Q-omics provides the consensus-scored L3HYPDH profile across patient tissues and cancer cell-line models. L3HYPDH expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, L3HYPDH is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, L3HYPDH protein abundance shows 34,342 significant protein co-abundance associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, HNSC, and BRCA as cancer lineages where L3HYPDH 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 L3HYPDH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes L3HYPDH survival associations across molecular data types. L3HYPDH RNA expression shows survival associations in the most cancer types (27), followed by mutation status (3) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible L3HYPDH RNA expression–survival associations across cancer types. High L3HYPDH expression shows unfavorable associations in KIRC, ACC, KICH, KIRP and UVM, but favorable associations in SKCM. 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 L3HYPDH RNA expression.
This table summarizes L3HYPDH tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 10. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for L3HYPDH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. L3HYPDH shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, KIRC, COAD and LIHC. The HNSC box plot shows higher L3HYPDH RNA expression in tumor versus normal tissue (log2 FC = +1.363, t-test p < 0.001).
This table shows molecular features associated with L3HYPDH in patient tissues and cancer cell lines. In patient samples, L3HYPDH shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, L3HYPDH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LARGE_INTESTINE.
