A Network Approach to Identify Biomarkers of Differential Chemotherapy Response Using Patient-Derived Xenografts of Triple-Negative Breast Cancer

Abstract

SummaryTriple negative breast cancer (TNBC) is a highly heterogeneous set of diseases that has, until recently, lacked any FDA-approved, molecularly targeted therapeutics. Thus, systemic chemotherapy regimens remain the standard of care for many. Unfortunately, even combination chemotherapy is ineffective for many TNBC patients, and side-effects can be severe or lethal. Identification of predictive biomarkers for chemotherapy response would allow for the prospective selection of responsive patients, thereby maximizing efficacy and minimizing unwanted toxicities. Here, we leverage a cohort of TNBC PDX models with responses to single-agent docetaxel or carboplatin to identify biomarkers predictive for differential response to these two drugs. To demonstrate their ability to function as a preclinical cohort, PDX were molecularly characterized using whole-exome DNA sequencing, RNAseq transcriptomics, and mass spectrometry-based total proteomics to show proteogenomic consistency with TCGA and CPTAC clinical samples. Focusing first on the transcriptome, we describe a network-based computational approach to identify candidate epithelial and stromal biomarkers of response to carboplatin (MSI1, TMSB15A, ARHGDIB, GGT1, SV2A, SEC14L2, SERPINI1, ADAMTS20, DGKQ) and docetaxel (ITGA7, MAGED4, CERS1, ST8SIA2, KIF24, PARPBP). Biomarker panels are predictive in PDX expression datasets (RNAseq and Affymetrix) for both taxane (docetaxel or paclitaxel) and platinum-based (carboplatin or cisplatin) response, thereby demonstrating both cross expression platform and cross drug class robustness. Biomarker panels were also predictive in clinical datasets with response to cisplatin or paclitaxel, thus demonstrating translational potential of PDX-based preclinical trials. This network-based approach is highly adaptable and can be used to evaluate biomarkers of response to other agents.

In Vivo Modeling of Human Breast Cancer Using Cell Line and Patient-Derived Xenografts

“…Only ~ 10% of PDX showed enhanced response over the best single agent, with ~ 10 showing a worse response to combination vs. the best single agent. Clinically, the combination also showed a higher response rate than historical single agent efficacy Trial: CADENCE-NCT02547987 Trial: NCT02124902 [ 19 ] STAT3 TTI-101 Tvardi Therapeutics In vivo results in breast cancer xenografts indicated efficacy, in combination with docetaxel for TNBC. The clinical trial includes breast cancer and is ongoing Trial: NCT03195699 [ 209 , 210 ] Microtubule Polymerization and PARP1/2 Eribulin + Talazoparib Eribulin – Eisai Co Talazoparib – Pfizer PDX-derived organoids showed response that was confirmed in a patient-matched PDX.…”

“…At the RNA level, early studies made use of gene expression arrays, which demonstrated consistency of gene expression patterns between PDX and matching primary tumor, in most cases, as well as excellent stability of gene expression across transplant generations [ 3 , 7 , 13 , 14 , 16 – 19 , 22 – 27 , 76 ]. More recent studies make use of RNAseq technology.…”

“…Here again, it is preferable to obtain data from both the PDX and the primary tumor from which it was derived for direct comparison of the fidelity of gene expression patterns between the two. However, generalized comparison of RNAseq gene expression patterns between PDX and patient tumors show remarkable consistency [ 15 – 17 , 19 ].…”

“…Human vs. mouse peptide origin can be discerned using differences in peptide mass based on amino acid composition using computational tools such as gpGrouper, which was designed for this purpose [ 198 ]. Patterns of protein expression in PDX compare favorably with breast cancers characterized by the CPTAC program [ 19 ].…”

Multiplexed triage of candidate biomarkers in plasma using internal standard triggered-parallel reaction monitoring mass spectrometry

“…Follow-up studies will be required to determine if the PDX model serves as a viable conduit for discovering clinically translatable biomarkers. Patient-derived xenografts of human cancer have emerged as powerful tools for clinical/translational science due to their recapitulation of many aspects of the biology of tumors derived from patients, including treatment responses, genomic mutation and copy number alterations, as well as RNA and protein expression [41][42][43] . This high degree of biological consistency with clinical samples may make PDX-bearing mice a potential discovery platform for identification of tumor-derived proteins in plasma since human sequences can be distinguished from mouse peptides using mass spectrometry 44,45 .…”