Q-omics provides the consensus-scored CLEC16A profile across patient tissues and cancer cell-line models. CLEC16A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, CLEC16A is differentially expressed in 11, with the highest sampling consensus in KIRP. Additionally, CLEC16A protein abundance shows 22,221 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRP, and LSCC as cancer lineages where CLEC16A 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 CLEC16A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLEC16A survival associations across molecular data types. CLEC16A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLEC16A RNA expression–survival associations across cancer types. High CLEC16A expression shows unfavorable associations in BLCA, LUAD and SKCM, but favorable associations in HNSC, LIHC 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 CLEC16A RNA expression.
This table summarizes CLEC16A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 4. The strongest signals are observed in KIRP for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for CLEC16A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLEC16A shows lower tumor expression in KIRC and higher tumor expression in KIRP, LIHC, STAD, THCA and HNSC. The KIRP box plot shows higher CLEC16A RNA expression in tumor versus normal tissue (log2 FC = +0.626, t-test p = .001).
This table shows molecular features associated with CLEC16A in patient tissues and cancer cell lines. In patient samples, CLEC16A 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, CLEC16A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
