adenylosuccinate lyaseGenealiases: AMPS · ASASE · ASL
Q-omics provides the consensus-scored ADSL profile across patient tissues and cancer cell-line models. ADSL expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ADSL is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, ADSL RNA expression shows 19,746 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where ADSL 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 ADSL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADSL survival associations across molecular data types. ADSL RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ADSL RNA expression–survival associations across cancer types. High ADSL expression shows unfavorable associations in ACC, LIHC, UVM, MESO, KICH and CESC. 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 ADSL RNA expression.
This table summarizes ADSL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ADSL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADSL shows higher tumor expression in KIRC, HNSC, LIHC, COAD, LUAD and LUSC. The KIRC box plot shows higher ADSL RNA expression in tumor versus normal tissue (log2 FC = +0.690, t-test p < 0.001).
This table shows molecular features associated with ADSL in patient tissues and cancer cell lines. In patient samples, ADSL 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, ADSL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Lymphoma.
