Q-omics provides the consensus-scored AMPD2 profile across patient tissues and cancer cell-line models. AMPD2 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, AMPD2 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, AMPD2 protein abundance shows 22,141 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, COAD, and LSCC as cancer lineages where AMPD2 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 AMPD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AMPD2 survival associations across molecular data types. AMPD2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 AMPD2 RNA expression–survival associations across cancer types. High AMPD2 expression shows unfavorable associations in KIRC, UCEC, HNSC, LIHC and KIRP, but favorable associations in READ. The KIRC 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 KIRC as the clearest survival context for AMPD2 RNA expression.
This table summarizes AMPD2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AMPD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AMPD2 shows lower tumor expression in KICH and higher tumor expression in COAD, HNSC, KIRC, BLCA and LUAD. The COAD box plot shows higher AMPD2 RNA expression in tumor versus normal tissue (log2 FC = +1.425, t-test p < 0.001).
This table shows molecular features associated with AMPD2 in patient tissues and cancer cell lines. In patient samples, AMPD2 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, AMPD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
