Q-omics provides the consensus-scored PRLR profile across patient tissues and cancer cell-line models. PRLR expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, PRLR is differentially expressed in 10, with the highest sampling consensus in KIRP. Additionally, PRLR protein abundance shows 20,188 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight UVM, KIRP, and PDAC as cancer lineages where PRLR 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 PRLR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRLR survival associations across molecular data types. PRLR RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRLR RNA expression–survival associations across cancer types. High PRLR expression shows unfavorable associations in UVM and THYM, but favorable associations in ACC, MESO, KIRC and PAAD. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for PRLR RNA expression.
This table summarizes PRLR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PRLR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRLR shows lower tumor expression in KIRP and KIRC and higher tumor expression in STAD, BRCA, KICH and LUSC. The KIRP box plot shows higher PRLR RNA expression in normal versus tumor tissue (log2 FC = −2.022, t-test p < 0.001).
This table shows molecular features associated with PRLR in patient tissues and cancer cell lines. In patient samples, PRLR shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PRLR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BREAST.
