SECIS binding protein 2 likeGenealiases: SBP2L · SLAN
Q-omics provides the consensus-scored SECISBP2L profile across patient tissues and cancer cell-line models. SECISBP2L expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SECISBP2L is differentially expressed in 14, with the highest sampling consensus in LUSC. Additionally, SECISBP2L RNA expression shows 21,751 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, LUSC, and THYM as cancer lineages where SECISBP2L 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 SECISBP2L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SECISBP2L survival associations across molecular data types. SECISBP2L RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SECISBP2L RNA expression–survival associations across cancer types. High SECISBP2L expression shows unfavorable associations in OV, LUSC and CESC, but favorable associations in KIRC, UCEC and PRAD. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for SECISBP2L RNA expression.
This table summarizes SECISBP2L 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 6. The strongest signals are observed in LUSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SECISBP2L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SECISBP2L shows lower tumor expression in LUSC, LUAD, COAD, THCA, UCEC and BRCA. The LUSC box plot shows higher SECISBP2L RNA expression in normal versus tumor tissue (log2 FC = −2.012, t-test p < 0.001).
This table shows molecular features associated with SECISBP2L in patient tissues and cancer cell lines. In patient samples, SECISBP2L shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SECISBP2L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
