Q-omics provides the consensus-scored SYP profile across patient tissues and cancer cell-line models. SYP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SYP is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, SYP protein abundance shows 21,746 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where SYP 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 SYP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYP survival associations across molecular data types. SYP RNA expression shows survival associations in the most cancer types (24), 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 SYP RNA expression–survival associations across cancer types. High SYP expression shows unfavorable associations in UVM and LAML, but favorable associations in KIRC, LGG, PAAD and LUAD. The UVM 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 UVM as the clearest survival context for SYP RNA expression.
This table summarizes SYP 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 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SYP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYP shows lower tumor expression in KIRC, KIRP, COAD, THCA and KICH and higher tumor expression in LIHC. The KIRC box plot shows higher SYP RNA expression in normal versus tumor tissue (log2 FC = −1.498, t-test p < 0.001).
This table shows molecular features associated with SYP in patient tissues and cancer cell lines. In patient samples, SYP 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, SYP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BONE and LARGE_INTESTINE.
