Q-omics provides the consensus-scored AMY2A profile across patient tissues and cancer cell-line models. AMY2A expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AMY2A is differentially expressed in 2, with the highest sampling consensus in UCEC. Additionally, AMY2A RNA expression shows 9,306 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, UCEC, and PDAC as cancer lineages where AMY2A 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 AMY2A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AMY2A survival associations across molecular data types. AMY2A RNA expression shows survival associations in the most cancer types (20), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AMY2A RNA expression–survival associations across cancer types. High AMY2A expression shows unfavorable associations in KIRC, LUAD, CHOL, UVM and LIHC, but favorable associations in OV. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KIRC as the clearest survival context for AMY2A RNA expression.
This table summarizes AMY2A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2, while mass-spec protein shows differences in 2. The strongest signals are observed in UCEC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for AMY2A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AMY2A shows lower tumor expression in UCEC and BLCA. The UCEC box plot shows higher AMY2A RNA expression in normal versus tumor tissue (log2 FC = −0.116, t-test p = .004).
This table shows molecular features associated with AMY2A in patient tissues and cancer cell lines. In patient samples, AMY2A 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, AMY2A 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 OESOPHAGUS.
