Q-omics provides the consensus-scored S100A10 profile across patient tissues and cancer cell-line models. S100A10 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, S100A10 is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, S100A10 protein abundance shows 31,852 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight HNSC, KIRC, and PDAC as cancer lineages where S100A10 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 S100A10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes S100A10 survival associations across molecular data types. S100A10 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 S100A10 RNA expression–survival associations across cancer types. High S100A10 expression shows unfavorable associations in HNSC, LIHC, LUAD, UCS, BLCA and KIRP. The HNSC 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 HNSC as the clearest survival context for S100A10 RNA expression.
This table summarizes S100A10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for S100A10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. S100A10 shows lower tumor expression in KICH and higher tumor expression in KIRC, KIRP, LIHC, HNSC and CHOL. The KIRC box plot shows higher S100A10 RNA expression in tumor versus normal tissue (log2 FC = +1.205, t-test p < 0.001).
This table shows molecular features associated with S100A10 in patient tissues and cancer cell lines. In patient samples, S100A10 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, S100A10 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 UPPER_AERODIGESTIVE_TRACT and BONE.
