Q-omics provides the consensus-scored HHEX profile across patient tissues and cancer cell-line models. HHEX expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, HHEX is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, HHEX RNA expression shows 20,037 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, KIRC, and GBM as cancer lineages where HHEX 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 HHEX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HHEX survival associations across molecular data types. HHEX RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HHEX RNA expression–survival associations across cancer types. High HHEX expression shows unfavorable associations in UVM, LGG and LIHC, but favorable associations in CESC, BRCA and HNSC. The CESC 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 CESC as the clearest survival context for HHEX RNA expression.
This table summarizes HHEX 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 2. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for HHEX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HHEX shows lower tumor expression in BLCA, LUSC, THCA and KICH and higher tumor expression in KIRC and STAD. The KIRC box plot shows higher HHEX RNA expression in tumor versus normal tissue (log2 FC = +1.218, t-test p < 0.001).
This table shows molecular features associated with HHEX in patient tissues and cancer cell lines. In patient samples, HHEX 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, HHEX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
