Q-omics provides the consensus-scored OGFR profile across patient tissues and cancer cell-line models. OGFR expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, OGFR is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, OGFR protein abundance shows 22,693 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, KIRC, and PDAC as cancer lineages where OGFR 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 OGFR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes OGFR survival associations across molecular data types. OGFR RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 OGFR RNA expression–survival associations across cancer types. High OGFR expression shows unfavorable associations in UVM, KIRC, LAML, LGG and KIRP, but favorable associations in SKCM. The UVM 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 UVM as the clearest survival context for OGFR RNA expression.
This table summarizes OGFR 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 KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for OGFR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. OGFR shows higher tumor expression in KIRC, HNSC, COAD, STAD, KIRP and READ. The KIRC box plot shows higher OGFR RNA expression in tumor versus normal tissue (log2 FC = +1.209, t-test p < 0.001).
This table shows molecular features associated with OGFR in patient tissues and cancer cell lines. In patient samples, OGFR 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, OGFR 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 SKIN and LARGE_INTESTINE.
