Q-omics provides the consensus-scored METTL23 profile across patient tissues and cancer cell-line models. METTL23 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, METTL23 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, METTL23 RNA expression shows 18,262 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, HNSC, and ACC as cancer lineages where METTL23 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 METTL23 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes METTL23 survival associations across molecular data types. METTL23 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible METTL23 RNA expression–survival associations across cancer types. High METTL23 expression shows unfavorable associations in UVM, KIRC, LIHC, ACC, KIRP and LGG. The UVM 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 UVM as the clearest survival context for METTL23 RNA expression.
This table summarizes METTL23 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for METTL23. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. METTL23 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRP, KIRC, LIHC and LUAD. The HNSC box plot shows higher METTL23 RNA expression in tumor versus normal tissue (log2 FC = +0.923, t-test p < 0.001).
This table shows molecular features associated with METTL23 in patient tissues and cancer cell lines. In patient samples, METTL23 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, METTL23 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 UPPER_AERODIGESTIVE_TRACT.
