Q-omics provides the consensus-scored MMP9 profile across patient tissues and cancer cell-line models. MMP9 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, MMP9 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, MMP9 protein abundance shows 32,052 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, HNSC, and PDAC as cancer lineages where MMP9 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 MMP9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MMP9 survival associations across molecular data types. MMP9 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (4) 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 MMP9 RNA expression–survival associations across cancer types. High MMP9 expression shows unfavorable associations in ACC, UVM, THCA and UCS, but favorable associations in UCEC and DLBC. The ACC 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 ACC as the clearest survival context for MMP9 RNA expression.
This table summarizes MMP9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 11. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MMP9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MMP9 shows higher tumor expression in HNSC, KIRC, COAD, LUAD, THCA and LUSC. The HNSC box plot shows higher MMP9 RNA expression in tumor versus normal tissue (log2 FC = +5.450, t-test p < 0.001).
This table shows molecular features associated with MMP9 in patient tissues and cancer cell lines. In patient samples, MMP9 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, MMP9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
