Q-omics provides the consensus-scored FCAR profile across patient tissues and cancer cell-line models. FCAR expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, FCAR is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, FCAR RNA expression shows 22,703 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, HNSC, and GBM as cancer lineages where FCAR 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 FCAR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FCAR survival associations across molecular data types. FCAR RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) 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 FCAR RNA expression–survival associations across cancer types. High FCAR expression shows unfavorable associations in UVM, LUSC, THCA and BLCA, but favorable associations in LUAD and SKCM. The UVM 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 UVM as the clearest survival context for FCAR RNA expression.
This table summarizes FCAR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for FCAR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FCAR shows lower tumor expression in LIHC, LUSC and KICH and higher tumor expression in HNSC, COAD and KIRC. The HNSC box plot shows higher FCAR RNA expression in tumor versus normal tissue (log2 FC = +0.390, t-test p < 0.001).
This table shows molecular features associated with FCAR in patient tissues and cancer cell lines. In patient samples, FCAR 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, FCAR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
