sperm equatorial segment protein 1Genealiases: ESP · SP-ESP
Q-omics provides the consensus-scored SPESP1 profile across patient tissues and cancer cell-line models. SPESP1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, SPESP1 is differentially expressed in 9, with the highest sampling consensus in UCEC. Additionally, SPESP1 RNA expression shows 11,884 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UCS, UCEC, and TGCT as cancer lineages where SPESP1 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 SPESP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPESP1 survival associations across molecular data types. SPESP1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPESP1 RNA expression–survival associations across cancer types. High SPESP1 expression shows unfavorable associations in UVM, COAD and HNSC, but favorable associations in UCS, ACC and BRCA. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .008). Together, the overview and detailed table identify UCS as the clearest survival context for SPESP1 RNA expression.
This table summarizes SPESP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for SPESP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPESP1 shows lower tumor expression in UCEC, KICH, KIRC, STAD, COAD and KIRP. The UCEC box plot shows higher SPESP1 RNA expression in normal versus tumor tissue (log2 FC = −1.834, t-test p < 0.001).
This table shows molecular features associated with SPESP1 in patient tissues and cancer cell lines. In patient samples, SPESP1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SPESP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
