PrognoScan is a new database for meta-analysis of the prognostic value of genes. It provides a large collection of publicly available cancer microarray datasets with clinical annotations and a tool for assessing the relationship between gene expression and prognosis. The database uses the minimum P-value approach to determine optimal cutpoints for survival analysis, enabling systematic meta-analysis of multiple datasets. PrognoScan allows researchers to evaluate potential tumor markers and therapeutic targets, accelerating cancer research. The database is publicly accessible at http://gibk21.bse.kyutech.ac.jp/PrognoScan/index.html. It includes over 40 datasets of various cancer types, covering a wide range of cancers. The database includes information on study design, cancer type, endpoint, therapy history, and pathological parameters. It also includes experimental procedures such as sample preparation, storage, array type, and signal processing method. PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets, and as a result, will accelerate cancer research. The database is publicly accessible and requires only a web browser. It is designed to facilitate the interpretation of results by providing curated information such as cohort, therapy history, pathological parameters, and array type. PrognoScan aims to fulfill substantial practical requirements by providing a platform for evaluating potential tumor markers and therapeutic targets. The database is continuously updated every six months. Further plans for PrognoScan include the development of an algorithm for finding multiple cutpoints. The database is freely available and has no competing interests. The authors designed the database and contributed to the writing of the manuscript. The database is a valuable resource for researchers in the field of cancer research.PrognoScan is a new database for meta-analysis of the prognostic value of genes. It provides a large collection of publicly available cancer microarray datasets with clinical annotations and a tool for assessing the relationship between gene expression and prognosis. The database uses the minimum P-value approach to determine optimal cutpoints for survival analysis, enabling systematic meta-analysis of multiple datasets. PrognoScan allows researchers to evaluate potential tumor markers and therapeutic targets, accelerating cancer research. The database is publicly accessible at http://gibk21.bse.kyutech.ac.jp/PrognoScan/index.html. It includes over 40 datasets of various cancer types, covering a wide range of cancers. The database includes information on study design, cancer type, endpoint, therapy history, and pathological parameters. It also includes experimental procedures such as sample preparation, storage, array type, and signal processing method. PrognoScan provides a powerful platform for evaluating potential tumor markers and therapeutic targets, and as a result, will accelerate cancer research. The database is publicly accessible and requires only a web browser. It is designed to facilitate the interpretation of results by providing curated information such as cohort, therapy history, pathological parameters, and array type. PrognoScan aims to fulfill substantial practical requirements by providing a platform for evaluating potential tumor markers and therapeutic targets. The database is continuously updated every six months. Further plans for PrognoScan include the development of an algorithm for finding multiple cutpoints. The database is freely available and has no competing interests. The authors designed the database and contributed to the writing of the manuscript. The database is a valuable resource for researchers in the field of cancer research.