Q-omics provides the consensus-scored HEBP1 profile across patient tissues and cancer cell-line models. HEBP1 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, HEBP1 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, HEBP1 protein abundance shows 22,779 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UCEC, THCA, and PDAC as cancer lineages where HEBP1 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 HEBP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HEBP1 survival associations across molecular data types. HEBP1 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HEBP1 RNA expression–survival associations across cancer types. High HEBP1 expression shows unfavorable associations in UCEC, PAAD, LGG and HNSC, but favorable associations in DLBC and ACC. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .005). Together, the overview and detailed table identify UCEC as the clearest survival context for HEBP1 RNA expression.
This table summarizes HEBP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HEBP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HEBP1 shows lower tumor expression in THCA, LUAD, UCEC and KIRC and higher tumor expression in HNSC and KIRP. The THCA box plot shows higher HEBP1 RNA expression in normal versus tumor tissue (log2 FC = −1.182, t-test p < 0.001).
This table shows molecular features associated with HEBP1 in patient tissues and cancer cell lines. In patient samples, HEBP1 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, HEBP1 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 LUNG_NSCLC_LUAD and BLOOD_Leukemia.
