Q-omics provides the consensus-scored A2M profile across patient tissues and cancer cell-line models. A2M expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, A2M is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, A2M RNA expression shows 25,955 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, BLCA, and LSCC as cancer lineages where A2M 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 A2M — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes A2M survival associations across molecular data types. A2M RNA expression shows survival associations in the most cancer types (24), followed by mutation status (10) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible A2M RNA expression–survival associations across cancer types. High A2M expression shows unfavorable associations in BLCA and LUSC, but favorable associations in KIRC, SKCM, THCA and HNSC. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for A2M RNA expression.
This table summarizes A2M tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 7. The strongest signals are observed in LUAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for A2M. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. A2M shows lower tumor expression in BLCA, LUAD, KICH, LUSC, COAD and KIRP. The BLCA box plot shows higher A2M RNA expression in normal versus tumor tissue (log2 FC = −3.051, t-test p < 0.001).
This table shows molecular features associated with A2M in patient tissues and cancer cell lines. In patient samples, A2M shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, A2M RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUSC and LARGE_INTESTINE.
