Q-omics provides the consensus-scored SFMBT2 profile across patient tissues and cancer cell-line models. SFMBT2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SFMBT2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, SFMBT2 RNA expression shows 19,524 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where SFMBT2 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 SFMBT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SFMBT2 survival associations across molecular data types. SFMBT2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SFMBT2 RNA expression–survival associations across cancer types. High SFMBT2 expression shows unfavorable associations in UVM and ACC, but favorable associations in HNSC, SKCM, CHOL and MESO. The HNSC 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 HNSC as the clearest survival context for SFMBT2 RNA expression.
This table summarizes SFMBT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SFMBT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SFMBT2 shows lower tumor expression in UCEC, COAD, THCA and BLCA and higher tumor expression in KIRC and HNSC. The KIRC box plot shows higher SFMBT2 RNA expression in tumor versus normal tissue (log2 FC = +0.867, t-test p < 0.001).
This table shows molecular features associated with SFMBT2 in patient tissues and cancer cell lines. In patient samples, SFMBT2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SFMBT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BLOOD_Leukemia.
