Q-omics provides the consensus-scored ATF2 profile across patient tissues and cancer cell-line models. ATF2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, ATF2 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, ATF2 protein abundance shows 23,954 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where ATF2 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 ATF2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ATF2 survival associations across molecular data types. ATF2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ATF2 RNA expression–survival associations across cancer types. High ATF2 expression shows unfavorable associations in KIRP, ACC, LIHC and UVM, but favorable associations in KIRC and SKCM. 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 ATF2 RNA expression.
This table summarizes ATF2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ATF2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ATF2 shows lower tumor expression in THCA and KICH and higher tumor expression in HNSC, LIHC, KIRP and CHOL. The HNSC box plot shows higher ATF2 RNA expression in tumor versus normal tissue (log2 FC = +0.948, t-test p < 0.001).
This table shows molecular features associated with ATF2 in patient tissues and cancer cell lines. In patient samples, ATF2 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ATF2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
