Q-omics provides the consensus-scored METTL22 profile across patient tissues and cancer cell-line models. METTL22 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, METTL22 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, METTL22 RNA expression shows 20,425 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, COAD, and ACC as cancer lineages where METTL22 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 METTL22 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes METTL22 survival associations across molecular data types. METTL22 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (6) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible METTL22 RNA expression–survival associations across cancer types. High METTL22 expression shows unfavorable associations in KIRC, ACC, STAD, MESO and LGG, but favorable associations in BRCA. The KIRC 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 KIRC as the clearest survival context for METTL22 RNA expression.
This table summarizes METTL22 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for METTL22. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. METTL22 shows lower tumor expression in THCA and higher tumor expression in COAD, KIRP, KIRC, HNSC and LIHC. The COAD box plot shows higher METTL22 RNA expression in tumor versus normal tissue (log2 FC = +0.958, t-test p < 0.001).
This table shows molecular features associated with METTL22 in patient tissues and cancer cell lines. In patient samples, METTL22 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, METTL22 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OVARY and UPPER_AERODIGESTIVE_TRACT.
