serpin family B member 9Genealiases: CAP-3 · CAP3 · PI-9 · PI9
Q-omics provides the consensus-scored SERPINB9 profile across patient tissues and cancer cell-line models. SERPINB9 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SERPINB9 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, SERPINB9 protein abundance shows 22,624 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, KIRC, and LSCC as cancer lineages where SERPINB9 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 SERPINB9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERPINB9 survival associations across molecular data types. SERPINB9 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERPINB9 RNA expression–survival associations across cancer types. High SERPINB9 expression shows unfavorable associations in KICH, LGG and KIRP, but favorable associations in UVM, BRCA and SKCM. The UVM 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 UVM as the clearest survival context for SERPINB9 RNA expression.
This table summarizes SERPINB9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SERPINB9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERPINB9 shows lower tumor expression in KICH and THCA and higher tumor expression in KIRC, COAD, STAD and ESCA. The KIRC box plot shows higher SERPINB9 RNA expression in tumor versus normal tissue (log2 FC = +1.560, t-test p < 0.001).
This table shows molecular features associated with SERPINB9 in patient tissues and cancer cell lines. In patient samples, SERPINB9 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SERPINB9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
