Q-omics provides the consensus-scored PRPH profile across patient tissues and cancer cell-line models. PRPH expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, PRPH is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, PRPH protein abundance shows 27,609 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight BLCA, COAD, and HNSC as cancer lineages where PRPH 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 PRPH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRPH survival associations across molecular data types. PRPH RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRPH RNA expression–survival associations across cancer types. High PRPH expression shows unfavorable associations in BLCA, UCS, LGG and THYM, but favorable associations in THCA and SCLC. The BLCA 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 BLCA as the clearest survival context for PRPH RNA expression.
This table summarizes PRPH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 10. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PRPH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRPH shows lower tumor expression in COAD, BLCA, STAD, LUAD and BRCA and higher tumor expression in KIRC. The COAD box plot shows higher PRPH RNA expression in normal versus tumor tissue (log2 FC = −2.035, t-test p < 0.001).
This table shows molecular features associated with PRPH in patient tissues and cancer cell lines. In patient samples, PRPH shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, PRPH 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 SOFT_TISSUE and BLOOD_Lymphoma.
