Q-omics provides the consensus-scored SYS1 profile across patient tissues and cancer cell-line models. SYS1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, SYS1 is differentially expressed in 14, with the highest sampling consensus in THCA. Additionally, SYS1 protein abundance shows 22,202 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight LIHC, THCA, and BRCA as cancer lineages where SYS1 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 SYS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SYS1 survival associations across molecular data types. SYS1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SYS1 RNA expression–survival associations across cancer types. High SYS1 expression shows unfavorable associations in LIHC, STAD and HNSC, but favorable associations in MESO, BRCA and LUAD. The LIHC 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 LIHC as the clearest survival context for SYS1 RNA expression.
This table summarizes SYS1 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 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SYS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SYS1 shows lower tumor expression in THCA, LUAD and LUSC and higher tumor expression in LIHC, STAD and HNSC. The THCA box plot shows higher SYS1 RNA expression in normal versus tumor tissue (log2 FC = −0.690, t-test p < 0.001).
This table shows molecular features associated with SYS1 in patient tissues and cancer cell lines. In patient samples, SYS1 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SYS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
