autophagy related 12Genealiases: APG12 · APG12L · FBR93 · HAPG12
Q-omics provides the consensus-scored ATG12 profile across patient tissues and cancer cell-line models. ATG12 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ATG12 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ATG12 RNA expression shows 19,812 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where ATG12 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 ATG12 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATG12 survival associations across molecular data types. ATG12 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (1) 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 ATG12 RNA expression–survival associations across cancer types. High ATG12 expression shows unfavorable associations in KIRP, KICH, UVM, HNSC, LUAD and LIHC. The KIRP 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 KIRP as the clearest survival context for ATG12 RNA expression.
This table summarizes ATG12 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 4. The strongest signals are observed in HNSC for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ATG12. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATG12 shows higher tumor expression in HNSC, KIRC, LIHC, KIRP, BRCA and CHOL. The HNSC box plot shows higher ATG12 RNA expression in tumor versus normal tissue (log2 FC = +0.877, t-test p < 0.001).
This table shows molecular features associated with ATG12 in patient tissues and cancer cell lines. In patient samples, ATG12 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, ATG12 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
