Q-omics provides the consensus-scored YPEL1 profile across patient tissues and cancer cell-line models. YPEL1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, YPEL1 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, YPEL1 RNA expression shows 20,805 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight HNSC, KICH, and KIRP as cancer lineages where YPEL1 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 YPEL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YPEL1 survival associations across molecular data types. YPEL1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YPEL1 RNA expression–survival associations across cancer types. High YPEL1 expression shows unfavorable associations in ACC, THCA and KICH, but favorable associations in HNSC, KIRC and LUAD. The HNSC 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 HNSC as the clearest survival context for YPEL1 RNA expression.
This table summarizes YPEL1 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 KICH for RNA.
This table ranks reproducible tumor–normal expression differences for YPEL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YPEL1 shows lower tumor expression in KICH, LUSC and LUAD and higher tumor expression in LIHC, UCEC and CHOL. The KICH box plot shows higher YPEL1 RNA expression in normal versus tumor tissue (log2 FC = −0.979, t-test p < 0.001).
This table shows molecular features associated with YPEL1 in patient tissues and cancer cell lines. In patient samples, YPEL1 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, YPEL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUAD.
