Q-omics provides the consensus-scored SYT3 profile across patient tissues and cancer cell-line models. SYT3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, SYT3 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, SYT3 RNA expression shows 13,736 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight STAD, KICH, and TGCT as cancer lineages where SYT3 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 SYT3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYT3 survival associations across molecular data types. SYT3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYT3 RNA expression–survival associations across cancer types. High SYT3 expression shows unfavorable associations in STAD, KIRC, LUSC and SCLC, but favorable associations in PAAD and LGG. The STAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify STAD as the clearest survival context for SYT3 RNA expression.
This table summarizes SYT3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for SYT3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYT3 shows lower tumor expression in KICH, KIRC and THCA and higher tumor expression in LIHC, KIRP and CHOL. The KICH box plot shows higher SYT3 RNA expression in normal versus tumor tissue (log2 FC = −0.620, t-test p < 0.001).
This table shows molecular features associated with SYT3 in patient tissues and cancer cell lines. In patient samples, SYT3 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SYT3 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 LUNG_NSCLC_LUAD and BONE.
