Q-omics provides the consensus-scored AKAP13 profile across patient tissues and cancer cell-line models. AKAP13 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AKAP13 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, AKAP13 protein abundance shows 24,588 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where AKAP13 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 AKAP13 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AKAP13 survival associations across molecular data types. AKAP13 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8) 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 AKAP13 RNA expression–survival associations across cancer types. High AKAP13 expression shows unfavorable associations in UVM, BLCA and LGG, but favorable associations in KIRC, SKCM and SCLC. The KIRC 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 KIRC as the clearest survival context for AKAP13 RNA expression.
This table summarizes AKAP13 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AKAP13. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AKAP13 shows lower tumor expression in LUAD, LUSC and COAD and higher tumor expression in KIRC, HNSC and STAD. The KIRC box plot shows higher AKAP13 RNA expression in tumor versus normal tissue (log2 FC = +0.797, t-test p < 0.001).
This table shows molecular features associated with AKAP13 in patient tissues and cancer cell lines. In patient samples, AKAP13 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, AKAP13 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
