Q-omics provides the consensus-scored PKLR profile across patient tissues and cancer cell-line models. PKLR expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PKLR is differentially expressed in 9, with the highest sampling consensus in KIRP. Additionally, PKLR protein abundance shows 14,917 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, KIRP, and GBM as cancer lineages where PKLR 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 PKLR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PKLR survival associations across molecular data types. PKLR RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PKLR RNA expression–survival associations across cancer types. High PKLR expression shows unfavorable associations in ACC and ESCA, but favorable associations in KIRC, HNSC, KIRP and UCEC. 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 PKLR RNA expression.
This table summarizes PKLR 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 7. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PKLR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PKLR shows lower tumor expression in KIRP, KICH and CHOL and higher tumor expression in LUSC, BRCA and HNSC. The KIRP box plot shows higher PKLR RNA expression in normal versus tumor tissue (log2 FC = −2.976, t-test p < 0.001).
This table shows molecular features associated with PKLR in patient tissues and cancer cell lines. In patient samples, PKLR 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, PKLR 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 OVARY and BLOOD_Leukemia.
