Q-omics provides the consensus-scored AASDHPPT profile across patient tissues and cancer cell-line models. AASDHPPT expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, AASDHPPT is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, AASDHPPT RNA expression shows 19,998 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCS, BLCA, and ACC as cancer lineages where AASDHPPT 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 AASDHPPT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AASDHPPT survival associations across molecular data types. AASDHPPT RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AASDHPPT RNA expression–survival associations across cancer types. High AASDHPPT expression shows unfavorable associations in HNSC, BLCA, SCLC and LIHC, but favorable associations in UCS and KIRC. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UCS as the clearest survival context for AASDHPPT RNA expression.
This table summarizes AASDHPPT 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 5. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for AASDHPPT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AASDHPPT shows higher tumor expression in BLCA, HNSC, COAD, LUAD, STAD and BRCA. The BLCA box plot shows higher AASDHPPT RNA expression in tumor versus normal tissue (log2 FC = +0.764, t-test p < 0.001).
This table shows molecular features associated with AASDHPPT in patient tissues and cancer cell lines. In patient samples, AASDHPPT shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, AASDHPPT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
