C-type lectin domain family 4 member FGenealiases: CLECSF13 · KCLR · KCR
Q-omics provides the consensus-scored CLEC4F profile across patient tissues and cancer cell-line models. CLEC4F expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, CLEC4F is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, CLEC4F RNA expression shows 16,987 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, COAD, and UVM as cancer lineages where CLEC4F 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 CLEC4F — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC4F survival associations across molecular data types. CLEC4F RNA expression shows survival associations in the most cancer types (23), followed by mutation status (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC4F RNA expression–survival associations across cancer types. High CLEC4F expression shows unfavorable associations in ACC, but favorable associations in PAAD, LUAD, LGG, BRCA and SARC. The PAAD Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify PAAD as the clearest survival context for CLEC4F RNA expression.
This table summarizes CLEC4F tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for CLEC4F. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC4F shows lower tumor expression in COAD, HNSC, LUAD, LUSC and BRCA and higher tumor expression in KIRC. The COAD box plot shows higher CLEC4F RNA expression in normal versus tumor tissue (log2 FC = −0.435, t-test p < 0.001).
This table shows molecular features associated with CLEC4F in patient tissues and cancer cell lines. In patient samples, CLEC4F 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, CLEC4F RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
