Q-omics provides the consensus-scored NVL profile across patient tissues and cancer cell-line models. NVL expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NVL is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, NVL RNA expression shows 20,932 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where NVL 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 NVL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NVL survival associations across molecular data types. NVL RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) 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 NVL RNA expression–survival associations across cancer types. High NVL expression shows unfavorable associations in ACC, KIRP, KICH, LIHC, KIRC and COAD. The ACC 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 ACC as the clearest survival context for NVL RNA expression.
This table summarizes NVL 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 4. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for NVL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NVL shows higher tumor expression in HNSC, BLCA, KIRC, LIHC, STAD and LUAD. The HNSC box plot shows higher NVL RNA expression in tumor versus normal tissue (log2 FC = +1.134, t-test p < 0.001).
This table shows molecular features associated with NVL in patient tissues and cancer cell lines. In patient samples, NVL 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, NVL 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 BLOOD_Leukemia and BLOOD_Lymphoma.
