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胰腺癌中海泽米滨耐药的研究进展:与患者来源异种移植中代谢重编程和 TP53 致病性的关联。

Insights into gemcitabine resistance in pancreatic cancer: association with metabolic reprogramming and TP53 pathogenicity in patient derived xenografts.

机构信息

Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA.

Leidos Biomedical Research, Inc, Frederick National Laboratory for Cancer Research, Frederick, MD, 21704, USA.

出版信息

J Transl Med. 2024 Aug 5;22(1):733. doi: 10.1186/s12967-024-05528-6.

DOI:10.1186/s12967-024-05528-6
PMID:39103840
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11301937/
Abstract

BACKGROUND

With poor prognosis and high mortality, pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. Standard of care therapies for PDAC have included gemcitabine for the past three decades, although resistance often develops within weeks of chemotherapy initiation through an array of possible mechanisms.

METHODS

We reanalyzed publicly available RNA-seq gene expression profiles of 28 PDAC patient-derived xenograft (PDX) models before and after a 21-day gemcitabine treatment using our validated analysis pipeline to identify molecular markers of intrinsic and acquired resistance.

RESULTS

Using normalized RNA-seq quantification measurements, we first identified oxidative phosphorylation and interferon alpha pathways as the two most enriched cancer hallmark gene sets in the baseline gene expression profile associated with intrinsic gemcitabine resistance and sensitivity, respectively. Furthermore, we discovered strong correlations between drug-induced expression changes in glycolysis and oxidative phosphorylation genes and response to gemcitabine, which suggests that these pathways may be associated with acquired gemcitabine resistance mechanisms. Thus, we developed prediction models using baseline gene expression profiles in those pathways and validated them in another dataset of 12 PDAC models from Novartis. We also developed prediction models based on drug-induced expression changes in genes from the Molecular Signatures Database (MSigDB)'s curated 50 cancer hallmark gene sets. Finally, pathogenic TP53 mutations correlated with treatment resistance.

CONCLUSION

Our results demonstrate that concurrent upregulation of both glycolysis and oxidative phosphorylation pathways occurs in vivo in PDAC PDXs following gemcitabine treatment and that pathogenic TP53 status had association with gemcitabine resistance in these models. Our findings may elucidate the molecular basis for gemcitabine resistance and provide insights for effective drug combination in PDAC chemotherapy.

摘要

背景

胰腺癌(PDAC)预后差、死亡率高,是致死率最高的恶性肿瘤之一。在过去的三十年中,PDAC 的标准治疗方法包括吉西他滨,但由于多种可能的机制,化疗开始后数周内通常会产生耐药性。

方法

我们使用经过验证的分析流程,重新分析了 28 个 PDAC 患者来源的异种移植(PDX)模型在接受 21 天吉西他滨治疗前后的公开可用 RNA-seq 基因表达谱,以鉴定内在和获得性耐药的分子标志物。

结果

使用标准化 RNA-seq 定量测量值,我们首先确定氧化磷酸化和干扰素 α 途径是与内在吉西他滨耐药性和敏感性相关的基线基因表达谱中两个最丰富的癌症标志性基因集。此外,我们发现糖酵解和氧化磷酸化基因的药物诱导表达变化与吉西他滨反应之间存在强烈相关性,这表明这些途径可能与获得性吉西他滨耐药机制有关。因此,我们使用这些途径的基线基因表达谱开发了预测模型,并在诺华公司的另一个包含 12 个 PDAC 模型的数据集进行了验证。我们还基于来自 MSigDB 中经过验证的 50 个癌症标志性基因集的基因的药物诱导表达变化开发了预测模型。最后,致病性 TP53 突变与治疗抵抗相关。

结论

我们的结果表明,吉西他滨治疗后,PDAC PDX 中这两条途径同时上调,致病性 TP53 状态与这些模型中的吉西他滨耐药性有关。我们的发现可能阐明了吉西他滨耐药的分子基础,并为 PDAC 化疗中的有效药物联合提供了思路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/93e3d46c0461/12967_2024_5528_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/3f1f0e12230d/12967_2024_5528_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/ecafa8462bc6/12967_2024_5528_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/00f85f1611e0/12967_2024_5528_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/59e913d46f75/12967_2024_5528_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/93e3d46c0461/12967_2024_5528_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/3f1f0e12230d/12967_2024_5528_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/ecafa8462bc6/12967_2024_5528_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/00f85f1611e0/12967_2024_5528_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/59e913d46f75/12967_2024_5528_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c7c/11301937/93e3d46c0461/12967_2024_5528_Fig5_HTML.jpg

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