Q-omics provides the consensus-scored PRMT2 profile across patient tissues and cancer cell-line models. PRMT2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, PRMT2 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PRMT2 RNA expression shows 19,462 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, KIRC, and ACC as cancer lineages where PRMT2 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 PRMT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRMT2 survival associations across molecular data types. PRMT2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRMT2 RNA expression–survival associations across cancer types. High PRMT2 expression shows unfavorable associations in LIHC, ACC, LGG and CESC, but favorable associations in HNSC and KIRC. The HNSC 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 HNSC as the clearest survival context for PRMT2 RNA expression.
This table summarizes PRMT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PRMT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRMT2 shows lower tumor expression in KICH, LUAD, UCEC and LUSC and higher tumor expression in KIRC and LIHC. The KIRC box plot shows higher PRMT2 RNA expression in tumor versus normal tissue (log2 FC = +0.604, t-test p < 0.001).
This table shows molecular features associated with PRMT2 in patient tissues and cancer cell lines. In patient samples, PRMT2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PRMT2 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
