Q-omics provides the consensus-scored CLEC17A profile across patient tissues and cancer cell-line models. CLEC17A 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, CLEC17A is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, CLEC17A RNA expression shows 15,635 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, and LSCC as cancer lineages where CLEC17A 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 CLEC17A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC17A survival associations across molecular data types. CLEC17A RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC17A RNA expression–survival associations across cancer types. High CLEC17A expression shows unfavorable associations in SCLC and LGG, but favorable associations in HNSC, LUAD, SKCM and ESCA. 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 CLEC17A RNA expression.
This table summarizes CLEC17A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for CLEC17A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC17A shows lower tumor expression in COAD and BLCA and higher tumor expression in HNSC, KIRC, LUAD and STAD. The HNSC box plot shows higher CLEC17A RNA expression in tumor versus normal tissue (log2 FC = +0.374, t-test p < 0.001).
This table shows molecular features associated with CLEC17A in patient tissues and cancer cell lines. In patient samples, CLEC17A 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, CLEC17A 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 BLOOD_Leukemia and BLOOD_Lymphoma.
