Introduction: The emergence of cancer immunotherapy has revolutionized cancer treatment, offering remarkable outcomes for patients across various malignancies. However, the heterogeneous response to immunotherapy underscores the necessity of understanding additional factors influencing treatment efficacy. Among these factors, the human microbiota has garnered significant attention for its potential role in modulating immune response. Body: This review explores the intricate relationship between the human microbiota and cancer immunotherapy, highlighting recent advances and potential mechanisms underlying microbial influence on treatment outcomes. Conclusion: Insights into the microbiome’s impact on immunotherapy response not only deepen our understanding of cancer pathogenesis but also hold promise for personalized therapeutic strategies aimed at optimizing patient outcomes.

Purpose: Cancer immunotherapy has transformed oncology, but underserved populations face persistent disparities in access and outcomes. This review explores how artificial intelligence (AI) can help mitigate these barriers. Methods: We conducted a narrative review based on peer-reviewed literature selected for relevance to artificial intelligence, cancer immunotherapy, and healthcare challenges, without restrictions on publication date. We searched three major electronic databases: PubMed, IEEE Xplore, and arXiv, covering both biomedical and computational literature. The search included publications from January 2015 through April 2024 to capture contemporary developments in AI and cancer immunotherapy. Results: AI tools such as machine learning, natural language processing, and predictive analytics can enhance early detection, personalize treatment, and improve clinical trial representation for historically underrepresented populations. Additionally, AI-driven solutions can aid in managing side effects, expanding telehealth, and addressing social determinants of health (SDOH). However, algorithmic bias, privacy concerns, and data diversity remain major challenges. Conclusions: With intentional design and implementation, AI holds the potential to reduce disparities in cancer immunotherapy and promote more inclusive oncology care. Future efforts must focus on ethical deployment, inclusive data collection, and interdisciplinary collaboration.