Network-guided prediction of aromatase inhibitor response in breast cancer.
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ABSTRACT:
SUBMITTER: Ruffalo M
PROVIDER: S-EPMC6386390 | biostudies-literature | 2019 Feb
REPOSITORIES: biostudies-literature
Publications
Network-guided prediction of aromatase inhibitor response in breast cancer.
Ruffalo Matthew M Thomas Roby R Chen Jian J Lee Adrian V AV Oesterreich Steffi S Bar-Joseph Ziv Z
PLoS computational biology 20190211 2
Prediction of response to specific cancer treatments is complicated by significant heterogeneity between tumors in terms of mutational profiles, gene expression, and clinical measures. Here we focus on the response of Estrogen Receptor (ER)+ post-menopausal breast cancer tumors to aromatase inhibitors (AI). We use a network smoothing algorithm to learn novel features that integrate several types of high throughput data and new cell line experiments. These features greatly improve the ability to ...[more]
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Project description:BACKGROUND:Aromatase inhibitors such as anastrozole and letrozole are highly effective suppressants of estrogen synthesis in postmenopausal women and are the most effective endocrine treatments for hormone receptor positive breast cancer in such women. Little is known of the molecular effects of these agents on human breast carcinomas in vivo. METHODS:We randomly assigned primary estrogen receptor positive breast cancer patients to treatment with anastrozole or letrozole for 2 weeks before surgery. Expression profiling using cDNA arrays was conducted on pretreatment and post-treatment biopsies. Sample pairs from 34 patients provided sufficient RNA for analysis. RESULTS:Profound changes in gene expression were seen with both aromatase inhibitors, including many classical estrogen-dependent genes such as TFF1, CCND1, PDZK1 and AGR2, but also many other genes that are likely to represent secondary responses; decrease in the expression of proliferation-related genes were particularly prominent. Many upregulated genes are involved in extracellular matrix remodelling, including collagens and members of the small leucine-rich proteoglycan family (LUM, DCN, and ASPN). No significant differences were seen between letrozole and anastrozole in terms of molecular effects. The gene changes were integrated into a Global Index of Dependence on Estrogen (GIDE), which enumerates the genes changing by at least twofold with therapy. The GIDE varied markedly between tumours and related significantly to pretreatment levels of HER2 and changes in immunohistochemically detected Ki67. CONCLUSION:Our findings identify the transcriptional signatures associated with aromatase inhibitor treatment of primary breast tumours. Larger datasets using this approach should enable identification of estrogen-dependent molecular changes, which are the determinants of benefit or resistance to endocrine therapy.
| S-EPMC1929101 | biostudies-literature
Project description:ObjectiveTo evaluate the associations between polymorphisms in two genes, catechol-O-methyltransferase and T-cell leukemia/lymphoma 1 A, and acupuncture-mediated pain reduction among breast cancer survivors with aromatase inhibitor-associated arthralgia.Design, setting, and subjectsBiospecimens were obtained from 38 patients enrolled in a clinical trial of acupuncture for aromatase inhibitor-associated arthralgia in postmenopausal hormone receptor-positive breast cancer survivors.MethodsWe used polymerase chain reaction to genotype the rs4680 (Val158Met) and rs4633 (His62His) variants in the catechol-O-methyltransferase gene and rs2369049 (A > G) and rs7158782 (A > G) variants in the T-cell leukemia/lymphoma 1 A gene. Response to acupuncture was defined by 30% reduction in end-of-treatment average pain, measured by the Brief Pain Inventory. We used Fisher exact tests to evaluate associations between genotype and treatment response.ResultsAmong participants, all six (15.8%) subjects who expressed AA in locus rs4680 responded to acupuncture. In a combined analysis, the 18 (47.4%) subjects with the responder genotype at either rs4680 (AA) or rs2369049 (GG or AG) were significantly more likely to respond to acupuncture than those without (77.8% vs 45.0%, P = 0.039).ConclusionsSpecific genetic variations at loci rs4680 and rs2369049 are associated with response to acupuncture-type intervention for management of arthralgia. These results serve as a proof of concept for applying a precision medicine framework to the study of cancer pain management.
| S-EPMC6329437 | biostudies-literature
Project description:BackgroundThe tamoxifen metabolite, Z-endoxifen, demonstrated promising antitumor activity in endocrine-resistant estrogen receptor-positive (ER+) breast cancer. We compared the antitumor activity of Z-endoxifen with tamoxifen and letrozole in the letrozole-sensitive MCF7 aromatase expressing model (MCF7AC1), as well as with tamoxifen, fulvestrant, exemestane, and exemestane plus everolimus in a letrozole-resistant MCF7 model (MCF7LR).MethodsMCF7AC1 tumor-bearing mice were randomized to control (no drug), letrozole (10 μg/day), tamoxifen (500 μg/day), or Z-endoxifen (25 and 75 mg/kg). Treatment in the letrozole arm was continued until resistance developed. MCF7LR tumor-bearing mice were then randomized to Z-endoxifen (50 mg/kg) or tamoxifen for 4 weeks and tumors harvested for microarray and immunohistochemistry analysis. The antitumor activity of Z-endoxifen in the MCF7LR tumors was further compared in a second in vivo study with exemestane, exemestane plus everolimus, and fulvestrant.ResultsIn the MCF7AC1 tumors, both Z-endoxifen doses were significantly superior to control and tamoxifen in reducing tumor volumes at 4 weeks. Additionally, the 75 mg/kg Z-endoxifen dose was additionally superior to letrozole. Prolonged letrozole exposure resulted in resistance at 25 weeks. In MCF7LR tumor-bearing mice, Z-endoxifen significantly reduced tumor volumes compared to tamoxifen, letrozole, and exemestane, with no significant differences compared to exemestane plus everolimus and fulvestrant. Additionally, compared to tamoxifen, Z-endoxifen markedly inhibited ERα target genes, Ki67 and Akt expression in vivo.ConclusionIn endocrine-sensitive and letrozole-resistant breast tumors, Z-endoxifen results in robust antitumor and antiestrogenic activity compared to tamoxifen and aromatase inhibitor monotherapy. These data support the ongoing development of Z-endoxifen.
| S-EPMC7238733 | biostudies-literature
Project description:IntroductionEstrogen deprivation using aromatase inhibitors (AIs) is currently the standard of care for postmenopausal women with hormone receptor-positive breast cancer. Unfortunately, the majority of patients treated with AIs eventually develop resistance, inevitably resulting in patient relapse and, ultimately, death. The mechanism by which resistance occurs is still not completely known, however, recent studies suggest that impaired/defective interferon signaling might play a role. In the present study, we assessed the functional role of IFITM1 and PLSCR1; two well-known interferon response genes in AI resistance.MethodsReal-time PCR and Western blot analyses were used to assess mRNA and protein levels of IFITM1, PLSCR1, STAT1, STAT2, and IRF-7 in AI-resistant MCF-7:5C breast cancer cells and AI-sensitive MCF-7 and T47D cells. Immunohistochemistry (IHC) staining was performed on tissue microarrays consisting of normal breast tissues, primary breast tumors, and AI-resistant recurrence tumors. Enzyme-linked immunosorbent assay was used to quantitate intracellular IFNα level. Neutralizing antibody was used to block type 1 interferon receptor IFNAR1 signaling. Small interference RNA (siRNA) was used to knockdown IFITM1, PLSCR1, STAT1, STAT2, IRF-7, and IFNα expression.ResultsWe found that IFITM1 and PLSCR1 were constitutively overexpressed in AI-resistant MCF-7:5C breast cancer cells and AI-resistant tumors and that siRNA knockdown of IFITM1 significantly inhibited the ability of the resistant cells to proliferate, migrate, and invade. Interestingly, suppression of IFITM1 significantly enhanced estradiol-induced cell death in AI-resistant MCF-7:5C cells and markedly increased expression of p21, Bax, and Noxa in these cells. Significantly elevated level of IFNα was detected in AI-resistant MCF-7:5C cells compared to parental MCF-7 cells and suppression of IFNα dramatically reduced IFITM1, PLSCR1, p-STAT1, and p-STAT2 expression in the resistant cells. Lastly, neutralizing antibody against IFNAR1/2 and knockdown of STAT1/STAT2 completely suppressed IFITM1, PLSCR1, p-STAT1, and p-STAT2 expression in the resistant cells, thus confirming the involvement of the canonical IFNα signaling pathway in driving the overexpression of IFITM1 and other interferon-stimulated genes (ISGs) in the resistant cells.ConclusionOverall, these results demonstrate that constitutive overexpression of ISGs enhances the progression of AI-resistant breast cancer and that suppression of IFITM1 and other ISGs sensitizes AI-resistant cells to estrogen-induced cell death.
| S-EPMC4336497 | biostudies-literature
Project description:<p>Highly variable outcomes are observed in patients with estrogen receptor positive (ER+) breast cancer who undergo preoperative estrogen deprivation therapy with aromatase inhibitors (AI). In this study, 46 tumor and normal genomes and 31 exomes of participants selected from two clinical trials of neoadjuvant AI therapy on ER+ breast cancer were sequenced to identify somatic alterations that correlate with response to AI, to screen for therapeutic targets and to elucidate the genetic landscape of ER+ breast cancer. Of the significantly mutated genes, GATA3 mutations correlated with low post-treatment Ki67 and up-regulation of IGF1R mRNA. TP53 mutations associated with multiple markers of poor outcome and mutations in MAP3K1 associated with inferior clinical response. Mutations in MAP3K1 and MAP2K4 were mutually exclusive and positively associated with mutations in PIK3CA. The majority of tumors were multiclonal, as defined by distinct mutation clusters. A number of potential therapeutic targets were provided by both common and rare variants. Potential therapeutically relevant mutations of tryosine kinase included ERBB2, KIT, PDGFRA, DDR1, CSF1R, and MET.</p>
| phs000472.v1.p1 | EGA
Project description:Androgen receptor (AR) is an attractive target in breast cancer because of its frequent expression in all the molecular subtypes, especially in estrogen receptor (ER)-positive luminal breast cancers. We have previously shown a role for AR overexpression in tamoxifen resistance. We engineered ER-positive MCF-7 cells to overexpress aromatase and AR (MCF-7 AR Arom cells) to explore the role of AR in aromatase inhibitor (AI) resistance. Androstendione (AD) was used as a substrate for aromatization to estrogen. The nonsteroidal AI anastrazole (Ana) inhibited AD-stimulated growth and ER transcriptional activity in MCF-7 Arom cells, but not in MCF-7 AR Arom cells. Enhanced activation of pIGF-1R and pAKT was found in AR-overexpressing cells, and their inhibitors restored sensitivity to Ana, suggesting that these pathways represent escape survival mechanisms. Sensitivity to Ana was restored with AR antagonists, or the antiestrogen fulvestrant. These results suggest that both AR and ER? must be blocked to restore sensitivity to hormonal therapies in AR-overexpressing ER?-positive breast cancers. AR contributed to ER? transcriptional activity in MCF-7 AR Arom cells, and AR and ER? co-localized in AD + Ana-treated cells, suggesting cooperation between the two receptors. AR-mediated resistance was associated with a failure to block ER transcriptional activity and enhanced up-regulation of AR and ER-responsive gene expression. Clinically, it may be necessary to block both AR and ER? in patients whose tumors express elevated levels of AR. In addition, inhibitors to the AKT/IGF-1R signaling pathways may provide alternative approaches to block escape pathways and restore hormone sensitivity in resistant breast tumors.
| S-EPMC4337991 | biostudies-literature
Project description:BackgroundEndocrine resistance is a major obstacle to optimal treatment effect in breast cancer. Some genetic markers have been proposed to predict response to aromatase inhibitors (AIs) but the data is insufficient. The aim of the study was to find new genetic treatment predictive markers of AIs.MethodsThe ongoing population-based BC-blood study in Lund, Sweden includes women with primary breast cancer. This paper is based on AI-treated patients with estrogen receptor positive tumors who underwent breast cancer surgery in 2002-2008. First, an exploratory analysis of 1931 SNPs in 227 genes involved in absorption, distribution, metabolism, and elimination of multiple medications, using DMET™ chips, was conducted in a subset of the cohort with last follow-up in December 31st 2011 (13 cases, 11 controls). Second, selected SNPs from the first analysis were re-analyzed concerning risk for early breast cancer events in the extended cohort of 201 AI-treated with last follow-up in June 30th 2014. Clinical data were obtained from medical records and population registries.ResultsOnly CYP1A2 rs762551 C-allele was significantly associated with increased risk for early events in the 24 patients (P = 0.0007) and in the extended cohort, adjusted Hazard ratio (HR) 2.22 (95% CI 1.03-4.80). However, the main prognostic impact was found within five years, adjusted HR 7.88 (95% CI 2.13-29.19). The impact of the CYP1A2 rs762551 C-allele was modified by a functional polymorphism in the regulator gene AhR Arg554Lys (G > A). Compared to patients who were homozygous for the major allele in both genes (CYP1A2 A/A and AhR G/G), a 9-fold risk for early events was found in patients who had at least one minor allele in both genes, adjusted HR 8.95 (95% CI 2.55-31.35), whereas patients with at least one minor allele in either but not both genes had a 3-fold risk for early events, adjusted HR 2.81 (95% CI 1.07-7.33). The impact of CYP1A2 rs762551 C-allele was also modified by the CYP19A1 rs4646 C/C, adjusted HR 3.39 (95% CI 1.60-7.16) for this combination. This association was strongest within the first five years, adjusted HR 10.42 (95% CI 3.45-31.51).ConclusionCYP1A2 rs762551 was identified as a new potential predictive marker for early breast cancer events in AI-treated breast cancer patients. Moreover, combined genotypes of CYP1A2 rs762551 and CYP19A1 rs4646 or AhR Arg554Lys could further improve prediction of early AI-treatment response. If confirmed, these results may provide a way to more personalized medicine.
| S-EPMC4815192 | biostudies-literature
Project description:We previously reported the establishment of several types of long-term estrogen-depleted-resistant (EDR) cell lines from MCF-7 breast cancer cells. Type 1 EDR cells exhibited the best-studied mechanism of aromatase inhibitor (AI) resistance, in which estrogen receptor (ER) expression remained positive and PI3K signaling was upregulated. Type 2 EDR cells showed reduced ER activity and upregulated JNK-related signaling. The mTOR inhibitor everolimus reduced growth in cells similar to Type 1 EDR cells. The present study generated everolimus-resistant (EvR) cells from Types 1 and 2 EDR cells following long-term exposure to everolimus in vitro. These EvR cells modeled resistance to AI and everolimus combination therapies following first-line AI treatment failure. In Type 1 EvR cells, everolimus resistance was dependent on MAPK signaling; single agents were not effective, but hormonal therapy combined with a kinase inhibitor effectively reduced cell growth. In Type 2 EvR cells, ER expression remained negative and a JNK inhibitor was ineffective, but a Src inhibitor reduced cell growth. The mechanism of acquired everolimus resistance appears to vary depending on the mechanism of AI resistance. Strategies targeting resistant tumors should be tailored based on the resistance mechanisms, as these mechanisms impact therapeutic efficacy.
| S-EPMC5940386 | biostudies-other
Project description:Many breast cancer (BC) patients treated with aromatase inhibitors (AIs) develop aromatase inhibitor-related arthralgia (AIA). Candidate gene studies to identify AIA risk are limited in scope. We evaluated the potential of a novel analytic algorithm (NAA) to predict AIA using germline single nucleotide polymorphisms (SNP) data obtained before treatment initiation. Systematic chart review of 700 AI-treated patients with stage I-III BC identified asymptomatic patients (n = 39) and those with clinically significant AIA resulting in AI termination or therapy switch (n = 123). Germline DNA was obtained and SNP genotyping performed using the Affymetrix UK BioBank Axiom Array to yield 695,277 SNPs. SNP clusters that most closely defined AIA risk were discovered using an NAA that sequentially combined statistical filtering and a machine-learning algorithm. NCBI PhenGenI and Ensemble databases defined gene attribution of the most discriminating SNPs. Phenotype, pathway, and ontologic analyses assessed functional and mechanistic validity. Demographics were similar in cases and controls. A cluster of 70 SNPs, correlating to 57 genes, was identified. This SNP group predicted AIA occurrence with a maximum accuracy of 75.93%. Strong associations with arthralgia, breast cancer, and estrogen phenotypes were seen in 19/57 genes (33%) and were functionally consistent. Using a NAA, we identified a 70 SNP cluster that predicted AIA risk with fair accuracy. Phenotype, functional, and pathway analysis of attributed genes was consistent with clinical phenotypes. This study is the first to link a specific SNP/gene cluster to AIA risk independent of candidate gene bias.
| S-EPMC5773952 | biostudies-literature
Project description:Postmenopausal women are at an increased risk of osteopenia and osteoporosis due to the physiologic loss of the bone protective effects of estrogen. Additionally, disease-related risk factors also contribute to the increased fracture risk. To further complicate matters, one of the most common and severe safety issues associated with cancer therapies for breast cancer patients is bone loss and the associated increased risk of fractures. These facts underscore the need to carefully monitor bone mineral density in patients with endocrine-responsive breast cancer, and to consider adjuvant therapy that may help manage and/or prevent bone loss and fracture. Aromatase inhibitors (AIs) are now in widespread clinical use for women with hormone receptor-positive breast cancer and have replaced tamoxifen as the gold standard of care. AIs target the estrogen biosynthetic pathway and deprive tumor cells of the growth-promoting effects of estrogen. These treatments provide significant benefit to patients in terms of improved disease-free and overall survival. Adversely, there is a concern of an increased risk of bone loss with prolonged therapy consequently leading to an increased fracture risk. This manuscript will review the recent literature pertaining to AI-associated bone loss and discuss suggested management and preventative approaches that may help patients remain on therapy to derive the most clinical benefits.
| S-EPMC3132952 | biostudies-literature