Q-omics provides the consensus-scored HEPH profile across patient tissues and cancer cell-line models. HEPH expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HEPH is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, HEPH protein abundance shows 31,547 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, KICH, and PDAC as cancer lineages where HEPH 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 HEPH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEPH survival associations across molecular data types. HEPH RNA expression shows survival associations in the most cancer types (20), followed by mutation status (13) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HEPH RNA expression–survival associations across cancer types. High HEPH expression shows unfavorable associations in KIRP, UVM, ESCA and BLCA, but favorable associations in KIRC and LUAD. The KIRC 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 KIRC as the clearest survival context for HEPH RNA expression.
This table summarizes HEPH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 8. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for HEPH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEPH shows lower tumor expression in KICH, KIRP, BLCA, UCEC and COAD and higher tumor expression in HNSC. The KICH box plot shows higher HEPH RNA expression in normal versus tumor tissue (log2 FC = −2.128, t-test p < 0.001).
This table shows molecular features associated with HEPH in patient tissues and cancer cell lines. In patient samples, HEPH 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, HEPH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
