Q-omics provides the consensus-scored SEL1L3 profile across patient tissues and cancer cell-line models. SEL1L3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SEL1L3 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SEL1L3 protein abundance shows 29,305 significant protein co-abundance associations, with the highest sampling consensus in UCEC. Together, these results highlight UVM, KIRC, and UCEC as cancer lineages where SEL1L3 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 SEL1L3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEL1L3 survival associations across molecular data types. SEL1L3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (7) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SEL1L3 RNA expression–survival associations across cancer types. High SEL1L3 expression shows unfavorable associations in UVM, LAML and LGG, but favorable associations in KIRC, SKCM and BLCA. 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 SEL1L3 RNA expression.
This table summarizes SEL1L3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SEL1L3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEL1L3 shows lower tumor expression in KICH and higher tumor expression in KIRC, THCA, HNSC, KIRP and LUAD. The KIRC box plot shows higher SEL1L3 RNA expression in tumor versus normal tissue (log2 FC = +2.100, t-test p < 0.001).
This table shows molecular features associated with SEL1L3 in patient tissues and cancer cell lines. In patient samples, SEL1L3 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, SEL1L3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Lymphoma.
