Safety and Preliminary Efficacy of Once-Weekly Split-Dose Selinexor in Soft Tissue Sarcoma: Results of the Phase Ib METSSAR Clinical Trial.

BACKGROUND: The approved dose of Selinexor, 60 mg twice-weekly, is associated with several clinically relevant toxicities. Preclinical studies show that a sustained-release formulation of selinexor results in a lower toxicity profile. OBJECTIVE: The phase 1b METSSAR trial assessed the safety and tolerability of an alternative dosing schedule of selinexor (to mimic the sustained-release formulation) in advanced soft tissue sarcoma (STS) patients. PATIENTS AND METHODS: Selinexor was administered in a split-dose schedule (40 mg, 20 mg, 20 mg in the morning, afternoon, and evening, respectively) on days 1, 8, 15, and 22 of a 28-day cycle, until unacceptable toxicity or disease progression. The primary endpoint was the rate of grade ≥ 3 treatment-related adverse events (TRAEs). Secondary objectives were EORTC QLQ-C30 quality of life (QoL) assessment, and preliminary efficacy. RESULTS: Twenty patients with 12 STS subtypes were enrolled and received a median of four cycles of treatment. There were no grade ≥ 3 TRAEs. Dysgeusia, nausea, fatigue, and thrombocytopenia were the most common grade ≤ 2 TRAEs. No treatments were discontinued due to TRAE, but four patients (20%) required dose reduction. Median change in global health status (GHS) score from baseline to cycle 2 (by QLQ-C30 v3.0) was - 8.33, and only 39% of patients reported a clinically meaningful decline in GHS score (≥ 10 points). Median symptom scale scores on treatment were increased for fatigue (+12.35), nausea/vomiting (+18.52), and anorexia (+16.67), but reduced for pain (- 3.70). The median progression-free survival (PFS) was 4.0 months (95% confidence interval 1.9-7.5). CONCLUSIONS: Split-dose once-weekly selinexor was reasonably well tolerated in this heterogeneous group of advanced STS patients with a better, or at least similar, clinician- and patient-reported toxicity profile compared to the standard dosing regimen. Further clinical evaluation is warranted, as better dose delivery can lead to improved antitumor efficacy.

Semen and serum platinum levels in cisplatin-treated survivors of germ cell cancer.

BACKGROUND: Testicular cancer survivors often have impaired gonadal function possibly related to chemotherapy. Platinum is a heavy metal that can be detected at low levels in serum many years after treatment, it is not known whether platinum also persists in semen and if platinum persistence in semen is associated with impaired fertility. METHODS: Adult cisplatin-treated testicular cancer survivors were enrolled. High-Performance Liquid Chromatography-tandem mass spectrometry was used to measure semen and serum platinum levels. Semen quality and DNA Fragmentation Index (DFI) were assessed. RESULTS: From 11/2017 to 12/2019, 38 patients (median age 32 years; range: 19-52) were enrolled. Median cumulative cisplatin dose was 301 mg/m2 (range: 274-404). Platinum levels were higher in semen than in blood (p = 0.03). Semen platinum levels were not significantly associated with time from last cisplatin dosing (r = -0.34; p = 0.09) nor cumulative dose (r = -0.10, p = 0.63). Sperm concentration was correlated with time from last cisplatin dosing (r = 0.58, p < 0.001) but not with semen platinum level (r = -0.15, p = 0.46). DFI was not significantly associated with time from last cisplatin dosing (r = 0.55, p = 0.08) or semen platinum level (r = -0.32, p = 0.33). In four patients with serial semen samples, platinum level decreased and sperm concentration and motility increased over time. CONCLUSIONS: Platinum is detected in semen of testicular cancer survivors at higher levels than matched blood samples. These preliminary findings may have important implications for the reproductive health of survivors of advanced testicular cancer, further study is needed to assess the relationship between platinum persistence in semen and recovery of fertility postchemotherapy.

Predictive radiomics signature for treatment response to nivolumab in patients with advanced renal cell carcinoma.

INTRODUCTION: The anti-programmed cell death protein-1 (PD-1) immune checkpoint inhibitor nivolumab is currently approved for the treatment of patients with metastatic renal cell carcinoma (mRCC); approximately 25% of patients respond. We hypothesized that we could identify a biomarker of response using radiomics to train a machine learning classifier to predict nivolumab response outcomes. METHODS: Patients with mRCC of different histologies treated with nivolumab in a single institution between 2013 and 2017 were retrospectively identified. Patients were labelled as responders (complete response [CR]/partial response [PR]/durable stable disease [SD]) or non-responders based on investigator tumor assessment using RECIST 1.1 criteria. For each patient, lesions were contoured from pre-treatment and first post-treatment computed tomography (CT) scans. This information was used to train a radial basis function support vector machine classifier to learn a prediction rule to distinguish responders from non-responders. The classifier was internally validated by a 10-fold nested cross-validation. RESULTS: Thirty-seven patients were identified; 27 (73%) met the inclusion criteria. One hundred and four lesions were contoured from these 27 patients. The median patient age was 56 years, 78% were male, 89% had clear-cell histology, 89% had prior nephrectomy, and 89% had prior systemic therapy. There were 19 responders vs. eight non-responders. The lesions selected were lymph nodes (60%), lung metastases (23%), and renal/adrenal metastases (17%). For the classifier trained on the baseline CT scans, 69% accuracy was achieved. For the classifier trained on the first post-treatment CT scans, 66% accuracy was achieved. CONCLUSIONS: The set of radiomic signatures was found to have limited ability to discriminate nivolumab responders from non-responders. The use of novel texture features (two-point correlation measure, two-point cluster measure, and minimum spanning tree measure) did not improve performance.

Molecular profiling for precision cancer therapies.

The number of druggable tumor-specific molecular aberrations has grown substantially in the past decade, with a significant survival benefit obtained from biomarker matching therapies in several cancer types. Molecular pathology has therefore become fundamental not only to inform on tumor diagnosis and prognosis but also to drive therapeutic decisions in daily practice. The introduction of next-generation sequencing technologies and the rising number of large-scale tumor molecular profiling programs across institutions worldwide have revolutionized the field of precision oncology. As comprehensive genomic analyses become increasingly available in both clinical and research settings, healthcare professionals are faced with the complex tasks of result interpretation and translation. This review summarizes the current and upcoming approaches to implement precision cancer medicine, highlighting the challenges and potential solutions to facilitate the interpretation and to maximize the clinical utility of molecular profiling results. We describe novel molecular characterization strategies beyond tumor DNA sequencing, such as transcriptomics, immunophenotyping, epigenetic profiling, and single-cell analyses. We also review current and potential applications of liquid biopsies to evaluate blood-based biomarkers, such as circulating tumor cells and circulating nucleic acids. Last, lessons learned from the existing limitations of genotype-derived therapies provide insights into ways to expand precision medicine beyond genomics.