Integrated Analysis of Transcriptome in Cancer Patient-Derived Xenografts

<div><p>Patient-derived xenograft (PDX) tumor model is a powerful technology in evaluating anti-cancer drugs and facilitating personalized medicines. Multiple research centers and commercial companies have put huge efforts into building PDX mouse models. However, PDX models have not been widely available and their molecular features have not been systematically characterized. In this study, we provided a comprehensive survey of PDX transcriptome by integrating analysis of 58 patients involving 8 different tumors. The median correlation coefficient between patients and xenografts is 0.94, which is higher than that between patients and cell line panel or between patients with the same tumor. Major differential gene expressions in PDX occur in the engraftment of human tumor tissue into mice, while gene expressions are relatively stable over passages. 48 genes are frequently differentially expressed in PDX mice of multiple cancers. They are enriched in extracellular matrix and immune response, and some are reported as targets for anticancer drugs. A simulation study showed that expression change between PDX and patient tumor (6%) would result in acceptable change in drug sensitivity (3%). Our findings demonstrate that PDX mice represent the gene-expression and drug-response features of primary tumors effectively, and it is recommended to monitoring the overall expression profiles and drug target genes in clinical application.</p></div

GEO expression datasets used in this study.

<p>GEO expression datasets used in this study.</p

Common differentially expressed genes in PDX mice and their interacting drugs.

<p>(A) Expression heatmap of 48 genes, which were differentially expressed in more than half cancer patients and more than two cancer types. (B) Number of differentially expressed genes that have interaction with anticancer drugs.</p

Expression correlation analysis for human cancer patients and PDX mouse models.

<p>(A) Heatmap showing the Spearman's rank correlation coefficient (SRCC) of 8 cancers in 9 GEO datasets. F0 indicates cancer patient biopsy, F1 is the 1^st passage PDX, F2 is the 2^nd passage PDX, …, F? is the PDX whose passage is unclear. (B) Boxplot showing the distribution of SRCC. The red line is the mean minus 1.5 standard deviations. (C) Comparison of the similarity between “human tumor VS. xenograft” (blue) and “xenograft VS. xenograft” (red).</p

Differentially expressed genes in multiple cancer datasets.

<p>(A). Genes in “human tumor VS. xenograft” comparisons in five datasets. (B) Genes in “human tumor VS. xenograft” comparisons, only using three datasets in the same platform GPL570. (C) Genes in “xenograft VS. xenograft” comparisons.</p

Comparison of human cancer patients (F0) and cancer models from three sources: 1) Mouse xenograft that’s derived from the same patient (“red”); 2) Cancer cell lines in GDSC dataset (“green”); 3) Other human solid tumors in GSE2109 dataset (“blue”).

<p>The Y-axis is the maximum correlation coefficient of gene expression profiles between F0 and cancer models.</p

Functional enrichment of differentially expressed genes in “human tumor VS. xenograft”.

<p>^a) The percentage that this function was significantly enriched (Benjamini P-value < 0.01) when analyzing differential gene sets in each “human tumor VS. xenograft” pair.</p><p>Functional enrichment of differentially expressed genes in “human tumor VS. xenograft”.</p

Effect of gene expression change on predicted cisplatin IC50.

<p>SRCC between simulated and real expression data was used to measure expression change. IC50 of simulated datasets were predicted by a ridge regression model. The relative “SRCC_IC50” for simulated datasets were used to measure the effect of expression change on drug sensitivity.</p

sj-docx-1-tam-10.1177_17588359221128356 – Supplemental material for Efficacy of neoadjuvant docetaxel + cisplatin chemo-hormonal therapy versus docetaxel chemo-hormonal therapy in patients with locally advanced prostate cancer with germline DNA damage repair gene alterations

Supplemental material, sj-docx-1-tam-10.1177_17588359221128356 for Efficacy of neoadjuvant docetaxel + cisplatin chemo-hormonal therapy versus docetaxel chemo-hormonal therapy in patients with locally advanced prostate cancer with germline DNA damage repair gene alterations by Chenfei Chi, Jiazhou Liu, Liancheng Fan, Yinjie Zhu, Yanqing Wang, Jianjun Sha, Yiran Huang, Baijun Dong, Jiahua Pan and Wei Xue in Therapeutic Advances in Medical Oncology</p