Q-omics provides the consensus-scored PMEL profile across patient tissues and cancer cell-line models. PMEL expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PMEL is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, PMEL RNA expression shows 17,635 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, BLCA, and THYM as cancer lineages where PMEL 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 PMEL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PMEL survival associations across molecular data types. PMEL RNA expression shows survival associations in the most cancer types (17), followed by mutation status (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PMEL RNA expression–survival associations across cancer types. High PMEL expression shows unfavorable associations in LGG and SKCM, but favorable associations in UVM, MESO, LUSC and BRCA. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .004). Together, the overview and detailed table identify UVM as the clearest survival context for PMEL RNA expression.
This table summarizes PMEL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in BLCA for RNA.
This table ranks reproducible tumor–normal expression differences for PMEL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PMEL shows lower tumor expression in KICH and BRCA and higher tumor expression in BLCA, STAD, LUAD and LUSC. The BLCA box plot shows higher PMEL RNA expression in tumor versus normal tissue (log2 FC = +0.881, t-test p < 0.001).
This table shows molecular features associated with PMEL in patient tissues and cancer cell lines. In patient samples, PMEL shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, PMEL 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 BLOOD_Leukemia and SKIN.
