Q-omics provides the consensus-scored VGLL4 profile across patient tissues and cancer cell-line models. VGLL4 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, VGLL4 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, VGLL4 protein abundance shows 21,574 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, BLCA, and GBM as cancer lineages where VGLL4 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 VGLL4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VGLL4 survival associations across molecular data types. VGLL4 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (5) 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 VGLL4 RNA expression–survival associations across cancer types. High VGLL4 expression shows unfavorable associations in MESO, LIHC, LGG and ACC, but favorable associations in KIRC and HNSC. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .007). Together, the overview and detailed table identify MESO as the clearest survival context for VGLL4 RNA expression.
This table summarizes VGLL4 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 5. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for VGLL4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VGLL4 shows lower tumor expression in THCA and higher tumor expression in BLCA, COAD, LIHC, READ and HNSC. The BLCA box plot shows higher VGLL4 RNA expression in tumor versus normal tissue (log2 FC = +0.705, t-test p = .001).
This table shows molecular features associated with VGLL4 in patient tissues and cancer cell lines. In patient samples, VGLL4 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, VGLL4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
