Q-omics provides the consensus-scored MLH3 profile across patient tissues and cancer cell-line models. MLH3 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, MLH3 is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, MLH3 RNA expression shows 20,986 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where MLH3 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 MLH3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MLH3 survival associations across molecular data types. MLH3 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (12) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MLH3 RNA expression–survival associations across cancer types. High MLH3 expression shows unfavorable associations in UVM, KICH, LGG and COAD, but favorable associations in KIRC and SKCM. 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 MLH3 RNA expression.
This table summarizes MLH3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for MLH3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MLH3 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, COAD and STAD. The THCA box plot shows higher MLH3 RNA expression in normal versus tumor tissue (log2 FC = −1.114, t-test p < 0.001).
This table shows molecular features associated with MLH3 in patient tissues and cancer cell lines. In patient samples, MLH3 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, MLH3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and UPPER_AERODIGESTIVE_TRACT.
