Comprehensive genetic evaluation of ductal carcinoma in situ

导管原位癌的综合遗传学评估

• 批准号: 20K17562
• 负责人: 山脇 幸子
• 金额: $ 2.75万
• 依托单位: Keio University
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Early-Career Scientists
• 财政年份: 2020
• 资助国家: 日本
• 起止时间: 2020-04-01 至 2021-03-31
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-20K17562/
• 关键词: Breast cancer; Ductal Carcinoma In Situ; Genome editing; Clinical sequencing; DCIS; Breast Cancer; Cancer genome

The aim of this project (part 1) was to identify the genetic signature that predict the progression of ductal carcinoma in situ (DCIS) to invasive ductal carcinoma (IDC) of the breast in clinical specimens. From the interim analysis of 236 specimens, we confirmed that the major genetic mutations such as PIK3CA, AKT1, and TP53 were consistently detected as previously reported in the TCGA dataset. In 2020, we collected more data from clinical sequencing and the cohort now includes total 313 specimens (252 from IDC and 61 from DCIS). Thus, we are updating the analysis of the entire cohort and attempt to identify the candidate genes responsible for progression from DCIS to IDC even in less frequently mutated genes.The aim of this project (part 2) was to describe the molecular mechanism of the breast cancer progression in the model. We obtained cell lines such as MCF10A and MCF10DCIS as models of normal epithelia and DCIS tumor in the breast, respectively. We optimized the conditions for CRISPR/Cas9 screen for both of the cell lines. The optimization included the identification of accurate doubling time of the cell lines, spinfection conditions such as cell density and polybrene concentration and appropriate puromycin/blasticidin concentrations to selected the infected cells.

本项目的目的（第1部分）是确定预测临床标本中乳腺导管原位癌（DCIS）进展为浸润性导管癌（IDC）的基因特征。从236份标本的中期分析中，我们证实了主要的基因突变，如PIK 3CA、AKT 1和TP 53，与之前在TCGA数据集中报告的一致。2020年，我们从临床测序中收集了更多数据，该队列现在总共包括313份样本（252份来自IDC，61份来自DCIS）。因此，我们正在更新整个队列的分析，并试图确定负责从DCIS进展到IDC的候选基因，即使在不太频繁突变的基因中。本项目（第2部分）的目的是描述模型中乳腺癌进展的分子机制。我们获得了细胞系如MCF 10A和MCF 10 DCIS，分别作为乳腺中正常上皮和DCIS肿瘤的模型。我们优化了两种细胞系的CRISPR/Cas9筛选条件。优化包括确定准确的细胞系倍增时间，spinfection条件，如细胞密度和聚凝胺浓度和适当的嘌呤霉素/杀稻瘟菌素浓度，以选择感染的细胞。