Q-omics provides the consensus-scored MSX2 profile across patient tissues and cancer cell-line models. MSX2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, MSX2 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, MSX2 RNA expression shows 14,453 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UCEC, COAD, and UVM as cancer lineages where MSX2 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 MSX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MSX2 survival associations across molecular data types. MSX2 RNA expression shows survival associations in the most cancer types (21), 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 MSX2 RNA expression–survival associations across cancer types. High MSX2 expression shows unfavorable associations in UVM, THCA, LUAD and KIRC, but favorable associations in UCEC and LGG. The UCEC 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 UCEC as the clearest survival context for MSX2 RNA expression.
This table summarizes MSX2 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 5. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MSX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MSX2 shows lower tumor expression in THCA and higher tumor expression in COAD, KIRP, LUAD, HNSC and UCEC. The COAD box plot shows higher MSX2 RNA expression in tumor versus normal tissue (log2 FC = +3.691, t-test p < 0.001).
This table shows molecular features associated with MSX2 in patient tissues and cancer cell lines. In patient samples, MSX2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, MSX2 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 BREAST and SKIN.
