Q-omics provides the consensus-scored SF3B5 profile across patient tissues and cancer cell-line models. SF3B5 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SF3B5 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, SF3B5 protein abundance shows 27,659 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, KICH, and LSCC as cancer lineages where SF3B5 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 SF3B5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SF3B5 survival associations across molecular data types. SF3B5 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SF3B5 RNA expression–survival associations across cancer types. High SF3B5 expression shows unfavorable associations in LIHC, ACC, HNSC and LUAD, but favorable associations in UVM 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 SF3B5 RNA expression.
This table summarizes SF3B5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SF3B5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SF3B5 shows lower tumor expression in KICH and higher tumor expression in LIHC, HNSC, COAD, STAD and CHOL. The KICH box plot shows higher SF3B5 RNA expression in normal versus tumor tissue (log2 FC = −1.311, t-test p < 0.001).
This table shows molecular features associated with SF3B5 in patient tissues and cancer cell lines. In patient samples, SF3B5 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SF3B5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
