Q-omics provides the consensus-scored SCNN1B profile across patient tissues and cancer cell-line models. SCNN1B expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, SCNN1B is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, SCNN1B RNA expression shows 14,543 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LUAD, KIRC, and LSCC as cancer lineages where SCNN1B 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 SCNN1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCNN1B survival associations across molecular data types. SCNN1B RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCNN1B RNA expression–survival associations across cancer types. High SCNN1B expression shows unfavorable associations in LGG and KIRC, but favorable associations in LUAD, HNSC, CESC and LAML. The LUAD 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 LUAD as the clearest survival context for SCNN1B RNA expression.
This table summarizes SCNN1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SCNN1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCNN1B shows lower tumor expression in KIRC, HNSC, KIRP, KICH, COAD and THCA. The KIRC box plot shows higher SCNN1B RNA expression in normal versus tumor tissue (log2 FC = −4.958, t-test p < 0.001).
This table shows molecular features associated with SCNN1B in patient tissues and cancer cell lines. In patient samples, SCNN1B 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, SCNN1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and LARGE_INTESTINE.
