Q-omics provides the consensus-scored VEGFC profile across patient tissues and cancer cell-line models. VEGFC expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, VEGFC is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, VEGFC RNA expression shows 20,806 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, and LSCC as cancer lineages where VEGFC 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 VEGFC — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes VEGFC survival associations across molecular data types. VEGFC RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible VEGFC RNA expression–survival associations across cancer types. High VEGFC expression shows unfavorable associations in HNSC, LUAD, ACC, MESO, UVM and KICH. The HNSC 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 HNSC as the clearest survival context for VEGFC RNA expression.
This table summarizes VEGFC tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 3. The strongest signals are observed in KIRC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for VEGFC. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. VEGFC shows lower tumor expression in THCA, UCEC and BRCA and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher VEGFC RNA expression in tumor versus normal tissue (log2 FC = +3.343, t-test p < 0.001).
This table shows molecular features associated with VEGFC in patient tissues and cancer cell lines. In patient samples, VEGFC shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, VEGFC RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and BONE.
