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Q-omics provides the consensus-scored LELP1 profile across patient tissues and cancer cell-line models. LELP1 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, LELP1 is differentially expressed in 2, with the highest sampling consensus in HNSC. Additionally, LELP1 RNA expression shows 7,801 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight READ, HNSC, and ESCA as cancer lineages where LELP1 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 LELP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LELP1 survival associations across molecular data types. LELP1 RNA expression shows survival associations in the most cancer types (13), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible LELP1 RNA expression–survival associations across cancer types. High LELP1 expression shows unfavorable associations in READ, KICH, LUAD, LIHC and PCPG, but favorable associations in ESCA. The READ 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 READ as the clearest survival context for LELP1 RNA expression.
This table summarizes LELP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for LELP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LELP1 shows higher tumor expression in HNSC and LUSC. The HNSC box plot shows higher LELP1 RNA expression in tumor versus normal tissue (log2 FC = +0.084, t-test p = .011).
This table shows molecular features associated with LELP1 in patient tissues and cancer cell lines. In patient samples, LELP1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, LELP1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BREAST and PANCREAS.
