Q-omics provides the consensus-scored ACTG1P23 profile across patient tissues and cancer cell-line models. ACTG1P23 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ACTG1P23 is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, ACTG1P23 RNA expression shows 13,974 significant gene co-expression associations, with the highest sampling consensus in KICH. Together, these results highlight MESO, BLCA, and KICH as cancer lineages where ACTG1P23 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 ACTG1P23 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTG1P23 survival associations across molecular data types. ACTG1P23 RNA expression shows survival associations in the most cancer types (26). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACTG1P23 RNA expression–survival associations across cancer types. High ACTG1P23 expression shows unfavorable associations in MESO, STAD, KIRC and LGG, but favorable associations in CESC and LUSC. The MESO 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 MESO as the clearest survival context for ACTG1P23 RNA expression.
This table summarizes ACTG1P23 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for ACTG1P23. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTG1P23 shows lower tumor expression in BLCA and KICH and higher tumor expression in BRCA, HNSC, KIRP and LIHC. The BLCA box plot shows higher ACTG1P23 RNA expression in normal versus tumor tissue (log2 FC = −0.481, t-test p = .012).
This table shows molecular features associated with ACTG1P23 in patient tissues and cancer cell lines. In patient samples, ACTG1P23 shows the broadest associations at the RNA and protein expression levels, with KICH recurring as the lineage with the largest associated feature set.
