Q-omics provides the consensus-scored AWAT2 profile across patient tissues and cancer cell-line models. AWAT2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, AWAT2 is differentially expressed in 7, with the highest sampling consensus in LUSC. Additionally, AWAT2 RNA expression shows 8,532 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KICH, LUSC, and TGCT as cancer lineages where AWAT2 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 AWAT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AWAT2 survival associations across molecular data types. AWAT2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AWAT2 RNA expression–survival associations across cancer types. High AWAT2 expression shows unfavorable associations in KICH, KIRC, BRCA, CHOL and SCLC, but favorable associations in PAAD. 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 AWAT2 RNA expression.
This table summarizes AWAT2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in LUSC for RNA.
This table ranks reproducible tumor–normal expression differences for AWAT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AWAT2 shows lower tumor expression in LUSC, LUAD, KICH, KIRC and LIHC and higher tumor expression in THCA. The LUSC box plot shows higher AWAT2 RNA expression in normal versus tumor tissue (log2 FC = −0.890, t-test p < 0.001).
This table shows molecular features associated with AWAT2 in patient tissues and cancer cell lines. In patient samples, AWAT2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, AWAT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and OVARY.
