Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1275653 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| Other | ||||
| SRR33950600_1.fastq.gz | Fastqsanger.gz | |||
| SRR33950600_2.fastq.gz | Fastqsanger.gz | |||
| SRR33950700_1.fastq.gz | Fastqsanger.gz | |||
| SRR33950700_2.fastq.gz | Fastqsanger.gz |
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Project description:Small cell lung cancer (SCLC) is a highly aggressive subtype of lung cancer that remains among the most lethal of solid tumor malignancies. Recent genomic sequencing studies have identified many recurrently mutated genes in human SCLC tumors. However, the functional roles of most of these genes remain to be validated. Here, we adapt the CRISPR-Cas9 system to a well-established murine model of SCLC to rapidly model loss-of-function mutations in candidate genes identified from SCLC sequencing studies. We show that loss of the gene p107 significantly accelerates tumor progression. Notably, compared with loss of the closely related gene p130, p107 loss results in fewer but larger tumors, as well as earlier metastatic spread. In addition, we observe differences in proliferation and apoptosis, as well as altered distribution of initiated tumors in the lung, resulting from loss of p107 or p130. Collectively, these data demonstrate the feasibility of using the CRISPR-Cas9 system to model loss of candidate tumor suppressor genes in SCLC, and we anticipate that this approach will greatly facilitate efforts to investigate mechanisms driving tumor progression in this deadly disease.
2019-12-19 | GSE139444 | GEO
Project description:Small cell lung carcinoma (SCLC) and large cell neuroendocrine carcinoma (LCNEC) are high-grade pulmonary neuroendocrine tumors. The neural basic helix-loop-helix (bHLH) transcription factors ASCL1 and NEUROD1 have been shown to play crucial roles in promoting the malignant behavior and survival of human SCLC cell lines. In this study, we find ASCL1 and NEUROD1 identify distinct neuroendocrine tumors, bind distinct genomic loci, and regulate mostly distinct genes. ASCL1 and NEUROD1 are often bound in super-enhancers that are associated with highly expressed genes in their respective SCLC cell lines suggesting different cell lineage of origin for these tumors. ASCL1 targets oncogenic genes such as MYCL1, RET, and NFIB, while NEUROD1 targets the oncogenic gene MYC. Although ASCL1 and NEUROD1 regulate different genes, many of these gene targets commonly contribute to neuroendocrine and cell migration function. ASCL1 in particular also regulates genes in the NOTCH pathway and genes important in cell-cycle dynamics. Finally, we demonstrate ASCL1 but not NEUROD1 is required for SCLC and LCNEC tumor formation in current in vivo genetic mouse models of pulmonary neuroendocrine tumors ChIP-seq analysis performed on three ASCL1high and two NEUROD1high human SCLC cell lines to identify ASCL1 and/or NEUROD1 binding sites in these two types of cells. Also, we performed ChIP-seq for Ascl1 binding sites in mouse neuroendocrine lung tumors obtained from Trp53;Rb1;Rbl2 triple knockout model mice treated with Adeno-CMVCRE intratracheally.
2016-07-21 | E-GEOD-69394 | biostudies-arrayexpress
Project description:The goal of this study was to characterize and classify pulmonary neuroendocrine tumors based on Array Comparative Genomic Hybridization (aCGH). Using aCGH, we performed karyotype analysis of 33 small cell lung cancer (SCLC) tumors, 13 SCLC cell lines, 19 bronchial carcinoids, and 9 gastrointestinal (GI) carcinoids. In contrast to the relatively stable karyotypes of carcinoid tumors, the karyotypes of SCLC tumors and cell lines were highly aberrant. High copy number (CN) gains were detected in SCLC tumors and cell lines in cytogenetic bands encoding JAK2, FGFR1, and MYC family members. In some of those samples, the CN of these genes exceeded 100, suggesting that they could represent driver alterations and potential drug targets in subgroups of SCLC patients. Recurrent CN alterations of a total of 203 genes, including the RB1 gene, and 59 microRNAs, most of which locate in the DLK1-DIO3 domain, were observed in SCLC tumors, bronchial carcinoids and carcinoids of GI origin; in contrast, CN alterations of the TP53 gene and the MYC family members were observed more frequently in SCLC. These findings suggest the existence of partially shared tumor-specific CN alterations in these tumors. Furthermore, we demonstrated that the aCGH profile of SCLC cell lines highly resemble that of clinical SCLC specimens. Finally, by analyzing potential drug targets, we provide a genomics based rationale for targeting the AKT-mTOR and apoptosis pathways in SCLC.
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Project description:Small cell lung cancer (SCLC) is a neuroendocrine tumor treated clinically as a single disease with poor outcomes. Distinct SCLC molecular subtypes have been defined based on expression of lineage-related transcription factors: ASCL1, NEUROD1, POU2F3 or YAP1, but their origins remain unknown. We developed an in vitro model of MYC-driven SCLC tumor cell progression, and performed a time-series analysis of single-cell transcriptome profiling to reveal that MYC drives the dynamic evolution of SCLC subtypes. Analyses of these single-cell RNA seq data reveal that MYC promotes a temporal shift from an ASCL1-to-NEUROD1-to-YAP1+ state from a neuroendocrine cell of origin. MYC activates Notch signaling to dedifferentiate tumor cells to non-neuroendocrine fates. Additional single-cell RNA sequencing of 4RPM tumors reveal individual tumors to consist of cells at nearly every stage of RPM tumor evolution modeled in vitro. With the single-cell RNA sequencing of this human SCLC liver biopsy, along with IHC on a panel of 21 human biopsies, we show that human SCLC exhibits intratumoral SCLC subtype heterogeneity, suggesting this dynamic evolution occurs in patient tumors. Together, these single-cell RNA sequencing data support our conclusions that genetics, cell of origin, and tumor cell plasticity determine SCLC subtype.
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Project description:Somatic transposon mutagenesis in mice is an efficient strategy to investigate the genetic mechanisms of tumorigenesis. The identification of tumor driving transposon insertions traditionally requires the generation of large tumor cohorts to obtain information about common insertion sites. Tumor driving insertions are also characterized by their clonal expansion in tumor tissue, a phenomenon that is facilitated by the slow and evolving transformation process of transposon mutagenesis. We describe here an improved approach for the detection of tumor driving insertions that assesses the clonal expansion of insertions by quantifying the relative proportion of sequence reads obtained in individual tumors. To this end, we have developed a protocol for insertion site sequencing that utilizes acoustic shearing of tumor DNA and Illumina sequencing. We analyzed various solid tumors generated by PiggyBac mutagenesis and for each tumor >10^6 reads corresponding to >10^4 insertion sites were obtained. In each tumor, 9 to 25 insertions stood out by their enriched sequence read frequencies when compared to frequencies obtained from tail DNA controls. These enriched insertions are potential clonally expanded tumor driving insertions, and thus identify candidate cancer genes. The candidate cancer genes of our study comprised many established cancer genes, but also novel candidate genes such as Mastermind-like1 (Mamld1) and Diacylglycerolkinase delta (Dgkd). We show that clonal expansion analysis by high-throughput sequencing is a robust approach for the identification of candidate cancer genes in insertional mutagenesis screens on the level of individual tumors. Solid tumors in mice were generated by somatic transposon mutagenesis with a PiggyBac transposon system. Insertion sites of transposons in 11 tumors and 6 non-cancerous tail controls were determined by Illumina high-throughput sequencing. Insertions were determined both on 5' and 3' sides of the transposon (PB5 and PB3, respectively). Quantitative analysis of read numbers revealed enrichment of certain insertions in tumors, but not in controls, and these enriched insertions identify candidate cancer genes.
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