Q-omics provides the consensus-scored INMT profile across patient tissues and cancer cell-line models. INMT expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, INMT is differentially expressed in 13, with the highest sampling consensus in LUAD. Additionally, INMT RNA expression shows 23,700 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight MESO, LUAD, and LSCC as cancer lineages where INMT 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 INMT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes INMT survival associations across molecular data types. INMT RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) 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 INMT RNA expression–survival associations across cancer types. High INMT expression shows unfavorable associations in KIRP and LGG, but favorable associations in MESO, HNSC, KIRC and SKCM. The MESO 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 MESO as the clearest survival context for INMT RNA expression.
This table summarizes INMT tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 2. The strongest signals are observed in LUAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for INMT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. INMT shows lower tumor expression in LUAD, BLCA, KICH, LUSC, KIRP and KIRC. The LUAD box plot shows higher INMT RNA expression in normal versus tumor tissue (log2 FC = −4.626, t-test p < 0.001).
This table shows molecular features associated with INMT in patient tissues and cancer cell lines. In patient samples, INMT 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, INMT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in SKIN and UPPER_AERODIGESTIVE_TRACT.
