Q-omics provides the consensus-scored HIBCH profile across patient tissues and cancer cell-line models. HIBCH expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, HIBCH is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, HIBCH RNA expression shows 20,705 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where HIBCH 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 HIBCH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HIBCH survival associations across molecular data types. HIBCH RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 HIBCH RNA expression–survival associations across cancer types. High HIBCH expression shows unfavorable associations in UCS, but favorable associations in KIRC, READ, KIRP, OV and MESO. 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 HIBCH RNA expression.
This table summarizes HIBCH 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HIBCH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HIBCH shows lower tumor expression in HNSC, KIRP, KICH, KIRC, BRCA and COAD. The HNSC box plot shows higher HIBCH RNA expression in normal versus tumor tissue (log2 FC = −0.639, t-test p < 0.001).
This table shows molecular features associated with HIBCH in patient tissues and cancer cell lines. In patient samples, HIBCH shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, HIBCH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
