Q-omics provides the consensus-scored ACTG1P19 profile across patient tissues and cancer cell-line models. ACTG1P19 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ACTG1P19 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, ACTG1P19 RNA expression shows 9,924 significant gene co-expression associations, with the highest sampling consensus in DLBC. Together, these results highlight KICH, HNSC, and DLBC as cancer lineages where ACTG1P19 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 ACTG1P19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ACTG1P19 survival associations across molecular data types. ACTG1P19 RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ACTG1P19 RNA expression–survival associations across cancer types. High ACTG1P19 expression shows unfavorable associations in KICH, DLBC, LGG, UCS and LUAD, but favorable associations in ESCA. The KICH 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 KICH as the clearest survival context for ACTG1P19 RNA expression.
This table summarizes ACTG1P19 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ACTG1P19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ACTG1P19 shows lower tumor expression in THCA and higher tumor expression in HNSC, COAD, LIHC, LUAD and KIRP. The HNSC box plot shows higher ACTG1P19 RNA expression in tumor versus normal tissue (log2 FC = +0.133, t-test p = .003).
This table shows molecular features associated with ACTG1P19 in patient tissues and cancer cell lines. In patient samples, ACTG1P19 shows the broadest associations at the RNA and protein expression levels, with DLBC recurring as the lineage with the largest associated feature set.
