Q-omics provides the consensus-scored PRMT3 profile across patient tissues and cancer cell-line models. PRMT3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PRMT3 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, PRMT3 RNA expression shows 20,079 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, COAD, and ACC as cancer lineages where PRMT3 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 PRMT3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRMT3 survival associations across molecular data types. PRMT3 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) 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 PRMT3 RNA expression–survival associations across cancer types. High PRMT3 expression shows unfavorable associations in LIHC, KICH, PAAD, UVM and KIRP, but favorable associations in BRCA. The LIHC 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 LIHC as the clearest survival context for PRMT3 RNA expression.
This table summarizes PRMT3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PRMT3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRMT3 shows lower tumor expression in THCA and higher tumor expression in COAD, HNSC, BLCA, LIHC and STAD. The COAD box plot shows higher PRMT3 RNA expression in tumor versus normal tissue (log2 FC = +1.533, t-test p < 0.001).
This table shows molecular features associated with PRMT3 in patient tissues and cancer cell lines. In patient samples, PRMT3 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, PRMT3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
