Q-omics provides the consensus-scored MAVS profile across patient tissues and cancer cell-line models. MAVS expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, MAVS is differentially expressed in 12, with the highest sampling consensus in LIHC. Additionally, MAVS protein abundance shows 22,537 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight LIHC, and LSCC as cancer lineages where MAVS 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 MAVS — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MAVS survival associations across molecular data types. MAVS RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 MAVS RNA expression–survival associations across cancer types. High MAVS expression shows unfavorable associations in LIHC, MESO, LGG, KICH and CESC, but favorable associations in THYM. The LIHC 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 LIHC as the clearest survival context for MAVS RNA expression.
This table summarizes MAVS 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 8. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for MAVS. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MAVS shows lower tumor expression in BRCA and COAD and higher tumor expression in LIHC, STAD, CHOL and KIRP. The LIHC box plot shows higher MAVS RNA expression in tumor versus normal tissue (log2 FC = +1.780, t-test p < 0.001).
This table shows molecular features associated with MAVS in patient tissues and cancer cell lines. In patient samples, MAVS 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, MAVS RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
