VETC, Prognostic and Predictive Value in Renal Cell Carcinoma and Adrenal Carcinoma
Metastasis is the main cause of death in cancer patients and often epithelial-to-mesenchymal transition (EMT) is advocated as the basic mechanism. Recently Fang and colleagues described an EMT-independent process of metastasis in hepatocellular carcinoma (HCC): endothelium covers small cluster of tumor cells allowing tumor dissemination. This process of angiogenesis, named VETC (vessels that encapsulate tumor clusters) in HCC literature, has been described under different names in other cancer types. Furthermore, the investigators confirmed the negative impact of VETC on patients' prognosis on a large multicenter cohort of HCCs. Moreover, Fang et al demonstrated that patients affected by VETC-positive HCC benefit more from sorafenib therapy. Interestingly, this type of angiogenesis was also found in renal cell carcinoma, adrenal gland pheochromocytoma, thyroid follicular carcinoma and alveolar soft part sarcoma (ASPS) and associated to prognosis. Moreover, the distinction between benign and malignant neoplasms of the adrenal gland is a complex matter, being the established criteria still lacking a strong reproducibility. Several tyrosine kinase inhibitors are available for different cancer types; among them, HCC, RCC, ASPS, and TC may benefit from the so-called antiangiogenic tyrosine kinase inhibitors (aTKI) (such as sunitinib, sorafenib, pazopanib). A general (histotype-independent) validation of the prognostic role of VETC is missing. Moreover, inhibitors of tyrosine-kinase vascular endothelial growth factor receptors (VEGFR-TKI), represent an effective treatment for different cancer types, but predictive markers are still needed. In addition, novel systemic immunotherapy agents are being approved in many cancer types, as alternative to angiogenesis inhibitors. A broader frame including metastatic mechanisms, tumor microenvironment (TME, i.e. angiogenesis and immune infiltrate) and treatment response could answer to several needs currently unmet. Bayesian networks and causal models can be employed to effectively draw conclusions from retrospective data. The aim of the present study is to investigate in patients with RCC and adrenal carcinoma (AC) the VETC-expression on tumor tissue, correlating the results with clinical data, patients characteristics, and outcome.
Start: January 2021