Q-omics provides the consensus-scored NECTIN4 profile across patient tissues and cancer cell-line models. NECTIN4 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, NECTIN4 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, NECTIN4 protein abundance shows 16,542 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where NECTIN4 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 NECTIN4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NECTIN4 survival associations across molecular data types. NECTIN4 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NECTIN4 RNA expression–survival associations across cancer types. High NECTIN4 expression shows unfavorable associations in KIRC, SKCM, ACC, UVM, BRCA and LGG. 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 NECTIN4 RNA expression.
This table summarizes NECTIN4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for NECTIN4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NECTIN4 shows lower tumor expression in KIRC and KIRP and higher tumor expression in THCA, COAD, LUSC and LUAD. The KIRC box plot shows higher NECTIN4 RNA expression in normal versus tumor tissue (log2 FC = −2.174, t-test p < 0.001).
This table shows molecular features associated with NECTIN4 in patient tissues and cancer cell lines. In patient samples, NECTIN4 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, NECTIN4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and LUNG_NSCLC_LUAD.
