Phase II study of sunitinib malate, a multitargeted tyrosine kinase inhibitor in patients with relapsed or refractory soft tissue sarcomas. Focus on three prevalent histologies: leiomyosarcoma, liposarcoma and malignant fibrous histiocytoma.

Soft tissue sarcomas (STS) represent a diverse group of histologic subtypes with targetable molecular alterations, often treated as a single disease. Sunitinib malate is a multitargeted receptor tyrosine kinase inhibitor active in other solid tumors carrying similar alterations (i.e., imatinib mesylate-refractory gastrointestinal stromal tumors). This single-institution phase II study investigated the safety and efficacy of sunitinib malate in three common STS subtypes. Patients with documented unresectable or metastatic STS (liposarcoma, leiomyosarcoma and malignant fibrous histiocytoma [MFH]), measurable disease, and 3 or less prior lines of therapy were eligible. Treatment consisted of sunitinib malate, 50 mg daily, for 4 weeks every 6 weeks. Forty-eight patients were enrolled, and 35% were heavily pretreated (≥ 2 prior lines of chemotherapy). The safety profile resembled previously known sunitinib malate toxicities. Median progression-free and overall survivals for liposarcoma, leiomyosarcoma, and MFH were 3.9 and 18.6, 4.2 and 10.1 and 2.5 and 13.6 months, respectively. The 3-month progression-free rates in the untreated and pretreated (chemotherapy) patients with liposarcoma, leiomyosarcoma and MFH were 75% and 69.2%, 60%, and 62.5% and 25% and 44.4%, respectively. With the caveats that a minority of patients with potentially indolent or low-grade disease could have been included and the small numbers, a 3-month progression-free rate of >40% suggests activity for sunitinib malate at least in liposarcomas and leiomyosarcomas. Thus, we believe that further investigation in these susceptible STS subtypes is warranted.

Added value of a serum proteomic signature in the diagnostic evaluation of lung nodules.

BACKGROUND: Current management of lung nodules is complicated by nontherapeutic resections and missed chances for cure. We hypothesized that a serum proteomic signature may add diagnostic information beyond that provided by combined clinical and radiographic data. METHODS: Cohort A included 265 and cohort B 114 patients. Using multivariable logistic regression analysis we calculated the area under the receiver operating characteristic curve (AUC) and quantified the added value of a previously described serum proteomic signature beyond clinical and radiographic risk factors for predicting lung cancer using the integration discrimination improvement (IDI) index. RESULTS: The average computed tomography (CT) measured nodule size in cohorts A and B was 37.83 versus 23.15 mm among patients with lung cancer and 15.82 versus 17.18 mm among those without, respectively. In cohort A, the AUC increased from 0.68 to 0.86 after adding chest CT imaging variables to the clinical results, but the proteomic signature did not provide meaningful added value. In contrast, in cohort B, the AUC improved from 0.46 with clinical data alone to 0.61 when combined with chest CT imaging data and to 0.69 after adding the proteomic signature (IDI of 20% P = 0.0003). In addition, in a subgroup of 100 nodules between 5 and 20 mm in diameter, the proteomic signature added value with an IDI of 15% (P ≤ 0.0001). CONCLUSIONS: The results show that this serum proteomic biomarker signature may add value to the clinical and chest CT evaluation of indeterminate lung nodules. IMPACT: This study suggests a possible role of a blood biomarker in the evaluation of indeterminate lung nodules.