angiogenic factor with G-patch and FHA domains 1 pseudogene 1Genealiases: []
Q-omics provides the consensus-scored AGGF1P1 profile across patient tissues and cancer cell-line models. AGGF1P1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, AGGF1P1 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, AGGF1P1 RNA expression shows 16,649 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, and THYM as cancer lineages where AGGF1P1 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 AGGF1P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGGF1P1 survival associations across molecular data types. AGGF1P1 RNA expression shows survival associations in the most cancer types (21). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGGF1P1 RNA expression–survival associations across cancer types. High AGGF1P1 expression shows unfavorable associations in HNSC, DLBC and KIRC, but favorable associations in KIRP, ESCA and LGG. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for AGGF1P1 RNA expression.
This table summarizes AGGF1P1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for AGGF1P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGGF1P1 shows higher tumor expression in HNSC, LUAD, LUSC, KIRC, UCEC and KIRP. The HNSC box plot shows higher AGGF1P1 RNA expression in tumor versus normal tissue (log2 FC = +0.062, t-test p = .001).
This table shows molecular features associated with AGGF1P1 in patient tissues and cancer cell lines. In patient samples, AGGF1P1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set.
