Q-omics provides the consensus-scored PCSK1N profile across patient tissues and cancer cell-line models. PCSK1N expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, PCSK1N is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PCSK1N protein abundance shows 34,034 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, KIRC, and GBM as cancer lineages where PCSK1N 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 PCSK1N — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCSK1N survival associations across molecular data types. PCSK1N RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCSK1N RNA expression–survival associations across cancer types. High PCSK1N expression shows unfavorable associations in UCS, UCEC, PRAD and STAD, but favorable associations in KIRC and PAAD. The UCS Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UCS as the clearest survival context for PCSK1N RNA expression.
This table summarizes PCSK1N 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 9. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PCSK1N. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCSK1N shows lower tumor expression in KIRC, KICH and COAD and higher tumor expression in THCA, BLCA and LUAD. The KIRC box plot shows higher PCSK1N RNA expression in normal versus tumor tissue (log2 FC = −3.490, t-test p < 0.001).
This table shows molecular features associated with PCSK1N in patient tissues and cancer cell lines. In patient samples, PCSK1N shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PCSK1N RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
