autophagy related 16 like 2Genealiases: ATG16B · WDR80
Q-omics provides the consensus-scored ATG16L2 profile across patient tissues and cancer cell-line models. ATG16L2 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, ATG16L2 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, ATG16L2 RNA expression shows 18,605 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, KIRC, and UVM as cancer lineages where ATG16L2 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 ATG16L2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATG16L2 survival associations across molecular data types. ATG16L2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATG16L2 RNA expression–survival associations across cancer types. High ATG16L2 expression shows unfavorable associations in KIRC, UVM and ACC, but favorable associations in HNSC, SKCM and PAAD. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify HNSC as the clearest survival context for ATG16L2 RNA expression.
This table summarizes ATG16L2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ATG16L2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATG16L2 shows lower tumor expression in KICH, LUSC and LUAD and higher tumor expression in KIRC, LIHC and CHOL. The KIRC box plot shows higher ATG16L2 RNA expression in tumor versus normal tissue (log2 FC = +1.107, t-test p < 0.001).
This table shows molecular features associated with ATG16L2 in patient tissues and cancer cell lines. In patient samples, ATG16L2 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, ATG16L2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BREAST and UPPER_AERODIGESTIVE_TRACT.
