heterogeneous nuclear ribonucleoprotein C pseudogene 3Genealiases: []
Q-omics provides the consensus-scored HNRNPCP3 profile across patient tissues and cancer cell-line models. HNRNPCP3 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HNRNPCP3 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, HNRNPCP3 RNA expression shows 12,794 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, HNSC, and ACC as cancer lineages where HNRNPCP3 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 HNRNPCP3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HNRNPCP3 survival associations across molecular data types. HNRNPCP3 RNA expression shows survival associations in the most cancer types (20). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HNRNPCP3 RNA expression–survival associations across cancer types. High HNRNPCP3 expression shows unfavorable associations in MESO, LUAD, KICH, LIHC and ACC, but favorable associations in LGG. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify MESO as the clearest survival context for HNRNPCP3 RNA expression.
This table summarizes HNRNPCP3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for HNRNPCP3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HNRNPCP3 shows lower tumor expression in KICH and higher tumor expression in HNSC, LUAD, BRCA, LIHC and THCA. The HNSC box plot shows higher HNRNPCP3 RNA expression in tumor versus normal tissue (log2 FC = +0.156, t-test p < 0.001).
This table shows molecular features associated with HNRNPCP3 in patient tissues and cancer cell lines. In patient samples, HNRNPCP3 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
