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DNA methylation data of PAC PDX models before Gemcitabine treatment

ABSTRACT: Purpose: Gemcitabine is most commonly used for pancreatic cancer (PC). However, the molecular features and mechanisms of the frequently occurred 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 present study, we established 66 patient-derived xenografts (PDXs) based on clinical PC specimens and treated them with gemcitabine. We generated multi-omics data (including whole exome-seq, RNA-seq, miRNA-seq 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 required resistance. Then, shRNA-based high-content screening was implemented to validate the function of the de-regulated genes. Results: The comprehensive multi-omics analysis and functional experiment revealed that MRPS5 and GSPT1 had strong effects on cell proliferation, and CD55 and DHTKD1 contributed to gemcitabine resistance in PC cells. Moreover, we found miR-135a-5p was significantly associated with the prognosis of PC patients 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, HIF-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 provide potential therapy targets for overcoming gemcitabine resistance.

ORGANISM(S): Homo sapiens

PROVIDER: GSE165687 | GEO | 2021/02/09

REPOSITORIES: GEO

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Project description:Breast cancer is a heterogeneous collection of disease arising from the breast with distinct molecular and phenotypic features. Certain subsets of patients have tumors that are particularly difficult-to-treat, which include triple-negative breast cancer (TNBC), metastatic/recurrent disease and rare histological variants. To delineate the underlying biology and identify therapeutic candidates for these patients, a series of 37 breast cancer patient-derived xenografts (PDX) from both chemo-naïve and pre-treated specimens was generated from 81 transplant attempts. Whole-genome and transcriptome sequencing revealed marked fidelity of the molecular landscape for the majority of PDXs in comparison to parental tumors. Reverse-phase protein array analysis of PDXs further identified potential therapeutic targets. Metastatic potential varied between PDXs, where low-penetrance lung micrometastases was the most common pattern of dissemination and observed in 34.5% of models. Three PDXs recapitulated the metastatic localization seen in the corresponding patients, including two lines with high-frequency metastases to multiple vital organ systems, while another PDX displayed tropism to the skull-base. Chemosensitivity profiling was performed in vivo with standard-of-care agents (doxorubicin, cisplatin, gemcitabine or paclitaxel), where multi-drug chemoresistance was found in 60.0% of PDXs and 64.7% of responses were concordant with pre-engraftment responses observed in the patient. Consolidating chemogenomic data identified potentially actionable features in 97.2% of PDXs, and marked regressions were seen in vivo when a subset of these underwent proof-of-concept functional studies. This included FGFR inhibitor sensitivity in a FGFR1-amplified lobular carcinoma, mTOR inhibitor sensitivity in a recurrent neuroendocrine breast cancer with proteomic evidence of mTOR/PI3K activation, and platinum sensitivity in a TNBC with BRCA1 germline mutation predicted as benign. Together, this clinically-annotated PDX library with comprehensive molecular and phenotypic profiling serves as a resource for both discovery and validation preclinical studies on difficult-to-treat breast tumors.

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DNA methylation data of PAC PDX models before Gemcitabine treatment

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