Q-omics provides the consensus-scored YPEL5 profile across patient tissues and cancer cell-line models. YPEL5 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, YPEL5 is differentially expressed in 16, with the highest sampling consensus in KICH. Additionally, YPEL5 RNA expression shows 19,357 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, KICH, and UVM as cancer lineages where YPEL5 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 YPEL5 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YPEL5 survival associations across molecular data types. YPEL5 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YPEL5 RNA expression–survival associations across cancer types. High YPEL5 expression shows unfavorable associations in HNSC, KIRP and LIHC, but favorable associations in KIRC, BLCA and CHOL. The KIRC 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 KIRC as the clearest survival context for YPEL5 RNA expression.
This table summarizes YPEL5 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in LIHC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for YPEL5. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YPEL5 shows lower tumor expression in KICH, KIRC, KIRP and LUAD and higher tumor expression in LIHC and HNSC. The KICH box plot shows higher YPEL5 RNA expression in normal versus tumor tissue (log2 FC = −2.051, t-test p < 0.001).
This table shows molecular features associated with YPEL5 in patient tissues and cancer cell lines. In patient samples, YPEL5 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, YPEL5 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
