Q-omics provides the consensus-scored ACCSL profile across patient tissues and cancer cell-line models. ACCSL expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, ACCSL is differentially expressed in 5, with the highest sampling consensus in UCEC. Additionally, ACCSL RNA expression shows 7,121 significant gene co-expression associations, with the highest sampling consensus in SARC. Together, these results highlight BLCA, UCEC, and SARC as cancer lineages where ACCSL 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 ACCSL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACCSL survival associations across molecular data types. ACCSL RNA expression shows survival associations in the most cancer types (18), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACCSL RNA expression–survival associations across cancer types. High ACCSL expression shows unfavorable associations in KICH, READ and KIRC, but favorable associations in BLCA, LUAD and UVM. The BLCA 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 BLCA as the clearest survival context for ACCSL RNA expression.
This table summarizes ACCSL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for ACCSL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACCSL shows lower tumor expression in UCEC, LUAD, COAD and THCA and higher tumor expression in KIRC. The UCEC box plot shows higher ACCSL RNA expression in normal versus tumor tissue (log2 FC = −0.156, t-test p = .001).
This table shows molecular features associated with ACCSL in patient tissues and cancer cell lines. In patient samples, ACCSL shows the broadest associations at the RNA and protein expression levels, with SARC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACCSL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SKIN.
