Q-omics provides the consensus-scored MMP19 profile across patient tissues and cancer cell-line models. MMP19 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, MMP19 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, MMP19 RNA expression shows 22,859 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where MMP19 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 MMP19 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MMP19 survival associations across molecular data types. MMP19 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (4) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MMP19 RNA expression–survival associations across cancer types. High MMP19 expression shows unfavorable associations in KIRC, LUSC, ACC, KIRP and LGG, but favorable associations in HNSC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for MMP19 RNA expression.
This table summarizes MMP19 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for MMP19. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MMP19 shows lower tumor expression in LUAD, KICH, LUSC and UCEC and higher tumor expression in HNSC and STAD. The HNSC box plot shows higher MMP19 RNA expression in tumor versus normal tissue (log2 FC = +1.908, t-test p < 0.001).
This table shows molecular features associated with MMP19 in patient tissues and cancer cell lines. In patient samples, MMP19 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, MMP19 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
