Q-omics provides the consensus-scored RNMT profile across patient tissues and cancer cell-line models. RNMT 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, RNMT is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, RNMT protein abundance shows 24,599 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where RNMT 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 RNMT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes RNMT survival associations across molecular data types. RNMT RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4) 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 RNMT RNA expression–survival associations across cancer types. High RNMT expression shows unfavorable associations in LIHC, KICH, CESC, UCEC and ACC, but favorable associations in KIRC. 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 RNMT RNA expression.
This table summarizes RNMT 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 8. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for RNMT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. RNMT shows higher tumor expression in HNSC, LIHC, CHOL, LUSC, KIRC and STAD. The HNSC box plot shows higher RNMT RNA expression in tumor versus normal tissue (log2 FC = +1.101, t-test p < 0.001).
This table shows molecular features associated with RNMT in patient tissues and cancer cell lines. In patient samples, RNMT shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, RNMT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
