| Literature DB >> 25436920 |
Hatem A Azim, Ann H Partridge.
Abstract
Breast cancer arising at a young age is relatively uncommon, particularly in the developed world. Several studies have demonstrated that younger patients often experience a more aggressive disease course and have poorer outcome compared to older women. Expression of key biomarkers, including endocrine receptors, HER2 and proliferation markers, appears to be different in younger patients and young women are more likely to harbor a genetic predisposition. Despite these differences, little research to date has focused on the biology of these tumors to refine prognosis, and potentially direct treatment strategies, which remain similar to those offered to older patients. Accumulating evidence suggests the differences in breast stroma in younger patients and changes that occur with pregnancy and breastfeeding likely contribute to the different biology of these tumors. Reproductive behaviors appear to impact the biology of tumors developing later in life. In addition, tumors arising during or shortly following pregnancy appear to exhibit unique biological features. In this review, we discuss our emerging understanding of the biology of breast cancer arising at a young age at both the pathologic and the genomic level. We elucidate the potential role of genomic signatures, the impact of pregnancy and breastfeeding on breast cancer biology, and how even current knowledge might advance the clinical management of young breast cancer patients.Entities:
Mesh:
Year: 2014 PMID: 25436920 PMCID: PMC4303229 DOI: 10.1186/s13058-014-0427-5
Source DB: PubMed Journal: Breast Cancer Res ISSN: 1465-5411 Impact factor: 6.466
Recent large studies investigating the impact of age on breast cancer prognosis
| Young age, years ( | Control age, years ( | Outcome definition | Impact of young age on outcomea | Factors controlled in multivariate model | ||
|---|---|---|---|---|---|---|
| Hazard ratio | 95% CI | |||||
| Gnerlich | <40 (15,548) | ≥40 (227,464) | BC-specific survival | 1.39 | 1.34-1.45 | T, N, grade, race, marital status, ER, PgR, local therapy |
| Fredholm | <35 (378) | 50-69 (13,486) | BC-specific survival | 1.76 | 1.36-2.28 | T, N, grade, ER, multifocality, local and systemic therapy |
| Cancello | <35 (315) | 35-50 (2,650) | BC-related event | 1.7 | 1.33-2.18 | T, N, grade, histology, ER, HER2, PgR, ki67 vascular invasion |
| Han | <35 (1,443) | 40-50 (6,354) | Overall survival | 30-34 years: 1.43 26–29 years: 1.97 | 1.18-1.74 1.48-2.62 | T, N, ER, systemic therapy |
| Azim | ≤40 (339) | >40 (2,562) | Relapse-free survival | 1.34 | 1.10-1.63 | T, N, grade, BC molecular subtype, systemic therapy |
aIn multivariate models. BC, breast cancer; CI, confidence interval; ER, estrogen receptor; n, number; N, nodal involvement; PgR, progesterone receptor; T, tumor size.
Figure 1Breast cancer subtypes. Subtypes determined by gene expression profiling.
Figure 2Breast cancer subtypes. Subtypes determined by immunohistochemistry. ER, estrogen receptor; PgR, progesterone receptor.
Recent large studies investigating the impact of pregnancy and breastfeeding on the risk of developing breast cancer according to biology
| Population | Number | Impact of parity on breast cancer risk according to subtype | Impact of breastfeeding on breast cancer risk according to subtype | |
|---|---|---|---|---|
| Shinde | MD Anderson | 2,473 | Increase TNBC risk | Reduce TNBC risk |
| Palmer | African American | 457 | Reduce ER + BC risk | Reduce TNBC risk |
| Redondo | Spanish | 501 | Reduce TNBC risk | |
| Chung | Korean | 6,952 | Reduce ER + BC risk | |
| Li | American | 1,962 (<45 years) | Reduce ER + BC risk | Reduce TNBC risk |
BC, breast cancer; ER+, estrogen receptor-positive; TNBC, triple-negative breast cancer.