heterogeneous nuclear ribonucleoprotein C pseudogene 2Genealiases: []
Q-omics provides the consensus-scored HNRNPCP2 profile across patient tissues and cancer cell-line models. HNRNPCP2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, HNRNPCP2 is differentially expressed in 11, with the highest sampling consensus in LUAD. Additionally, HNRNPCP2 RNA expression shows 19,331 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, LUAD, and ACC as cancer lineages where HNRNPCP2 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 HNRNPCP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HNRNPCP2 survival associations across molecular data types. HNRNPCP2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HNRNPCP2 RNA expression–survival associations across cancer types. High HNRNPCP2 expression shows unfavorable associations in MESO, ACC, LIHC, KIRP, UVM and KICH. The MESO Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify MESO as the clearest survival context for HNRNPCP2 RNA expression.
This table summarizes HNRNPCP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for HNRNPCP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HNRNPCP2 shows lower tumor expression in KICH and higher tumor expression in LUAD, LIHC, HNSC, BRCA and KIRP. The LUAD box plot shows higher HNRNPCP2 RNA expression in tumor versus normal tissue (log2 FC = +0.630, t-test p < 0.001).
This table shows molecular features associated with HNRNPCP2 in patient tissues and cancer cell lines. In patient samples, HNRNPCP2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
