Q-omics provides the consensus-scored ATG16L1 profile across patient tissues and cancer cell-line models. ATG16L1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ATG16L1 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, ATG16L1 protein abundance shows 37,508 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight ACC, KIRC, and PDAC as cancer lineages where ATG16L1 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 ATG16L1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATG16L1 survival associations across molecular data types. ATG16L1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATG16L1 RNA expression–survival associations across cancer types. High ATG16L1 expression shows unfavorable associations in ACC, LGG, LIHC, UVM, KICH and KIRP. The ACC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify ACC as the clearest survival context for ATG16L1 RNA expression.
This table summarizes ATG16L1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 11. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATG16L1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATG16L1 shows higher tumor expression in KIRC, KIRP, COAD, HNSC, LUAD and LIHC. The KIRC box plot shows higher ATG16L1 RNA expression in tumor versus normal tissue (log2 FC = +1.144, t-test p < 0.001).
This table shows molecular features associated with ATG16L1 in patient tissues and cancer cell lines. In patient samples, ATG16L1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATG16L1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
