Q-omics provides the consensus-scored PRR23C profile across patient tissues and cancer cell-line models. PRR23C expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, PRR23C is differentially expressed in 1, with the highest sampling consensus in LIHC. Additionally, PRR23C RNA expression shows 6,536 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight CESC, LIHC, and TGCT as cancer lineages where PRR23C 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 PRR23C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRR23C survival associations across molecular data types. PRR23C RNA expression shows survival associations in the most cancer types (21), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRR23C RNA expression–survival associations across cancer types. High PRR23C expression shows unfavorable associations in CESC, LIHC, KIRC, MESO, LUSC and COAD. The CESC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify CESC as the clearest survival context for PRR23C RNA expression.
This table summarizes PRR23C tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 1. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for PRR23C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRR23C shows higher tumor expression in LIHC. The LIHC box plot shows higher PRR23C RNA expression in tumor versus normal tissue (log2 FC = +0.005, t-test p = .002).
This table shows molecular features associated with PRR23C in patient tissues and cancer cell lines. In patient samples, PRR23C 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, PRR23C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in CNS and SKIN.
