Q-omics provides the consensus-scored SRSF2P1 profile across patient tissues and cancer cell-line models. SRSF2P1 expression is associated with patient survival in 14 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, SRSF2P1 is differentially expressed in 6, with the highest sampling consensus in UCEC. Additionally, SRSF2P1 RNA expression shows 8,747 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, UCEC, and GBM as cancer lineages where SRSF2P1 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 SRSF2P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRSF2P1 survival associations across molecular data types. SRSF2P1 RNA expression shows survival associations in the most cancer types (14). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRSF2P1 RNA expression–survival associations across cancer types. High SRSF2P1 expression shows unfavorable associations in CESC, THCA, KIRC, MESO, LIHC and READ. The CESC 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 CESC as the clearest survival context for SRSF2P1 RNA expression.
This table summarizes SRSF2P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in UCEC for RNA.
This table ranks reproducible tumor–normal expression differences for SRSF2P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRSF2P1 shows lower tumor expression in UCEC, BRCA, READ and THCA and higher tumor expression in COAD and LUSC. The UCEC box plot shows higher SRSF2P1 RNA expression in normal versus tumor tissue (log2 FC = −0.153, t-test p = .002).
This table shows molecular features associated with SRSF2P1 in patient tissues and cancer cell lines. In patient samples, SRSF2P1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
