Q-omics provides the consensus-scored NEPRO profile across patient tissues and cancer cell-line models. NEPRO 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, NEPRO is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, NEPRO protein abundance shows 21,493 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where NEPRO 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 NEPRO — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes NEPRO survival associations across molecular data types. NEPRO RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3) 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 NEPRO RNA expression–survival associations across cancer types. High NEPRO expression shows unfavorable associations in ACC, LIHC, UCEC and KICH, but favorable associations in KIRC and READ. 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 NEPRO RNA expression.
This table summarizes NEPRO 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 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for NEPRO. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. NEPRO shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, BLCA, COAD and CHOL. The HNSC box plot shows higher NEPRO RNA expression in tumor versus normal tissue (log2 FC = +0.994, t-test p < 0.001).
This table shows molecular features associated with NEPRO in patient tissues and cancer cell lines. In patient samples, NEPRO 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, NEPRO RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
