matrix Gla proteinGenealiases: GIG36 · MGLAP · NTI
Q-omics provides the consensus-scored MGP profile across patient tissues and cancer cell-line models. MGP expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, MGP is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, MGP RNA expression shows 26,115 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRP, KICH, and LUAD as cancer lineages where MGP 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 MGP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MGP survival associations across molecular data types. MGP RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MGP RNA expression–survival associations across cancer types. High MGP expression shows unfavorable associations in KIRP, LGG and COAD, but favorable associations in ACC, SKCM and LAML. The KIRP 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 KIRP as the clearest survival context for MGP RNA expression.
This table summarizes MGP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MGP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MGP shows lower tumor expression in KICH, THCA, COAD, LUAD, BLCA and LUSC. The KICH box plot shows higher MGP RNA expression in normal versus tumor tissue (log2 FC = −3.094, t-test p < 0.001).
This table shows molecular features associated with MGP in patient tissues and cancer cell lines. In patient samples, MGP shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, MGP 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 BLOOD_Myeloma and SKIN.
