Q-omics provides the consensus-scored SYBU profile across patient tissues and cancer cell-line models. SYBU expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, SYBU is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, SYBU RNA expression shows 17,168 significant gene co-expression associations, with the highest sampling consensus in PCPG. Together, these results highlight BRCA, THCA, and PCPG as cancer lineages where SYBU 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 SYBU — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYBU survival associations across molecular data types. SYBU RNA expression shows survival associations in the most cancer types (26), 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 SYBU RNA expression–survival associations across cancer types. High SYBU expression shows unfavorable associations in ESCA, but favorable associations in BRCA, MESO, UVM, LIHC and LGG. The BRCA 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 BRCA as the clearest survival context for SYBU RNA expression.
This table summarizes SYBU tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 4. The strongest signals are observed in THCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SYBU. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYBU shows lower tumor expression in THCA, LUSC, BLCA and UCEC and higher tumor expression in COAD and KIRP. The THCA box plot shows higher SYBU RNA expression in normal versus tumor tissue (log2 FC = −1.979, t-test p < 0.001).
This table shows molecular features associated with SYBU in patient tissues and cancer cell lines. In patient samples, SYBU shows the broadest associations at the RNA and protein expression levels, with PCPG recurring as the lineage with the largest associated feature set. In cancer cell lines, SYBU RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
