Q-omics provides the consensus-scored S100G profile across patient tissues and cancer cell-line models. S100G expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, S100G is differentially expressed in 4, with the highest sampling consensus in KIRC. Additionally, S100G RNA expression shows 9,941 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, and ESCA as cancer lineages where S100G 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 S100G — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes S100G survival associations across molecular data types. S100G RNA expression shows survival associations in the most cancer types (15), followed by mutation status (1) 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 S100G RNA expression–survival associations across cancer types. High S100G expression shows unfavorable associations in KIRC, THCA, ACC, COAD, DLBC and STAD. The KIRC 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 KIRC as the clearest survival context for S100G RNA expression.
This table summarizes S100G tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 4, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for S100G. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. S100G shows lower tumor expression in STAD and higher tumor expression in KIRC, ESCA and UCEC. The KIRC box plot shows higher S100G RNA expression in tumor versus normal tissue (log2 FC = +0.319, t-test p = .006).
This table shows molecular features associated with S100G in patient tissues and cancer cell lines. In patient samples, S100G 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, S100G RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Myeloma.
