Q-omics provides the consensus-scored ACTG1P2 profile across patient tissues and cancer cell-line models. ACTG1P2 expression is associated with patient survival in 15 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, ACTG1P2 is differentially expressed in 2, with the highest sampling consensus in READ. Additionally, ACTG1P2 RNA expression shows 4,435 significant pathway-activity associations, with the highest sampling consensus in LIHC. Together, these results highlight MESO, READ, and LIHC as cancer lineages where ACTG1P2 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 ACTG1P2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTG1P2 survival associations across molecular data types. ACTG1P2 RNA expression shows survival associations in the most cancer types (15). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACTG1P2 RNA expression–survival associations across cancer types. High ACTG1P2 expression shows unfavorable associations in MESO, THYM, KICH and SARC, but favorable associations in BRCA and ESCA. 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 ACTG1P2 RNA expression.
This table summarizes ACTG1P2 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 READ for RNA.
This table ranks reproducible tumor–normal expression differences for ACTG1P2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTG1P2 shows lower tumor expression in READ and KIRP. The READ box plot shows higher ACTG1P2 RNA expression in normal versus tumor tissue (log2 FC = −0.086, t-test p = .003).
This table shows molecular features associated with ACTG1P2 in patient tissues and cancer cell lines. In patient samples, ACTG1P2 shows the broadest associations at the RNA and protein expression levels, with LIHC recurring as the lineage with the largest associated feature set.
