Q-omics provides the consensus-scored HRC profile across patient tissues and cancer cell-line models. HRC expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, HRC is differentially expressed in 14, with the highest sampling consensus in KIRP. Additionally, HRC RNA expression shows 19,971 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight KIRP, and CCRCC as cancer lineages where HRC 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 HRC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HRC survival associations across molecular data types. HRC RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) 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 HRC RNA expression–survival associations across cancer types. High HRC expression shows unfavorable associations in KIRP, UVM, MESO and LUSC, but favorable associations in KIRC and THCA. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRP as the clearest survival context for HRC RNA expression.
This table summarizes HRC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in LUAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for HRC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HRC shows lower tumor expression in KIRP, BLCA, LUAD, KICH, HNSC and LUSC. The KIRP box plot shows higher HRC RNA expression in normal versus tumor tissue (log2 FC = −1.830, t-test p < 0.001).
This table shows molecular features associated with HRC in patient tissues and cancer cell lines. In patient samples, HRC shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, HRC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and SOFT_TISSUE.
