Q-omics provides the consensus-scored MED4 profile across patient tissues and cancer cell-line models. MED4 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ESCA. Among the 18 cancer types available for tumor–normal comparison, MED4 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, MED4 protein abundance shows 28,737 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ESCA, KICH, and LSCC as cancer lineages where MED4 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 MED4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MED4 survival associations across molecular data types. MED4 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MED4 RNA expression–survival associations across cancer types. High MED4 expression shows unfavorable associations in ESCA, UVM, CESC and ACC, but favorable associations in KIRC and THCA. The ESCA 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 ESCA as the clearest survival context for MED4 RNA expression.
This table summarizes MED4 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 9. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MED4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MED4 shows lower tumor expression in KICH and THCA and higher tumor expression in HNSC, STAD, CHOL and LIHC. The KICH box plot shows higher MED4 RNA expression in normal versus tumor tissue (log2 FC = −1.548, t-test p < 0.001).
This table shows molecular features associated with MED4 in patient tissues and cancer cell lines. In patient samples, MED4 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, MED4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
