Q-omics provides the consensus-scored SRSF1 profile across patient tissues and cancer cell-line models. SRSF1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SRSF1 is differentially expressed in 15, with the highest sampling consensus in BLCA. Additionally, SRSF1 protein abundance shows 28,859 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, BLCA, and GBM as cancer lineages where SRSF1 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 SRSF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SRSF1 survival associations across molecular data types. SRSF1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 SRSF1 RNA expression–survival associations across cancer types. High SRSF1 expression shows unfavorable associations in UVM, LIHC, ACC, KIRP, LGG and SCLC. The UVM 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 UVM as the clearest survival context for SRSF1 RNA expression.
This table summarizes SRSF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 4. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SRSF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SRSF1 shows lower tumor expression in THCA and higher tumor expression in BLCA, HNSC, STAD, LIHC and BRCA. The BLCA box plot shows higher SRSF1 RNA expression in tumor versus normal tissue (log2 FC = +0.810, t-test p < 0.001).
This table shows molecular features associated with SRSF1 in patient tissues and cancer cell lines. In patient samples, SRSF1 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, SRSF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
