Q-omics provides the consensus-scored FAT2 profile across patient tissues and cancer cell-line models. FAT2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, FAT2 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, FAT2 RNA expression shows 17,623 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SKCM, HNSC, and TGCT as cancer lineages where FAT2 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 FAT2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FAT2 survival associations across molecular data types. FAT2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (10) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FAT2 RNA expression–survival associations across cancer types. High FAT2 expression shows unfavorable associations in SKCM, KICH, LIHC, KIRP, KIRC and MESO. The SKCM 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 SKCM as the clearest survival context for FAT2 RNA expression.
This table summarizes FAT2 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 1. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FAT2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FAT2 shows lower tumor expression in KIRC and BRCA and higher tumor expression in HNSC, THCA, LUSC and LUAD. The HNSC box plot shows higher FAT2 RNA expression in tumor versus normal tissue (log2 FC = +1.253, t-test p < 0.001).
This table shows molecular features associated with FAT2 in patient tissues and cancer cell lines. In patient samples, FAT2 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, FAT2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUSC, while CRISPR and shRNA rows add functional-dependency signals in BREAST and SOFT_TISSUE.
