proprotein convertase subtilisin/kexin type 2Genealiases: NEC 2 · NEC-2 · NEC2 · PC2 · SPC2
Q-omics provides the consensus-scored PCSK2 profile across patient tissues and cancer cell-line models. PCSK2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PCSK2 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, PCSK2 protein abundance shows 13,596 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, COAD, and GBM as cancer lineages where PCSK2 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 PCSK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCSK2 survival associations across molecular data types. PCSK2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (12) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCSK2 RNA expression–survival associations across cancer types. High PCSK2 expression shows unfavorable associations in SKCM, KIRC, UVM and LIHC, but favorable associations in LGG and PAAD. The SKCM 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 SKCM as the clearest survival context for PCSK2 RNA expression.
This table summarizes PCSK2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for PCSK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCSK2 shows lower tumor expression in COAD, BLCA, KIRP, KIRC and STAD and higher tumor expression in THCA. The COAD box plot shows higher PCSK2 RNA expression in normal versus tumor tissue (log2 FC = −1.707, t-test p < 0.001).
This table shows molecular features associated with PCSK2 in patient tissues and cancer cell lines. In patient samples, PCSK2 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, PCSK2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
