Q-omics provides the consensus-scored PLVAP profile across patient tissues and cancer cell-line models. PLVAP expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PLVAP is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, PLVAP protein abundance shows 33,651 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where PLVAP 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 PLVAP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLVAP survival associations across molecular data types. PLVAP RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLVAP RNA expression–survival associations across cancer types. High PLVAP expression shows unfavorable associations in KIRP and MESO, but favorable associations in KIRC, HNSC, UCEC and LIHC. 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 PLVAP RNA expression.
This table summarizes PLVAP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PLVAP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLVAP shows lower tumor expression in KIRP and KICH and higher tumor expression in KIRC, HNSC, LIHC and STAD. The KIRC box plot shows higher PLVAP RNA expression in tumor versus normal tissue (log2 FC = +2.303, t-test p < 0.001).
This table shows molecular features associated with PLVAP in patient tissues and cancer cell lines. In patient samples, PLVAP 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, PLVAP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
