Q-omics provides the consensus-scored VILL profile across patient tissues and cancer cell-line models. VILL expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, VILL is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, VILL protein abundance shows 29,399 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, COAD, and GBM as cancer lineages where VILL 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 VILL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VILL survival associations across molecular data types. VILL RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible VILL RNA expression–survival associations across cancer types. High VILL expression shows unfavorable associations in LGG, PAAD and LUAD, but favorable associations in HNSC, UVM and BLCA. The HNSC 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 HNSC as the clearest survival context for VILL RNA expression.
This table summarizes VILL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 12. The strongest signals are observed in COAD for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for VILL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VILL shows lower tumor expression in COAD, KICH, LUSC, THCA and READ and higher tumor expression in KIRC. The COAD box plot shows higher VILL RNA expression in normal versus tumor tissue (log2 FC = −1.696, t-test p < 0.001).
This table shows molecular features associated with VILL in patient tissues and cancer cell lines. In patient samples, VILL shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, VILL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
