Artificial intelligence for predictive biomarker discovery in immuno-oncology: a systematic review.

BACKGROUND: The widespread use of immune checkpoint inhibitors (ICIs) has revolutionised treatment of multiple cancer types. However, selecting patients who may benefit from ICI remains challenging. Artificial intelligence (AI) approaches allow exploitation of high-dimension oncological data in research and development of precision immuno-oncology. MATERIALS AND METHODS: We conducted a systematic literature review of peer-reviewed original articles studying the ICI efficacy prediction in cancer patients across five data modalities: genomics (including genomics, transcriptomics, and epigenomics), radiomics, digital pathology (pathomics), and real-world and multimodality data. RESULTS: A total of 90 studies were included in this systematic review, with 80% published in 2021-2022. Among them, 37 studies included genomic, 20 radiomic, 8 pathomic, 20 real-world, and 5 multimodal data. Standard machine learning (ML) methods were used in 72% of studies, deep learning (DL) methods in 22%, and both in 6%. The most frequently studied cancer type was non-small-cell lung cancer (36%), followed by melanoma (16%), while 25% included pan-cancer studies. No prospective study design incorporated AI-based methodologies from the outset; rather, all implemented AI as a post hoc analysis. Novel biomarkers for ICI in radiomics and pathomics were identified using AI approaches, and molecular biomarkers have expanded past genomics into transcriptomics and epigenomics. Finally, complex algorithms and new types of AI-based markers, such as meta-biomarkers, are emerging by integrating multimodal/multi-omics data. CONCLUSION: AI-based methods have expanded the horizon for biomarker discovery, demonstrating the power of integrating multimodal data from existing datasets to discover new meta-biomarkers. While most of the included studies showed promise for AI-based prediction of benefit from immunotherapy, none provided high-level evidence for immediate practice change. A priori planned prospective trial designs are needed to cover all lifecycle steps of these software biomarkers, from development and validation to integration into clinical practice.

Mexiletine is an effective antimyotonia treatment in myotonic dystrophy type 1.

OBJECTIVE: To determine if mexiletine is safe and effective in reducing myotonia in myotonic dystrophy type 1 (DM1). BACKGROUND: Myotonia is an early, prominent symptom in DM1 and contributes to decreased dexterity, gait instability, difficulty with speech/swallowing, and muscle pain. A few preliminary trials have suggested that the antiarrhythmic drug mexiletine is useful, symptomatic treatment for nondystrophic myotonic disorders and DM1. METHODS: We performed 2 randomized, double-blind, placebo-controlled crossover trials, each involving 20 ambulatory DM1 participants with grip or percussion myotonia on examination. The initial trial compared 150 mg of mexiletine 3 times daily to placebo, and the second trial compared 200 mg of mexiletine 3 times daily to placebo. Treatment periods were 7 weeks in duration separated by a 4- to 8-week washout period. The primary measure of myotonia was time for isometric grip force to relax from 90% to 5% of peak force after a 3-second maximum grip contraction. EKG measurements and adverse events were monitored in both trials. RESULTS: There was a significant reduction in grip relaxation time with both 150 and 200 mg dosages of mexiletine. Treatment with mexiletine at either dosage was not associated with any serious adverse events, or with prolongation of the PR or QTc intervals or of QRS duration. Mild adverse events were observed with both placebo and mexiletine treatment. CONCLUSIONS: Mexiletine at dosages of 150 and 200 mg 3 times daily is effective, safe, and well-tolerated over 7 weeks as an antimyotonia treatment in DM1. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that mexiletine at dosages of 150 and 200 mg 3 times daily over 7 weeks is well-tolerated and effective in reducing handgrip relaxation time in DM1.

Neonatal diethylstilbestrol alters blood pressure and CNS drinking response in SHR and WKY rats.

Neonatal SHR and WKY rats were treated with diethylstilbestrol or propylene glycol (controls). Control SHR had higher blood pressures than WKY rats. Neonatal diethylstilbestrol treatment delayed the onset and full expression of hypertension in the male SHR but had no effect on blood pressure in the other animals. Neonatal diethylstilbestrol treatment had an adverse effect on body weights of male SHR and WKY rats through 98 days of age (not statistically decreased thereafter). Adult female SHR and WKY rats treated neonatally with diethylstilbestrol had body weights significantly greater than the control females. Neonatal treatment with diethylstilbestrol resulted in precocious puberty in female SHR and WKY rats. Control female SHR and WKY rats and female SHR treated neonatally with diethylstilbestrol had attenuated angiotensin - II induced drinking response from the central administration of estrogen in adulthood. The angiotensin II - induced drinking response was not significantly attenuated by central estrogen in adult WKY females exposed neonatally to diethylstilbestrol. Neonatal diethylstilbestrol treatment of WKY female rats appears to have altered neuroendocrine secretions that control CNS drinking behavior.