Q-omics provides the consensus-scored LECT2 profile across patient tissues and cancer cell-line models. LECT2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, LECT2 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, LECT2 protein abundance shows 20,255 significant protein co-abundance associations, with the highest sampling consensus in LUAD. Together, these results highlight LUAD, and KICH as cancer lineages where LECT2 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 LECT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LECT2 survival associations across molecular data types. LECT2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (1) 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 LECT2 RNA expression–survival associations across cancer types. High LECT2 expression shows unfavorable associations in LUAD, DLBC, CHOL and LUSC, but favorable associations in LIHC and BRCA. The LUAD 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 LUAD as the clearest survival context for LECT2 RNA expression.
This table summarizes LECT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 4. The strongest signals are observed in KICH for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for LECT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LECT2 shows lower tumor expression in KICH, CHOL, LIHC and PRAD and higher tumor expression in KIRC and BRCA. The KICH box plot shows higher LECT2 RNA expression in normal versus tumor tissue (log2 FC = −0.244, t-test p < 0.001).
This table shows molecular features associated with LECT2 in patient tissues and cancer cell lines. In patient samples, LECT2 shows the broadest associations at the RNA and protein expression levels, with LUAD recurring as the lineage with the largest associated feature set. In cancer cell lines, LECT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and OVARY.
