Q-omics provides the consensus-scored SEZ6L profile across patient tissues and cancer cell-line models. SEZ6L expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, SEZ6L is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, SEZ6L protein abundance shows 15,055 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, COAD, and GBM as cancer lineages where SEZ6L 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 SEZ6L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEZ6L survival associations across molecular data types. SEZ6L RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) 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 SEZ6L RNA expression–survival associations across cancer types. High SEZ6L expression shows favorable associations in LUAD, KIRC, LGG, PAAD, BRCA and SKCM. The LUAD 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 LUAD as the clearest survival context for SEZ6L RNA expression.
This table summarizes SEZ6L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 3. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SEZ6L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEZ6L shows lower tumor expression in COAD, STAD, LIHC and READ and higher tumor expression in KICH and KIRC. The COAD box plot shows higher SEZ6L RNA expression in normal versus tumor tissue (log2 FC = −0.530, t-test p < 0.001).
This table shows molecular features associated with SEZ6L in patient tissues and cancer cell lines. In patient samples, SEZ6L 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, SEZ6L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
