Q-omics provides the consensus-scored FDXR profile across patient tissues and cancer cell-line models. FDXR expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, FDXR is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, FDXR protein abundance shows 18,857 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UCEC, KIRC, and LSCC as cancer lineages where FDXR 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 FDXR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FDXR survival associations across molecular data types. FDXR RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) 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 FDXR RNA expression–survival associations across cancer types. High FDXR expression shows unfavorable associations in MESO and UCS, but favorable associations in UCEC, KIRP, STAD and UVM. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .003). Together, the overview and detailed table identify UCEC as the clearest survival context for FDXR RNA expression.
This table summarizes FDXR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for FDXR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FDXR shows higher tumor expression in KIRC, KIRP, COAD, LIHC, BLCA and BRCA. The KIRC box plot shows higher FDXR RNA expression in tumor versus normal tissue (log2 FC = +1.379, t-test p < 0.001).
This table shows molecular features associated with FDXR in patient tissues and cancer cell lines. In patient samples, FDXR shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, FDXR 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 SKIN and SOFT_TISSUE.
