The increasing burden of cancer globally necessitates innovative approaches for diagnosis, prognosis, and treatment. This article explores the transformative impact of genomics and artificial intelligence (AI) in precision oncology, addressing how their convergence is reshaping cancer care and its challenges. Methods: This review synthesizes current research on the applications of genomics, including next-generation sequencing, and AI, such as machine learning and deep learning, across the cancer care continuum. It examines their roles in identifying genetic variants, assessing cancer risk, guiding targeted therapies and immunotherapy, predicting treatment response, and enabling early detection through liquid biopsies. Results: Genomics and AI are revolutionizing oncology by enabling personalized treatment strategies, improving early detection, and overcoming drug resistance. AI enhances the interpretation of complex genomic data, facilitates drug repurposing, and accelerates the development of novel therapeutics. However, challenges remain regarding data standardization, interpretability, bias in AI algorithms, and ethical considerations. Conclusions: The integration of genomics and AI holds immense potential to advance precision oncology, offering more effective, equitable, and sustainable cancer care. Addressing current challenges and fostering interdisciplinary training will be crucial to fully harness these technologies and redefine oncology practice.

Background/Objectives: Artificial intelligence and large language models like ChatGPT and Google’s Gemini are promising tools with remarkable potential to assist healthcare professionals. This study explores ChatGPT and Gemini’s potential utility in assisting clinicians during the first evaluation of patients with suspected neurogenetic disorders. Methods: By analyzing the model’s performance in identifying relevant clinical features, suggesting differential diagnoses, and providing insights into possible genetic testing, this research seeks to determine whether these AI tools could serve as a valuable adjunct in neurogenetic assessments. Ninety questions were posed to ChatGPT (Versions 4o, 4, and 3.5) and Gemini: four questions about clinical diagnosis, seven about genetic inheritance, estimable recurrence risks, and available tests, and four questions about patient management, each for six different neurogenetic rare disorders (Hereditary Spastic Paraplegia type 4 and type 7, Huntington Disease, Fragile X-associated Tremor/Ataxia Syndrome, Becker Muscular Dystrophy, and FacioScapuloHumeral Muscular Dystrophy). Results: According to the results of this study, GPT chatbots demonstrated significantly better performance than Gemini. Nonetheless, all AI chatbots showed notable gaps in diagnostic accuracy and a concerning level of hallucinations. Conclusions: As expected, these tools can empower clinicians in assessing neurogenetic disorders, yet their effective use demands meticulous collaboration and oversight from both neurologists and geneticists.

Background: Mutations in the FBXO7 gene (PARK15) cause an autosomal recessive, early-onset neurodegenerative disorder typically presenting as Parkinsonian-Pyramidal Syndrome (PPS). Despite its recognition, the high phenotypic variability often delays diagnosis. Here, we report a novel Italian family and synthesize data from all published cases to date, offering an updated clinical and molecular overview of the disease. Methods: We performed clinical and molecular characterization of a newly identified family. Furthermore, we conducted a systematic literature review (from 2008 to 2026) to aggregate clinical, genetic, and geographic data of all reported PARK15 cases. Results: Two siblings presented with a complex phenotype including early-onset parkinsonism, cognitive decline, psychiatric symptoms, and aphasia-type speech disorders. Genetic analyses identified two novel likely pathogenic variants: a missense substitution in the UBL domain (p.Ile74Met) and a frameshift indel (p.Val233GlufsTer8). The literature review (incorporating clinical data from Europe, Asia, and South America) confirms a high prevalence of postural instability (87.5%), bradykinesia (83.3%), and pyramidal signs (~60%). We observed a distinct distribution of variants: missense mutations cluster in the N-terminal UBL and F-box domains, while truncating variants are more common in the C-terminal region. Discussion: Our findings expand the FBXO7 mutational landscape and underscore the “atypical” clinical markers, such as pyramidal signs and cognitive decline, that distinguish PARK15 from other recessive forms of parkinsonism like PARK2 and PARK6. The dual role of FBXO7 in mitochondrial quality control and proteasomal assembly suggests a broad disruption of cellular homeostasis. These observations refine genotype–phenotype correlations and may guide variant interpretation in routine diagnostic settings.