Q-omics provides the consensus-scored AMFR profile across patient tissues and cancer cell-line models. AMFR expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BRCA. Among the 18 cancer types available for tumor–normal comparison, AMFR is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, AMFR RNA expression shows 19,391 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight BRCA, KIRC, and ACC as cancer lineages where AMFR 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 AMFR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AMFR survival associations across molecular data types. AMFR RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AMFR RNA expression–survival associations across cancer types. High AMFR expression shows unfavorable associations in HNSC, KIRP and BLCA, but favorable associations in BRCA, SCLC and COAD. The BRCA 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 BRCA as the clearest survival context for AMFR RNA expression.
This table summarizes AMFR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AMFR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AMFR shows lower tumor expression in KIRC, KIRP, UCEC and KICH and higher tumor expression in COAD and LIHC. The KIRC box plot shows higher AMFR RNA expression in normal versus tumor tissue (log2 FC = −1.453, t-test p < 0.001).
This table shows molecular features associated with AMFR in patient tissues and cancer cell lines. In patient samples, AMFR shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, AMFR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
