Q-omics provides the consensus-scored PLEK profile across patient tissues and cancer cell-line models. PLEK expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, PLEK is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, PLEK protein abundance shows 28,699 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KIRC, and GBM as cancer lineages where PLEK 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 PLEK — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLEK survival associations across molecular data types. PLEK RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLEK RNA expression–survival associations across cancer types. High PLEK expression shows unfavorable associations in LGG, but favorable associations in SKCM, HNSC, LUAD, KIRC and UCEC. 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 PLEK RNA expression.
This table summarizes PLEK tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 8. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLEK. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLEK shows lower tumor expression in LUAD and LUSC and higher tumor expression in KIRC, KIRP, STAD and BRCA. The KIRC box plot shows higher PLEK RNA expression in tumor versus normal tissue (log2 FC = +2.557, t-test p < 0.001).
This table shows molecular features associated with PLEK in patient tissues and cancer cell lines. In patient samples, PLEK 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, PLEK RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
