Q-omics provides the consensus-scored ACTL6A profile across patient tissues and cancer cell-line models. ACTL6A expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ACTL6A is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ACTL6A protein abundance shows 33,315 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where ACTL6A 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 ACTL6A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTL6A survival associations across molecular data types. ACTL6A RNA expression shows survival associations in the most cancer types (28), followed by mutation status (2) 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 ACTL6A RNA expression–survival associations across cancer types. High ACTL6A expression shows unfavorable associations in ACC, LIHC, PAAD, KICH, MESO and KIRP. 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 ACTL6A RNA expression.
This table summarizes ACTL6A 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ACTL6A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTL6A shows higher tumor expression in HNSC, BLCA, LUAD, COAD, LUSC and LIHC. The HNSC box plot shows higher ACTL6A RNA expression in tumor versus normal tissue (log2 FC = +1.888, t-test p < 0.001).
This table shows molecular features associated with ACTL6A in patient tissues and cancer cell lines. In patient samples, ACTL6A 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, ACTL6A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
