Q-omics provides the consensus-scored FRG1 profile across patient tissues and cancer cell-line models. FRG1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, FRG1 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, FRG1 protein abundance shows 21,679 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, LIHC, and GBM as cancer lineages where FRG1 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 FRG1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FRG1 survival associations across molecular data types. FRG1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FRG1 RNA expression–survival associations across cancer types. High FRG1 expression shows unfavorable associations in HNSC, ACC, SCLC and LIHC, but favorable associations in KIRC and STAD. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .004). Together, the overview and detailed table identify HNSC as the clearest survival context for FRG1 RNA expression.
This table summarizes FRG1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for FRG1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FRG1 shows lower tumor expression in KICH, LUAD, BRCA and READ and higher tumor expression in LIHC and CHOL. The LIHC box plot shows higher FRG1 RNA expression in tumor versus normal tissue (log2 FC = +0.725, t-test p < 0.001).
This table shows molecular features associated with FRG1 in patient tissues and cancer cell lines. In patient samples, FRG1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, FRG1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
