Q-omics provides the consensus-scored VMAC profile across patient tissues and cancer cell-line models. VMAC expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, VMAC is differentially expressed in 12, with the highest sampling consensus in THCA. Additionally, VMAC RNA expression shows 20,147 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UCEC, THCA, and ACC as cancer lineages where VMAC 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 VMAC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VMAC survival associations across molecular data types. VMAC RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1) 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 VMAC RNA expression–survival associations across cancer types. High VMAC expression shows unfavorable associations in ACC and KIRC, but favorable associations in UCEC, SCLC, HNSC and BLCA. The UCEC 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 UCEC as the clearest survival context for VMAC RNA expression.
This table summarizes VMAC 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 2. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for VMAC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VMAC shows lower tumor expression in THCA and KICH and higher tumor expression in LIHC, BLCA, BRCA and COAD. The THCA box plot shows higher VMAC RNA expression in normal versus tumor tissue (log2 FC = −0.595, t-test p < 0.001).
This table shows molecular features associated with VMAC in patient tissues and cancer cell lines. In patient samples, VMAC shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, VMAC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Leukemia.
