Q-omics provides the consensus-scored SERPINF1 profile across patient tissues and cancer cell-line models. SERPINF1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SERPINF1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, SERPINF1 protein abundance shows 31,065 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, and PDAC as cancer lineages where SERPINF1 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 SERPINF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERPINF1 survival associations across molecular data types. SERPINF1 RNA expression shows survival associations in the most cancer types (22), 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 SERPINF1 RNA expression–survival associations across cancer types. High SERPINF1 expression shows unfavorable associations in KIRC, BLCA and LGG, but favorable associations in LUAD, HNSC and DLBC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SERPINF1 RNA expression.
This table summarizes SERPINF1 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 8. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SERPINF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERPINF1 shows lower tumor expression in BLCA, THCA, UCEC, BRCA and CHOL and higher tumor expression in KIRC. The KIRC box plot shows higher SERPINF1 RNA expression in tumor versus normal tissue (log2 FC = +1.030, t-test p < 0.001).
This table shows molecular features associated with SERPINF1 in patient tissues and cancer cell lines. In patient samples, SERPINF1 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, SERPINF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Lymphoma.
