Q-omics provides the consensus-scored SCN1B profile across patient tissues and cancer cell-line models. SCN1B expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SCN1B is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, SCN1B RNA expression shows 22,351 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where SCN1B 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 SCN1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SCN1B survival associations across molecular data types. SCN1B RNA expression shows survival associations in the most cancer types (26), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SCN1B RNA expression–survival associations across cancer types. High SCN1B expression shows unfavorable associations in UVM and OV, but favorable associations in PAAD, KIRP, THCA and ESCA. The UVM 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 UVM as the clearest survival context for SCN1B RNA expression.
This table summarizes SCN1B tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SCN1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SCN1B shows lower tumor expression in BLCA, COAD and UCEC and higher tumor expression in KIRC, THCA and KICH. The KIRC box plot shows higher SCN1B RNA expression in tumor versus normal tissue (log2 FC = +1.799, t-test p < 0.001).
This table shows molecular features associated with SCN1B in patient tissues and cancer cell lines. In patient samples, SCN1B shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SCN1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BONE and CNS.
