Q-omics provides the consensus-scored PRR9 profile across patient tissues and cancer cell-line models. PRR9 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, PRR9 is differentially expressed in 10, with the highest sampling consensus in BLCA. Additionally, PRR9 RNA expression shows 8,865 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight STAD, BLCA, and TGCT as cancer lineages where PRR9 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 PRR9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRR9 survival associations across molecular data types. PRR9 RNA expression shows survival associations in the most cancer types (24), followed by 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 PRR9 RNA expression–survival associations across cancer types. High PRR9 expression shows unfavorable associations in STAD, KIRP, BLCA, SCLC and DLBC, but favorable associations in BRCA. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify STAD as the clearest survival context for PRR9 RNA expression.
This table summarizes PRR9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PRR9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRR9 shows lower tumor expression in THCA and higher tumor expression in BLCA, HNSC, COAD, LUSC and READ. The BLCA box plot shows higher PRR9 RNA expression in tumor versus normal tissue (log2 FC = +1.868, t-test p = .020).
This table shows molecular features associated with PRR9 in patient tissues and cancer cell lines. In patient samples, PRR9 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, PRR9 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 LUNG_NSCLC_LUAD and LARGE_INTESTINE.
