Q-omics provides the consensus-scored SERPINA9 profile across patient tissues and cancer cell-line models. SERPINA9 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, SERPINA9 is differentially expressed in 8, with the highest sampling consensus in COAD. Additionally, SERPINA9 RNA expression shows 6,712 significant pathway-activity associations, with the highest sampling consensus in THCA. Together, these results highlight ESCA, COAD, and THCA as cancer lineages where SERPINA9 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 SERPINA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERPINA9 survival associations across molecular data types. SERPINA9 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERPINA9 RNA expression–survival associations across cancer types. High SERPINA9 expression shows unfavorable associations in UCS, THCA and LIHC, but favorable associations in ESCA, LUAD and CESC. The ESCA Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .003). Together, the overview and detailed table identify ESCA as the clearest survival context for SERPINA9 RNA expression.
This table summarizes SERPINA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SERPINA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERPINA9 shows lower tumor expression in COAD, LUAD and LUSC and higher tumor expression in HNSC, KIRC and BRCA. The COAD box plot shows higher SERPINA9 RNA expression in normal versus tumor tissue (log2 FC = −0.826, t-test p < 0.001).
This table shows molecular features associated with SERPINA9 in patient tissues and cancer cell lines. In patient samples, SERPINA9 shows the broadest associations at the RNA and protein expression levels, with THCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SERPINA9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Lymphoma.
