Q-omics provides the consensus-scored S100A9 profile across patient tissues and cancer cell-line models. S100A9 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, S100A9 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, S100A9 protein abundance shows 29,954 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight BRCA, KIRC, and PDAC as cancer lineages where S100A9 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 S100A9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes S100A9 survival associations across molecular data types. S100A9 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible S100A9 RNA expression–survival associations across cancer types. High S100A9 expression shows unfavorable associations in BRCA, LUAD, ACC, STAD and LGG, but favorable associations in LUSC. 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 S100A9 RNA expression.
This table summarizes S100A9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for S100A9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. S100A9 shows lower tumor expression in KICH and HNSC and higher tumor expression in KIRC, COAD, THCA and BLCA. The KIRC box plot shows higher S100A9 RNA expression in tumor versus normal tissue (log2 FC = +1.542, t-test p < 0.001).
This table shows molecular features associated with S100A9 in patient tissues and cancer cell lines. In patient samples, S100A9 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, S100A9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
