angiogenic factor with G-patch and FHA domains 1 pseudogene 3Genealiases: []
Q-omics provides the consensus-scored AGGF1P3 profile across patient tissues and cancer cell-line models. AGGF1P3 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, AGGF1P3 is differentially expressed in 6, with the highest sampling consensus in LUAD. Additionally, AGGF1P3 RNA expression shows 15,847 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UCEC, LUAD, and THYM as cancer lineages where AGGF1P3 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 AGGF1P3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGGF1P3 survival associations across molecular data types. AGGF1P3 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGGF1P3 RNA expression–survival associations across cancer types. High AGGF1P3 expression shows unfavorable associations in UCEC, READ, KIRC, KICH and LUAD, but favorable associations in KIRP. The UCEC 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 UCEC as the clearest survival context for AGGF1P3 RNA expression.
This table summarizes AGGF1P3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in LUAD for RNA.
This table ranks reproducible tumor–normal expression differences for AGGF1P3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGGF1P3 shows lower tumor expression in BRCA and COAD and higher tumor expression in LUAD, LUSC, KIRP and LIHC. The LUAD box plot shows higher AGGF1P3 RNA expression in tumor versus normal tissue (log2 FC = +0.109, t-test p < 0.001).
This table shows molecular features associated with AGGF1P3 in patient tissues and cancer cell lines. In patient samples, AGGF1P3 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set.
