Q-omics provides the consensus-scored SCNN1A profile across patient tissues and cancer cell-line models. SCNN1A 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, SCNN1A is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, SCNN1A RNA expression shows 15,971 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight HNSC, KIRC, and TGCT as cancer lineages where SCNN1A 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 SCNN1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCNN1A survival associations across molecular data types. SCNN1A RNA expression shows survival associations in the most cancer types (28), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCNN1A RNA expression–survival associations across cancer types. High SCNN1A expression shows unfavorable associations in PAAD, OV and LAML, but favorable associations in HNSC, MESO and LUAD. The HNSC 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 HNSC as the clearest survival context for SCNN1A RNA expression.
This table summarizes SCNN1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SCNN1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCNN1A shows lower tumor expression in KIRC, HNSC, KIRP and LUSC and higher tumor expression in BRCA and CHOL. The KIRC box plot shows higher SCNN1A RNA expression in normal versus tumor tissue (log2 FC = −5.127, t-test p < 0.001).
This table shows molecular features associated with SCNN1A in patient tissues and cancer cell lines. In patient samples, SCNN1A shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SCNN1A 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 LUNG_SCLC.
