Q-omics provides the consensus-scored AKAP8 profile across patient tissues and cancer cell-line models. AKAP8 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, AKAP8 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, AKAP8 protein abundance shows 35,933 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, KIRC, and GBM as cancer lineages where AKAP8 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 AKAP8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AKAP8 survival associations across molecular data types. AKAP8 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AKAP8 RNA expression–survival associations across cancer types. High AKAP8 expression shows unfavorable associations in KICH, ACC, LGG and UVM, but favorable associations in HNSC and SCLC. The HNSC 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 HNSC as the clearest survival context for AKAP8 RNA expression.
This table summarizes AKAP8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 10. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for AKAP8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AKAP8 shows lower tumor expression in THCA and higher tumor expression in KIRC, HNSC, COAD, LIHC and STAD. The KIRC box plot shows higher AKAP8 RNA expression in tumor versus normal tissue (log2 FC = +0.857, t-test p < 0.001).
This table shows molecular features associated with AKAP8 in patient tissues and cancer cell lines. In patient samples, AKAP8 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, AKAP8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
