Post-treatment tumor gene expression signatures are more predictive of treatment outcomes than baseline signatures in breast cancer

Lee, Soo‐Chin; Xu, Xin; Chng, Wee‐Joo; Watson, Mark A.; Lim, Yi-Wan; Wong, Chin‐Ho; Iau, Philip; Sukri, Norita; Lim, Siak Piang; Yap, Hui-Kim; Tan, Patrick; Guo, Jiayi; Chuah, Benjamin; McLeod, Howard L.; Goh, Boon-Cher

doi:10.1097/fpc.0b013e328330a39f

Cited by 13 publications

(7 citation statements)

References 24 publications

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“…One to two core biopsies from the primary breast tumor were taken each at baseline and approximately 3 weeks after the first cycle of chemotherapy, snap frozen in liquid nitrogen and stored at -80°C until analysis. Only RNA was extracted from the first tumor core for gene expression analysis, the data of which has been reported previously [ 4 , 7 ], while both DNA and RNA was extracted from the second tumor core if available, for DNA mutational analysis and other RNA expression work. Bidimensional breast tumor assessments were performed at every cycle.…”

Section: Methodsmentioning

confidence: 99%

High-Throughput Mutation Profiling Changes before and 3 Weeks after Chemotherapy in Newly Diagnosed Breast Cancer Patients

et al. 2015

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BackgroundChanges in tumor DNA mutation status during chemotherapy can provide insights into tumor biology and drug resistance. The purpose of this study is to analyse the presence or absence of mutations in cancer-related genes using baseline breast tumor samples and those obtained after exposure to one cycle of chemotherapy to determine if any differences exist, and to correlate these differences with clinical and pathological features.MethodsPaired breast tumor core biopsies obtained pre- and post-first cycle doxorubicin (n = 18) or docetaxel (n = 22) in treatment-naïve breast cancer patients were analysed for 238 mutations in 19 cancer-related genes by the Sequenom Oncocarta assay.ResultsMedian age of patients was 48 years (range 32–64); 55% had estrogen receptor-positive tumors, and 60% had tumor reduction ≥25% after cycle 1. Mutations were detected in 10/40 (25%) pre-treatment and 11/40 (28%) post-treatment samples. Four mutation pattern categories were identified based on tumor mutation status pre- → post-treatment: wildtype (WT)→WT, n = 24; mutant (MT)→MT, n = 5; MT→WT, n = 5; WT→MT, n = 6. Overall, the majority of tumors were WT at baseline (30/40, 75%), of which 6/30 (20%) acquired new mutations after chemotherapy. Pre-treatment mutations were predominantly in PIK3CA (8/10, 80%), while post-treatment mutations were distributed in PIK3CA, EGFR, PDGFRA, ABL1 and MET. All 6 WT→MT cases were treated with docetaxel. Higher mutant allele frequency in baseline MT tumors (n = 10; PIK3CA mutations n = 8) correlated with less tumor reduction after cycle 1 chemotherapy (R = -0.667, p = 0.035). No other associations were observed between mutation pattern category with treatment, clinicopathological features, and tumor response or survival.ConclusionTumor mutational profiles can change as quickly as after one cycle of chemotherapy in breast cancer. Understanding of these changes can provide insights on potential therapeutic options in residual resistant tumors.Trial RegistrationClinicalTrials.gov NCT00212082

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Section: Methodsmentioning

confidence: 99%

High-Throughput Mutation Profiling Changes before and 3 Weeks after Chemotherapy in Newly Diagnosed Breast Cancer Patients

et al. 2015

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“…Lee, et al demonstrated that postchemotherapy tumor gene signatures outperforms baseline signatures and clinical predictors in predicting for pathological response and progression-free survival [42], although these investigators collected posttreatment breast tumors 3 weeks after chemotherapy, not at the time of progressive disease as in our study. Our data is consistent with the aforementioned study [42] that comparing postchemotherapy and prechemotherapy gene expression signatures might be a feasible approach to the identification of predictive signatures. Also, our data provides the first genomic evidence in clinical samples supporting a conventional model for the emergence of acquired resistance whereby resistance emerges through a selective, clonal outgrowth of small populations of pre-existing, chemoresistant tumor cells [3].…”

Section: Discussionmentioning

confidence: 98%

“…No prior studies have explored acquired resistance using genome-wide analysis of clinical samples, although 2 prior studies evaluated the gene expression pattern in residual disease after the completion of neoadjuvant chemotherapy [40], [41]. Lee, et al demonstrated that postchemotherapy tumor gene signatures outperforms baseline signatures and clinical predictors in predicting for pathological response and progression-free survival [42], although these investigators collected posttreatment breast tumors 3 weeks after chemotherapy, not at the time of progressive disease as in our study. Our data is consistent with the aforementioned study [42] that comparing postchemotherapy and prechemotherapy gene expression signatures might be a feasible approach to the identification of predictive signatures.…”

Section: Discussionmentioning

confidence: 99%

A Gene Expression Signature of Acquired Chemoresistance to Cisplatin and Fluorouracil Combination Chemotherapy in Gastric Cancer Patients

et al. 2011

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BackgroundWe initiated a prospective trial to identify transcriptional alterations associated with acquired chemotherapy resistance from pre- and post-biopsy samples from the same patient and uncover potential molecular pathways involved in treatment failure to help guide therapeutic alternatives.Methodology/Principal FindingsA prospective, high-throughput transcriptional profiling study was performed using endoscopic biopsy samples from 123 metastatic gastric cancer patients prior to cisplatin and fluorouracil (CF) combination chemotherapy. 22 patients who initially responded to CF were re-biopsied after they developed resistance to CF. An acquired chemotherapy resistance signature was identified by analyzing the gene expression profiles from the matched pre- and post-CF treated samples.The acquired resistance signature was able to segregate a separate cohort of 101 newly-diagnosed gastric cancer patients according to the time to progression after CF. Hierarchical clustering using a 633-gene acquired resistance signature (feature selection at P<0.01) separated the 101 pretreatment patient samples into two groups with significantly different times to progression (2.5 vs. 4.7 months). This 633-gene signature included the upregulation of AKT1, EIF4B, and RPS6 (mTOR pathway), DNA repair and drug metabolism genes, and was enriched for genes overexpressed in embryonic stem cell signatures. A 72-gene acquired resistance signature (a subset of the 633 gene signature also identified in ES cell-related gene sets) was an independent predictor for time to progression (adjusted P = 0.011) and survival (adjusted P = 0.034) of these 101 patients.Conclusion/SignificanceThis signature may offer new insights into identifying new targets and therapies required to overcome the acquired resistance of gastric cancer to CF.

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“…In consequence, patients in Cohort B had fewer ductal carcinomas and, even more importantly, less frequently received neoadjuvant chemotherapy. Gene expression alterations of breast cancer were recently demonstrated to be drug-specific, and drug-induced tumor gene signatures may be more informative than unchallenged signatures in predicting treatment outcomes [ 18 , 19 ]. The study by Bos et al [ 20 ] showed that BM gene set tested in various breast cancer cohorts was less BM predictive in patients whom received postoperative systemic therapy compared to those whom did not.…”

Section: Discussionmentioning

confidence: 99%

Predicting early brain metastases based on clinicopathological factors and gene expression analysis in advanced HER2-positive breast cancer patients

et al. 2015

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The overexpression or amplification of the human epidermal growth factor receptor 2 gene (HER2/neu) is associated with high risk of brain metastasis (BM). The identification of patients at highest immediate risk of BM could optimize screening and facilitate interventional trials. We performed gene expression analysis using complementary deoxyribonucleic acid-mediated annealing, selection, extension and ligation and real-time quantitative reverse transcription PCR (qRT-PCR) in primary tumor samples from two independent cohorts of advanced HER2 positive breast cancer patients. Additionally, we analyzed predictive relevance of clinicopathological factors in this series. Study group included discovery Cohort A (84 patients) and validation Cohort B (75 patients). The only independent variables associated with the development of early BM in both cohorts were the visceral location of first distant relapse [Cohort A: hazard ratio (HR) 7.4, 95 % CI 2.4–22.3; p < 0.001; Cohort B: HR 6.1, 95 % CI 1.5–25.6; p = 0.01] and the lack of trastuzumab administration in the metastatic setting (Cohort A: HR 5.0, 95 % CI 1.4–10.0; p = 0.009; Cohort B: HR 10.0, 95 % CI 2.0–100.0; p = 0.008). A profile including 13 genes was associated with early (≤36 months) symptomatic BM in the discovery cohort. This was refined by qRT-PCR to a 3-gene classifier (RAD51, HDGF, TPR) highly predictive of early BM (HR 5.3, 95 % CI 1.6–16.7; p = 0.005; multivariate analysis). However, predictive value of the classifier was not confirmed in the independent validation Cohort B. The presence of visceral metastases and the lack of trastuzumab administration in the metastatic setting apparently increase the likelihood of early BM in advanced HER2-positive breast cancer.

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Post-treatment tumor gene expression signatures are more predictive of treatment outcomes than baseline signatures in breast cancer

Cited by 13 publications

References 24 publications

High-Throughput Mutation Profiling Changes before and 3 Weeks after Chemotherapy in Newly Diagnosed Breast Cancer Patients

High-Throughput Mutation Profiling Changes before and 3 Weeks after Chemotherapy in Newly Diagnosed Breast Cancer Patients

A Gene Expression Signature of Acquired Chemoresistance to Cisplatin and Fluorouracil Combination Chemotherapy in Gastric Cancer Patients

Predicting early brain metastases based on clinicopathological factors and gene expression analysis in advanced HER2-positive breast cancer patients

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