Q-omics provides the consensus-scored SERPINB12 profile across patient tissues and cancer cell-line models. SERPINB12 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SERPINB12 is differentially expressed in 6, with the highest sampling consensus in HNSC. Additionally, SERPINB12 RNA expression shows 11,802 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, and THYM as cancer lineages where SERPINB12 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 SERPINB12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERPINB12 survival associations across molecular data types. SERPINB12 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) 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 SERPINB12 RNA expression–survival associations across cancer types. High SERPINB12 expression shows unfavorable associations in BLCA, KIRP and SCLC, but favorable associations in HNSC, UCS and LUSC. The HNSC 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 HNSC as the clearest survival context for SERPINB12 RNA expression.
This table summarizes SERPINB12 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SERPINB12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERPINB12 shows lower tumor expression in HNSC, KIRC and BRCA and higher tumor expression in LUSC, BLCA and COAD. The HNSC box plot shows higher SERPINB12 RNA expression in normal versus tumor tissue (log2 FC = −1.585, t-test p < 0.001).
This table shows molecular features associated with SERPINB12 in patient tissues and cancer cell lines. In patient samples, SERPINB12 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SERPINB12 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
