Q-omics provides the consensus-scored SNU13 profile across patient tissues and cancer cell-line models. SNU13 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SNU13 is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, SNU13 protein abundance shows 29,147 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, COAD, and GBM as cancer lineages where SNU13 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 SNU13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNU13 survival associations across molecular data types. SNU13 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SNU13 RNA expression–survival associations across cancer types. High SNU13 expression shows unfavorable associations in ACC, LIHC, KICH, UVM and HNSC, but favorable associations in LGG. The ACC 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 ACC as the clearest survival context for SNU13 RNA expression.
This table summarizes SNU13 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 7. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SNU13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNU13 shows higher tumor expression in COAD, LIHC, HNSC, LUSC, STAD and CHOL. The COAD box plot shows higher SNU13 RNA expression in tumor versus normal tissue (log2 FC = +0.867, t-test p < 0.001).
This table shows molecular features associated with SNU13 in patient tissues and cancer cell lines. In patient samples, SNU13 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, SNU13 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.