Q-omics provides the consensus-scored PDHA1P1 profile across patient tissues and cancer cell-line models. PDHA1P1 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PDHA1P1 is differentially expressed in 4, with the highest sampling consensus in STAD. Additionally, PDHA1P1 RNA expression shows 6,849 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, STAD, and ESCA as cancer lineages where PDHA1P1 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 PDHA1P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDHA1P1 survival associations across molecular data types. PDHA1P1 RNA expression shows survival associations in the most cancer types (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDHA1P1 RNA expression–survival associations across cancer types. High PDHA1P1 expression shows unfavorable associations in KIRC, ACC, LIHC, CESC and PRAD, but favorable associations in HNSC. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for PDHA1P1 RNA expression.
This table summarizes PDHA1P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4. The strongest signals are observed in STAD for RNA.
This table ranks reproducible tumor–normal expression differences for PDHA1P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDHA1P1 shows lower tumor expression in KICH and higher tumor expression in STAD, PAAD and KIRC. The STAD box plot shows higher PDHA1P1 RNA expression in tumor versus normal tissue (log2 FC = +0.083, t-test p = .004).
This table shows molecular features associated with PDHA1P1 in patient tissues and cancer cell lines. In patient samples, PDHA1P1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set.
