Uveal melanoma metastases develop in 6.5-35% of patients, most commonly to the liver. Metastatic uveal melanoma (MUM) survival is poor, with 5-7 months of median survival. We reviewed retrospectively all patients with MUM diagnosed between January 1990 and December 2008 at our institution. We analyzed a total of 58 patients with a median age of 61 years (31-84 years). Median time for metastases development was 25.63 months (0.17-102.43 months). Fifty-six patients had hepatic involvement, 63.8% bilobar and 51.7% had more than or equal to five hepatic metastatic lesions. Sixteen patients (27.6%) had two or more organs involved. Six patients (10.71%) were treated with surgery, 25 patients (44.67%) received systemic chemotherapy, and 23 (41.07%) had best supportive care (BSC). The median overall survival (OS) for all the patients was 10.83 months [95% confidence interval (CI): 6.92-14.74]. Patients who had undergone chemotherapy presented 10.83 months (95% CI: 5.35-16.308) of median OS whereas the patients who did not undergo this treatment had an OS of 8.033 months (95% CI: 2.46-13.61). There were more patients with poor survival characteristics such as worse Eastern Cooperative Oncology Group performance status in the BSC group. OS was poor in treated and BSC patients. Differences in survival are more likely to be related to patient characteristics rather than to a chemotherapy effect. Patients with MUM should be included in clinical trials evaluating other options with newer agents.

• Bone is a common metastatic site in renal cell carcinoma (RCC). • HGF/c-Met pathway is particularly relevant in tumors with bone metastases. • c-Met/HGF pathway is involved in RCC progression, conferring poor prognosis. • Several c-Met targeting therapies are currently in clinical development. • c-Met expression is an important therapeutic target in RCC with bone metastases.

Osteosarcoma (OS) is a rare condition with very poor prognosis in a metastatic setting. Basic research has enabled a better understanding of OS pathogenesis and the discovery of new potential therapeutic targets. Phase I and II clinical trials are already ongoing, with some promising results for these patients. This article reviews OS pathogenesis and new potential therapeutic targets.

The vast array of metabolic adaptations that cancer cells are capable of assuming, not only support their biosynthetic activity, but also fulfill their bioenergetic demands and keep their intracellular reduction–oxidation (redox) balance. Spotlight has recently been placed on the energy metabolism reprogramming strategies employed by cancer cells to proliferate. Knowledge regarding soft tissue and bone sarcomas metabolome is relatively sparse. Further characterization of sarcoma metabolic landscape may pave the way for diagnostic refinement and new therapeutic target identification, with benefit to sarcoma patients. This review covers the state-of-the-art knowledge on cancer metabolomics and explores in detail the most recent evidence on soft tissue and bone sarcoma metabolomics.

Introduction: Somatostatin analogs (SSAs) are used as part of standard treatment for advanced neuroendocrine tumors (NETs). The mechanisms behind the antiproliferative action of SSAs remain largely unknown, but a connection with the mammalian target of rapamycin (mTOR) signaling pathway has been suggested. Our purpose was to evaluate the activation status of the AKT/mTOR pathway in advanced metastatic NETs and identify biomarkers of response to SSA therapy. Patients and methods: Expression of phosphatase and tensin homolog (PTEN), phosphorylated (p)-AKT(Ser473), and p-S6(Ser240/244) was evaluated using immunohistochemistry in archival paraffin samples from 23 patients. Expression levels were correlated with clinicopathological parameters and progression-free survival under treatment with SSAs. Results: A positive association between p-AKT and p-S6 expression was identified (P = 0.01) and higher expression of both markers was observed in pancreatic NETs. AKT/mTOR activation was observed without the loss of PTEN expression. Tumors showing AKT/mTOR signaling activation progressed faster when treated with SSAs: higher expression of p-AKT or p-S6 predicted a median progression-free survival of 1 month vs 26.5 months for lower expression (P = 0.02). Conclusion: Constitutive activation of the AKT/mTOR pathway was associated with shorter time-to-progression in patients undergoing treatment with SSAs. Larger case series are needed to validate whether p-AKT(Ser473) and p-S6(Ser240/244) can be used as prognostic markers of response to therapy with SSAs.

Background: Soft tissue sarcomas (STSs) histopathological classification system and the clinical and molecular-based tools that are currently employed to estimate its prognosis have several limitations, impacting prognostication and treatment. Clinically driven molecular profiling studies may cover these gaps and offer alternative tools with superior prognostication capability and enhanced precision and personalized treatment approaches identification ability. Materials and Methods /Results: We performed DNA sequencing (DNA-seq) and RNA sequencing (RNA-seq) to portray the molecular profile of 102 samples of high-grade STS, comprising the three most common STS histotypes. The analysis of RNA-seq data using unsupervised machine learning models revealed previously unknown molecular patterns, identifying four transcriptomic subtypes/clusters (TCs). This TC-based classification has a clear prognostic value (in terms of overall survival (OS) and disease-free survival (DFS)), a finding that was externally validated using independent patient cohorts. The prognostic value of this TC-based classification outperforms the prognostic accuracy of clinical-based (SARCULATOR nomograms) and molecular-based (CINSARC) prognostication tools, being one of the first molecular-based classifications capable of predicting OS in STS. The analysis of DNA-seq data from the same cohort revealed numerous and, in some cases, never documented molecular targets for precision treatment across different transcriptomic subtypes. The functional and predictive value of each genomic variant was analyzed using the Molecular Tumor Board Portal. Conclusions : This newly identified TC-based classification offers a superior prognostic value when compared with current gold-standard clinical and molecular-based prognostication tools, and identifies novel molecular targets for precision treatment, representing a cutting-edge tool for predicting prognosis and guiding treatment across different stages of STS.