Selinexor for the treatment of recurrent or metastatic salivary gland tumors: Results from the GEMS-001 clinical trial.

OBJECTIVES: We aimed to evaluate the activity of selinexor, an oral selective inhibitor of nuclear export, in patients with recurrent or metastatic salivary gland tumors (SGT). METHODS: GEMS-001 is an open-label Phase 2 study for patients with recurrent or metastatic SGT with two parts. In Part 1 of the protocol, patients had tumor samples profiled with targeted next generation sequencing as well as immunohistochemistry for androgen receptor, HER-2 and ALK. For Part 2, patients with no targeted therapies available were eligible to receive selinexor 60 mg given twice weekly every 28 days. The primary endpoint was objective response rate. Secondary endpoints included progression-free survival (PFS) and prevalence of druggable alterations across SGT. RESULTS: One hundred patients were enrolled in GEMS-001 and underwent genomic and immunohistochemistry profiling. A total of 21 patients who lacked available matched therapies were treated with selinexor. SGT subtypes (WHO classification) included adenoid cystic carcinoma (n = 10), salivary duct carcinoma (n = 3), acinic cell carcinoma (n = 2), myoepithelial carcinoma (n = 2), carcinoma ex pleomorphic adenoma (n = 2) and other (n = 2). Of 18 evaluable patients, stable disease (SD) was observed in 17 patients (94%) (SD ≥6 months in 7 patients (39%)). However, no objective responses were observed. The median PFS was 4.9 months (95% confidence interval, 3.4-10). The most common treatment-related Grade 1-2 adverse events were nausea [17 patients (81%)], fatigue [16 patients (76%)], and dysgeusia [12 patients (57%)]. Most common treatment-related Grade 3-4 adverse events were hyponatremia [3 patients (14%)], neutrophil count decrease [3 patients (14%)] and cataracts [2 patients (10%)]. No treatment-related deaths were observed. CONCLUSIONS: Although tumor reduction was observed across participants, single agent selinexor anti-tumor activity was limited.

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.

Quality of patient-reported outcomes in oncology clinical trials using immune checkpoint inhibitors: A systematic review.

BACKGROUND: There are limited data regarding the quality of patient-reported outcome (PRO) data in immune checkpoint inhibitor (ICI) clinical trial publications. METHODS: A systematic search of citations from various databases was conducted to identify prospective clinical trials involving ICI in advanced tumors from 2003 to 2020. A 30-point score was adapted from the CONSORT PRO extension statement to assess adherence to CONSORT PRO reporting. Linear regression was used to identify factors associated with quality reporting. RESULTS: After the review of 8058 articles, 33 trials were included with ICIs as either monotherapy (91%) or part of a combination regimen (9%). The median score was 23.5 points (range 15-29). In the majority of cases (82%), PROs were reported in a separate publication from the original study. Most of the trials were conducted in the metastatic setting and predominantly in melanoma, lung, and renal cell carcinoma (RCC) (73%). Univariate analysis revealed that trials with greater than 250 patients were associated with a higher score. The score was more likely to be lower in disease sites other than melanoma, lung, and RCC and was higher in the KEYNOTE than in the CHECKMATE trial series. There was no significant correlation between the score and whether a trial met its primary end-point or if the trial improved or worsened the quality of life. In the multivariate analysis, the number of patients enrolled to the trial, disease site, and trial series remained significant. CONCLUSIONS: The quality of reporting of PROs in ICI phase II and III clinical trials is heterogeneous across various cancer sites. As PRO data are increasingly used to counsel patients and complement clinical decision making, innovative and collaborative efforts are required to improve the reporting of these essential data.

A phase 1b trial of selinexor, a first-in-class selective inhibitor of nuclear export (SINE), in combination with doxorubicin in patients with advanced soft tissue sarcomas (STS).

BACKGROUND: Selinexor is a first-in-class selective inhibitor of nuclear export (SINE) compound with single-agent activity in soft tissue sarcoma (STS). The study's aim was to determine the safety and efficacy of selinexor in combination with doxorubicin in patients with locally advanced/metastatic STS. METHODS: This phase 1b study used a mTPI design. Patients received selinexor at either 60 or 80 mg weekly PO plus doxorubicin (75 mg/m2 IV q21 days). Patients with clinical benefit (defined as ≥stable disease via RECIST 1.1) after six cycles of combination treatment received maintenance selinexor until disease progression or unacceptable toxicity. Disease assessments were conducted every two cycles. Pharmacokinetic data were collected on the first three patients per dose level. RESULTS: Twenty-five patients were enrolled (20 female, ECOG 0/1: 13/12, median age 57 years [range 21-74]). Disease subtypes included leiomyosarcoma (n = 6), malignant peripheral nerve sheath tumour (n = 3) and other sarcomas (n = 16). Three (12%) and 22 (88%) patients were treated at 60 mg and 80 mg of selinexor, respectively. The most common ≥G3 drug-related adverse events (AEs) were haematological, including neutropenia (56%), febrile neutropenia (28%) and anaemia (24%). There were four dose-limiting toxicities (febrile neutropenia (x2), vomiting, fatigue) all at the 80 mg dose level. There was one death secondary to heart failure. Of the 24 evaluable patients, 5 (21%) had a partial response and 15 (63%) had SD as best response. The estimated median progression-free survival (PFS) and overall survival (OS) were 5.5 (95% CI:4.1-5.7) and 10.5 (95% CI:7.5-14) months. CONCLUSION: In a heterogeneous group of patients with locally advanced/metastatic STS, the combination of selinexor and doxorubicin fulfilled the prespecified boundary for tolerability.

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.

Precision Medicine in Head and Neck Cancer: Myth or Reality?

Standard treatment in head and neck squamous cell carcinoma (HNSCC) is limited currently with decisions being made primarily based on tumor location, histology, and stage. The role of the human papillomavirus in risk stratification is actively under clinical trial evaluations. The molecular complexity and intratumoral heterogeneity of the disease are not actively integrated into management decisions of HNSCC, despite a growing body of knowledge in these areas. The advent of the genomic era has delivered vast amounts of information regarding different cancer subtypes and is providing new therapeutic targets, which can potentially be elucidated using next-generation sequencing and other modern technologies. The task ahead is to expand beyond the existent armamentarium by exploiting beyond the genome and perform integrative analysis using innovative systems biology methods, with the goal to deliver effective precision medicine-based theragnostic options in HNSCC.