autophagy related 10Genealiases: APG10 · APG10L · ATG10S · pp12616
Q-omics provides the consensus-scored ATG10 profile across patient tissues and cancer cell-line models. ATG10 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ATG10 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, ATG10 RNA expression shows 19,633 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, KIRC, and ACC as cancer lineages where ATG10 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 ATG10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATG10 survival associations across molecular data types. ATG10 RNA expression shows survival associations in the most cancer types (23), followed by mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATG10 RNA expression–survival associations across cancer types. High ATG10 expression shows unfavorable associations in KICH, LUAD, LIHC and LGG, but favorable associations in READ and KIRC. The KICH 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 KICH as the clearest survival context for ATG10 RNA expression.
This table summarizes ATG10 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 ATG10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATG10 shows lower tumor expression in KICH, BRCA and THCA and higher tumor expression in KIRC, LIHC and CHOL. The KIRC box plot shows higher ATG10 RNA expression in tumor versus normal tissue (log2 FC = +0.273, t-test p < 0.001).
This table shows molecular features associated with ATG10 in patient tissues and cancer cell lines. In patient samples, ATG10 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ATG10 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 LIVER and BLOOD_Leukemia.
