Q-omics provides the consensus-scored NPHP4 profile across patient tissues and cancer cell-line models. NPHP4 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, NPHP4 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, NPHP4 RNA expression shows 20,258 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where NPHP4 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 NPHP4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NPHP4 survival associations across molecular data types. NPHP4 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible NPHP4 RNA expression–survival associations across cancer types. High NPHP4 expression shows unfavorable associations in ACC, LUSC, KICH, BLCA and LGG, but favorable associations in SCLC. The ACC 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 ACC as the clearest survival context for NPHP4 RNA expression.
This table summarizes NPHP4 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 4. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for NPHP4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NPHP4 shows lower tumor expression in KICH and higher tumor expression in COAD, HNSC, BLCA, STAD and LIHC. The COAD box plot shows higher NPHP4 RNA expression in tumor versus normal tissue (log2 FC = +1.097, t-test p < 0.001).
This table shows molecular features associated with NPHP4 in patient tissues and cancer cell lines. In patient samples, NPHP4 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, NPHP4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
