Response to Nivolumab and Ipilimumab in Microsatellite Instability-High (MSI-H) Cervical Carcinoma with Acquired Resistance to Pembrolizumab: A Case Report and Literature Review.

As the use of immune checkpoint inhibitors (ICIs) in treating a variety of cancer types has increased in recent years, so too have the number of reports on patients acquiring resistance to these therapies. Overcoming acquired resistance to immunotherapy remains an important need in the field of immuno-oncology. Herein, we present a case that suggests sequential administration of combination immunotherapy may be beneficial to advanced cervical cancer patients exhibiting acquired resistance to mono-immunotherapy. The patient's tumor is microsatellite instability-high (MSI-H), which is an important biomarker in predicting ICI response. Results from recent interim prospective studies using combination immunotherapy (eg, nivolumab and ipilimumab) with anti-PD-1 plus anti-CTLA-4 inhibitor following progression on anti-PD-1 inhibitors (eg, nivolumab) have shown anti-tumor activity in patients with advanced melanoma and metastatic urothelial carcinoma. We also introduce retrospective studies and case reports/case series of dual checkpoint inhibition with anti-PD-1 inhibitor plus anti-CTLA-4 inhibitor after progression on prior anti-PD/PD-L1 monotherapy. To date, there has been no prospective study on the use of combined anti-PD-1 and anti-CTLA-4 therapy at the time of progression on anti-PD-1 therapy in patients with MSI-H tumors or advanced cervical cancer. In this report, we provide evidence that supports future investigations into such treatments.

Artificial Intelligence-based Radiomics in the Era of Immuno-oncology.

The recent, rapid advances in immuno-oncology have revolutionized cancer treatment and spurred further research into tumor biology. Yet, cancer patients respond variably to immunotherapy despite mounting evidence to support its efficacy. Current methods for predicting immunotherapy response are unreliable, as these tests cannot fully account for tumor heterogeneity and microenvironment. An improved method for predicting response to immunotherapy is needed. Recent studies have proposed radiomics-the process of converting medical images into quantitative data (features) that can be processed using machine learning algorithms to identify complex patterns and trends-for predicting response to immunotherapy. Because patients undergo numerous imaging procedures throughout the course of the disease, there exists a wealth of radiological imaging data available for training radiomics models. And because radiomic features reflect cancer biology, such as tumor heterogeneity and microenvironment, these models have enormous potential to predict immunotherapy response more accurately than current methods. Models trained on preexisting biomarkers and/or clinical outcomes have demonstrated potential to improve patient stratification and treatment outcomes. In this review, we discuss current applications of radiomics in oncology, followed by a discussion on recent studies that use radiomics to predict immunotherapy response and toxicity.

Soticlestat, a novel cholesterol 24-hydroxylase inhibitor, reduces seizures and premature death in Dravet syndrome mice.

OBJECTIVE: Dravet syndrome is a severe developmental and epileptic encephalopathy (DEE) most often caused by de novo pathogenic variants in SCN1A. Individuals with Dravet syndrome rarely achieve seizure control and have significantly elevated risk for sudden unexplained death in epilepsy (SUDEP). Heterozygous deletion of Scn1a in mice (Scn1a+/- ) recapitulates several core phenotypes, including temperature-dependent and spontaneous seizures, SUDEP, and behavioral abnormalities. Furthermore, Scn1a+/- mice exhibit a similar clinical response to standard anticonvulsants. Cholesterol 24-hydroxlase (CH24H) is a brain-specific enzyme responsible for cholesterol catabolism. Recent research has indicated the therapeutic potential of CH24H inhibition for diseases associated with neural excitation, including seizures. METHODS: In this study, the novel compound soticlestat, a CH24H inhibitor, was administered to Scn1a+/- mice to investigate its ability to improve Dravet-like phenotypes in this preclinical model. RESULTS: Soticlestat treatment reduced seizure burden, protected against hyperthermia-induced seizures, and completely prevented SUDEP in Scn1a+/- mice. Video-electroencephalography (EEG) analysis confirmed the ability of soticlestat to reduce occurrence of electroclinical seizures. SIGNIFICANCE: This study demonstrates that soticlestat-mediated inhibition of CH24H provides therapeutic benefit for the treatment of Dravet syndrome in mice and has the potential for treatment of DEEs.