Q-omics provides the consensus-scored PABPN1 profile across patient tissues and cancer cell-line models. PABPN1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PABPN1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, PABPN1 protein abundance shows 27,495 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, HNSC, and PDAC as cancer lineages where PABPN1 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 PABPN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PABPN1 survival associations across molecular data types. PABPN1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PABPN1 RNA expression–survival associations across cancer types. High PABPN1 expression shows unfavorable associations in KIRC, ACC, LIHC, KICH and UVM, but favorable associations in SCLC. The KIRC 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 KIRC as the clearest survival context for PABPN1 RNA expression.
This table summarizes PABPN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PABPN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PABPN1 shows higher tumor expression in HNSC, STAD, BLCA, LIHC, LUSC and LUAD. The HNSC box plot shows higher PABPN1 RNA expression in tumor versus normal tissue (log2 FC = +0.938, t-test p < 0.001).
This table shows molecular features associated with PABPN1 in patient tissues and cancer cell lines. In patient samples, PABPN1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, PABPN1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and SOFT_TISSUE.
