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- W4292972817 abstract "Estrogen receptor-positive (ER+) breast cancer (BC) is a common subtype of BC with a relatively good prognosis. However, recurrence and death from ER+ BC occur because of tumor heterogeneity. This study aimed to explore tumor heterogeneity using next-generation sequencing (NGS) and tumor-organoid models to promote BC precise therapy. We collected needle biopsy, surgical excision, and cerebrospinal fluid (CSF) samples to establish tumor organoids. We found that the histological characteristics of organoids were consistent with original lesions and recapitulated their heterogenicity. In addition, the NGS results showed that PIK3CA and TP53 genes had detrimental mutations. BAP1, RET, AXIN2, and PPP2R2A genes had mutations with unknown function. The score for homologous recombination deficiency (HRD) of genome was 56, indicating that the tumor was likely sensitive to PARPi. The mutant-allele tumor heterogeneity (MATH) value of the tumor genome was 68.03, indicating high tumor heterogeneity. At last, we performed a drug screening on organoids. The toxicity of different drugs toward BC organoids originated from needle biopsy and surgical excision was tested, respectively. The IC50 values in the needle biopsy groups were paclitaxel 2.83 μM, carboplatin 61.47 μM, neratinib 0.8 μM, lapatinib >100 μM; in the surgical excision groups: trastuzumab >100 μM, docetaxel 0.036 μM, tamoxifen 20.54 μM, olaparib 5.478 μM, BYL719 < 0.1 μM. The toxicity data showed that the BC organoids could show dynamic characteristics of tumor progression and reflect the heterogeneity of BC. Our study demonstrates that the combined use of tumor organoids and NGS is a potential way to test tumor heterogeneity and predict drug response in ER + BC, which contributes to the development of personalized therapy." @default.
- W4292972817 created "2022-08-24" @default.
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- W4292972817 date "2022-08-22" @default.
- W4292972817 modified "2023-09-30" @default.
- W4292972817 title "Combining Organoid Models with Next-Generation Sequencing to Reveal Tumor Heterogeneity and Predict Therapeutic Response in Breast Cancer" @default.
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- W4292972817 doi "https://doi.org/10.1155/2022/9390912" @default.
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