Q-omics provides the consensus-scored SYT1 profile across patient tissues and cancer cell-line models. SYT1 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, SYT1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SYT1 protein abundance shows 19,027 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BRCA, HNSC, and GBM as cancer lineages where SYT1 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 SYT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYT1 survival associations across molecular data types. SYT1 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) 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 SYT1 RNA expression–survival associations across cancer types. High SYT1 expression shows unfavorable associations in HNSC, KIRP, COAD, STAD and UVM, but favorable associations in BRCA. 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 SYT1 RNA expression.
This table summarizes SYT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SYT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYT1 shows lower tumor expression in KIRC, KIRP and KICH and higher tumor expression in HNSC, THCA and LUAD. The HNSC box plot shows higher SYT1 RNA expression in tumor versus normal tissue (log2 FC = +1.806, t-test p < 0.001).
This table shows molecular features associated with SYT1 in patient tissues and cancer cell lines. In patient samples, SYT1 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, SYT1 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 LARGE_INTESTINE and BLOOD_Leukemia.
