Q-omics provides the consensus-scored ATP11C profile across patient tissues and cancer cell-line models. ATP11C expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ATP11C is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ATP11C RNA expression shows 20,872 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where ATP11C 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 ATP11C — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP11C survival associations across molecular data types. ATP11C RNA expression shows survival associations in the most cancer types (20), followed by mutation status (10) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP11C RNA expression–survival associations across cancer types. High ATP11C expression shows unfavorable associations in UVM, LGG, UCEC and PAAD, but favorable associations in KIRC and SKCM. The KIRC 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 KIRC as the clearest survival context for ATP11C RNA expression.
This table summarizes ATP11C 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 3. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ATP11C. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP11C shows lower tumor expression in KICH, THCA, LIHC and BRCA and higher tumor expression in HNSC and STAD. The HNSC box plot shows higher ATP11C RNA expression in tumor versus normal tissue (log2 FC = +1.250, t-test p < 0.001).
This table shows molecular features associated with ATP11C in patient tissues and cancer cell lines. In patient samples, ATP11C shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATP11C RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
