“…The team cautioned that several outbred mouse stocks are known to have active sPLA 2 genes causing abnormally high serum sPLA 2 levels and similar findings have been noted for cancer patients, thus causing the premature activation of the liposomes in circulation. More recently, an mRNA-based LiPlaCis® drug response predictor for heavily pretreated-platin metastatic breast cancer is scheduled to undergo randomized phase II trials after the phase I clinical trial [ 357 ] showed promising efficacy in metastatic breast cancer patients (NCT01861496). Fig.…”
Section: Targeted Nanoliposomes For Breast Cancer Treatmentmentioning
“…The team cautioned that several outbred mouse stocks are known to have active sPLA 2 genes causing abnormally high serum sPLA 2 levels and similar findings have been noted for cancer patients, thus causing the premature activation of the liposomes in circulation. More recently, an mRNA-based LiPlaCis® drug response predictor for heavily pretreated-platin metastatic breast cancer is scheduled to undergo randomized phase II trials after the phase I clinical trial [ 357 ] showed promising efficacy in metastatic breast cancer patients (NCT01861496). Fig.…”
Section: Targeted Nanoliposomes For Breast Cancer Treatmentmentioning
“…Drug Response Prediction (DRP®) is used to significantly increase the probability of success in clinical trials. Patients undergo genetic screening of tumors, then are selected for the trial based upon those most likely to respond to treatment, providing a highly-defined patient group and subsequently lowering costs and risks [ 126 ]. DRP® has provided statistically significant prediction of drug treatment clinical outcome for cancer patients in 29 out of 37 clinical studies that were examined.…”
Section: Applications Of Nanotechnology In Cancer Therapeuticsmentioning
Modern medicine has been waging a war on cancer for nearly a century with no tangible end in sight. Cancer treatments have significantly progressed, but the need to increase specificity and decrease systemic toxicities remains. Early diagnosis holds a key to improving prognostic outlook and patient quality of life, and diagnostic tools are on the cusp of a technological revolution. Nanotechnology has steadily expanded into the reaches of cancer chemotherapy, radiotherapy, diagnostics, and imaging, demonstrating the capacity to augment each and advance patient care. Nanomaterials provide an abundance of versatility, functionality, and applications to engineer specifically targeted cancer medicine, accurate early-detection devices, robust imaging modalities, and enhanced radiotherapy adjuvants. This review provides insights into the current clinical and pre-clinical nanotechnological applications for cancer drug therapy, diagnostics, imaging, and radiation therapy.
“…Totally, 1,199 patients with locally advanced or metastatic breast cancer have given informed consent to be enrolled in a screening cohort selecting patients to a phase II trial with liposomal cisplatin (LiPlaCis), the DBCG screening cohort. The phase II trial with LiPlaCis is registered with ClinicalTrials.gov as NCT01861496 (38). Data from medical records for patients enrolled in the DBCG screening cohort was used to test markers for prior treatments as previously described by Buhl…”
Background Even with positive oestrogen receptor (ER+) status some advanced breast cancer (ABC) patients fail to benefit from endocrine therapy (ET). A method that previously predicted other drugs in various cancers was evaluated. Here multigene markers based on aromatase inhibitor (AI) effect in vitro were used for prediction of AI benefit in ER+ ABC patients. Simultaneously effects of long-term ET on predictive efficacy was evaluated. Methods The Drug Response Predictors (DRPs) are based on correlations between baseline gene expression and growth inhibition patterns of exemestane, anastrozole and letrozole, respectively, in the National Cancer Institute 60 cell lines. The genes were controlled for expression in 3,500 tumours. In a Danish Breast Cancer Cooperative Group cohort of 695 ABC patients with complete gene expression and time-to-progression (TTP) data, 414 received an AI as monotherapy. Hereof, 57 received anastrozole, 166 received exemestane, and 327 received letrozole. mRNA was isolated from archival formalin-fixed paraffin embedded tumour tissue and run on microarray and 60% of the tumours were from time of primary diagnosis. Medical records of the patients were assessed for TTP for all treatments given for ABC. Results The DRPs were tested in subsets 1) with no adjuvant ET and 2) with adjuvant ET. In 1) the anastrozole DRP predicted benefit of anastrozole (hazard ratio (HR) was 0.21 upper 95%-confidence interval limit (CI) 0.76, p=0.023) but not in 2). Dichotomised by a DRP of 50, the anastrozole DRP did predict benefit (HR=0.16, upper 95%-CI 0.75, p=0.026). Only in 1) the exemestane DRP predicted benefit of exemestane (HR=0.57, upper 95%-CI 1.00, p=0.0497). The letrozole DRP had no predictive value. Additionally, we tested each DRPs ability to predict other AIs. Only the anastrozole DRP predicted benefit of overall AI treatment, in 1)with an HR of 0.76 (upper 95%-CI 0.99, p=0.044) and in 2) with an HR of 0.71 (upper 95%-CI 0.92, p=0.015). The anastrozole DRP did though not predict benefit of letrozole. All tests are one-sided, alpha=5%. Conclusions Among the DRPs for AIs, the anastrozole DRP was strongest with clinically relevant prediction of TTP in AI treated ER+ ABC patients. Trial registration: ClinicalTrials.gov NCT01861496.
BackgroundApproximately 70% of women with advanced breast cancer (ABC) have oestrogen-receptor positive
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