SERPINE1 mRNA binding protein 1 pseudogene 2Genealiases: []
Q-omics provides the consensus-scored SERBP1P2 profile across patient tissues and cancer cell-line models. SERBP1P2 expression is associated with patient survival in 7 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, SERBP1P2 is differentially expressed in 2, with the highest sampling consensus in LUSC. Additionally, SERBP1P2 RNA expression shows 3,165 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight STAD, and LUSC as cancer lineages where SERBP1P2 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 SERBP1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERBP1P2 survival associations across molecular data types. SERBP1P2 RNA expression shows survival associations in the most cancer types (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERBP1P2 RNA expression–survival associations across cancer types. High SERBP1P2 expression shows unfavorable associations in STAD, COAD, DLBC, KIRP, THCA and LIHC. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify STAD as the clearest survival context for SERBP1P2 RNA expression.
This table summarizes SERBP1P2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for SERBP1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERBP1P2 shows higher tumor expression in LUSC and HNSC. The LUSC box plot shows higher SERBP1P2 RNA expression in tumor versus normal tissue (log2 FC = +0.025, t-test p = .012).
This table shows molecular features associated with SERBP1P2 in patient tissues and cancer cell lines. In patient samples, SERBP1P2 shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set.
