Q-omics provides the consensus-scored SYK profile across patient tissues and cancer cell-line models. SYK expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SYK is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, SYK protein abundance shows 19,854 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, THCA, and GBM as cancer lineages where SYK 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 SYK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYK survival associations across molecular data types. SYK RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYK RNA expression–survival associations across cancer types. High SYK expression shows unfavorable associations in LGG, LAML and UVM, but favorable associations in HNSC, KIRC and CHOL. 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 SYK RNA expression.
This table summarizes SYK 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 4. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SYK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYK shows lower tumor expression in THCA and KIRC and higher tumor expression in STAD, HNSC, COAD and BRCA. The THCA box plot shows higher SYK RNA expression in normal versus tumor tissue (log2 FC = −0.831, t-test p < 0.001).
This table shows molecular features associated with SYK in patient tissues and cancer cell lines. In patient samples, SYK 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, SYK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Lymphoma.
