhancers tend to be spatially proximal. Interestingly, weak enhancers tend to correlate with significantly greater numbers of other enhancers relative to strong enhancers. Furthermore, strong/weak enhancers preferentially correlate with strong/weak enhancers, respectively. We constructed enhancer networks based on shared motif and correlated activity and show significant functional enrichment in their putative target gene clusters. Overall, our analyses show extensive correlated activity among enhancers and reveal clusters of enhancers whose activities are coordinately regulated by multiple potential mechanisms involving shared TF binding, chromatin modifying enzymes and 3D chromatin structure, which ultimately co-regulate functionally linked genes.
Subject(s)
Deoxyribonucleases , Enhancer Elements, Genetic , Chromatin/chemistry , Gene Expression , Gene Regulatory Networks , Humans , Transcription Factors/metabolismABSTRACT
BACKGROUND: Understanding the evolution of biological networks can provide insight into how their modular structure arises and how they are affected by environmental changes. One approach to studying the evolution of these networks is to reconstruct plausible common ancestors of present-day networks, allowing us to analyze how the topological properties change over time and to posit mechanisms that drive the networks' evolution. Further, putative ancestral networks can be used to help solve other difficult problems in computational biology, such as network alignment. RESULTS: We introduce a combinatorial framework for encoding network histories, and we give a fast procedure that, given a set of gene duplication histories, in practice finds network histories with close to the minimum number of interaction gain or loss events to explain the observed present-day networks. In contrast to previous studies, our method does not require knowing the relative ordering of unrelated duplication events. Results on simulated histories and real biological networks both suggest that common ancestral networks can be accurately reconstructed using this parsimony approach. A software package implementing our method is available under the Apache 2.0 license at http://cbcb.umd.edu/kingsford-group/parana. CONCLUSIONS: Our parsimony-based approach to ancestral network reconstruction is both efficient and accurate. We show that considering a larger set of potential ancestral interactions by not assuming a relative ordering of unrelated duplication events can lead to improved ancestral network inference.