Separation of breast cancer and organ microenvironment transcriptomes in metastases

Abstract

Background The seed and soil hypothesis was proposed over a century ago to describe why cancer cells (seeds) grow in certain organs (soil). Since then, the genetic properties that define the cancer cells have been heavily investigated; however, genomic mediators within the organ microenvironment that mediate successful metastatic growth are less understood. These studies sought to identify cancer- and organ-specific genomic programs that mediate metastasis. Methods In these studies, a set of 14 human breast cancer patient-derived xenograft (PDX) metastasis models was developed and then tested for metastatic tropism with two approaches: spontaneous metastases from mammary tumors and intravenous injection of PDX cells. The transcriptomes of the cancer cells when growing as tumors or metastases were separated from the transcriptomes of the microenvironment via species-specific separation of the genomes. Drug treatment of PDX spheroids was performed to determine if genes activated in metastases may identify targetable mediators of viability. Results The experimental approaches that generated metastases in PDX models were identified. RNA sequencing of 134 tumors, metastases, and normal non-metastatic organs identified cancer- and organ-specific genomic properties that mediated metastasis. A common genomic response of the liver microenvironment was found to occur in reaction to the invading PDX cells. Genes within the cancer cells were found to be either transiently regulated by the microenvironment or permanently altered due to clonal selection of metastatic sublines. Gene Set Enrichment Analyses identified more than 400 gene signatures that were commonly activated in metastases across basal-like PDXs. A Src signaling signature was found to be extensively upregulated in metastases, and Src inhibitors were found to be cytotoxic to PDX spheroids. Conclusions These studies identified that during the growth of breast cancer metastases, there were genomic changes that occurred within both the cancer cells and the organ microenvironment. We hypothesize that pathways upregulated in metastases are mediators of viability and that simultaneously targeting changes within different cancer cell pathways and/or different tissue compartments may be needed for inhibition of disease progression. Electronic supplementary material The online version of this article (10.1186/s13058-019-1123-2) contains supplementary material, which is available to authorized users.

Novel Breast Cancer Brain Metastasis Patient-Derived Orthotopic Xenograft Model for Preclinical Studies

“…Alzubi et al demonstrated RNA sequencing data of human breast cancer tumors grown as PDXs at different sites in mouse and separated it into human (cancer) and mouse (microenvironment) transcriptomic datasets. They showed that the cancer transcriptome within PDX was affected by the microenvironment of the tumor implantation site [49]. Rashid et al utilized a syngeneic immunocompetent mouse model to show transcriptome differences between breast cancer tumors grown in MFP and subcutaneously [50].…”

Identification of synergistic drug combinations using breast cancer patient-derived xenografts

“…Analysis of previous RNA-sequencing data 42 revealed that about half of the genes encoding human targets of the 176 drugs are highly expressed in TNBC PDXs (Fig. 1b).…”

“…els of EGFR and BIRC5 were assessed using a PDX RNA-sequencing dataset 42 , as well as RNA sequencing data from two publicly available breast cancer cell line gene expression databases: the Harvard Medical School (HMS) Library of Integrated Network-based Cellular Signatures (LINCS) Breast Cancer Profiling Project (http://lincs. hms.harvard.edu/db/datasets/20348/) and the Broad Institute Cancer Cell Line Encyclopedia (CCLE) (https:// portals.broadinstitute.org/ccle).…”

Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines

“…Consequently, the main application of PDX systems is to understand the molecular mechanisms of human cancers within controlled in vivo conditions. With the wide adoption of sequencing technologies, sequencing of PDX samples is now a standard (Turner et al 2018;Alzubi et al 2019;Girotti et al 2016;Li et al 2013).…”

“…To address the effect of mouse read removal in PDX sequencing data, we evaluated three strategies for preprocessing PDX Hi-C data: Direct, Xenome, and Combined. Using different library preparation strategies, we generated two deeply sequenced Hi-C datasets of a carboplatin-resistant UCD52 cell line (Turner et al 2018;Alzubi et al 2019). We further created three in silico PDX Hi-C datasets with either 10% or 30% of mouse read contamination, mirroring the percent of mouse reads observed in our experimental Hi-C data.…”