Q-omics provides the consensus-scored COL15A1 profile across patient tissues and cancer cell-line models. COL15A1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, COL15A1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, COL15A1 protein abundance shows 27,243 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight KIRP, KIRC, and UCEC as cancer lineages where COL15A1 shows reproducible signals across survival, tumor–normal expression, and patient cross-omics analyses.
Every result is evaluated using two consensus scores. Sampling consensus measures how consistently a finding is reproduced within a cancer lineage across different conditions. Lineage consensus measures how broadly the result is shared across cancer types, distinguishing pan-cancer signals from lineage-specific patterns.
Premium analyses for COL15A1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes COL15A1 survival associations across molecular data types. COL15A1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible COL15A1 RNA expression–survival associations across cancer types. High COL15A1 expression shows unfavorable associations in KIRP, MESO, ACC and UVM, but favorable associations in KIRC and HNSC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRP as the clearest survival context for COL15A1 RNA expression.
This table summarizes COL15A1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for COL15A1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. COL15A1 shows lower tumor expression in UCEC and higher tumor expression in KIRC, LIHC, LUAD, HNSC and STAD. The KIRC box plot shows higher COL15A1 RNA expression in tumor versus normal tissue (log2 FC = +1.904, t-test p < 0.001).
This table shows molecular features associated with COL15A1 in patient tissues and cancer cell lines. In patient samples, COL15A1 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, COL15A1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Leukemia.
