glycine-N-acyltransferase like 1 pseudogene 4Genealiases: []
Q-omics provides the consensus-scored GLYATL1P4 profile across patient tissues and cancer cell-line models. GLYATL1P4 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, GLYATL1P4 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, GLYATL1P4 RNA expression shows 11,909 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight MESO, LIHC, and TGCT as cancer lineages where GLYATL1P4 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 GLYATL1P4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes GLYATL1P4 survival associations across molecular data types. GLYATL1P4 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible GLYATL1P4 RNA expression–survival associations across cancer types. High GLYATL1P4 expression shows unfavorable associations in MESO and STAD, but favorable associations in BLCA, KIRC, SKCM and COAD. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .010). Together, the overview and detailed table identify MESO as the clearest survival context for GLYATL1P4 RNA expression.
This table summarizes GLYATL1P4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in LIHC for RNA.
This table ranks reproducible tumor–normal expression differences for GLYATL1P4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. GLYATL1P4 shows higher tumor expression in LIHC, COAD, KIRP, KIRC, KICH and PRAD. The LIHC box plot shows higher GLYATL1P4 RNA expression in tumor versus normal tissue (log2 FC = +1.310, t-test p < 0.001).
This table shows molecular features associated with GLYATL1P4 in patient tissues and cancer cell lines. In patient samples, GLYATL1P4 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set.
