Q-omics provides the consensus-scored AMPD3 profile across patient tissues and cancer cell-line models. AMPD3 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AMPD3 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, AMPD3 protein abundance shows 38,814 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where AMPD3 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 AMPD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AMPD3 survival associations across molecular data types. AMPD3 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AMPD3 RNA expression–survival associations across cancer types. High AMPD3 expression shows unfavorable associations in KIRP, LGG and LUAD, but favorable associations in ACC, HNSC and SKCM. The ACC 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 ACC as the clearest survival context for AMPD3 RNA expression.
This table summarizes AMPD3 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 12. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AMPD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AMPD3 shows higher tumor expression in HNSC, KICH, LUAD, COAD, LIHC and STAD. The HNSC box plot shows higher AMPD3 RNA expression in tumor versus normal tissue (log2 FC = +0.701, t-test p < 0.001).
This table shows molecular features associated with AMPD3 in patient tissues and cancer cell lines. In patient samples, AMPD3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, AMPD3 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 PANCREAS and SOFT_TISSUE.
