Q-omics provides the consensus-scored S100A7A profile across patient tissues and cancer cell-line models. S100A7A expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, S100A7A is differentially expressed in 4, with the highest sampling consensus in BRCA. Additionally, S100A7A RNA expression shows 7,115 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight BRCA, and ESCA as cancer lineages where S100A7A 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 S100A7A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes S100A7A survival associations across molecular data types. S100A7A RNA expression shows survival associations in the most cancer types (19), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible S100A7A RNA expression–survival associations across cancer types. High S100A7A expression shows unfavorable associations in BRCA, UCS, TGCT, UCEC, BLCA and SKCM. The BRCA 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 BRCA as the clearest survival context for S100A7A RNA expression.
This table summarizes S100A7A 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 2. The strongest signals are observed in BRCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for S100A7A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. S100A7A shows higher tumor expression in BRCA, LUSC, HNSC and KIRC. The BRCA box plot shows higher S100A7A RNA expression in tumor versus normal tissue (log2 FC = +0.655, t-test p < 0.001).
This table shows molecular features associated with S100A7A in patient tissues and cancer cell lines. In patient samples, S100A7A 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, S100A7A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SKIN.
