Q-omics provides the consensus-scored CLEC9A profile across patient tissues and cancer cell-line models. CLEC9A expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, CLEC9A is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, CLEC9A RNA expression shows 17,975 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, COAD, and LSCC as cancer lineages where CLEC9A 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 CLEC9A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC9A survival associations across molecular data types. CLEC9A RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC9A RNA expression–survival associations across cancer types. High CLEC9A expression shows favorable associations in HNSC, SKCM, THCA, UCEC, KIRC and CESC. The HNSC 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 HNSC as the clearest survival context for CLEC9A RNA expression.
This table summarizes CLEC9A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for CLEC9A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC9A shows lower tumor expression in COAD, LUAD, UCEC, LUSC and BLCA and higher tumor expression in KIRC. The COAD box plot shows higher CLEC9A RNA expression in normal versus tumor tissue (log2 FC = −0.908, t-test p < 0.001).
This table shows molecular features associated with CLEC9A in patient tissues and cancer cell lines. In patient samples, CLEC9A shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CLEC9A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and SKIN.
