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Modeling Tumor Development and Metastasis using Paired Organoids Derived from Patients with Colorectal Cancer Liver Metastases

ABSTRACT: 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 patients (CRC). 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, altered during the progression of CRC. Further study shows that inducible knockdown of SOX2 attenuated invasion, proliferation, and liver metastasis outgrowth. Taken together, we use patient-derived organoids to model cancer metastasis. Our data propose that SOX2 is not only a critical biomarker for the development and metastasis of CRC, but also a potent target for the disease treatment.

ORGANISM(S): Homo sapiens

PROVIDER: GSE148918 | GEO | 2020/10/05

REPOSITORIES: GEO

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Project description:Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity.We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results.Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes.Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

Dataset Information

Modeling Tumor Development and Metastasis using Paired Organoids Derived from Patients with Colorectal Cancer Liver Metastases

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