Q-omics provides the consensus-scored PABPC4 profile across patient tissues and cancer cell-line models. PABPC4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PABPC4 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, PABPC4 protein abundance shows 22,122 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, KIRC, and GBM as cancer lineages where PABPC4 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 PABPC4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PABPC4 survival associations across molecular data types. PABPC4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PABPC4 RNA expression–survival associations across cancer types. High PABPC4 expression shows unfavorable associations in KIRP, ACC, KICH, LIHC, LGG and HNSC. 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 PABPC4 RNA expression.
This table summarizes PABPC4 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 6. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PABPC4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PABPC4 shows higher tumor expression in KIRC, KIRP, COAD, LIHC, LUAD and LUSC. The KIRC box plot shows higher PABPC4 RNA expression in tumor versus normal tissue (log2 FC = +0.794, t-test p < 0.001).
This table shows molecular features associated with PABPC4 in patient tissues and cancer cell lines. In patient samples, PABPC4 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, PABPC4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and LARGE_INTESTINE.
