ATP binding cassette subfamily B member 9Genealiases: EST122234 · TAPL
Q-omics provides the consensus-scored ABCB9 profile across patient tissues and cancer cell-line models. ABCB9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ABCB9 is differentially expressed in 14, with the highest sampling consensus in LUAD. Additionally, ABCB9 RNA expression shows 18,909 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, LUAD, and TGCT as cancer lineages where ABCB9 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 ABCB9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABCB9 survival associations across molecular data types. ABCB9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ABCB9 RNA expression–survival associations across cancer types. High ABCB9 expression shows unfavorable associations in KIRC, UVM, BRCA, ACC, KICH and LGG. The KIRC 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 KIRC as the clearest survival context for ABCB9 RNA expression.
This table summarizes ABCB9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for ABCB9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABCB9 shows higher tumor expression in LUAD, BLCA, HNSC, THCA, LIHC and COAD. The LUAD box plot shows higher ABCB9 RNA expression in tumor versus normal tissue (log2 FC = +0.684, t-test p < 0.001).
This table shows molecular features associated with ABCB9 in patient tissues and cancer cell lines. In patient samples, ABCB9 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, ABCB9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
