poly(rC) binding protein 2Genealiases: HNRNPE2 · HNRPE2 · hnRNP-E2
Q-omics provides the consensus-scored PCBP2 profile across patient tissues and cancer cell-line models. PCBP2 expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, PCBP2 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PCBP2 protein abundance shows 25,343 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LIHC, HNSC, and GBM as cancer lineages where PCBP2 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 PCBP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCBP2 survival associations across molecular data types. PCBP2 RNA expression shows survival associations in the most cancer types (30), followed by mutation status (2) 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 PCBP2 RNA expression–survival associations across cancer types. High PCBP2 expression shows unfavorable associations in LIHC, ACC, LUAD and HNSC, but favorable associations in UCS and KIRC. The LIHC 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 LIHC as the clearest survival context for PCBP2 RNA expression.
This table summarizes PCBP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PCBP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCBP2 shows higher tumor expression in HNSC, LIHC, COAD, STAD, LUSC and BLCA. The HNSC box plot shows higher PCBP2 RNA expression in tumor versus normal tissue (log2 FC = +0.541, t-test p < 0.001).
This table shows molecular features associated with PCBP2 in patient tissues and cancer cell lines. In patient samples, PCBP2 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, PCBP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and UPPER_AERODIGESTIVE_TRACT.
