Q-omics provides the consensus-scored LEPROT profile across patient tissues and cancer cell-line models. LEPROT expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, LEPROT is differentially expressed in 14, with the highest sampling consensus in KICH. Additionally, LEPROT RNA expression shows 20,147 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight CESC, KICH, and UVM as cancer lineages where LEPROT 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 LEPROT — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LEPROT survival associations across molecular data types. LEPROT RNA expression shows survival associations in the most cancer types (25), followed by mutation status (2) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LEPROT RNA expression–survival associations across cancer types. High LEPROT expression shows unfavorable associations in CESC, LGG, PAAD and STAD, but favorable associations in KIRC and COAD. The CESC 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 CESC as the clearest survival context for LEPROT RNA expression.
This table summarizes LEPROT 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 1. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for LEPROT. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LEPROT shows lower tumor expression in KICH, LUSC, LUAD and COAD and higher tumor expression in LIHC and HNSC. The KICH box plot shows higher LEPROT RNA expression in normal versus tumor tissue (log2 FC = −2.650, t-test p < 0.001).
This table shows molecular features associated with LEPROT in patient tissues and cancer cell lines. In patient samples, LEPROT 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, LEPROT RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BONE and LUNG_NSCLC_LUAD.
