Q-omics provides the consensus-scored SPX profile across patient tissues and cancer cell-line models. SPX expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SPX is differentially expressed in 16, with the highest sampling consensus in THCA. Additionally, SPX RNA expression shows 16,505 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, THCA, and TGCT as cancer lineages where SPX 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 SPX — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPX survival associations across molecular data types. SPX RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPX RNA expression–survival associations across cancer types. High SPX expression shows unfavorable associations in KIRP, MESO, STAD, COAD and LUAD, but favorable associations in KIRC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify KIRP as the clearest survival context for SPX RNA expression.
This table summarizes SPX tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SPX. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPX shows lower tumor expression in THCA, KIRC, BLCA, HNSC, COAD and LUAD. The THCA box plot shows higher SPX RNA expression in normal versus tumor tissue (log2 FC = −4.904, t-test p < 0.001).
This table shows molecular features associated with SPX in patient tissues and cancer cell lines. In patient samples, SPX 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, SPX RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BREAST.
