Integrative Genomic Analysis of Gemcitabine Resistance in Pancreatic Cancer by Patient-derived Xenograft Models
Integrative Genomic Analysis of Gemcitabine Resistance in Pancreatic Cancer by Patient-derived Xenograft Models
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DOI：
10.1158/1078-0432.ccr-19-3975
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发表时间：
2021-06-15
影响因子：
11.5
通讯作者：
Gu, Jin
中科院分区：
文献类型：
--
作者：
Yang, Gang;Guan, Wenfang;Gu, Jin
目的：吉西他滨是胰腺癌最常用的药物。然而，频繁发生的耐药性的分子特征和机制仍不清楚。这项工作的目的是探索吉西他滨耐药的分子特征，并确定候选的生物标志物和组合靶点的treatment.Experimental Design：在这项研究中，我们建立了66患者来源的异种移植（PDXs）的基础上，临床胰腺癌标本和治疗吉西他滨。我们生成了吉西他滨治疗前后15个药物敏感和13个耐药PDX的多组学数据（包括全外显子组测序、RNA测序、miRNA测序和DNA甲基化阵列）。我们进行了综合计算分析，以确定与吉西他滨内在和获得性耐药相关的分子网络。结果：综合多组学分析和功能实验结果显示，MRPSS和GSPT 1对胰腺癌细胞的增殖有较强的影响，CD 55和DHTKDI对胰腺癌细胞吉西他滨耐药有重要作用。此外，我们发现miR-135 a-5 p与胰腺癌患者的预后显著相关，可能是预测吉西他滨疗效的候选生物标志物。比较治疗前后的分子特征，我们发现PI 3 K-Akt、p53和缺氧诱导因子-1通路在多个患者中发生了显著改变，为降低获得性耐药提供了候选靶通路。这项综合性基因组研究系统地研究了胰腺癌化疗耐药的预测标志物和分子机制，并为克服化疗耐药提供了潜在的治疗靶点。吉西他滨耐药。
Purpose: Gemcitabine is most commonly used for pancreatic cancer. However, the molecular features and mechanisms of the frequently occurring resistance remain unclear. This work aims at exploring the molecular features of gemcitabine resistance and identifying candidate biomarkers and combinatorial targets for the treatment.Experimental Design: In this study, we established 66 patient-derived xenografts (PDXs) on the basis of clinical pancreatic cancer specimens and treated them with gemcitabine. We generated multiomics data (including whole-exome sequencing, RNA sequencing, miRNA sequencing, and DNA methylation array) of 15 drug-sensitive and 13 -resistant PDXs before and after the gemcitabine treatment. We performed integrative computational analysis to identify the molecular networks related to gemcitabine intrinsic and acquired resistance. Then, short hairpin RNA-based high-content screening was implemented to validate the function of the deregulated genes.Results: The comprehensive multiomics analysis and functional experiment revealed that MRPSS and GSPT1 had strong effects on cell proliferation, and CD55 and DHTKDI contributed to gemcitabine resistance in pancreatic cancer cells. Moreover, we found miR-135a-5p was significantly associated with the prognosis of patients with pancreatic cancer and could be a candidate biomarker to predict gemcitabine response. Comparing the molecular features before and after the treatment, we found that PI3K-Akt, p53, and hypoxia-inducible factor-1 pathways were significantly altered in multiple patients, providing candidate target pathways for reducing the acquired resistance.Conclusions: This integrative genomic study systematically investigated the predictive markers and molecular mechanisms of chemoresistance in pancreatic cancer and provides potential therapy targets for overcoming gemcitabine resistance.