C-type lectin domain family 4 member GGenealiases: DTTR431 · LP2698 · LSECtin · UNQ431
Q-omics provides the consensus-scored CLEC4G profile across patient tissues and cancer cell-line models. CLEC4G expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CLEC4G is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, CLEC4G RNA expression shows 13,709 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, BLCA, and UVM as cancer lineages where CLEC4G 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 CLEC4G — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC4G survival associations across molecular data types. CLEC4G RNA expression shows survival associations in the most cancer types (22), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC4G RNA expression–survival associations across cancer types. High CLEC4G expression shows unfavorable associations in KIRC, UVM, ACC and MESO, but favorable associations in LUAD and LGG. 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 CLEC4G RNA expression.
This table summarizes CLEC4G tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in BLCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CLEC4G. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC4G shows lower tumor expression in BLCA, LIHC, KICH, COAD, BRCA and UCEC. The BLCA box plot shows higher CLEC4G RNA expression in normal versus tumor tissue (log2 FC = −1.143, t-test p < 0.001).
This table shows molecular features associated with CLEC4G in patient tissues and cancer cell lines. In patient samples, CLEC4G 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, CLEC4G 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 SOFT_TISSUE and LARGE_INTESTINE.
