Q-omics provides the consensus-scored SNCB profile across patient tissues and cancer cell-line models. SNCB expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SNCB is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SNCB RNA expression shows 16,404 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where SNCB 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 SNCB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNCB survival associations across molecular data types. SNCB RNA expression shows survival associations in the most cancer types (26), 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 SNCB RNA expression–survival associations across cancer types. High SNCB expression shows unfavorable associations in KIRC, ACC, STAD, UCEC, KIRP and MESO. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for SNCB RNA expression.
This table summarizes SNCB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SNCB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNCB shows lower tumor expression in COAD and READ and higher tumor expression in HNSC, LUAD, KICH and LUSC. The HNSC box plot shows higher SNCB RNA expression in tumor versus normal tissue (log2 FC = +0.543, t-test p < 0.001).
This table shows molecular features associated with SNCB in patient tissues and cancer cell lines. In patient samples, SNCB 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, SNCB RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BONE and LUNG_SCLC.
