Q-omics provides the consensus-scored S100A12 profile across patient tissues and cancer cell-line models. S100A12 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, S100A12 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, S100A12 protein abundance shows 30,087 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight LUAD, KIRC, and PDAC as cancer lineages where S100A12 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 S100A12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes S100A12 survival associations across molecular data types. S100A12 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible S100A12 RNA expression–survival associations across cancer types. High S100A12 expression shows unfavorable associations in LUAD, STAD, SCLC and COAD, but favorable associations in MESO and LUSC. The LUAD 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 LUAD as the clearest survival context for S100A12 RNA expression.
This table summarizes S100A12 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for S100A12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. S100A12 shows lower tumor expression in LIHC, LUAD, KICH, BRCA and STAD and higher tumor expression in KIRC. The KIRC box plot shows higher S100A12 RNA expression in tumor versus normal tissue (log2 FC = +1.200, t-test p < 0.001).
This table shows molecular features associated with S100A12 in patient tissues and cancer cell lines. In patient samples, S100A12 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, S100A12 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and SOFT_TISSUE.
