Q-omics provides the consensus-scored MPG profile across patient tissues and cancer cell-line models. MPG expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, MPG is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, MPG protein abundance shows 19,527 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KIRC, and GBM as cancer lineages where MPG 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 MPG — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MPG survival associations across molecular data types. MPG RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MPG RNA expression–survival associations across cancer types. High MPG expression shows unfavorable associations in UVM, KIRC, ACC and HNSC, but favorable associations in STAD and THCA. 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 MPG RNA expression.
This table summarizes MPG 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 10. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MPG. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MPG shows higher tumor expression in KIRC, KIRP, COAD, HNSC, THCA and LIHC. The KIRC box plot shows higher MPG RNA expression in tumor versus normal tissue (log2 FC = +0.995, t-test p < 0.001).
This table shows molecular features associated with MPG in patient tissues and cancer cell lines. In patient samples, MPG 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, MPG RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and SOFT_TISSUE.
