Q-omics provides the consensus-scored SELE profile across patient tissues and cancer cell-line models. SELE expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SELE is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, SELE RNA expression shows 13,366 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KICH, and UVM as cancer lineages where SELE 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 SELE — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SELE survival associations across molecular data types. SELE RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SELE RNA expression–survival associations across cancer types. High SELE expression shows unfavorable associations in KIRP, MESO, UVM and COAD, but favorable associations in HNSC and KIRC. 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 SELE RNA expression.
This table summarizes SELE tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for SELE. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SELE shows lower tumor expression in KICH, KIRC, KIRP, UCEC, LUSC and BRCA. The KICH box plot shows higher SELE RNA expression in normal versus tumor tissue (log2 FC = −4.332, t-test p < 0.001).
This table shows molecular features associated with SELE in patient tissues and cancer cell lines. In patient samples, SELE shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SELE 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 LARGE_INTESTINE and LUNG_SCLC.
