seizure related 6 homolog like 2Genealiases: BSRPA · PSK-1
Q-omics provides the consensus-scored SEZ6L2 profile across patient tissues and cancer cell-line models. SEZ6L2 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, SEZ6L2 is differentially expressed in 15, with the highest sampling consensus in THCA. Additionally, SEZ6L2 protein abundance shows 16,390 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight COAD, THCA, and GBM as cancer lineages where SEZ6L2 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 SEZ6L2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SEZ6L2 survival associations across molecular data types. SEZ6L2 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (7) 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 SEZ6L2 RNA expression–survival associations across cancer types. High SEZ6L2 expression shows unfavorable associations in COAD, LUSC, UCS and CESC, but favorable associations in KIRC and LGG. The COAD 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 COAD as the clearest survival context for SEZ6L2 RNA expression.
This table summarizes SEZ6L2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SEZ6L2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SEZ6L2 shows higher tumor expression in THCA, KIRC, STAD, KIRP, LIHC and LUAD. The THCA box plot shows higher SEZ6L2 RNA expression in tumor versus normal tissue (log2 FC = +3.552, t-test p < 0.001).
This table shows molecular features associated with SEZ6L2 in patient tissues and cancer cell lines. In patient samples, SEZ6L2 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, SEZ6L2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
