coagulation factor II, thrombinGenealiases: PT · RPRGL2 · THPH1
Q-omics provides the consensus-scored F2 profile across patient tissues and cancer cell-line models. F2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, F2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, F2 protein abundance shows 22,659 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, KIRC, and GBM as cancer lineages where F2 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 F2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes F2 survival associations across molecular data types. F2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) 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 F2 RNA expression–survival associations across cancer types. High F2 expression shows unfavorable associations in LUAD, MESO, KIRC, CHOL and STAD, but favorable associations in COAD. The LUAD 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 LUAD as the clearest survival context for F2 RNA expression.
This table summarizes F2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for F2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. F2 shows lower tumor expression in THCA and CHOL and higher tumor expression in KIRC, LUAD, BRCA and COAD. The KIRC box plot shows higher F2 RNA expression in tumor versus normal tissue (log2 FC = +1.869, t-test p < 0.001).
This table shows molecular features associated with F2 in patient tissues and cancer cell lines. In patient samples, F2 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, F2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BREAST.
