Q-omics provides the consensus-scored PRRC2C profile across patient tissues and cancer cell-line models. PRRC2C expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PRRC2C is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PRRC2C protein abundance shows 28,551 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where PRRC2C 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 PRRC2C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRRC2C survival associations across molecular data types. PRRC2C RNA expression shows survival associations in the most cancer types (26), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRRC2C RNA expression–survival associations across cancer types. High PRRC2C expression shows unfavorable associations in ACC, KIRP, PAAD and BLCA, but favorable associations in KIRC and UCS. 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 PRRC2C RNA expression.
This table summarizes PRRC2C 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 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PRRC2C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRRC2C shows higher tumor expression in HNSC, KIRC, STAD, KIRP, BLCA and LIHC. The HNSC box plot shows higher PRRC2C RNA expression in tumor versus normal tissue (log2 FC = +1.042, t-test p < 0.001).
This table shows molecular features associated with PRRC2C in patient tissues and cancer cell lines. In patient samples, PRRC2C shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, PRRC2C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
