Q-omics provides the consensus-scored SOST profile across patient tissues and cancer cell-line models. SOST expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, SOST is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, SOST RNA expression shows 8,739 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight SCLC, KIRC, and ESCA as cancer lineages where SOST 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 SOST — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SOST survival associations across molecular data types. SOST RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SOST RNA expression–survival associations across cancer types. High SOST expression shows unfavorable associations in SCLC, LIHC, GBM, UCS and KIRP, but favorable associations in CHOL. The SCLC 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 SCLC as the clearest survival context for SOST RNA expression.
This table summarizes SOST tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SOST. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SOST shows lower tumor expression in KIRC, KIRP, KICH, THCA and LUAD and higher tumor expression in HNSC. The KIRC box plot shows higher SOST RNA expression in normal versus tumor tissue (log2 FC = −4.008, t-test p < 0.001).
This table shows molecular features associated with SOST in patient tissues and cancer cell lines. In patient samples, SOST shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SOST 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 URINARY_TRACT and LARGE_INTESTINE.
