endogenous retrovirus group V member 2, envelopeGenealiases: ENVV2 · HERV-V2
Q-omics provides the consensus-scored ERVV-2 profile across patient tissues and cancer cell-line models. ERVV-2 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, ERVV-2 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, ERVV-2 RNA expression shows 6,737 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, HNSC, and TGCT as cancer lineages where ERVV-2 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 ERVV-2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ERVV-2 survival associations across molecular data types. ERVV-2 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ERVV-2 RNA expression–survival associations across cancer types. High ERVV-2 expression shows unfavorable associations in KIRC, UCEC, LIHC, BLCA and LGG, but favorable associations in OV. The KIRC 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 KIRC as the clearest survival context for ERVV-2 RNA expression.
This table summarizes ERVV-2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ERVV-2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ERVV-2 shows lower tumor expression in KICH and higher tumor expression in HNSC, BRCA, LUAD, COAD and KIRP. The HNSC box plot shows higher ERVV-2 RNA expression in tumor versus normal tissue (log2 FC = +0.132, t-test p < 0.001).
This table shows molecular features associated with ERVV-2 in patient tissues and cancer cell lines. In patient samples, ERVV-2 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, ERVV-2 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 URINARY_TRACT and LUNG_NSCLC_LUSC.
