Q-omics provides the consensus-scored ATP2A3 profile across patient tissues and cancer cell-line models. ATP2A3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ATP2A3 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, ATP2A3 protein abundance shows 22,809 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, COAD, and LSCC as cancer lineages where ATP2A3 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 ATP2A3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP2A3 survival associations across molecular data types. ATP2A3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) 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 ATP2A3 RNA expression–survival associations across cancer types. High ATP2A3 expression shows unfavorable associations in UVM and KIRP, but favorable associations in HNSC, KIRC, SKCM and BLCA. 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 ATP2A3 RNA expression.
This table summarizes ATP2A3 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 5. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ATP2A3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP2A3 shows lower tumor expression in COAD, KICH, BLCA, LUSC and KIRP and higher tumor expression in BRCA. The COAD box plot shows higher ATP2A3 RNA expression in normal versus tumor tissue (log2 FC = −1.252, t-test p < 0.001).
This table shows molecular features associated with ATP2A3 in patient tissues and cancer cell lines. In patient samples, ATP2A3 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, ATP2A3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
