Q-omics provides the consensus-scored PCBP1 profile across patient tissues and cancer cell-line models. PCBP1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PCBP1 is differentially expressed in 11, with the highest sampling consensus in KIRC. Additionally, PCBP1 protein abundance shows 24,695 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, and LSCC as cancer lineages where PCBP1 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 PCBP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCBP1 survival associations across molecular data types. PCBP1 RNA expression shows survival associations in the most cancer types (24), 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 PCBP1 RNA expression–survival associations across cancer types. High PCBP1 expression shows unfavorable associations in ACC, LUAD and LUSC, but favorable associations in KIRC, SCLC and UCS. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for PCBP1 RNA expression.
This table summarizes PCBP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, 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 PCBP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCBP1 shows lower tumor expression in THCA and KICH and higher tumor expression in KIRC, HNSC, LIHC and COAD. The KIRC box plot shows higher PCBP1 RNA expression in tumor versus normal tissue (log2 FC = +0.778, t-test p < 0.001).
This table shows molecular features associated with PCBP1 in patient tissues and cancer cell lines. In patient samples, PCBP1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PCBP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and UPPER_AERODIGESTIVE_TRACT.
