ankyrin repeat and SOCS box containing 6Genealiases: []
Q-omics provides the consensus-scored ASB6 profile across patient tissues and cancer cell-line models. ASB6 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, ASB6 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, ASB6 RNA expression shows 18,564 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where ASB6 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 ASB6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ASB6 survival associations across molecular data types. ASB6 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ASB6 RNA expression–survival associations across cancer types. High ASB6 expression shows unfavorable associations in ACC, COAD, LIHC, SKCM and LGG, but favorable associations in CHOL. 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 ASB6 RNA expression.
This table summarizes ASB6 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 3. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ASB6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ASB6 shows lower tumor expression in KICH and higher tumor expression in COAD, LIHC, HNSC, LUAD and LUSC. The COAD box plot shows higher ASB6 RNA expression in tumor versus normal tissue (log2 FC = +0.676, t-test p < 0.001).
This table shows molecular features associated with ASB6 in patient tissues and cancer cell lines. In patient samples, ASB6 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, ASB6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
