Q-omics provides the consensus-scored ABCA6 profile across patient tissues and cancer cell-line models. ABCA6 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ABCA6 is differentially expressed in 14, with the highest sampling consensus in LUAD. Additionally, ABCA6 RNA expression shows 24,297 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, LUAD, and LSCC as cancer lineages where ABCA6 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 ABCA6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABCA6 survival associations across molecular data types. ABCA6 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (9) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ABCA6 RNA expression–survival associations across cancer types. High ABCA6 expression shows unfavorable associations in LGG, but favorable associations in HNSC, LUAD, LIHC, SKCM and BRCA. The HNSC 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 HNSC as the clearest survival context for ABCA6 RNA expression.
This table summarizes ABCA6 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 4. The strongest signals are observed in LUAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ABCA6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABCA6 shows lower tumor expression in LUAD, COAD, LUSC, THCA, KICH and KIRC. The LUAD box plot shows higher ABCA6 RNA expression in normal versus tumor tissue (log2 FC = −1.211, t-test p < 0.001).
This table shows molecular features associated with ABCA6 in patient tissues and cancer cell lines. In patient samples, ABCA6 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ABCA6 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BLOOD_Lymphoma.
