Q-omics provides the consensus-scored ACTA1 profile across patient tissues and cancer cell-line models. ACTA1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ACTA1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, ACTA1 protein abundance shows 22,615 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight HNSC as cancer lineages where ACTA1 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 ACTA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTA1 survival associations across molecular data types. ACTA1 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) 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 ACTA1 RNA expression–survival associations across cancer types. High ACTA1 expression shows unfavorable associations in HNSC, STAD, MESO, ACC, UCEC and UVM. The HNSC 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 HNSC as the clearest survival context for ACTA1 RNA expression.
This table summarizes ACTA1 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 HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for ACTA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTA1 shows lower tumor expression in HNSC, KICH, BLCA and PRAD and higher tumor expression in LIHC and CHOL. The HNSC box plot shows higher ACTA1 RNA expression in normal versus tumor tissue (log2 FC = −3.655, t-test p = .006).
This table shows molecular features associated with ACTA1 in patient tissues and cancer cell lines. In patient samples, ACTA1 shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, ACTA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and SOFT_TISSUE.
