Sir Peter MacCallum Department of Oncology - Research Publications
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ItemNo Preview AvailableTamoxifen in early-stage estrogen receptor-positive breast cancer: overview of clinical use and molecular biomarkers for patient selection(DOVE MEDICAL PRESS LTD, 2011)Tamoxifen was the first targeted anticancer agent for breast cancer patients and its effects on reduction of breast cancer events and improvement in overall survival are undisputed. Hence, it has long been considered an essential part of patient care. Recent results of several large adjuvant hormonal trials evaluating the use of aromatase inhibitors in comparison with the previous standard of five years of tamoxifen has led to a paradigm shift, ensuring the inclusion of an aromatase inhibitor as part of standard endocrine therapy for most postmenopausal women diagnosed today with estrogen receptor-positive breast cancer. However, one could argue that despite statistically significant improvements in breast cancer events, an overall survival advantage has not been clear. In this review, we discuss recent genomic and molecular data pertaining to estrogen receptor-positive breast cancer and how this knowledge may aid clinicians to prescribe adjuvant hormonal treatment in the future. A combination of gene expression and genetic aberration markers may be most useful in discerning a population that is still appropriate for adjuvant tamoxifen treatment.
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ItemOxaliplatin combined with infusional 5-fluorouracil and concomitant radiotherapy in inoperable and metastatic rectal cancer: a phase I trial(NATURE PUBLISHING GROUP, 2005-02-28)The aim of this study was to define the recommended dose of oxaliplatin when combined with infusional 5-fluorouracil (5-FU) and concurrent pelvic radiotherapy. Eligible patients had inoperable rectal cancer, or symptomatic primary rectal cancer with metastasis. Oxaliplatin was given on day 1 of weeks 1, 3 and 5 of radiotherapy. Dose level 1 was oxaliplatin 70 mg m(-2) with 5-FU 200 mg m(-2) day(-1) continuous infusion 96 h week(-1). On dose level 2, the oxaliplatin dose was increased to 85 mg m(-2). On dose level 3, the duration of the 5-FU was increased to 168 h per week. Pelvic radiotherapy was 45 Gray (Gy) in 25 fractions over 5 weeks with a boost of 5.4 Gy. Fluorine-18 fluoro deoxyglucose and Fluorine-18 fluoro misonidazole positron emission tomography (FDG-PET and FMISO-PET) were used to assess metabolic tumour response and hypoxia. In all, 16 patients were accrued. Dose-limiting toxicities occurred in one patient at level 2 (grade 3 chest infection), and two patients at level 3 (grade 3 diarrhoea). Dose level 2 was declared the recommended dose level. FDG-PET imaging showed metabolic responses in 11 of the 12 primary tumours assessed. Four of six tumours had detectable hypoxia on FMISO-PET scans. The addition of oxaliplatin to infusional 5-FU chemoradiotherapy was feasible and generally well tolerated. For future trials, oxaliplatin 85 mg m(-2) and 5-FU 200 mg m(-2) day(-1) continuous infusion 96 h week(-1) is the recommended dose when combined with 50.4 Gy of pelvic radiotherapy.
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ItemGene expression profiling identifies activated growth factor signaling in poor prognosis (Luminal-B) estrogen receptor positive breast cancer(BMC, 2009-06-24)BACKGROUND: Within estrogen receptor-positive breast cancer (ER+ BC), the expression levels of proliferation-related genes can define two clinically distinct molecular subtypes. When treated with adjuvant tamoxifen, those ER+ BCs that are lowly proliferative have a good prognosis (luminal-A subtype), however the clinical outcome of those that are highly proliferative is poor (luminal-B subtype). METHODS: To investigate the biological basis for these observations, gene set enrichment analysis (GSEA) was performed using microarray data from 246 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. To create an in vitro model of growth factor (GF) signaling activation, MCF-7 cells were treated with heregulin (HRG), an HER3 ligand. RESULTS: We found that a gene set linked to GF signaling was significantly enriched in the luminal-B tumors, despite only 10% of samples over-expressing HER2 by immunohistochemistry. To determine the biological significance of this observation, MCF-7 cells were treated with HRG. These cells displayed phosphorylation of HER2/3 and downstream ERK and S6. Treatment with HRG overcame tamoxifen-induced cell cycle arrest with higher S-phase fraction and increased anchorage independent colony formation. Gene expression profiles of MCF-7 cells treated with HRG confirmed enrichment of the GF signaling gene set and a similar proliferative signature observed in human ER+ BCs resistant to tamoxifen. CONCLUSION: These data demonstrate that activation of GF signaling pathways, independent of HER2 over-expression, could be contributing to the poor prognosis of the luminal-B ER+ BC subtype.
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ItemIdentification of Functional Networks of Estrogen- and c-Myc-Responsive Genes and Their Relationship to Response to Tamoxifen Therapy in Breast Cancer(PUBLIC LIBRARY SCIENCE, 2008-08-20)BACKGROUND: Estrogen is a pivotal regulator of cell proliferation in the normal breast and breast cancer. Endocrine therapies targeting the estrogen receptor are effective in breast cancer, but their success is limited by intrinsic and acquired resistance. METHODOLOGY/PRINCIPAL FINDINGS: With the goal of gaining mechanistic insights into estrogen action and endocrine resistance, we classified estrogen-regulated genes by function, and determined the relationship between functionally-related genesets and the response to tamoxifen in breast cancer patients. Estrogen-responsive genes were identified by transcript profiling of MCF-7 breast cancer cells. Pathway analysis based on functional annotation of these estrogen-regulated genes identified gene signatures with known or predicted roles in cell cycle control, cell growth (i.e. ribosome biogenesis and protein synthesis), cell death/survival signaling and transcriptional regulation. Since inducible expression of c-Myc in antiestrogen-arrested cells can recapitulate many of the effects of estrogen on molecular endpoints related to cell cycle progression, the estrogen-regulated genes that were also targets of c-Myc were identified using cells inducibly expressing c-Myc. Selected genes classified as estrogen and c-Myc targets displayed similar levels of regulation by estrogen and c-Myc and were not estrogen-regulated in the presence of siMyc. Genes regulated by c-Myc accounted for 50% of all acutely estrogen-regulated genes but comprised 85% (110/129 genes) in the cell growth signature. siRNA-mediated inhibition of c-Myc induction impaired estrogen regulation of ribosome biogenesis and protein synthesis, consistent with the prediction that estrogen regulates cell growth principally via c-Myc. The 'cell cycle', 'cell growth' and 'cell death' gene signatures each identified patients with an attenuated response in a cohort of 246 tamoxifen-treated patients. In multivariate analysis the cell death signature was predictive independent of the cell cycle and cell growth signatures. CONCLUSIONS/SIGNIFICANCE: These functionally-based gene signatures can stratify patients treated with tamoxifen into groups with differing outcome, and potentially identify distinct mechanisms of tamoxifen resistance.
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ItemPrediction of breast cancer prognosis using gene set statistics provides signature stability and biological context(BMC, 2010-05-25)BACKGROUND: Different microarray studies have compiled gene lists for predicting outcomes of a range of treatments and diseases. These have produced gene lists that have little overlap, indicating that the results from any one study are unstable. It has been suggested that the underlying pathways are essentially identical, and that the expression of gene sets, rather than that of individual genes, may be more informative with respect to prognosis and understanding of the underlying biological process. RESULTS: We sought to examine the stability of prognostic signatures based on gene sets rather than individual genes. We classified breast cancer cases from five microarray studies according to the risk of metastasis, using features derived from predefined gene sets. The expression levels of genes in the sets are aggregated, using what we call a set statistic. The resulting prognostic gene sets were as predictive as the lists of individual genes, but displayed more consistent rankings via bootstrap replications within datasets, produced more stable classifiers across different datasets, and are potentially more interpretable in the biological context since they examine gene expression in the context of their neighbouring genes in the pathway. In addition, we performed this analysis in each breast cancer molecular subtype, based on ER/HER2 status. The prognostic gene sets found in each subtype were consistent with the biology based on previous analysis of individual genes. CONCLUSIONS: To date, most analyses of gene expression data have focused at the level of the individual genes. We show that a complementary approach of examining the data using predefined gene sets can reduce the noise and could provide increased insight into the underlying biological pathways.
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ItemPIK3CA Genotype and a PIK3CA Mutation-Related Gene Signature and Response to Everolimus and Letrozole in Estrogen Receptor Positive Breast Cancer(PUBLIC LIBRARY SCIENCE, 2013-01-02)The phosphatidylinositol 3' kinase (PI3K) pathway is commonly activated in breast cancer and aberrations such as PI3K mutations are common. Recent exciting clinical trial results in advanced estrogen receptor-positive (ER) breast cancer support mTOR activation is a major means of estrogen-independent tumor growth. Hence the means to identify a responsive breast cancer population that would most benefit from these compounds in the adjuvant or earlier stage setting is of high interest. Here we study PIK3CA genotype as well as a previously reported PI3K/mTOR-pathway gene signature (PIK3CA-GS) and their ability to estimate the level of PI3K pathway activation in two clinical trials of newly diagnosed ER-positive breast cancer patients- a total of 81 patients- one of which was randomized between letrozole and placebo vs letrozole and everolimus. The main objectives were to correlate the baseline PIK3CA genotype and GS with the relative change from baseline to day 15 in Ki67 (which has been shown to be prognostic in breast cancer) and phosphorylated S6 (S240) immunohistochemistry (a substrate of mTOR). In the randomized dataset, the PIK3CA-GS could identify those patients with the largest relative decreases in Ki67 to letrozole/everolimus (R = -0.43, p = 0.008) compared with letrozole/placebo (R = 0.07, p = 0.58; interaction test p = 0.02). In a second dataset of pre-surgical everolimus alone, the PIK3CA-GS was not significantly correlated with relative change in Ki67 (R = -0.11, p = 0.37) but with relative change in phosphorlyated S6 (S240) (R = -0.46, p = 0.028). PIK3CA genotype was not significantly associated with any endpoint in either datasets. Our results suggest that the PIK3CA-GS has potential to identify those ER-positive BCs who may benefit from the addition of everolimus to letrozole. Further evaluation of the PIK3CA-GS as a predictive biomarker is warranted as it may facilitate better selection of responsive patient populations for mTOR inhibition in combination with letrozole.
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ItemSomatic Mutation Profiling and Associations With Prognosis and Trastuzumab Benefit in Early Breast Cancer(OXFORD UNIV PRESS INC, 2013-07)BACKGROUND: Certain somatic alterations in breast cancer can define prognosis and response to therapy. This study investigated the frequencies, prognostic effects, and predictive effects of known cancer somatic mutations using a randomized, adjuvant, phase III clinical trial dataset. METHODS: The FinHER trial was a phase III, randomized adjuvant breast cancer trial involving 1010 women. Patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer were further randomized to 9 weeks of trastuzumab or no trastuzumab. Seven hundred five of 1010 tumors had sufficient DNA for genotyping of 70 somatic hotspot mutations in 20 genes using mass spectrometry. Distant disease-free survival (DDFS), overall survival (OS), and interactions with trastuzumab were explored with Kaplan-Meier and Cox regression analyses. All statistical tests were two-sided. RESULTS: Median follow-up was 62 months. Of 705 tumors, 687 were successfully genotyped. PIK3CA mutations (exons 1, 2, 4, 9, 13, 18, and 20) were present in 25.3% (174 of 687) and TP53 mutations in 10.2% (70 of 687). Few other mutations were found: three ERBB2 and single cases of KRAS, ALK, STK11/LKB1, and AKT2. PIK3CA mutations were associated with estrogen receptor positivity (P < .001) and the luminal-A phenotype (P = .04) but were not statistically significantly associated with prognosis (DDFS: hazard ratio [HR] = 0.88, 95% confidence [CI] = 0.58 to 1.34, P = .56; OS: HR = 0.603, 95% CI = .32 to 1.13, P = .11), although a statistically significant nonproportional prognostic effect was observed for DDFS (P = .002). PIK3CA mutations were not statistically significantly associated with trastuzumab benefit (P(interaction): DDFS P = .14; OS P = .24). CONCLUSIONS: In this dataset, targeted genotyping revealed only two alterations at a frequency greater than 10%, with other mutations observed infrequently. PIK3CA mutations were associated with a better outcome, however this effect disappeared after 3 years. There were no statistically significant associations with trastuzumab benefit.
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ItemPredicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen(BMC, 2008-05-22)BACKGROUND: Estrogen receptor positive (ER+) breast cancers (BC) are heterogeneous with regard to their clinical behavior and response to therapies. The ER is currently the best predictor of response to the anti-estrogen agent tamoxifen, yet up to 30-40% of ER+BC will relapse despite tamoxifen treatment. New prognostic biomarkers and further biological understanding of tamoxifen resistance are required. We used gene expression profiling to develop an outcome-based predictor using a training set of 255 ER+ BC samples from women treated with adjuvant tamoxifen monotherapy. We used clusters of highly correlated genes to develop our predictor to facilitate both signature stability and biological interpretation. Independent validation was performed using 362 tamoxifen-treated ER+ BC samples obtained from multiple institutions and treated with tamoxifen only in the adjuvant and metastatic settings. RESULTS: We developed a gene classifier consisting of 181 genes belonging to 13 biological clusters. In the independent set of adjuvantly-treated samples, it was able to define two distinct prognostic groups (HR 2.01 95%CI: 1.29-3.13; p = 0.002). Six of the 13 gene clusters represented pathways involved in cell cycle and proliferation. In 112 metastatic breast cancer patients treated with tamoxifen, one of the classifier components suggesting a cellular inflammatory mechanism was significantly predictive of response. CONCLUSION: We have developed a gene classifier that can predict clinical outcome in tamoxifen-treated ER+ BC patients. Whilst our study emphasizes the important role of proliferation genes in prognosis, our approach proposes other genes and pathways that may elucidate further mechanisms that influence clinical outcome and prediction of response to tamoxifen.
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ItemTumor-infiltrating lymphocytes, breast cancer subtypes and therapeutic efficacy(LANDES BIOSCIENCE, 2013-07-01)By analyzing over 2000 samples from a randomized clinical trial, we have recently associated high levels of tumor-infiltrating lymphocytes with an excellent prognosis among triple negative breast cancer patients as well with improved clinical responses to immunogenic chemotherapy among patients bearing HER2 over-expression. These findings suggest that immunomodulation could represent a new approach to treat these aggressive breast cancer subtypes.
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ItemNo Preview AvailableCD73 promotes anthracycline resistance and poor prognosis in triple negative breast cancer(NATL ACAD SCIENCES, 2013-07-02)Using gene-expression data from over 6,000 breast cancer patients, we report herein that high CD73 expression is associated with a poor prognosis in triple-negative breast cancers (TNBC). Because anthracycline-based chemotherapy regimens are standard treatment for TNBC, we investigated the relationship between CD73 and anthracycline efficacy. In TNBC patients treated with anthracycline-only preoperative chemotherapy, high CD73 gene expression was significantly associated with a lower rate of pathological complete response or the disappearance of invasive tumor at surgery. Using mouse models of breast cancer, we demonstrated that CD73 overexpression in tumor cells conferred chemoresistance to doxorubicin, a commonly used anthracycline, by suppressing adaptive antitumor immune responses via activation of A2A adenosine receptors. Targeted blockade of CD73 enhanced doxorubicin-mediated antitumor immune responses and significantly prolonged the survival of mice with established metastatic breast cancer. Taken together, our data suggest that CD73 constitutes a therapeutic target in TNBC.