Q-omics provides the consensus-scored NPHP3 profile across patient tissues and cancer cell-line models. NPHP3 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, NPHP3 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, NPHP3 RNA expression shows 19,946 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where NPHP3 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 NPHP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NPHP3 survival associations across molecular data types. NPHP3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4) 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 NPHP3 RNA expression–survival associations across cancer types. High NPHP3 expression shows unfavorable associations in KIRC, STAD, LIHC and LGG, but favorable associations in UCS and BLCA. 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 NPHP3 RNA expression.
This table summarizes NPHP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for NPHP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NPHP3 shows lower tumor expression in KICH, BRCA and UCEC and higher tumor expression in HNSC, KIRC and LIHC. The HNSC box plot shows higher NPHP3 RNA expression in tumor versus normal tissue (log2 FC = +0.514, t-test p < 0.001).
This table shows molecular features associated with NPHP3 in patient tissues and cancer cell lines. In patient samples, NPHP3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, NPHP3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
