signal peptide peptidase like 2BGenealiases: IMP-4 · IMP4 · PSH4 · PSL1
Q-omics provides the consensus-scored SPPL2B profile across patient tissues and cancer cell-line models. SPPL2B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SPPL2B is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SPPL2B RNA expression shows 19,351 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KIRC as cancer lineages where SPPL2B 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 SPPL2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPPL2B survival associations across molecular data types. SPPL2B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPPL2B RNA expression–survival associations across cancer types. High SPPL2B expression shows unfavorable associations in ACC, KIRC, LGG and KICH, but favorable associations in HNSC and PAAD. The ACC 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 ACC as the clearest survival context for SPPL2B RNA expression.
This table summarizes SPPL2B 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 2. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SPPL2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPPL2B shows higher tumor expression in KIRC, BLCA, LIHC, STAD, COAD and HNSC. The KIRC box plot shows higher SPPL2B RNA expression in tumor versus normal tissue (log2 FC = +0.573, t-test p < 0.001).
This table shows molecular features associated with SPPL2B in patient tissues and cancer cell lines. In patient samples, SPPL2B shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPPL2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and OVARY.
