Q-omics provides the consensus-scored ATP2B4 profile across patient tissues and cancer cell-line models. ATP2B4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATP2B4 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, ATP2B4 protein abundance shows 23,046 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where ATP2B4 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 ATP2B4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP2B4 survival associations across molecular data types. ATP2B4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (10) 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 ATP2B4 RNA expression–survival associations across cancer types. High ATP2B4 expression shows unfavorable associations in ACC, BLCA and STAD, but favorable associations in KIRC, THYM and SARC. The KIRC 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 KIRC as the clearest survival context for ATP2B4 RNA expression.
This table summarizes ATP2B4 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATP2B4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP2B4 shows lower tumor expression in COAD and BLCA and higher tumor expression in KIRC, HNSC, LIHC and KIRP. The KIRC box plot shows higher ATP2B4 RNA expression in tumor versus normal tissue (log2 FC = +1.096, t-test p < 0.001).
This table shows molecular features associated with ATP2B4 in patient tissues and cancer cell lines. In patient samples, ATP2B4 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP2B4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
