Q-omics provides the consensus-scored PABPC1L profile across patient tissues and cancer cell-line models. PABPC1L expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, PABPC1L is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, PABPC1L protein abundance shows 23,796 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight KIRC, COAD, and LUAD as cancer lineages where PABPC1L 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 PABPC1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PABPC1L survival associations across molecular data types. PABPC1L RNA expression shows survival associations in the most cancer types (28), followed by mutation status (5) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PABPC1L RNA expression–survival associations across cancer types. High PABPC1L expression shows unfavorable associations in KIRC, ACC, COAD, LIHC, KICH and LGG. 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 PABPC1L RNA expression.
This table summarizes PABPC1L 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 9. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for PABPC1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PABPC1L shows higher tumor expression in COAD, BLCA, LIHC, STAD, HNSC and KIRC. The COAD box plot shows higher PABPC1L RNA expression in tumor versus normal tissue (log2 FC = +2.521, t-test p < 0.001).
This table shows molecular features associated with PABPC1L in patient tissues and cancer cell lines. In patient samples, PABPC1L 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, PABPC1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
