Q-omics provides the consensus-scored SYNGAP1 profile across patient tissues and cancer cell-line models. SYNGAP1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SYNGAP1 is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, SYNGAP1 RNA expression shows 20,687 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight HNSC, LIHC, and KIRP as cancer lineages where SYNGAP1 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 SYNGAP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYNGAP1 survival associations across molecular data types. SYNGAP1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYNGAP1 RNA expression–survival associations across cancer types. High SYNGAP1 expression shows unfavorable associations in THCA, ACC, COAD and KIRC, but favorable associations in HNSC and BRCA. 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 SYNGAP1 RNA expression.
This table summarizes SYNGAP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for SYNGAP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYNGAP1 shows lower tumor expression in BLCA, KICH and LUAD and higher tumor expression in LIHC, COAD and HNSC. The LIHC box plot shows higher SYNGAP1 RNA expression in tumor versus normal tissue (log2 FC = +0.520, t-test p < 0.001).
This table shows molecular features associated with SYNGAP1 in patient tissues and cancer cell lines. In patient samples, SYNGAP1 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, SYNGAP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
