Q-omics provides the consensus-scored PDHA2 profile across patient tissues and cancer cell-line models. PDHA2 expression is associated with patient survival in 12 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, PDHA2 is differentially expressed in 4, with the highest sampling consensus in LUAD. Additionally, PDHA2 mutation status shows 4,631 significant gene co-expression associations, with the highest sampling consensus in UCEC. Together, these results highlight STAD, LUAD, and UCEC as cancer lineages where PDHA2 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 PDHA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PDHA2 survival associations across molecular data types. PDHA2 RNA expression shows survival associations in the most cancer types (12), followed by mutation status (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PDHA2 RNA expression–survival associations across cancer types. High PDHA2 expression shows unfavorable associations in STAD, READ, MESO, KICH and BRCA, but favorable associations in SKCM. The STAD 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 STAD as the clearest survival context for PDHA2 RNA expression.
This table summarizes PDHA2 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PDHA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PDHA2 shows higher tumor expression in LUAD, KIRC, UCEC and LIHC. The LUAD box plot shows higher PDHA2 RNA expression in tumor versus normal tissue (log2 FC = +0.014, t-test p = .014).
This table shows molecular features associated with PDHA2 in patient tissues and cancer cell lines. In patient samples, PDHA2 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, PDHA2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
