Q-omics provides the consensus-scored SCN9A profile across patient tissues and cancer cell-line models. SCN9A expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SCN9A is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, SCN9A RNA expression shows 17,258 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRP, and COAD as cancer lineages where SCN9A 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 SCN9A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCN9A survival associations across molecular data types. SCN9A RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCN9A RNA expression–survival associations across cancer types. High SCN9A expression shows unfavorable associations in KIRP, HNSC, UVM, MESO and LGG, but favorable associations in SKCM. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRP as the clearest survival context for SCN9A RNA expression.
This table summarizes SCN9A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in COAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SCN9A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCN9A shows lower tumor expression in COAD, READ, BRCA and UCEC and higher tumor expression in KIRC and HNSC. The COAD box plot shows higher SCN9A RNA expression in normal versus tumor tissue (log2 FC = −1.922, t-test p < 0.001).
This table shows molecular features associated with SCN9A in patient tissues and cancer cell lines. In patient samples, SCN9A shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, SCN9A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
