High-resolution clonal mapping of multi-organ metastasis in triple negative breast cancer
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ABSTRACT:
PROVIDER: PRJNA505575 | ENA |
REPOSITORIES: ENA
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Project description:Most triple negative breast cancers (TNBCs) are aggressively metastatic with a high degree of intratumoral heterogeneity. We employed patient-derived xenograft models established from the breast tumors of patients with treatment-naïve metastatic TNBC to study clonal dynamics during metastasis. Genomic sequencing coupled with high-complexity barcode-mediated clonal tracking revealed robust alterations in clonal architecture between primary tumors and corresponding metastases that were deterministic rather than stochastic. The presence of numerous rare subclones in each metastatic lesion demonstrated that polyclonal seeding occurred and that heterogeneous populations of low-abundance clones were maintained in metastases. An identical population of subclones was enriched in lung, liver, and brain metastases, demonstrating that primary tumor clones harbor properties enabling them to seed and thrive in multiple organ sites. Further, clones that dominated multi-organ metastases shared a genomic lineage. Thus, intrinsic properties of rare primary tumor subclones enable the seeding and colonization of metastases in multiple organ sites.
2018-12-11 | GSE120753 | GEO
Project description:High-resolution clonal mapping of multi-organ metastasis in triple negative breast cancer
| PRJNA494390 | ENA
Project description:High-resolution clonal mapping of multi-organ metastasis in triple negative breast cancer
| PRJNA505576 | ENA
Project description:Most triple negative breast cancers (TNBCs) are aggressively metastatic with a high degree of intra-tumoral heterogeneity (ITH), but how ITH contributes to metastasis is unclear. Here, clonal dynamics during metastasis were studied in vivo using two patient-derived xenograft (PDX) models established from the treatment-naive primary breast tumors of TNBC patients diagnosed with synchronous metastasis. Genomic sequencing and high-complexity barcode-mediated clonal tracking reveal robust alterations in clonal architecture between primary tumors and corresponding metastases. Polyclonal seeding and maintenance of heterogeneous populations of low-abundance subclones is observed in each metastasis. However, lung, liver, and brain metastases are enriched for an identical population of high-abundance subclones, demonstrating that primary tumor clones harbor properties enabling them to seed and thrive in multiple organ sites. Further, clones that dominate multi-organ metastases share a genomic lineage. Thus, intrinsic properties of rare primary tumor subclones enable the seeding and colonization of metastases in secondary organs in these models.
| S-EPMC6265294 | biostudies-literature
Project description:Metastasis in triple-negative breast cancer
| PRJNA437929 | ENA
Project description:Purpose: To understand the underlying mechanisms of oncolytic virus therapy in breast cancer. Methods: The primary tumors of 4T1 in BALB/C mice were exstracted and analyzed by RNA-seq. Results: In consistent with previous studies, we found some anti-tumor factors were up-regulated. Interestingly, several immunosupressive genes were activited. Conclusion: Our study identified the intercellular and intracellular factors restricting the optimized oHSV efficacy and supported the rationally designed triple therapy for clinical translation.
2023-05-01 | GSE201760 | GEO
Project description:This microarray dataset contains 51 triple-negative breast cancers with clinical and recurrence information for at least 3 years of follow-up and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). A novel set of 45-gene signature that was statistically predictive of distant metastasis recurrence for triple-negative breast cancer was identified in this study.
2012-11-01 | GSE33926 | GEO
Project description:BackgroundThe distant metastasis was the most predictive characters of poor prognosis for triple-negative breast cancer (TNBC). We aimed to evaluate the correlation between patient characters and preferential distant metastatic sites (DMS) and its effects on prognosis.MethodsUsing the 2010-2014 Surveillance, Epidemiology, and End Results Program (SEER) data, patients with TNBC were classified into eight histologic subtypes. Patient characters were compared using a chi-squared test. Logistic regression was used for identification of predictive factors. The log-rank testing was utilized with disease-specific survival (DSS) and overall survival (OS) as the primary outcomes.ResultsA total of 23 270 patients with TNBC were involved, including 1544 patients with distant metastatic cancer. Bone metastasis was diagnosed in 559 cases, brain metastasis in 124 cases, liver metastasis found in 369 cases and lung metastasis in 492 cases. Histologic subtypes including metaplastic breast carcinoma and invasive lobular carcinoma showed significant differences in preferential DMS compared with invasive ductal carcinoma. Furthermore, we found different histologic subtypes with specific DMS showed various prognosis. We also evaluated different DMS of specific histologic subtypes showed different prognosis.ConclusionCertain histologic subtypes of breast cancer are associated with preferential DMS and prognosis; this knowledge may help to further understand the mechanism of breast cancer metastasis and to monitor the prognosis of patients with TNBC.
| S-EPMC6997059 | biostudies-literature
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE151569 | GEO
Project description:The remarkable evolutionary capacity of cancer poses major challenges to current therapeutic efforts, and results from the vast clonal heterogeneity and ability of individual cancer cells to adapt to diverse selective pressures. More complete mechanistic understanding of the basis of therapeutic resistance has been limited by difficulties in coupling information regarding genetic and epigenetic alterations present within individual cells to their respective transcriptomic and functional outputs. To this end, we developed a novel high-complexity expressed barcode system, ClonMapper, that integrates DNA barcoding with single-cell RNA-sequencing and clonal isolation to characterize thousands of clones within a mixed cancer cell population. In applying this system to the chronic lymphocytic leukemia cell line HG3 in the setting of resistance to fludarabine-based chemotherapy, we discover pretreatment sub-populations with distinct expression profiles (i.e. upregulated Wnt, Notch and CXCR4 signaling) that not only confer distinct treatment survivorship trajectories, but also provide the basis for long-term clonal equilibrium between co-existing clones in the absence of treatment. Characterization of individual clones comprising these sub-populations revealed remarkable genetic heterogeneity and the persistence of unique transcriptomic signatures throughout treatment exposure. These data reveal the diverse clonal characteristics and therapeutic responses of a heterogeneous cancer cell population and highlight the unprecedented resolution that can be achieved using ClonMapper.
2021-04-18 | GSE151430 | GEO