Q-omics provides the consensus-scored HPCA profile across patient tissues and cancer cell-line models. HPCA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, HPCA is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, HPCA RNA expression shows 15,717 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight ACC, KIRC, and TGCT as cancer lineages where HPCA 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 HPCA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HPCA survival associations across molecular data types. HPCA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HPCA RNA expression–survival associations across cancer types. High HPCA expression shows unfavorable associations in ACC, UCEC and UCS, but favorable associations in KIRP, CESC and SCLC. The ACC 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 ACC as the clearest survival context for HPCA RNA expression.
This table summarizes HPCA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for HPCA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HPCA shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, LUSC, LUAD and KIRP. The KIRC box plot shows higher HPCA RNA expression in tumor versus normal tissue (log2 FC = +1.502, t-test p < 0.001).
This table shows molecular features associated with HPCA in patient tissues and cancer cell lines. In patient samples, HPCA shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, HPCA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
