Q-omics provides the consensus-scored PLG profile across patient tissues and cancer cell-line models. PLG 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, PLG is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PLG protein abundance shows 17,541 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where PLG 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 PLG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLG survival associations across molecular data types. PLG RNA expression shows survival associations in the most cancer types (21), followed by mutation status (8) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLG RNA expression–survival associations across cancer types. High PLG expression shows unfavorable associations in STAD, but favorable associations in KIRC, LIHC, BLCA, SKCM and READ. 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 PLG RNA expression.
This table summarizes PLG 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 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PLG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLG shows lower tumor expression in KIRC, KIRP, KICH, LIHC, CHOL and LUAD. The KIRC box plot shows higher PLG RNA expression in normal versus tumor tissue (log2 FC = −2.889, t-test p < 0.001).
This table shows molecular features associated with PLG in patient tissues and cancer cell lines. In patient samples, PLG 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, PLG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
