Q-omics provides the consensus-scored ADAT2 profile across patient tissues and cancer cell-line models. ADAT2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, ADAT2 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, ADAT2 RNA expression shows 19,797 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, COAD, and UVM as cancer lineages where ADAT2 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 ADAT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ADAT2 survival associations across molecular data types. ADAT2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ADAT2 RNA expression–survival associations across cancer types. High ADAT2 expression shows unfavorable associations in LIHC, KIRC, ACC, DLBC and BLCA, but favorable associations in READ. The LIHC 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 LIHC as the clearest survival context for ADAT2 RNA expression.
This table summarizes ADAT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 4. The strongest signals are observed in COAD for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ADAT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ADAT2 shows lower tumor expression in THCA and higher tumor expression in COAD, LIHC, HNSC, READ and STAD. The COAD box plot shows higher ADAT2 RNA expression in tumor versus normal tissue (log2 FC = +1.225, t-test p < 0.001).
This table shows molecular features associated with ADAT2 in patient tissues and cancer cell lines. In patient samples, ADAT2 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, ADAT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BONE and SOFT_TISSUE.
