Q-omics provides the consensus-scored PCCA-DT profile across patient tissues and cancer cell-line models. PCCA-DT 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, PCCA-DT is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, PCCA-DT RNA expression shows 18,430 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where PCCA-DT 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 PCCA-DT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCCA-DT survival associations across molecular data types. PCCA-DT RNA expression shows survival associations in the most cancer types (26). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCCA-DT RNA expression–survival associations across cancer types. High PCCA-DT expression shows unfavorable associations in ACC, KICH, SKCM, KIRC and UVM, but favorable associations in UCEC. 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 PCCA-DT RNA expression.
This table summarizes PCCA-DT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PCCA-DT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCCA-DT shows lower tumor expression in KIRC and KICH and higher tumor expression in BLCA, LUAD, LUSC and UCEC. The KIRC box plot shows higher PCCA-DT RNA expression in normal versus tumor tissue (log2 FC = −1.135, t-test p < 0.001).
This table shows molecular features associated with PCCA-DT in patient tissues and cancer cell lines. In patient samples, PCCA-DT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
