Q-omics provides the consensus-scored SF3B3 profile across patient tissues and cancer cell-line models. SF3B3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, SF3B3 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, SF3B3 protein abundance shows 33,063 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SCLC, COAD, and LSCC as cancer lineages where SF3B3 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 SF3B3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SF3B3 survival associations across molecular data types. SF3B3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (11) 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 SF3B3 RNA expression–survival associations across cancer types. High SF3B3 expression shows unfavorable associations in MESO, ACC and LIHC, but favorable associations in SCLC, KIRC and UVM. The SCLC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SCLC as the clearest survival context for SF3B3 RNA expression.
This table summarizes SF3B3 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 7. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SF3B3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SF3B3 shows higher tumor expression in COAD, BLCA, KIRP, HNSC, STAD and LUAD. The COAD box plot shows higher SF3B3 RNA expression in tumor versus normal tissue (log2 FC = +1.311, t-test p < 0.001).
This table shows molecular features associated with SF3B3 in patient tissues and cancer cell lines. In patient samples, SF3B3 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, SF3B3 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 SKIN and UPPER_AERODIGESTIVE_TRACT.
