Q-omics provides the consensus-scored HP profile across patient tissues and cancer cell-line models. HP expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HP is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, HP protein abundance shows 17,202 significant protein co-abundance associations, with the highest sampling consensus in COAD. Together, these results highlight MESO, LIHC, and COAD as cancer lineages where HP 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 HP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HP survival associations across molecular data types. HP RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HP RNA expression–survival associations across cancer types. High HP expression shows unfavorable associations in KIRC, STAD, LUSC, BLCA and CHOL, but favorable associations in MESO. The MESO 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 MESO as the clearest survival context for HP RNA expression.
This table summarizes HP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for HP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HP shows lower tumor expression in LIHC, LUSC, HNSC and CHOL and higher tumor expression in KIRC and THCA. The LIHC box plot shows higher HP RNA expression in normal versus tumor tissue (log2 FC = −3.865, t-test p < 0.001).
This table shows molecular features associated with HP in patient tissues and cancer cell lines. In patient samples, HP shows the broadest associations at the RNA and protein expression levels, with COAD recurring as the lineage with the largest associated feature set. In cancer cell lines, HP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SKIN.
