Q-omics provides the consensus-scored CNP profile across patient tissues and cancer cell-line models. CNP expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, CNP is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, CNP protein abundance shows 20,795 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, KICH, and GBM as cancer lineages where CNP 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 CNP — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CNP survival associations across molecular data types. CNP RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CNP RNA expression–survival associations across cancer types. High CNP expression shows unfavorable associations in BLCA, ACC, LIHC, KIRC and KICH, but favorable associations in PAAD. The BLCA 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 BLCA as the clearest survival context for CNP RNA expression.
This table summarizes CNP 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 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CNP. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CNP shows lower tumor expression in KICH and KIRC and higher tumor expression in LUAD, HNSC, LIHC and THCA. The KICH box plot shows higher CNP RNA expression in normal versus tumor tissue (log2 FC = −2.684, t-test p < 0.001).
This table shows molecular features associated with CNP in patient tissues and cancer cell lines. In patient samples, CNP 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, CNP RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
