Introduction: Sunitinib is a multi-target, anti-angiogenic tyrosine kinase inhibitor and a key molecule in the treatment of metastatic renal cell carcinoma (mRCC). Since it first demonstrated its efficacy ten years ago, overall survival of mRCC has more than doubled, in part due to sunitinib. In most recent years, progress has been made in the comprehension of its mechanism of action and resistance. Areas Covered: In this article, clinical trials involving sunitinib in kidney cancer have been reviewed, defining its different indications in metastatic and localized RCC. The rationale of sunitinib’s efficacy, preclinical trials, past-clinical trials and ongoing clinical trials are summarized. Dose and scheme base are discussed, as the recommended dosage is frequently not well tolerated. Combination therapies appear to be toxic. Novel immunotherapies are changing the landscape of mRCC treatment and challenging sunitinib. Special attention has been paid towards cancer cell biology and immunity involved in treatment response. Expert Commentary: Sunitinib’s place in the therapeutic arsenal is being redefined with the arrival of major challengers. Dosage and scheduling of sunitinib remains a major challenge.

Leiomyosarcoma (LMS) is a rare, aggressive mesenchymal tumor with smooth muscle differentiation. LMS is one of the most common histologic subtypes of soft tissue sarcoma; it most frequently occurs in the extremities, retroperitoneum, or uterus. LMS often demonstrates aggressive tumor biology, with a higher risk of developing distant metastatic disease than most sarcoma histologic types. The prognosis is poor, particularly in patients with uterine disease, and there is a need for the development of more effective therapies. Genetically, LMS is karyotypically complex and characterized by a low tumor mutational burden, with frequent alterations in TP53, RB1, PTEN, and DNA damage response pathways that may contribute to resistance against immune-checkpoint blockade monotherapy. The LMS immune microenvironment is highly infiltrated with tumor-associated macrophages and tumor-infiltrating lymphocytes, which may represent promising biomarkers. This review provides an overview of the clinical and pathologic behavior of both soft tissue and uterine LMS and summarizes the genomic and immune characteristics of these tumors and how they may provide opportunities for the development of biomarker-based immune therapies.

Introduction: Undifferentiated pleomorphic sarcoma (UPS) can be associated with a relatively dense immune infiltration. Immune checkpoint inhibitors (anti-PD1, anti-PDL1, and anti-CTLA4) are effective in 20% of UPS patients. We characterize the immune microenvironment of UPS and its association with oncologic outcomes.Material and methods: Surgically resected UPS samples were stained by immunohistochemistry (IHC) for the following: tumor-associated immune cells (CD3, CD8, CD163, CD20), immune checkpoints (stimulatory: OX40, ICOS; inhibitory: PD-L1, LAG3, IDO1, PD1), and the adenosine pathway (CD73, CD39). Sections were reviewed for the presence of lymphoid aggregates (LA). Clinical data were retrospectively obtained for all samples. The Wilcoxon rank-sum and Kruskal-Wallis tests were used to compare distributions. Correlations between biomarkers were measured by Spearman correlation. Univariate and multivariate Cox models were used to identify biomarkers associated with overall survival (OS) and disease-free survival (DFS). Unsupervised clustering was performed, and Kaplan-Meier curves and log-rank tests used for comparison of OS and DFS between immune clusters.Results: Samples analyzed (n=105) included 46 primary tumors, 34 local recurrences, and 25 metastases. LA were found in 23% (n=10/43), 17% (n=4/24), and 30% (n=7/23) of primary, recurrent, and metastatic samples, respectively. In primary UPS, CD73 expression was significantly higher after preoperative radiation therapy (p=0.009). CD39 expression was significantly correlated with PD1 expression (primary: p=0.002, recurrent: p=0.004, metastatic: p=0.001), PD-L1 expression (primary: p=0.009), and CD3+ cell densities (primary: p=0.016, recurrent: p=0.043, metastatic: p=0.028). In recurrent tumors, there was a strong correlation between CD39 and CD73 (p=0.015), and both were also correlated with CD163+ cell densities (CD39 p=0.013; CD73 p&lt;0.001). In multivariate analyses, higher densities of CD3+ and CD8+ cells (Cox Hazard Ratio [HR]=0.33; p=0.010) were independently associated with OS (CD3+, HR=0.19, p<0.001; CD8+, HR= 0.33, p=0.010) and DFS (CD3+, HR=0.34, p=0.018; CD8+, HR=0.34, p= 0.014). Unsupervised clustering of IHC values revealed three immunologically distinct clusters: immune high, intermediate, and low. In primary tumors, these clusters were significantly associated with OS (log-rank p<0.0001) and DFS (p<0.001).Conclusion: We identified three immunologically distinct clusters of UPS Associated with OS and DFS. Our data support further investigations of combination anti-PD-1/PD-L1 and adenosine pathway inhibitors in UPS.