Q-omics provides the consensus-scored F10 profile across patient tissues and cancer cell-line models. F10 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, F10 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, F10 protein abundance shows 19,149 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, and GBM as cancer lineages where F10 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 F10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes F10 survival associations across molecular data types. F10 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible F10 RNA expression–survival associations across cancer types. High F10 expression shows unfavorable associations in BLCA, LUSC, LGG, STAD and READ, but favorable associations in PAAD. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify BLCA as the clearest survival context for F10 RNA expression.
This table summarizes F10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for F10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. F10 shows lower tumor expression in BLCA, THCA, LUAD, LUSC, HNSC and UCEC. The BLCA box plot shows higher F10 RNA expression in normal versus tumor tissue (log2 FC = −3.932, t-test p < 0.001).
This table shows molecular features associated with F10 in patient tissues and cancer cell lines. In patient samples, F10 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, F10 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and UPPER_AERODIGESTIVE_TRACT.
