Q-omics provides the consensus-scored MSH3 profile across patient tissues and cancer cell-line models. MSH3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MSH3 is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, MSH3 RNA expression shows 19,744 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where MSH3 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 MSH3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MSH3 survival associations across molecular data types. MSH3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MSH3 RNA expression–survival associations across cancer types. High MSH3 expression shows unfavorable associations in KICH, STAD and THCA, but favorable associations in KIRC, READ and COAD. The KIRC 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 KIRC as the clearest survival context for MSH3 RNA expression.
This table summarizes MSH3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MSH3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MSH3 shows lower tumor expression in THCA, KICH and KIRP and higher tumor expression in LIHC, LUAD and READ. The THCA box plot shows higher MSH3 RNA expression in normal versus tumor tissue (log2 FC = −0.450, t-test p < 0.001).
This table shows molecular features associated with MSH3 in patient tissues and cancer cell lines. In patient samples, MSH3 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, MSH3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BLOOD_Lymphoma.
