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. 2020 Sep 10;15(9):e0238594.
doi: 10.1371/journal.pone.0238594. eCollection 2020.

High accuracy gene expression profiling of sorted cell subpopulations from breast cancer PDX model tissue

Warren Porter  1 , Eileen Snowden  1 , Friedrich Hahn  1 , Mitchell Ferguson  1 , Frances Tong  1 , W Shannon Dillmore  1 , Rainer Blaesius  1
Affiliations

High accuracy gene expression profiling of sorted cell subpopulations from breast cancer PDX model tissue

Warren Porter et al. PLoS One. .

Abstract

Intratumor Heterogeneity (ITH) is a functionally important property of tumor tissue and may be involved in drug resistance mechanisms. Although descriptions of ITH can be traced back to very early reports about cancer tissue, mechanistic investigations are still limited by the precision of analysis methods and access to relevant tissue sources. PDX models have provided a reproducible source of tissue with at least a partial representation of naturally occurring ITH. We investigated the properties of phenotypically distinct cell populations by Fluorescence activated cell sorting (FACS) tissue derived cells from multiple tumors from a triple negative breast cancer patient derived xenograft (PDX) model. We subsequently subjected each population to in depth gene expression analysis. Our findings suggest that process related gene expression changes (caused by tissue dissociation and FACS sorting) are restricted to Immediate Early Genes (IEGs). This allowed us to discover highly reproducible gene expression profiles of distinct cellular compartments identifiable by cell surface markers in this particular tumor model. Within the context of data from a previously published model our work suggests that gene expression profiles associated with hypoxia, stemness and drug resistance may reside in tumor subpopulations predictably growing in PDX models. This approach provides a novel opportunity for prospective mechanistic studies of ITH.

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Conflict of interest statement

WP, ES, FT, WSD and RB are employees of BD Technologies and Innovation and FH and MF were employees of BD Technologies and Innovation at the time the work was carried out. The funder had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Schematic of experimental setup.
Tumor tissue was extracted and gene expression profiles from 8 different samples per tumor were generated from 4 mice (i.e. total of 8x4 = 32 RNASeq profiles) of the same breast cancer PDX model, BRC13. The left part addressed the sample handling aspects of the procedure while the samples marked by the grey box were generated to investigate ITH present in this model. See text for details.
Fig 2
Fig 2. Pairwise comparisons between gene expression profiles generated through bulk RNASeq for 4 different conditions.
0h time point represents cells immediately after dissociation; 3h time point represents cells left undisturbed for 3 hours after dissociation while sorted cells underwent flow sorting which generally took up to 3 hours. Volcano plots show the log2 fold-change (x-axis) and the statistical significance as–log(FDR) (y-axis). Lines indicate the cutoff values chosen (4-fold and FDR<0.05). FDR values were calculated across the entire data set.
Fig 3
Fig 3. Volcano plots of DEGs identified between tumor subpopulations sorted with either CD49f (left) or CD133 (right).
Cutoff values shown (black lines, for illustration only) are >4-fold and FDR <0.05.
Fig 4
Fig 4
Flow cytometric analysis of sorted populations using CD49f and CD133 (a) and correlations between DEGs identified by using either CD49f or CD133 as sorting criteria (b and c, FDR<0.05).
Fig 5
Fig 5. Gene expression signatures identified in BRC12 and BRC13 tumor cell subpopulations.
A hypoxia gene signature composed of 3 published signatures [–32] was found in BRC12 CD184lo and BRC13 CD49flo subpopulations (a) while a proliferative gene signature identified in histologically normal breast tissue from cancer patients [41] was present in BRC12 CD184hi and BRC13 CD133hi subpopulations (b). Genes with lowest FDR and highest x-fold values are labeled in volcano plots and marked with arrows in heatmaps, respectively.
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Publication types

Grants and funding

This study was completely funded by BD Technologies and Innovation. The funder provided support in the form of salaries for authors WP, ES, FT, WSD, FH, MF and RB, but did not have any additional role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.