C-type lectin domain family 2 member BGenealiases: AICL · CLECSF2 · HP10085 · IFNRG1
Q-omics provides the consensus-scored CLEC2B profile across patient tissues and cancer cell-line models. CLEC2B expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, CLEC2B is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, CLEC2B RNA expression shows 22,721 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight SKCM, KIRC, and GBM as cancer lineages where CLEC2B 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 CLEC2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC2B survival associations across molecular data types. CLEC2B RNA expression shows survival associations in the most cancer types (20), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC2B RNA expression–survival associations across cancer types. High CLEC2B expression shows unfavorable associations in KIRC, KIRP, LGG and PAAD, but favorable associations in SKCM and ESCA. The SKCM 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 SKCM as the clearest survival context for CLEC2B RNA expression.
This table summarizes CLEC2B 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 4. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CLEC2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC2B shows lower tumor expression in LUAD, KICH, LUSC and UCEC and higher tumor expression in KIRC and THCA. The KIRC box plot shows higher CLEC2B RNA expression in tumor versus normal tissue (log2 FC = +2.094, t-test p < 0.001).
This table shows molecular features associated with CLEC2B in patient tissues and cancer cell lines. In patient samples, CLEC2B shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, CLEC2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in OVARY and SOFT_TISSUE.
