Q-omics provides the consensus-scored KLKB1 profile across patient tissues and cancer cell-line models. KLKB1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, KLKB1 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, KLKB1 protein abundance shows 22,371 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight SKCM, KICH, and PDAC as cancer lineages where KLKB1 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 KLKB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes KLKB1 survival associations across molecular data types. KLKB1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible KLKB1 RNA expression–survival associations across cancer types. High KLKB1 expression shows unfavorable associations in LGG, UVM and LUAD, but favorable associations in SKCM, COAD and CESC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for KLKB1 RNA expression.
This table summarizes KLKB1 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 6. The strongest signals are observed in KICH for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for KLKB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. KLKB1 shows lower tumor expression in KICH, LIHC, BLCA, LUSC and COAD and higher tumor expression in KIRC. The KICH box plot shows higher KLKB1 RNA expression in normal versus tumor tissue (log2 FC = −1.387, t-test p < 0.001).
This table shows molecular features associated with KLKB1 in patient tissues and cancer cell lines. In patient samples, KLKB1 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, KLKB1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LARGE_INTESTINE.
