Q-omics provides the consensus-scored SRSF10 profile across patient tissues and cancer cell-line models. SRSF10 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SRSF10 is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, SRSF10 protein abundance shows 28,601 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, BLCA, and GBM as cancer lineages where SRSF10 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 SRSF10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRSF10 survival associations across molecular data types. SRSF10 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SRSF10 RNA expression–survival associations across cancer types. High SRSF10 expression shows unfavorable associations in LIHC, ACC, LGG and UVM, but favorable associations in UCS and READ. The LIHC 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 LIHC as the clearest survival context for SRSF10 RNA expression.
This table summarizes SRSF10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SRSF10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRSF10 shows lower tumor expression in THCA and higher tumor expression in BLCA, HNSC, COAD, STAD and LIHC. The BLCA box plot shows higher SRSF10 RNA expression in tumor versus normal tissue (log2 FC = +0.832, t-test p < 0.001).
This table shows molecular features associated with SRSF10 in patient tissues and cancer cell lines. In patient samples, SRSF10 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SRSF10 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 LIVER and CNS.
