Q-omics provides the consensus-scored VCY profile across patient tissues and cancer cell-line models. VCY expression is associated with patient survival in 11 of 34 cancer types, with the highest sampling consensus in COAD. Additionally, VCY protein abundance shows 6,403 significant protein co-abundance associations, with the highest sampling consensus in HNSC. Together, these results highlight COAD, and HNSC as cancer lineages where VCY 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 VCY — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VCY survival associations across molecular data types. VCY RNA expression shows survival associations in the most cancer types (11), followed by mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible VCY RNA expression–survival associations across cancer types. High VCY expression shows unfavorable associations in COAD, KIRC, LIHC, UCEC, KIRP and SKCM. The COAD 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 COAD as the clearest survival context for VCY RNA expression.
This table shows molecular features associated with VCY in patient tissues and cancer cell lines. In patient samples, VCY shows the broadest associations at the RNA and protein expression levels, with HNSC recurring as the lineage with the largest associated feature set. In cancer cell lines, VCY RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS.
