Q-omics provides the consensus-scored ACTL7A profile across patient tissues and cancer cell-line models. ACTL7A expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, ACTL7A is differentially expressed in 2, with the highest sampling consensus in ESCA. Additionally, ACTL7A RNA expression shows 6,526 significant protein co-abundance associations, with the highest sampling consensus in CCRCC. Together, these results highlight UCS, ESCA, and CCRCC as cancer lineages where ACTL7A 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 ACTL7A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTL7A survival associations across molecular data types. ACTL7A RNA expression shows survival associations in the most cancer types (11), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACTL7A RNA expression–survival associations across cancer types. High ACTL7A expression shows unfavorable associations in UCS, READ, LUSC, SCLC and COAD, but favorable associations in CESC. The UCS 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 UCS as the clearest survival context for ACTL7A RNA expression.
This table summarizes ACTL7A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in ESCA for RNA.
This table ranks reproducible tumor–normal expression differences for ACTL7A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTL7A shows lower tumor expression in KICH and higher tumor expression in ESCA. The ESCA box plot shows higher ACTL7A RNA expression in tumor versus normal tissue (log2 FC = +0.036, t-test p = .037).
This table shows molecular features associated with ACTL7A in patient tissues and cancer cell lines. In patient samples, ACTL7A shows the broadest associations at the RNA and protein expression levels, with CCRCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACTL7A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and LARGE_INTESTINE.
