Q-omics provides the consensus-scored MON1B profile across patient tissues and cancer cell-line models. MON1B expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, MON1B is differentially expressed in 12, with the highest sampling consensus in KIRP. Additionally, MON1B RNA expression shows 19,622 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SCLC, KIRP, and UVM as cancer lineages where MON1B 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 MON1B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MON1B survival associations across molecular data types. MON1B RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 MON1B RNA expression–survival associations across cancer types. High MON1B expression shows unfavorable associations in LUAD and BLCA, but favorable associations in SCLC, HNSC, KIRC and MESO. The SCLC 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 SCLC as the clearest survival context for MON1B RNA expression.
This table summarizes MON1B 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 5. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MON1B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MON1B shows lower tumor expression in THCA and higher tumor expression in KIRP, HNSC, LIHC, STAD and BLCA. The KIRP box plot shows higher MON1B RNA expression in tumor versus normal tissue (log2 FC = +1.154, t-test p < 0.001).
This table shows molecular features associated with MON1B in patient tissues and cancer cell lines. In patient samples, MON1B 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, MON1B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and UPPER_AERODIGESTIVE_TRACT.
