BACKGROUND Solid tumors are angiogenesis dependent, and elevated levels of proangiogenic cytokines have been reported in a variety of histologies. Endostatin is an antiangiogenic fragment of the basement membrane protein, collagen XVIII. Because antiangiogenic protein fragments may be generated by tumor‐derived proteases, the authors sought to determine whether circulating levels of endostatin were elevated in patients with localized soft tissue sarcoma. METHODS The authors analyzed preoperative serum levels of endostatin, vascular endothelial growth factor (VEGF), and basic fibroblast growth factor (bFGF) in 25 patients (14 males and 11 females; mean age, 44 years) with soft tissue sarcoma. For each serum sample, two aliquots were assayed in duplicate using a competitive enzyme immunoassay. Serum levels were compared with levels from 34 age‐matched and gender‐matched volunteer blood donors. RESULTS Endostatin levels were significantly higher in sera from sarcoma patients than in sera from healthy controls (43.0 ng/mL vs. 25.8 ng/mL, respectively; P = 0.0002; Mann–Whitney U test). Significant elevations also were noted in VEGF and bFGF levels (P = 0.0002 and P = 0.0001, respectively). Furthermore, endostatin levels > 2 standard deviations above the control mean (55 ng/mL) were associated with an increased risk of tumor recurrence after resection (P = 0.047; log‐rank test). CONCLUSIONS Serum endostatin, VEGF, and bFGF levels are elevated in patients with soft tissue sarcoma. Elevated endostatin levels appear to be associated with tumor aggressiveness. The role of these cytokines in sarcoma angiogenesis and as potential targets for therapy warrants further study. Cancer 2001;91:1525–9. © 2001 American Cancer Society.

PURPOSE National guidelines recommend sentinel lymph node biopsy (SLNB) be offered to patients with > 10% likelihood of sentinel lymph node (SLN) positivity. On the other hand, guidelines do not recommend SLNB for patients with T1a tumors without high-risk features who have < 5% likelihood of a positive SLN. However, the decision to perform SLNB is less certain for patients with higher-risk T1 melanomas in which a positive node is expected 5%-10% of the time. We hypothesized that integrating clinicopathologic features with the 31-gene expression profile (31-GEP) score using advanced artificial intelligence techniques would provide more precise SLN risk prediction. METHODS An integrated 31-GEP (i31-GEP) neural network algorithm incorporating clinicopathologic features with the continuous 31-GEP score was developed using a previously reported patient cohort (n = 1,398) and validated using an independent cohort (n = 1,674). RESULTS Compared with other covariates in the i31-GEP, the continuous 31-GEP score had the largest likelihood ratio (G2 = 91.3, P < .001) for predicting SLN positivity. The i31-GEP demonstrated high concordance between predicted and observed SLN positivity rates (linear regression slope = 0.999). The i31-GEP increased the percentage of patients with T1-T4 tumors predicted to have < 5% SLN-positive likelihood from 8.5% to 27.7% with a negative predictive value of 98%. Importantly, for patients with T1 tumors originally classified with a likelihood of SLN positivity of 5%-10%, the i31-GEP reclassified 63% of cases as having < 5% or > 10% likelihood of positive SLN, for a more precise, personalized, and clinically actionable SLN-positive likelihood estimate. CONCLUSION These data suggest the i31-GEP could reduce the number of SLNBs performed by identifying patients with likelihood under the 5% threshold for performance of SLNB and improve the yield of positive SLNBs by identifying patients more likely to have a positive SLNB.

Our data show that extensive targeted metastasectomy in the setting of a tertiary center can be beneficial to patients with disseminated ThyrCa with persistent or recurrent distant disease, when used in conjunction with nonsurgical treatment modalities.