Q-omics provides the consensus-scored ATP1B3P1 profile across patient tissues and cancer cell-line models. ATP1B3P1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, ATP1B3P1 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, ATP1B3P1 RNA expression shows 11,049 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight CESC, HNSC, and ESCA as cancer lineages where ATP1B3P1 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 ATP1B3P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATP1B3P1 survival associations across molecular data types. ATP1B3P1 RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATP1B3P1 RNA expression–survival associations across cancer types. High ATP1B3P1 expression shows unfavorable associations in MESO, LIHC, UVM, STAD and KICH, but favorable associations in CESC. The CESC 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 CESC as the clearest survival context for ATP1B3P1 RNA expression.
This table summarizes ATP1B3P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ATP1B3P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATP1B3P1 shows lower tumor expression in KIRC, KIRP and PAAD and higher tumor expression in HNSC, LUSC and LIHC. The HNSC box plot shows higher ATP1B3P1 RNA expression in tumor versus normal tissue (log2 FC = +0.302, t-test p < 0.001).
This table shows molecular features associated with ATP1B3P1 in patient tissues and cancer cell lines. In patient samples, ATP1B3P1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set.
