Q-omics provides the consensus-scored SYT9 profile across patient tissues and cancer cell-line models. SYT9 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SYT9 is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, SYT9 RNA expression shows 20,917 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KICH, and GBM as cancer lineages where SYT9 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 SYT9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYT9 survival associations across molecular data types. SYT9 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYT9 RNA expression–survival associations across cancer types. High SYT9 expression shows unfavorable associations in HNSC, STAD and KIRP, but favorable associations in KIRC, BRCA and BLCA. The KIRC 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 KIRC as the clearest survival context for SYT9 RNA expression.
This table summarizes SYT9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for SYT9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYT9 shows lower tumor expression in KICH, THCA, KIRP, COAD and LIHC and higher tumor expression in BRCA. The KICH box plot shows higher SYT9 RNA expression in normal versus tumor tissue (log2 FC = −2.145, t-test p < 0.001).
This table shows molecular features associated with SYT9 in patient tissues and cancer cell lines. In patient samples, SYT9 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, SYT9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
