UGT1A1 Guided Cancer Therapy: Review of the Evidence and Considerations for Clinical Implementation

Multi-gene assays often include UGT1A1 and, in certain instances, may report associated toxicity risks for irinotecan, belinostat, pazopanib, and nilotinib. However, guidance for incorporating UGT1A1 results into therapeutic decision-making is mostly lacking for these anticancer drugs. We summarized meta-analyses, genome-wide association studies, clinical trials, drug labels, and guidelines relating to the impact of UGT1A1 polymorphisms on irinotecan, belinostat, pazopanib, or nilotinib toxicities. For irinotecan, UGT1A1*28 was significantly associated with neutropenia and diarrhea, particularly with doses ≥ 180 mg/m2, supporting the use of UGT1A1 to guide irinotecan prescribing. The drug label for belinostat recommends a reduced starting dose of 750 mg/m2 for UGT1A1*28 homozygotes, though published studies supporting this recommendation are sparse. There was a correlation between UGT1A1 polymorphisms and pazopanib-induced hepatotoxicity, though further studies are needed to elucidate the role of UGT1A1-guided pazopanib dose adjustments. Limited studies have investigated the association between UGT1A1 polymorphisms and nilotinib-induced hepatotoxicity, with data currently insufficient for UGT1A1-guided nilotinib dose adjustments

Response to sunitinib in combination with proton beam radiation in a patient with chondrosarcoma: a case report

<p>Abstract</p> <p>Introduction</p> <p>Chondrosarcoma is well-known to be primarily resistant to conventional radiation and chemotherapy.</p> <p>Case presentation</p> <p>We present the case of a 32-year-old Caucasian man with clear cell chondrosarcoma who presented with symptomatic recurrence in his pelvis and metastases to his skull and lungs. Our patient underwent systemic therapy with sunitinib and then consolidation with proton beam radiation to his symptomatic site. He achieved complete symptomatic relief with a significantly improved performance status and had an almost complete and durable metabolic response on fluorine-18-fluorodeoxyglucose positron emission tomography.</p> <p>Conclusions</p> <p>Our findings have important clinical implications and suggest novel clinical trials for this difficult to treat disease.</p

Combination therapy for renal cell cancer: what are possible options?

Antiangiogenic therapy has shown promise in the treatment of patients with renal cell carcinoma (RCC). Two classes of antiangiogenic drugs, the anti-vascular endothelial growth factor antibody bevacizumab and the tyrosine kinase inhibitors sorafenib, sunitinib and pazopanib, have shown efficacy in patients with RCC and are approved by the US Food and Drug Administration for treatment of this cancer. In practice, the clinical benefit of antiangiogenic drugs in RCC has been heterogeneous, and in patients who do respond, benefits are modest and/or short-lived. To improve efficacy, combination targeted therapy has been attempted, but with either very limited additional efficacy or nontolerable toxicities. Recent advances in the molecular understanding of tumor angiogenesis and mechanism of resistance, along with the rapid development of targeted drug discovery, have made it possible to further explore novel combination therapy for RCC

Pretreatment CT and PET Radiomics Predicting Rectal Cancer Patients in Response to Neoadjuvant Chemoradiotherapy

Background: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACRT). Material and methods: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET. Results: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1–3; 91% accuracy in predicting TRG 0–1 vs. TRG 2–3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores. Conclusion: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACRT. A larger cohort is warranted for further validation