Q-omics provides the consensus-scored ABCA9 profile across patient tissues and cancer cell-line models. ABCA9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ABCA9 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, ABCA9 RNA expression shows 22,462 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, THCA, and LSCC as cancer lineages where ABCA9 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 ABCA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABCA9 survival associations across molecular data types. ABCA9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) 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 ABCA9 RNA expression–survival associations across cancer types. High ABCA9 expression shows unfavorable associations in KICH, LAML and KIRP, but favorable associations in HNSC, LIHC 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 = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for ABCA9 RNA expression.
This table summarizes ABCA9 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 2. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ABCA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABCA9 shows lower tumor expression in THCA, COAD, KIRC, LUAD, KIRP and UCEC. The THCA box plot shows higher ABCA9 RNA expression in normal versus tumor tissue (log2 FC = −2.103, t-test p < 0.001).
This table shows molecular features associated with ABCA9 in patient tissues and cancer cell lines. In patient samples, ABCA9 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, ABCA9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
