Q-omics provides the consensus-scored FCER1A profile across patient tissues and cancer cell-line models. FCER1A expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, FCER1A is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, FCER1A RNA expression shows 20,898 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, HNSC, and LSCC as cancer lineages where FCER1A 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 FCER1A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FCER1A survival associations across molecular data types. FCER1A RNA expression shows survival associations in the most cancer types (24), followed by mutation status (4) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FCER1A RNA expression–survival associations across cancer types. High FCER1A expression shows favorable associations in KIRC, HNSC, ACC, BRCA, LUSC and SARC. The KIRC 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 KIRC as the clearest survival context for FCER1A RNA expression.
This table summarizes FCER1A tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 2. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for FCER1A. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FCER1A shows lower tumor expression in HNSC, COAD, BLCA, KICH, LUAD and LUSC. The HNSC box plot shows higher FCER1A RNA expression in normal versus tumor tissue (log2 FC = −2.569, t-test p < 0.001).
This table shows molecular features associated with FCER1A in patient tissues and cancer cell lines. In patient samples, FCER1A shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, FCER1A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
