Q-omics provides the consensus-scored AK2 profile across patient tissues and cancer cell-line models. AK2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, AK2 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, AK2 protein abundance shows 20,013 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where AK2 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 AK2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AK2 survival associations across molecular data types. AK2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AK2 RNA expression–survival associations across cancer types. High AK2 expression shows unfavorable associations in ACC, PAAD, LGG, KICH and LIHC, but favorable associations in LUAD. The ACC 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 ACC as the clearest survival context for AK2 RNA expression.
This table summarizes AK2 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 HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AK2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AK2 shows lower tumor expression in KICH, KIRP and THCA and higher tumor expression in HNSC, BLCA and STAD. The HNSC box plot shows higher AK2 RNA expression in tumor versus normal tissue (log2 FC = +0.602, t-test p < 0.001).
This table shows molecular features associated with AK2 in patient tissues and cancer cell lines. In patient samples, AK2 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, AK2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
