Dataset Information

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer.

ABSTRACT: Background:Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown. Methods:We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient-derived xenografts (PDXs) using core needle biopsies. Chemotherapy response was assessed at surgery. Results:Recurrent "targetable" alterations were not enriched in patients without pathologic complete response (pCR); however, upregulation of steroid receptor signaling and lower pCR rates (16.7%, 1/6) were observed in triple-negative breast cancer (TNBC) patients with luminal androgen receptor (LAR) vs basal subtypes (60.0%, 21/35). Within TNBC, TP53 mutation frequency (75.6%, 31/41) did not differ comparing basal (74.3%, 26/35) and LAR (83.3%, 5/6); however, TP53 stop-gain mutations were more common in basal (22.9%, 8/35) vs LAR (0.0%, 0/6), which was confirmed in The Cancer Genome Atlas and British Columbia data sets. In luminal B tumors, Ki-67 responses were observed in tumors that harbored mutations conferring endocrine resistance ( p53, AKT, and IKBKE ). PDX take rate (27.4%, 31/113) varied according to tumor subtype, and in a patient with progression on NAC, sequencing data informed drug selection (olaparib) with in vivo antitumor activity observed in the primary and resistant (postchemotherapy) PDXs. Conclusions:In this study, we demonstrate the feasibility of tumor sequencing and PDX generation in the NAC setting. "Targetable" alterations were not enriched in chemotherapy-resistant tumors; however, prioritization of drug testing based on sequence data may accelerate drug development.

SUBMITTER: Goetz MP

PROVIDER: S-EPMC5408989 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer.

Goetz Matthew P MP Kalari Krishna R KR Suman Vera J VJ Moyer Ann M AM Yu Jia J Visscher Daniel W DW Dockter Travis J TJ Vedell Peter T PT Sinnwell Jason P JP Tang Xiaojia X Thompson Kevin J KJ McLaughlin Sarah A SA Moreno-Aspitia Alvaro A Copland John A JA Northfelt Donald W DW Gray Richard J RJ Hunt Katie K Conners Amy A Sicotte Hugues H Eckel-Passow Jeanette E JE Kocher Jean-Pierre JP Ingle James N JN Ellingson Marissa S MS McDonough Michelle M Wieben Eric D ED Weinshilboum Richard R Wang Liewei L Boughey Judy C JC

Journal of the National Cancer Institute 20170701 7

<h4>Background</h4>Breast cancer patients with residual disease after neoadjuvant chemotherapy (NAC) have increased recurrence risk. Molecular characterization, knowledge of NAC response, and simultaneous generation of patient-derived xenografts (PDXs) may accelerate drug development. However, the feasibility of this approach is unknown.<h4>Methods</h4>We conducted a prospective study of 140 breast cancer patients treated with NAC and performed tumor and germline sequencing and generated patient ...[more]

PMID: 28376176

Similar Datasets

Project description:Patient-derived xenograft (PDX) models have been recognized as being more suitable for predicting therapeutic efficacy than cell-culture models. However, there are several limitations in applying PDX models in preclinical studies, including their availability-especially for cancers such as gastric cancer-that are not frequently encountered in Western countries. In addition, the differences in morphology between primary, PDX, and tumor cell line-derived xenograft (CDX) models have not been well established. In this study, we aimed to establish a series of gastric cancer PDXs and cell-lines from a relatively large number of gastric cancer patients. We also investigated the clinicopathological factors associated with the establishment of PDX and CDX models, and compared the histology between the primary tumor, PDX, and CDX that originated from the same patient. We engrafted 232 gastric cancer tissues into immune-deficient mice subcutaneously and successfully established 35 gastric cancer PDX models (15.1% success rate). Differentiated type adenocarcinomas (DAs, 19.4%) were more effectively established than poorly differentiated type adenocarcinomas (PDAs, 10.8%). For establishing CDXs, the success rate was less influenced by histological differentiation grade (DA vs. PDA, 12.1% vs. 9.8%). In addition, concordance of histological differentiation grade between primary tumors and PDXs was significant (p < 0.01), while concordance between primary tumors and CDXs was not. Among clinicopathological factors investigated, pathological nodal metastasis status (pN) was significantly associated with the success rate of PDX establishment. Although establishing cell lines from ascites fluid was more efficient (41.2%, 7/17) than resected tissues, it should be noted that all CDXs from ascites fluid had the PDA phenotype. In conclusion, we established 35 PDX and 32 CDX models from 249 gastric cancer patients; among them, 21 PDX/CDX models were established from the same patients. Our findings may provide helpful insights for establishing PDX and CDX models not only from gastric but from other cancer types, as well as select preclinical models for developing new therapeutics.

Project description:Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the "peptide-to-protein" inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0-30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0-30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

Project description:Brain metastases are an increasing burden among breast cancer patients, particularly for those with HER2+ and triple negative (TN) subtypes. Mechanistic insight into the pathophysiology of brain metastases and preclinical validation of therapies has relied almost exclusively on intracardiac injection of brain-homing cells derived from highly aggressive TN MDA-MB-231 and HER2+ BT474 breast cancer cell lines. Yet, these well characterized models are far from representing the tumor heterogeneity observed clinically and, due to their fast progression in vivo, their suitability to validate therapies for established brain metastasis remains limited. The goal of this study was to develop and characterize novel human brain metastasis breast cancer patient-derived xenografts (BM-PDXs) to study the biology of brain metastasis and to serve as tools for testing novel therapeutic approaches. We obtained freshly resected brain metastases from consenting donors with breast cancer. Tissue was immediately implanted in the mammary fat pad of female immunocompromised mice and expanded as BM-PDXs. Brain metastases from 3/4 (75%) TN, 1/1 (100%) estrogen receptor positive (ER+), and 5/9 (55.5%) HER2+ clinical subtypes were established as transplantable BM-PDXs. To facilitate tracking of metastatic dissemination using BM-PDXs, we labeled PDX-dissociated cells with EGFP-luciferase followed by reimplantation in mice, and generated a BM-derived cell line (F2-7). Immunohistologic analyses demonstrated that parental and labeled BM-PDXs retained expression of critical clinical markers such as ER, progesterone receptor, epidermal growth factor receptor, HER2, and the basal cell marker cytokeratin 5. Similarly, RNA sequencing analysis showed clustering of parental, labeled BM-PDXs and their corresponding cell line derivative. Intracardiac injection of dissociated cells from BM-E22-1, resulted in magnetic resonance imaging-detectable macrometastases in 4/8 (50%) and micrometastases (8/8) (100%) mice, suggesting that BM-PDXs remain capable of colonizing the brain at high frequencies. Brain metastases developed 8-12?weeks after ic injection, located to the brain parenchyma, grew around blood vessels, and elicited astroglia activation characteristic of breast cancer brain metastasis. These novel BM-PDXs represent heterogeneous and clinically relevant models to study mechanisms of brain metastatic colonization, with the added benefit of a slower progression rate that makes them suitable for preclinical testing of drugs in therapeutic settings.

Dataset Information

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer.

Publications

Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets