Q-omics provides the consensus-scored PCOLCE profile across patient tissues and cancer cell-line models. PCOLCE expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PCOLCE is differentially expressed in 5, with the highest sampling consensus in HNSC. Additionally, PCOLCE protein abundance shows 27,437 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where PCOLCE 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 PCOLCE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCOLCE survival associations across molecular data types. PCOLCE RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCOLCE RNA expression–survival associations across cancer types. High PCOLCE expression shows unfavorable associations in KIRC, UVM, KICH, LGG and ACC, but favorable associations in DLBC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for PCOLCE RNA expression.
This table summarizes PCOLCE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PCOLCE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCOLCE shows lower tumor expression in BLCA and higher tumor expression in HNSC, LUAD, COAD and STAD. The HNSC box plot shows higher PCOLCE RNA expression in tumor versus normal tissue (log2 FC = +1.396, t-test p < 0.001).
This table shows molecular features associated with PCOLCE in patient tissues and cancer cell lines. In patient samples, PCOLCE shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PCOLCE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
