Q-omics provides the consensus-scored STYX profile across patient tissues and cancer cell-line models. STYX expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, STYX is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, STYX RNA expression shows 19,861 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BLCA, HNSC, and ACC as cancer lineages where STYX 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 STYX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes STYX survival associations across molecular data types. STYX 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 STYX RNA expression–survival associations across cancer types. High STYX expression shows unfavorable associations in BLCA, STAD, KICH, KIRP and ACC, but favorable associations in KIRC. The BLCA 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 BLCA as the clearest survival context for STYX RNA expression.
This table summarizes STYX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for STYX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. STYX shows lower tumor expression in THCA and higher tumor expression in HNSC, LUAD, KIRP, KIRC and LUSC. The HNSC box plot shows higher STYX RNA expression in tumor versus normal tissue (log2 FC = +0.659, t-test p < 0.001).
This table shows molecular features associated with STYX in patient tissues and cancer cell lines. In patient samples, STYX shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, STYX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in CNS and UPPER_AERODIGESTIVE_TRACT.
