Q-omics provides the consensus-scored ETNPPL profile across patient tissues and cancer cell-line models. ETNPPL expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, ETNPPL is differentially expressed in 10, with the highest sampling consensus in THCA. Additionally, ETNPPL RNA expression shows 15,431 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, THCA, and GBM as cancer lineages where ETNPPL 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 ETNPPL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ETNPPL survival associations across molecular data types. ETNPPL RNA expression shows survival associations in the most cancer types (27), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ETNPPL RNA expression–survival associations across cancer types. High ETNPPL expression shows unfavorable associations in UVM and KICH, but favorable associations in KIRP, BRCA, MESO and LGG. The UVM 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 UVM as the clearest survival context for ETNPPL RNA expression.
This table summarizes ETNPPL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in THCA for RNA.
This table ranks reproducible tumor–normal expression differences for ETNPPL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ETNPPL shows lower tumor expression in THCA, KIRP, STAD, KICH, KIRC and HNSC. The THCA box plot shows higher ETNPPL RNA expression in normal versus tumor tissue (log2 FC = −2.413, t-test p < 0.001).
This table shows molecular features associated with ETNPPL in patient tissues and cancer cell lines. In patient samples, ETNPPL 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, ETNPPL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in SKIN and SOFT_TISSUE.
