Q-omics provides the consensus-scored YPEL4 profile across patient tissues and cancer cell-line models. YPEL4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, YPEL4 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, YPEL4 RNA expression shows 18,485 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KIRC, and GBM as cancer lineages where YPEL4 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 YPEL4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YPEL4 survival associations across molecular data types. YPEL4 RNA expression shows survival associations in the most cancer types (25). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YPEL4 RNA expression–survival associations across cancer types. High YPEL4 expression shows unfavorable associations in KIRP, STAD and ACC, but favorable associations in SKCM, UCS and LGG. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for YPEL4 RNA expression.
This table summarizes YPEL4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for YPEL4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YPEL4 shows lower tumor expression in LUAD, LUSC and COAD and higher tumor expression in KIRC, HNSC and THCA. The KIRC box plot shows higher YPEL4 RNA expression in tumor versus normal tissue (log2 FC = +0.942, t-test p < 0.001).
This table shows molecular features associated with YPEL4 in patient tissues and cancer cell lines. In patient samples, YPEL4 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, YPEL4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and SOFT_TISSUE.
