mex-3 RNA binding family member DGenealiases: MEX-3D · MEX3 · OK/SW-cl.4 · RKHD1 · RNF193 · TINO
Q-omics provides the consensus-scored MEX3D profile across patient tissues and cancer cell-line models. MEX3D expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, MEX3D is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, MEX3D RNA expression shows 19,283 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, HNSC, and ACC as cancer lineages where MEX3D 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 MEX3D — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MEX3D survival associations across molecular data types. MEX3D RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) 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 MEX3D RNA expression–survival associations across cancer types. High MEX3D expression shows unfavorable associations in MESO, ACC, KIRP and LGG, but favorable associations in SCLC and UCEC. The MESO 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 MESO as the clearest survival context for MEX3D RNA expression.
This table summarizes MEX3D tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MEX3D. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MEX3D shows higher tumor expression in HNSC, COAD, LUAD, BLCA, STAD and LIHC. The HNSC box plot shows higher MEX3D RNA expression in tumor versus normal tissue (log2 FC = +1.396, t-test p < 0.001).
This table shows molecular features associated with MEX3D in patient tissues and cancer cell lines. In patient samples, MEX3D 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, MEX3D RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Leukemia.
