Q-omics provides the consensus-scored F2R profile across patient tissues and cancer cell-line models. F2R expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, F2R is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, F2R RNA expression shows 19,687 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where F2R 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 F2R — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes F2R survival associations across molecular data types. F2R RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible F2R RNA expression–survival associations across cancer types. High F2R expression shows unfavorable associations in KIRP, MESO, UVM, STAD and LGG, but favorable associations in KIRC. The KIRP 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 KIRP as the clearest survival context for F2R RNA expression.
This table summarizes F2R tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for F2R. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. F2R shows lower tumor expression in KICH and higher tumor expression in HNSC, KIRC, COAD, BLCA and STAD. The HNSC box plot shows higher F2R RNA expression in tumor versus normal tissue (log2 FC = +2.611, t-test p < 0.001).
This table shows molecular features associated with F2R in patient tissues and cancer cell lines. In patient samples, F2R shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, F2R 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 BLOOD_Lymphoma and LARGE_INTESTINE.
