Q-omics provides the consensus-scored MSLN profile across patient tissues and cancer cell-line models. MSLN expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, MSLN is differentially expressed in 11, with the highest sampling consensus in COAD. Additionally, MSLN protein abundance shows 25,468 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight PAAD, COAD, and LSCC as cancer lineages where MSLN 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 MSLN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MSLN survival associations across molecular data types. MSLN RNA expression shows survival associations in the most cancer types (26), followed by mutation status (7) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MSLN RNA expression–survival associations across cancer types. High MSLN expression shows unfavorable associations in PAAD, LGG and BLCA, but favorable associations in MESO, UCS and KIRP. The PAAD 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 PAAD as the clearest survival context for MSLN RNA expression.
This table summarizes MSLN tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 10. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for MSLN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MSLN shows lower tumor expression in LUSC and KICH and higher tumor expression in COAD, STAD, THCA and PAAD. The COAD box plot shows higher MSLN RNA expression in tumor versus normal tissue (log2 FC = +3.331, t-test p < 0.001).
This table shows molecular features associated with MSLN in patient tissues and cancer cell lines. In patient samples, MSLN shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, MSLN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and OVARY.
