Single-cell analyses reveal increasing intratumoral heterogeneity as an essential component of treatment resistance in small cell lung cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE138474 | GEO | 2020/02/12
REPOSITORIES: GEO
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Project description:The natural history of small cell lung cancer (SCLC) includes rapid evolution from exquisite chemosensitivity to insurmountable chemoresistance. The mechanisms underlying treatment-resistance in SCLC remain obscure due to scarcity of tissue samples following relapse. We generated circulating tumor cell (CTC)-derived xenografts (CDXs) from SCLC patients to study intratumoral heterogeneity (ITH) and its contribution to treatment resistance. To investigate this, we performed single-cell RNAseq analyses of chemo-sensitive and -resistant CDXs, as well as longitudinal analyses of CDXs and patient CTCs. We found increased ITH, heterogeneous expression of pathways known to be associated with resistance, and transcriptional diversity of either therapeutic targets or EMT genes between cellular subpopulations following treatment-resistance to either chemotherapy or targeted therapies (PARP or CHK inhibitors). Similarly, serial profiling of patient CTCs directly from blood confirmed increased ITH post-relapse, with gene expression patterns similar to a CDX from the same patient. These data suggest that treatment-resistance in SCLC is characterized by the presence of coexisting subpopulations of tumor cells with heterogeneous gene expression leading to activation of multiple, concurrent resistance mechanisms. These findings emphasize the need for drug development efforts to focus on rational combination therapies for treatment-naïve SCLC tumors to maximize the depth and duration of initial responses and counteract the rapid increase in ITH and emergence of broad therapeutic resistance.
2020-02-12 | GSE138267 | GEO
Project description:The natural history of small cell lung cancer (SCLC) includes rapid evolution from chemosensitivity to chemoresistance, although mechanisms underlying this evolution remain obscure due to scarcity of post-relapse tissue samples. We generated circulating tumor cell (CTC)-derived xenografts (CDXs) from SCLC patients to study intratumoral heterogeneity (ITH) via single-cell RNAseq of chemo-sensitive and -resistant CDXs and patient CTCs. We found globally increased ITH including heterogeneous expression of therapeutic targets and potential resistance pathways, such as EMT, between cellular subpopulations following treatment-resistance. Similarly, serial profiling of patient CTCs directly from blood confirmed increased ITH post-relapse. These data suggest that treatment-resistance in SCLC is characterized by coexisting subpopulations of cells with heterogeneous gene expression leading to multiple, concurrent resistance mechanisms. These findings emphasize the need for clinical efforts to focus on rational combination therapies for treatment-naïve SCLC tumors to maximize initial responses and counteract the emergence of ITH and diverse resistance mechanisms.
| S-EPMC7842382 | biostudies-literature
Project description:Single-cell analyses reveal increasing intratumoral heterogeneity as an essential component of treatment resistance in small cell lung cancer
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Project description:Single-cell analyses reveal increasing intratumoral heterogeneity as an essential component of treatment resistance in small cell lung cancer [RNA-Seq]
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Project description:Recent data have demonstrated that cancer drug resistance reflects complex biologic factors, including tumor heterogeneity, varying growth, differentiation, apoptosis pathways, and cell density. As a result, there is a need to find new ways to incorporate these complexities in the mathematical modeling of multidrug resistance. Here, we derive a novel structured population model that describes the behavior of cancer cells under selection with cytotoxic drugs. Our model is designed to estimate intratumoral heterogeneity as a function of the resistance level and time. This updated model of the multidrug resistance problem integrates both genetic and epigenetic changes, density dependence, and intratumoral heterogeneity. Our results suggest that treatment acts as a selection process, whereas genetic/epigenetic alteration rates act as a diffusion process. Application of our model to cancer treatment suggests that reducing alteration rates as a first step in treatment causes a reduction in tumor heterogeneity and may improve targeted therapy. The new insight provided by this model could help to dramatically change the ability of clinical oncologists to design new treatment protocols and analyze the response of patients to therapy.
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Project description:Cellular heterogeneity is a major cause of treatment resistance in cancer. Despite recent advances in single-cell genomic and transcriptomic sequencing, it remains difficult to relate measured molecular profiles to the cellular activities underlying cancer. Here, we present an integrated experimental system that connects single cell gene expression to heterogeneous cancer cell growth, metastasis, and treatment response. Our system integrates single cell transcriptome profiling with DNA barcode based clonal tracking in patient-derived xenograft models. We show that leukemia cells exhibiting unique gene expression respond to different chemotherapies in distinct but consistent manners across multiple mice. In addition, we uncover a form of leukemia expansion that is spatially confined to the bone marrow of single anatomical sites and driven by cells with distinct gene expression. Our integrated experimental system can interrogate the molecular and cellular basis of the intratumoral heterogeneity underlying disease progression and treatment resistance. DNA barcoding is a promising technology for the simultaneous analysis of genetic and phenotypic heterogeneity. Here, the authors combine DNA barcoding and single-cell RNA-seq to study heterogeneity, progression and response to therapy in B-cell acute lymphoblastic leukaemia patient-derived xenografts.
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Project description:Small cell lung cancer (SCLC) is a highly malignant tumor with extensive genomic alterations as detected by single-region sequencing. Yet, the intratumoral heterogeneity (ITH) of SCLC remains unknown. We subjected 120 tumor samples from 40 stage I-III SCLC to multi-regional whole-exome sequencing.
2021-07-02 | PRJEB45988 | EVA
Project description:Combining whole exome sequencing, transcriptome profiling, and T cell repertoire analysis, we investigate the spatial features of surgically-removed biopsies from multiple loci in tumor masses of 15 patients with non-small cell lung cancer (NSCLC). This revealed that the immune microenvironment has high spatial heterogeneity such that intratumoral regional variation is as large as inter-personal variation. While the local total mutational burden (TMB) is associated with local T-cell clonal expansion, local anti-tumor cytotoxicity does not directly correlate with neoantigen abundance. Together, these findings caution against that immunological signatures can be predicted solely from TMB or microenvironmental analysis from a single locus biopsy.
| S-EPMC6299138 | biostudies-literature
Project description:Small cell lung cancer (SCLC) tumors comprise heterogeneous mixtures of cell states, categorized into neuroendocrine (NE) and non-neuroendocrine (non-NE) transcriptional subtypes. NE to non-NE state transitions, fueled by plasticity, likely underlie adaptability to treatment and dismal survival rates. Here, we apply an archetypal analysis to model plasticity by recasting SCLC phenotypic heterogeneity through multi-task evolutionary theory. Cell line and tumor transcriptomics data fit well in a five-dimensional convex polytope whose vertices optimize tasks reminiscent of pulmonary NE cells, the SCLC normal counterparts. These tasks, supported by knowledge and experimental data, include proliferation, slithering, metabolism, secretion, and injury repair, reflecting cancer hallmarks. SCLC subtypes, either at the population or single-cell level, can be positioned in archetypal space by bulk or single-cell transcriptomics, respectively, and characterized as task specialists or multi-task generalists by the distance from archetype vertex signatures. In the archetype space, modeling single-cell plasticity as a Markovian process along an underlying state manifold indicates that task trade-offs, in response to microenvironmental perturbations or treatment, may drive cell plasticity. Stifling phenotypic transitions and plasticity may provide new targets for much-needed translational advances in SCLC. A record of this paper's Transparent Peer Review process is included in the supplemental information.
| S-EPMC9615940 | biostudies-literature
Project description:Small cell lung cancer (SCLC) is a highly malignant tumor which is eventually refractory to any treatment. Intratumoral heterogeneity (ITH) may contribute to treatment failure. However, the extent of ITH in SCLC is still largely unknown. Here, we subject 120 tumor samples from 40 stage I-III SCLC patients to multi-regional whole-exome sequencing. The most common mutant genes are TP53 (88%) and RB1 (72%). We observe a medium level of mutational heterogeneity (0.30, range 0.0~0.98) and tumor mutational burden (TMB, 10.2 mutations/Mb, range 1.1~51.7). Our SCLC samples also exhibit somatic copy number variation (CNV) across all patients, with an average CNV ITH of 0.49 (range 0.02~0.99). In terms of mutation distribution, ITH, TMB, mutation clusters, and gene signatures, patients with combined SCLC behave roughly the same way as patients with pure SCLC. This condition also exists in smoking patients and patients with EGFR mutations. A higher TMB per cluster is associated with better disease-free survival while single-nucleotide variant ITH is linked to worse overall survival, and therefore these features may be used as prognostic biomarkers for SCLC. Together, these findings demonstrate the intratumoral genetic heterogeneity of surgically resected SCLC and provide insights into resistance to treatment.
| S-EPMC8440529 | biostudies-literature