Serous ovarian borderline tumors (s-BOTs) and advanced stage invasive ovarian cancer (IOC) differ regarding morphological, clinical and molecular characteristics. s-BOTs show an atypical degree of proliferation lacking obvious stromal invasion . According to the Malpica grading system s-BOTs may be associated with low-grade IOC , while high grade IOCs show marked nuclear atypia and mitotic activity .
Usually s-BOTs are characterized by their excellent clinical outcome as compared to advanced stage IOC [3, 4]. Though, it needs to be noted that, in contrast to IOC, s-BOTs frequently affect younger patients and might, in certain rare but not insignificant cases, also progress into low grade IOC [1, 5]. Since it remains challenging to identify patients at risk, it has been discussed repeatedly, to which extent so called implants, representing extra-ovarian lesions coincidentally occurring in about 20% of particularly serous s-BOT cases, influence patients’ prognosis [1, 4, 6]. While it is broadly accepted that implants presenting with invasive features are of adverse prognostic significance [7–9], the impact of non-invasive implants is less clear. As stated by the WHO non-invasive implants have no to little effect on patients’ outcome, while invasive implants are associated with increased recurrence rates and a significantly reduced 10 year survival . Hence it is critical to further investigate implant pathophysiology and genetic origin.
It remains to be elusive whether implants actually arise independently alongside the ovarian s-BOT as part of a field effect, or whether they may directly develop from the ovarian primary resembling its metastasis. Within the first scenario implants are supposed to be of heterogeneous origin and thus comprise a different genetic pattern as compared to the ovarian tumor while metastases are postulated to rise in a clonal manner and thus should closely mimic their primary. In general, since clonality of neoplastic lesions is discussed to be of prognostic significance, determining the mutation status of s-BOT and their corresponding implants may turn out to be of clinical use.
To address this question, this study employed pyrosequencing of KRAS (Kirsten rat sarcoma viral oncogene homolog) and BRAF (v-raf murine sarcoma viral oncogene homolog B1) hot spot regions in s-BOTs and corresponding implants. Since both KRAS and BRAF are known to be frequently mutated in s-BOTs , they are especially suitable to indicate a possible genetic descent of extraovarian implants in s-BOT patients. BRAF and KRAS are upstream activators of the mitogen-activated protein kinase (MAPK) cascade which is commonly hyper-activated in different types of human cancer .
Further, p16INK4a (p16) and p53 immunoreactivity of s-BOTs and associated implants was compared. p16 acts as a cell cycle inhibitor antagonizing MAPK signaling and is compensatory up-regulated under hyper-proliferative conditions including high risk human papilloma virus infection or oncogene activation [13–15]. Accumulation of the tumor suppressor protein p53 was observed in malignant cells  thus leading to the assumption that mutation in TP53 may cause overexpression of p53 protein [16, 17]. Up to now the mechanism leading to p53 up-regulation remains to be controversial . Today, assessing p53 by immunohistochemistry instead of TP53 mutation analysis is a well-established method [18–21] and has been intensively studied [22, 23]. However, it needs to be mentioned that so far p53 immunohistochemistry may not fully resemble TP53 mutation testing. Though high grade IOC is characterized by p53 overexpression, the latter is considered a seldom event in both low grade IOC [24, 25] and in s-BOTs . We included both p16 and p53 immunohistochemistry in order to investigate whether these markers might be useful to match implants and their corresponding s-BOT(s).
Ultimately, our goal was to clarify whether implants actually resemble the mutation (regarding KRAS and BRAF) or protein expression (regarding p16 and p53) profile of corresponding s-BOTs. Further insights on origin and genetic causes of both s-BOTs and corresponding implants may help to identify patient subgroups that might benefit from more individualized therapy.