Q-omics provides the consensus-scored MAT2A profile across patient tissues and cancer cell-line models. MAT2A expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MAT2A is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, MAT2A RNA expression shows 20,730 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, THCA, and ACC as cancer lineages where MAT2A 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 MAT2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAT2A survival associations across molecular data types. MAT2A RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MAT2A RNA expression–survival associations across cancer types. High MAT2A expression shows unfavorable associations in LIHC, ACC and UCEC, but favorable associations in KIRC, READ and UCS. 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 MAT2A RNA expression.
This table summarizes MAT2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MAT2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAT2A shows lower tumor expression in THCA, BLCA, KICH, KIRP and LUSC and higher tumor expression in COAD. The THCA box plot shows higher MAT2A RNA expression in normal versus tumor tissue (log2 FC = −1.177, t-test p < 0.001).
This table shows molecular features associated with MAT2A in patient tissues and cancer cell lines. In patient samples, MAT2A shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, MAT2A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and UPPER_AERODIGESTIVE_TRACT.
