Q-omics provides the consensus-scored HFE profile across patient tissues and cancer cell-line models. HFE expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, HFE is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, HFE protein abundance shows 24,200 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where HFE 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 HFE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HFE survival associations across molecular data types. HFE RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 HFE RNA expression–survival associations across cancer types. High HFE expression shows unfavorable associations in LGG and PAAD, but favorable associations in UVM, ACC, READ and KIRC. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for HFE RNA expression.
This table summarizes HFE 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 8. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for HFE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HFE shows lower tumor expression in KICH and higher tumor expression in KIRC, KIRP, HNSC, BLCA and LIHC. The KIRC box plot shows higher HFE RNA expression in tumor versus normal tissue (log2 FC = +1.034, t-test p < 0.001).
This table shows molecular features associated with HFE in patient tissues and cancer cell lines. In patient samples, HFE 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, HFE RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
