Q-omics provides the consensus-scored MED28 profile across patient tissues and cancer cell-line models. MED28 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UCS. Among the 18 cancer types available for tumor–normal comparison, MED28 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, MED28 protein abundance shows 27,141 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCS, HNSC, and GBM as cancer lineages where MED28 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 MED28 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MED28 survival associations across molecular data types. MED28 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (5) 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 MED28 RNA expression–survival associations across cancer types. High MED28 expression shows unfavorable associations in LIHC, ESCA and CESC, but favorable associations in UCS, BRCA and KIRC. The UCS Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .004). Together, the overview and detailed table identify UCS as the clearest survival context for MED28 RNA expression.
This table summarizes MED28 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MED28. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MED28 shows lower tumor expression in LUAD and higher tumor expression in HNSC, LIHC, COAD, CHOL and LUAD. The HNSC box plot shows higher MED28 RNA expression in tumor versus normal tissue (log2 FC = +0.504, t-test p < 0.001).
This table shows molecular features associated with MED28 in patient tissues and cancer cell lines. In patient samples, MED28 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, MED28 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 STOMACH and BLOOD_Leukemia.
