Q-omics provides the consensus-scored ANKRD13A profile across patient tissues and cancer cell-line models. ANKRD13A expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in OV. Among the 18 cancer types available for tumor–normal comparison, ANKRD13A is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, ANKRD13A protein abundance shows 28,780 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight OV, KIRC, and LSCC as cancer lineages where ANKRD13A 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 ANKRD13A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ANKRD13A survival associations across molecular data types. ANKRD13A RNA expression shows survival associations in the most cancer types (23), followed by mutation status (7) 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 ANKRD13A RNA expression–survival associations across cancer types. High ANKRD13A expression shows unfavorable associations in OV, ACC and MESO, but favorable associations in LUAD, HNSC and UCS. The OV 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 OV as the clearest survival context for ANKRD13A RNA expression.
This table summarizes ANKRD13A 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 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ANKRD13A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ANKRD13A shows lower tumor expression in COAD, THCA, LUSC and READ and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher ANKRD13A RNA expression in tumor versus normal tissue (log2 FC = +0.866, t-test p < 0.001).
This table shows molecular features associated with ANKRD13A in patient tissues and cancer cell lines. In patient samples, ANKRD13A 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, ANKRD13A 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 SKIN and BLOOD_Leukemia.
