**PrognoScan: A New Database for Meta-Analysis of the Prognostic Value of Genes** Hideaki Mizuno, Kunio Kitada, Kenta Nakai, and Akinori Sarai **Background:** In cancer research, the association between a gene and clinical outcome is crucial for understanding disease etiology and guiding further studies. The availability of published cancer microarray datasets with clinical annotation provides an opportunity to link gene expression to prognosis. However, accessing and analyzing these data without an effective platform is challenging. **Description:** To address this issue, a database named "PrognoScan" has been developed. It includes a large collection of publicly available cancer microarray datasets with clinical annotation and a tool for assessing the biological relationship between gene expression and prognosis. PrognoScan employs the minimum P-value approach to find the optimal cutpoint in continuous gene expression measurements, enabling systematic meta-analysis of multiple datasets. **Conclusion:** PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets, accelerating cancer research. The database is publicly accessible at http://gbk21.bse.kyutech.ac.jp/PrognoScan/index.html. **Key Features:** - **Data Collection:** Over 40 datasets from various cancer types, including bladder, blood, breast, brain, esophagus, head and neck, kidney, lung, and ovarian. - **Data Analysis:** Uses the minimum P-value approach for survival analysis, correcting for multiple testing. - **Utility:** Simple user interface, detailed reports, and intuitive visualization tools. **Discussion and Conclusion:** PrognoScan focuses on the prognostic value of individual genes, differing from gene signatures. It aims to facilitate the evaluation of potential tumor markers and therapeutic targets, accelerating cancer research. The database is regularly updated with new datasets and will continue to evolve to enhance its robustness and utility.**PrognoScan: A New Database for Meta-Analysis of the Prognostic Value of Genes** Hideaki Mizuno, Kunio Kitada, Kenta Nakai, and Akinori Sarai **Background:** In cancer research, the association between a gene and clinical outcome is crucial for understanding disease etiology and guiding further studies. The availability of published cancer microarray datasets with clinical annotation provides an opportunity to link gene expression to prognosis. However, accessing and analyzing these data without an effective platform is challenging. **Description:** To address this issue, a database named "PrognoScan" has been developed. It includes a large collection of publicly available cancer microarray datasets with clinical annotation and a tool for assessing the biological relationship between gene expression and prognosis. PrognoScan employs the minimum P-value approach to find the optimal cutpoint in continuous gene expression measurements, enabling systematic meta-analysis of multiple datasets. **Conclusion:** PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets, accelerating cancer research. The database is publicly accessible at http://gbk21.bse.kyutech.ac.jp/PrognoScan/index.html. **Key Features:** - **Data Collection:** Over 40 datasets from various cancer types, including bladder, blood, breast, brain, esophagus, head and neck, kidney, lung, and ovarian. - **Data Analysis:** Uses the minimum P-value approach for survival analysis, correcting for multiple testing. - **Utility:** Simple user interface, detailed reports, and intuitive visualization tools. **Discussion and Conclusion:** PrognoScan focuses on the prognostic value of individual genes, differing from gene signatures. It aims to facilitate the evaluation of potential tumor markers and therapeutic targets, accelerating cancer research. The database is regularly updated with new datasets and will continue to evolve to enhance its robustness and utility.