Q-omics provides the consensus-scored VCX2 profile across patient tissues and cancer cell-line models. VCX2 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, VCX2 is differentially expressed in 5, with the highest sampling consensus in KIRC. Additionally, VCX2 RNA expression shows 5,201 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KIRC as cancer lineages where VCX2 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 VCX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VCX2 survival associations across molecular data types. VCX2 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible VCX2 RNA expression–survival associations across cancer types. High VCX2 expression shows unfavorable associations in UVM, STAD, LIHC, UCEC, KIRP and CHOL. The UVM 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 UVM as the clearest survival context for VCX2 RNA expression.
This table summarizes VCX2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for VCX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VCX2 shows lower tumor expression in KIRC and KIRP and higher tumor expression in HNSC, LUAD and LUSC. The KIRC box plot shows higher VCX2 RNA expression in normal versus tumor tissue (log2 FC = −0.053, t-test p = .012).
This table shows molecular features associated with VCX2 in patient tissues and cancer cell lines. In patient samples, VCX2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, VCX2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and CNS.
