Although colorectal cancer is one of the most lethal cancer types in the world, its metastasis to the ovary is rare, compared to metastasis to other organs. Consequently, the genomic basis for colon-to-ovary metastasis remains unstudied, due to limited available patients, and thus there have been no attempts to construct individual-specific networks. Due to its rarity, the small sample size makes common mutations difficult to find. To overcome this problem, we herein attempted to apply a biological connectivity map called a sample-specific network (SSN), to reveal common biological functions in three samples. Our three samples were compared to a clinical dataset contained in The Cancer Genome Atlas (TCGA) Colorectal Adenocarcinoma (COAD), showing different mutational spectra, compared to matched samples based on age, gender, microsatellite instability (MSI) status, and tumor, node, metastasis (TNM) stage. The SSNs for the three samples revealed significant correlations of the mutation statuses of several apoptosis genes, in contrast to the TCGA-matched samples. Further analysis of a targeted-gene panel sequencing dataset for colon-to-ovary metastasis of primary tumor samples also confirmed significant correlations of the mutational statuses among apoptosis genes. In summary, using SSN, we successfully identified a common function (apoptosis) among our three patients having colon-to-ovary metastasis, despite no common mutations in the three patients. Such computational analyses could facilitate productive study of rare cancers and other diseases.