Q-omics provides the consensus-scored MVP profile across patient tissues and cancer cell-line models. MVP expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, MVP is differentially expressed in 15, with the highest sampling consensus in KIRC. Additionally, MVP protein abundance shows 33,363 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, KIRC, and LSCC as cancer lineages where MVP 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 MVP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MVP survival associations across molecular data types. MVP RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) 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 MVP RNA expression–survival associations across cancer types. High MVP expression shows unfavorable associations in UVM, LGG and LAML, but favorable associations in SKCM, MESO and KIRP. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify UVM as the clearest survival context for MVP RNA expression.
This table summarizes MVP tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for MVP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MVP shows higher tumor expression in KIRC, KIRP, THCA, LIHC, HNSC and STAD. The KIRC box plot shows higher MVP RNA expression in tumor versus normal tissue (log2 FC = +1.252, t-test p < 0.001).
This table shows molecular features associated with MVP in patient tissues and cancer cell lines. In patient samples, MVP 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, MVP 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 LIVER and BONE.
