[Show abstract][Hide abstract] ABSTRACT:
Breast cancer (BC) under age 40 is a complex disease to manage due to the additionally fertility-related factors to be taken in consideration. More than 90 % of young patients with BC are symptomatic. Women <40 years are more likely to develop BC with worse clinicopathological features and more aggressive subtype. This has been frequently associated with inferior outcomes. Recently, the prognostic significance of age <40 has been shown to differ according to the BC subtype, being associated with worst recurrence-free survival (RFS) and overall survival (OS) for luminal BC. The biology of BC <40 has also been explored through analysis of large genomic data set, and specific pathways overexpressed in these tumors have been identified which can lead to the development of targeted therapy in the future. A multidisciplinary tumor board should determine the optimal locoregional and systemic management strategies for every individual patient with BC before the start of any therapy including surgery. This applies to both early (early breast cancer (EBC)) and advanced (advanced breast cancer (ABC)) disease, before the start of any therapy. Mastectomy even in young patients confers no overall survival advantage when compared to breast-conserving treatment (BCT), followed by radiotherapy. Regarding axillary approach, indications are identical to other age groups. Young age is one of the most important risk factors for local recurrence after both breast-conserving surgery (BCS) and mastectomy, associated with a higher risk of distant metastasis and death. Radiation after BCS reduces local recurrence from 19.5 to 10.2 % in BC patients 40 years and younger. The indications for and the choice of systemic treatment for invasive BC (both early and advanced disease) should not be based on age alone but driven by the biological characteristics of the individual tumor (including hormone receptor status, human epidermal growth factor receptor 2 (HER-2) status, grade, and proliferative activity), disease stage, and patient's comorbidities. Recommendations regarding the use of genomic profiles such as MammaPrint, Oncotype Dx, and Genomic grade index in young women are similar to the general BC population. Especially in the metastatic setting, patient preferences should always be taken into account, as the disease is incurable. The best strategy for these patients is the inclusion into well-designed, independent, prospective randomized clinical trials. Metastatic disease should always be biopsied whenever feasible for histological confirmation and reassessment of biology. Endocrine therapy is the preferred option for hormone receptor-positive disease (HR+ve), even in presence of visceral metastases, unless there is concern or proof of endocrine resistance or there is a need for rapid disease response and/or symptom control. Recommendations for chemotherapy (CT) should not differ from those for older patients with the same characteristics of the metastatic disease and its extent. Young age by itself should not be an indication to prescribe more intensive and combination CT regimens over the sequential use of monotherapy. Poly(ADP-ribose) polymerase inhibitors (PARP inhibitors) represent an important group of promising drugs in managing patients with breast cancer susceptibility gene (BRCA)-1- or BRCA-2-associated BC. Specific age-related side effects of systemic treatment (e.g., menopausal symptoms, change in body image, bone morbidity, cognitive function impairment, fertility damage, sexual dysfunction) and the social impact of diagnosis and treatment (job discrimination, taking care for children) should also be carefully addressed when planning systemic long-lasting therapy, such as endocrine therapy. Survivorship concerns for young women are different compared to older women, including issues of fertility, preservation, and pregnancy.
Current Treatment Options in Oncology 04/2015; 16(4):334. DOI:10.1007/s11864-015-0334-8 · 3.24 Impact Factor
[Show abstract][Hide abstract] ABSTRACT:
Systematic analysis of cancer gene-expression patterns using high-throughput transcriptional profiling technologies has led to the discovery and publication of hundreds of gene-expression signatures. However, few public signature values have been cross-validated over multiple studies for the prediction of cancer prognosis and chemosensitivity in the neoadjuvant setting.
To analyze the prognostic and predictive values of publicly available signatures, we have implemented a systematic method for high-throughput and efficient validation of a large number of datasets and gene-expression signatures. Using this method, we performed a meta-analysis including 351 publicly available signatures, 37,000 random signatures, and 31 breast cancer datasets. Survival analyses and pathologic responses were used to assess prediction of prognosis, chemoresponsiveness, and chemo-drug sensitivity.
Among 31 breast cancer datasets and 351 public signatures, we identified 22 validation datasets, two robust prognostic signatures (BRmet50 and PMID18271932Sig33) in breast cancer and one signature (PMID20813035Sig137) specific for prognosis prediction in patients with ER-negative tumors. The 22 validation datasets demonstrated enhanced ability to distinguish cancer gene profiles from random gene profiles. Both prognostic signatures are composed of genes associated with TP53 mutations and were able to stratify the good and poor prognostic groups successfully in 82%and 68% of the 22 validation datasets, respectively. We then assessed the abilities of the two signatures to predict treatment responses of breast cancer patients treated with commonly used chemotherapeutic regimens. Both BRmet50 and PMID18271932Sig33 retrospectively identified those patients with an insensitive response to neoadjuvant chemotherapy (mean positive predictive values 85%-88%). Among those patients predicted to be treatment sensitive, distant relapse-free survival (DRFS) was improved (negative predictive values 87%-88%). BRmet50 was further shown to prospectively predict taxane-anthracycline sensitivity in patients with HER2-negative (HER2-) breast cancer.
We have developed and applied a high-throughput screening method for public cancer signature validation. Using this method, we identified appropriate datasets for cross-validation and two robust signatures that differentiate TP53 mutation status and have prognostic and predictive value for breast cancer patients.
BMC Cancer 03/2015; 15(1):179. DOI:10.1186/s12885-015-1102-7 · 3.32 Impact Factor
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