Q-omics provides the consensus-scored PABPC1 profile across patient tissues and cancer cell-line models. PABPC1 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PABPC1 is differentially expressed in 16, with the highest sampling consensus in KIRC. Additionally, PABPC1 protein abundance shows 33,792 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRP, KIRC, and LUAD as cancer lineages where PABPC1 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 PABPC1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PABPC1 survival associations across molecular data types. PABPC1 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PABPC1 RNA expression–survival associations across cancer types. High PABPC1 expression shows unfavorable associations in KIRP, KICH, ACC, LIHC, UVM and CESC. The KIRP 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 KIRP as the clearest survival context for PABPC1 RNA expression.
This table summarizes PABPC1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 9. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PABPC1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PABPC1 shows higher tumor expression in KIRC, COAD, LUSC, LUAD, KIRP and LIHC. The KIRC box plot shows higher PABPC1 RNA expression in tumor versus normal tissue (log2 FC = +1.067, t-test p < 0.001).
This table shows molecular features associated with PABPC1 in patient tissues and cancer cell lines. In patient samples, PABPC1 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, PABPC1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in CNS and UPPER_AERODIGESTIVE_TRACT.
