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Clinical Application Progress of Artificial Intelligence in Pancreatic Cancer: From Diagnosis to Immunotherapy
Zehao Wei1, Xuejian Liu2, Zheng Zhang1
1Department of Gastroenterology, Affiliated Hospital of Jiangsu University, Jiangsu University, Zhenjiang, China.
Abstract:
Pancreatic cancer is one of the most lethal malignancies, characterized by difficulties in early diagnosis, limited therapeutic options, and generally poor patient prognosis. In recent years, immunotherapy has provided new opportunities for the treatment of pancreatic cancer; however, its clinical efficacy has been substantially constrained by the complex tumor microenvironment (TME) and immune evasion mechanisms. With the rapid advancement of artificial intelligence (AI) technologies, AI has demonstrated great potential in the early detection of pancreatic cancer, prediction of immunotherapeutic responses, and design of personalized treatment strategies. This review systematically summarizes the latest advances in the application of artificial intelligence in pancreatic cancer immunotherapy, with a particular focus on key AI assisted technologies, including tumor immune microenvironment characterization, prediction of genetic mutation profiles, nanomedicine design, and dynamic monitoring of therapeutic responses. By integrating single cell sequencing and multi-omics data analyses, we discuss how AI can effectively address critical bottlenecks in immunotherapy. In addition, this article analyzes current technical challenges and future development trends, aiming to provide a theoretical foundation and practical guidance for achieving precision immunotherapy in pancreatic cancer and to promote clinical translation and application in this field.
Insights
Artificial intelligence (AI) offers new hope for pancreatic cancer immunotherapy by overcoming challenges like complex tumor microenvironments. AI aids in early detection, treatment response prediction, and personalized strategies for better patient outcomes.
Area of Science:
- Oncology
- Immunology
- Artificial Intelligence
Background:
- Pancreatic cancer is a highly lethal malignancy with poor prognosis due to diagnostic challenges and limited treatments.
- Immunotherapy shows promise for pancreatic cancer but faces significant hurdles from the tumor microenvironment and immune evasion.
- Artificial intelligence (AI) presents a transformative potential for improving pancreatic cancer diagnosis and treatment.
Purpose of the Study:
- To systematically review the latest advancements in AI applications for pancreatic cancer immunotherapy.
- To highlight key AI-assisted technologies in characterizing the tumor immune microenvironment and predicting treatment responses.
- To provide insights into AI's role in nanomedicine design and therapeutic monitoring for precision immunotherapy.
Main Methods:
- Review of recent literature on AI applications in pancreatic cancer immunotherapy.
- Integration of single-cell sequencing and multi-omics data analysis facilitated by AI.
- Analysis of AI's role in tumor immune microenvironment characterization and genetic mutation profiling.
Main Results:
- AI demonstrates significant potential in early detection, predicting immunotherapeutic responses, and designing personalized treatment strategies.
- AI integration with multi-omics data addresses critical bottlenecks in pancreatic cancer immunotherapy.
- AI facilitates advanced tumor immune microenvironment characterization and nanomedicine design.
Conclusions:
- AI is crucial for overcoming limitations in pancreatic cancer immunotherapy, enabling precision medicine approaches.
- Further development and application of AI are essential for advancing clinical translation in pancreatic cancer treatment.
- AI offers a theoretical foundation and practical guidance for enhancing immunotherapy efficacy and patient outcomes.
