Serum estradiol should be monitored not only during the peri-menopausal period but also the post-menopausal period at the time of aromatase inhibitor administration

<p>Abstract</p> <p>Background</p> <p>Aromatase inhibitor (AI) therapy is being extensively used as postoperative adjuvant therapy in patients with hormone receptor-positive postmenopausal breast cancer. On the other hand, it has been reported that ovarian function was restored when AI was administered to patients who had undergone chemical menopause with chemotherapy or tamoxifen. However, there have been no reports of comprehensive monitoring of estradiol (E2) in breast cancer patients with ordinary menopause who were being administered AI.</p> <p>Patients and Methods</p> <p>Beginning in March 2008, regular monitoring of the serum levels of E2, luteinizing hormone (LH) and follicle-stimulating hormone (FSH) was performed for 66 postmenopausal breast cancer patients who had been started on AI therapy. For this study, we chose anastrozole as the AI. The assays of those hormones were outsourced to a commercial clinical laboratory.</p> <p>Results</p> <p>In 4 of the 66 patients the serum E2 level was decreased at 3 months but had then increased at 6 months, while in 2 other patients E2 was decreased at both 3 and 6 months but had increased at 9 months.</p> <p>Conclusion</p> <p>The results indicate that, in some breast cancer patients with ordinary menopause, E2 rebounds following AI therapy. In the future, E2 monitoring should be performed for a larger number of patients being administered AI therapy.</p> <p>Trial registration</p> <p>Our trial registration number is 19-11-1211.</p

Prediction Models of Breast Cancer Outcome

The goal of this study is to establish a method for predicting overall survival (OS ) and disease‐free survival (DFS ) in breast cancer patients after surgical operation. The gene expression profiles of cancer tissues from the patients, who underwent complete surgical resection of breast cancer and were subsequently monitored for postoperative survival, were analyzed using cDNA microarrays. We detected seven and three probes/genes associated with the postoperative OS and DFS , respectively, from our discovery cohort data. By incorporating these genes associated with the postoperative survival into MammaPrint genes, often used to predict prognosis of patients with early‐stage breast cancer, we constructed postoperative OS and DFS prediction models from the discovery cohort data using a Cox proportional hazard model. The predictive ability of the models was evaluated in another independent cohort using Kaplan–Meier (KM ) curves and the area under the receiver operating characteristic curve (AUC ). The KM curves showed a statistically significant difference between the predicted high‐ and low‐risk groups in both OS (log‐rank trend test P = 0.0033) and DFS (log‐rank trend test P = 0.00030). The models also achieved high AUC scores of 0.71 in OS and of 0.60 in DFS . Furthermore, our models had improved KM curves when compared to the models using MammaPrint genes (OS : P = 0.0058, DFS : P = 0.00054). Similar results were observed when our model was tested in publicly available datasets. These observations indicate that there is still room for improvement in the current methods of predicting postoperative OS and DFS in breast cancer

PREDICTION SYSTEMS FOR BLADDER CANCER THERAPY

The present study established systems to predict the chemo‑sensitivity of muscle invasive bladder cancer (MIBC) for neoadjuvant chemotherapy (NAC) with methotrexate, vinblastine, doxorubicin plus cisplatin (M‑VAC) and carboplatin plus gemcitabine (CaG) by analyzing microarray data. The primary aim of the study was to investigate whether the clinical response would increase by combining these prediction systems. Treatment of each MIBC case was allocated into M‑VAC NAC, CaG NAC, surgery, or radiation therapy groups by their prediction score (PS), which was calculated using the designed chemo‑sensitivity prediction system. The therapeutic effect of the present study was compared with the results of historical controls (n=76 patients) whose treatments were not allocated using the chemo‑sensitivity prediction system. In addition, the overall survival between the predicted to be responder (positive PS) group and predicted to be non‑responder (negative PS) group was investigated in the present study. Of the 33 patients with MIBC, 25 cases were positive PS and 8 were negative PS. Among the 25 positive PS cases, 7 were allocated to receive M‑VAC NAC and 18 were allocated to receive CaG NAC according to the results of the prediction systems. Of the 8 negative PS cases, 3 received CaG NAC, 1 received surgery without NAC and 4 received radiation therapy. The total clinical response to NAC was 88.0% (22/25), which was significantly increased compared with the historical controls [56.6% (43/76) P=0.0041]. Overall survival of the positive PS group in the study was significantly increased compared with the negative PS group (P=0.027). In conclusion, the combination of the two prediction systems may increase the treatment efficacy for patients with MIBC by proposing the optimal NAC regimen. In addition, the positive PS group would have a better prognosis compared with the negative PS group. These results suggest that the two prediction systems may lead to the achievement of ‘precision medicine’

Significant effect of polymorphisms in CYP2D6 and ABCC2 on clinical outcomes of adjuvant tamoxifen therapy for breast cancer patients

Purpose The clinical efficacy of tamoxifen is suspected to be influenced by the activity of drug-metabolizing enzymes and transporters involved in the formation, metabolism, and elimination of its active forms. We investigated relationships of polymorphisms in transporter genes and CYP2D6 to clinical outcome of patients receiving tamoxifen. Patients and Methods We studied 282 patients with hormone receptor–positive, invasive breast cancer receiving tamoxifen monotherapy, including 67 patients who have been previously reported. We investigated the effects of allelic variants of CYP2D6 and haplotype-tagging single nucleotide polymorphisms (tag-SNPs) of ABCB1, ABCC2, and ABCG2 on recurrence-free survival using the Kaplan-Meier method and Cox regression analysis. Plasma concentrations of tamoxifen metabolites were measured in 98 patients receiving tamoxifen 20 mg/d. Results CYP2D6 variants were significantly associated with shorter recurrence-free survival (P = .000036; hazard ratio [HR] = 9.52; 95% CI, 2.79 to 32.45 in patients with two variant alleles v patients without variant alleles). Among 51 tag-SNPs in transporter genes, a significant association was found at rs3740065 in ABCC2 (P = .00017; HR = 10.64; 95% CI, 1.44 to 78.88 in patients with AA v GG genotypes). The number of risk alleles of CYP2D6 and ABCC2 showed cumulative effects on recurrence-free survival (P = .000000055). Patients carrying four risk alleles had 45.25-fold higher risk compared with patients with ≤ one risk allele. CYP2D6 variants were associated with lower plasma levels of endoxifen and 4-hydroxytamoxifen (P = .0000043 and .00052), whereas no significant difference was found among ABCC2 genotype groups. Conclusion Our results suggest that polymorphisms in CYP2D6 and ABCC2 are important predictors for the prognosis of patients with breast cancer treated with tamoxifen

A Genome-Wide Association Study of Overall Survival in Pancreatic Cancer Patients Treated with Gemcitabine in CALGB 80303

CALGB 80303 was a randomized, phase III study in advanced pancreatic cancer patients treated with gemcitabine plus either bevacizumab or placebo. We prospectively collected germline DNA and conducted a genome-wide association study (GWAS) using overall survival (OS) as the endpoint

A Genome-Wide Association Study Identifies Novel Loci for Paclitaxel-Induced Sensory Peripheral Neuropathy in CALGB 40101

Sensory peripheral neuropathy is a common and sometimes debilitating toxicity associated with paclitaxel therapy. This study aims to identify genetic risk factors for development of this toxicity