Q-omics provides the consensus-scored VIL1 profile across patient tissues and cancer cell-line models. VIL1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, VIL1 is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, VIL1 RNA expression shows 13,857 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, KIRP, and TGCT as cancer lineages where VIL1 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 VIL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VIL1 survival associations across molecular data types. VIL1 RNA expression shows survival associations in the most cancer types (23), 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 VIL1 RNA expression–survival associations across cancer types. High VIL1 expression shows unfavorable associations in LGG, LUSC and ACC, but favorable associations in KIRC, SCLC and SKCM. The KIRC 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 KIRC as the clearest survival context for VIL1 RNA expression.
This table summarizes VIL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for VIL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VIL1 shows lower tumor expression in KIRP and KICH and higher tumor expression in LUAD, STAD, HNSC and CHOL. The KIRP box plot shows higher VIL1 RNA expression in normal versus tumor tissue (log2 FC = −3.774, t-test p < 0.001).
This table shows molecular features associated with VIL1 in patient tissues and cancer cell lines. In patient samples, VIL1 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, VIL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and LARGE_INTESTINE.
