Q-omics provides the consensus-scored FARSA profile across patient tissues and cancer cell-line models. FARSA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, FARSA is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, FARSA RNA expression shows 19,061 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and COAD as cancer lineages where FARSA 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 FARSA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FARSA survival associations across molecular data types. FARSA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (7) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FARSA RNA expression–survival associations across cancer types. High FARSA expression shows unfavorable associations in ACC, LUAD, BLCA and KICH, but favorable associations in LUSC and CESC. The ACC 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 ACC as the clearest survival context for FARSA RNA expression.
This table summarizes FARSA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for FARSA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. FARSA shows higher tumor expression in COAD, HNSC, KIRP, STAD, LIHC and BLCA. The COAD box plot shows higher FARSA RNA expression in tumor versus normal tissue (log2 FC = +1.307, t-test p < 0.001).
This table shows molecular features associated with FARSA in patient tissues and cancer cell lines. In patient samples, FARSA 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, FARSA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and BONE.
