Breast cancer treatment has experienced several changes in the past decades due to the discovery of specific prognostic and predictive biomarkers that enable the application of more individualized therapies to different molecular subgroups. These subgroups show specific differences regarding biological clinical behavior. In addition to the classical clinical prognostic factors of breast cancer, established molecular biomarkers such as estrogen receptor and progesterone receptor have played a significant role in the selection of patients benefiting from endocrine therapy for many years. More recently, the human epidermal growth factor receptor 2 (HER2) has been validated to be not only a prognostic factor, but also a predictor of response to HER2 targeting therapy. The shift toward an earlier diagnosis of breast cancer due to improved imaging methods and screening programs highlights the need for new factors and combinations of biomarkers to quantify the residual risk of patients and to indicate the potential value of additional treatment strategies. The marker of proliferation Ki67 has recently emerged as an important marker due to several applications in neoadjuvant therapy in addition to its moderate prognostic value. With the introduction of high-throughput technologies, numerous multigene signatures have been identified that aim to outperform traditional markers: current prospective clinical trials are seeking evidence for their definitive role in breast cancer. There exist many more factors and approaches that have the potential to become relevant in the near future including the detection of single disseminating and circulating tumor cells in blood and bone marrow as well as of circulating cell-free DNA and microRNA. Careful randomized prospective testing and comparison with existing established factors will be required to select those emerging markers that offer substantial cost-effective benefit and thereby justify their routine use for breast cancer therapy decision-making.

EpidemiologyVulvar cancer can be classified into two groups according to predisposing factors: the first type correlates with a HPV infection and occurs mostly in younger patients. The second group is not HPV associated and occurs often in elderly women without neoplastic epithelial disorders.HistologySquamous cell carcinoma (SCC) is the most common malignant tumor of the vulva (95%).Clinical featuresPruritus is the most common and long-lasting reported symptom of vulvar cancer, followed by vulvar bleeding, discharge, dysuria, and pain.TherapyThe gold standard for even a small invasive carcinoma of the vulva was historically radical vulvectomy with removal of the tumor with a wide margin followed by an en bloc resection of the inguinal and often the pelvic lymph nodes. Currently, a more individualized and less radical treatment is suggested: a radical wide local excision is possible in the case of localized lesions (T1). A sentinel lymph node (SLN) biopsy may be performed to reduce wound complications and lymphedema.PrognosisThe survival of patients with vulvar cancer is good when convenient therapy is arranged quickly after initial diagnosis. Inguinal and/or femoral node involvement is the most significant prognostic factor for survival.

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Objective: Many patients with ovarian cancer disease relapse within 6 months after adjuvant chemotherapy, with a limited prognosis. Epigenetic modifications have been shown to play an important role in tumor development and formation. Therefore, global analysis of DNA methylation patterns might reveal specific CpG sites that correlate with progression-free interval (PFI) after therapy. Methods: Twenty samples of advanced ovarian cancer with a predominantly serous papillary histological subtype were subjected to DNA methylation profiling. Illumina HumanMethylation27 BeadChip technology was used for simultaneous analysis of 27,578 CpG sites in >14,000 genes. Results: Differential DNA methylation of various cytosines correlated with PFI. However, this becomes only significant by classification according to PFI with a cutoff of >28 months. Longer survival was associated with hypomethylation at specific CpG sites (e.g. GREB1, TGIF and TOB1) and hypermethylation in other genes (e.g. TMCO5, PTPRN and GUCY2C). Gene ontology analysis revealed that differentially methylated genes were significantly overrepresented in the categories telomere organization, mesoderm development and immune regulation. Conclusion: Epigenetic modifications at specific CpG sites correlate with PFI in ovarian cancer. Therefore, such analysis might be of prognostic value.