Modeling Tumor Development and Metastasis using Paired Organoids Derived from Patients with Colorectal Cancer Liver Metastases
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA626540 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR11573854_1.fastq.gz | Fastqsanger.gz | |||
| SRR11573854_2.fastq.gz | Fastqsanger.gz | |||
| SRR11573855_1.fastq.gz | Fastqsanger.gz | |||
| SRR11573855_2.fastq.gz | Fastqsanger.gz | |||
| SRR11573856_1.fastq.gz | Fastqsanger.gz |
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Project description:Tumor metastasis accounts for the majority of cancer-related deaths; it is therefore important to develop preclinical models that faithfully recapitulate disease progression. Here, we generated paired organoids derived from primary tumors and matched liver metastases in the same colorectal cancer (CRC) patients. Despite the fact that paired organoids exhibit comparable gene expression and cell morphology, organoids from metastatic lesions demonstrate more aggressive phenotypes, tumorigenesis, and metastatic capacity than those from primary lesions. Transcriptional analyses of the paired organoids reveal signature genes and pathways altered during the progression of CRC, including SOX2. Further study shows that inducible knockdown of SOX2 attenuated invasion, proliferation, and liver metastasis outgrowth. Taken together, we use patient-derived paired primary and metastatic cancer organoids to model CRC metastasis and illustrate that SOX2 is associated with CRC progression and may serve as a potential prognostic biomarker and therapeutic target of CRC.
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Project description:Gene Expression Profiling of Breast Cancer Patients with Brain Metastases Brain metastases confer the worst prognosis of breast cancer as no therapy exists that prevents or eliminates the cancer from spreading to the brain. We developed a new computational modeling method to derive specific downstream signaling pathways that reveal unknown target-disease connections and new mechanisms for specific cancer subtypes. The model enables us to reposition drugs based on available gene expression data of patients. We applied this model to repurpose known or shelved drugs for brain, lung, and bone metastases of breast cancer with the hypothesis that cancer subtypes have their own specific signaling mechanisms. To test the hypothesis, we addressed the specific CSBs for each metastasis that satisfy that (1) CSB proteins are activated by the maximal number of enriched signaling pathways specific to this metastasis, and (2) CSB proteins involve in the most differential expressed coding-genes specific to the specific breast cancer metastasis. The identified signaling networks for the three types of metastases contain 31, 15, and 18 proteins, respectively, and are used to reposition 15, 9, and 2 drug candidates for the brain, lung, and bone metastases of breast cancer. We performed in vitro and in vivo preclinical experiments as well as analysis on patient tumor specimens to evaluate the targets and repositioned drugs. Two known drugs, Sunitinib (FDA approved for renal cell carcinoma and imatinib-resistant gastrointestinal stromal tumor) and Dasatinib (FDA approved for chronic myelogenous leukemia (CML) after imatinib treatment and Philadelphia chromosome-positive acute lymphoblastic leukemia), were shown to prohibit the metastatic colonization in brain. The TMH-52 cohort includes 11 patients who were examined with brain metastasis at the time of breast cancer diagnosis. The other 41 patients were examined with other organ metastasis at the time of breast cancer diagnosis.
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