Q-omics provides the consensus-scored AGXT2 profile across patient tissues and cancer cell-line models. AGXT2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AGXT2 is differentially expressed in 8, with the highest sampling consensus in KIRP. Additionally, AGXT2 RNA expression shows 8,897 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRC, KIRP, and TGCT as cancer lineages where AGXT2 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 AGXT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGXT2 survival associations across molecular data types. AGXT2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGXT2 RNA expression–survival associations across cancer types. High AGXT2 expression shows unfavorable associations in UVM, THYM, KICH and LUAD, but favorable associations in KIRC and ESCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for AGXT2 RNA expression.
This table summarizes AGXT2 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 KIRP for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AGXT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGXT2 shows lower tumor expression in KIRP, KICH, LIHC, CHOL and UCEC and higher tumor expression in BRCA. The KIRP box plot shows higher AGXT2 RNA expression in normal versus tumor tissue (log2 FC = −2.918, t-test p < 0.001).
This table shows molecular features associated with AGXT2 in patient tissues and cancer cell lines. In patient samples, AGXT2 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, AGXT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
