Q-omics provides the consensus-scored ATP1B2 profile across patient tissues and cancer cell-line models. ATP1B2 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ATP1B2 is differentially expressed in 13, with the highest sampling consensus in KIRP. Additionally, ATP1B2 RNA expression shows 16,999 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRP, and THYM as cancer lineages where ATP1B2 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 ATP1B2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP1B2 survival associations across molecular data types. ATP1B2 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (2) 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 ATP1B2 RNA expression–survival associations across cancer types. High ATP1B2 expression shows unfavorable associations in KIRP, UVM and ACC, but favorable associations in KIRC, PAAD and LUAD. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRP as the clearest survival context for ATP1B2 RNA expression.
This table summarizes ATP1B2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ATP1B2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP1B2 shows lower tumor expression in KIRP, KICH, BLCA, COAD, KIRC and LUSC. The KIRP box plot shows higher ATP1B2 RNA expression in normal versus tumor tissue (log2 FC = −3.360, t-test p < 0.001).
This table shows molecular features associated with ATP1B2 in patient tissues and cancer cell lines. In patient samples, ATP1B2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP1B2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BONE.
