Q-omics provides the consensus-scored RFESD profile across patient tissues and cancer cell-line models. RFESD expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, RFESD is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, RFESD RNA expression shows 19,773 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, LIHC, and UVM as cancer lineages where RFESD 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 RFESD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RFESD survival associations across molecular data types. RFESD RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible RFESD RNA expression–survival associations across cancer types. High RFESD expression shows unfavorable associations in KIRP, LGG, KICH, LIHC and SCLC, but favorable associations in MESO. The KIRP 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 KIRP as the clearest survival context for RFESD RNA expression.
This table summarizes RFESD tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 5. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for RFESD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RFESD shows lower tumor expression in UCEC, THCA and KICH and higher tumor expression in LIHC, CHOL and BRCA. The LIHC box plot shows higher RFESD RNA expression in tumor versus normal tissue (log2 FC = +0.347, t-test p < 0.001).
This table shows molecular features associated with RFESD in patient tissues and cancer cell lines. In patient samples, RFESD 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, RFESD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia.
