Q-omics provides the consensus-scored BCL2L2-PABPN1 profile across patient tissues and cancer cell-line models. BCL2L2-PABPN1 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, BCL2L2-PABPN1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, BCL2L2-PABPN1 RNA expression shows 18,631 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where BCL2L2-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 BCL2L2-PABPN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BCL2L2-PABPN1 survival associations across molecular data types. BCL2L2-PABPN1 RNA expression shows survival associations in the most cancer types (24). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BCL2L2-PABPN1 RNA expression–survival associations across cancer types. High BCL2L2-PABPN1 expression shows unfavorable associations in KIRC, ACC, HNSC, LIHC, SKCM and LUAD. 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 BCL2L2-PABPN1 RNA expression.
This table summarizes BCL2L2-PABPN1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for BCL2L2-PABPN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BCL2L2-PABPN1 shows higher tumor expression in HNSC, KIRP, BLCA, LUSC, STAD and LUAD. The HNSC box plot shows higher BCL2L2-PABPN1 RNA expression in tumor versus normal tissue (log2 FC = +1.225, t-test p < 0.001).
This table shows molecular features associated with BCL2L2-PABPN1 in patient tissues and cancer cell lines. In patient samples, BCL2L2-PABPN1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, BCL2L2-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 STOMACH and LARGE_INTESTINE.
