Q-omics provides the consensus-scored FAM243A profile across patient tissues and cancer cell-line models. FAM243A expression is associated with patient survival in 4 of 34 cancer types, with the highest sampling consensus in PAAD. Additionally, FAM243A RNA expression shows 2,695 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight PAAD, and STAD as cancer lineages where FAM243A 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 FAM243A — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FAM243A survival associations across molecular data types. FAM243A RNA expression shows survival associations in the most cancer types (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FAM243A RNA expression–survival associations across cancer types. High FAM243A expression shows unfavorable associations in PAAD, PRAD and LUSC, but favorable associations in SKCM. The PAAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .009). Together, the overview and detailed table identify PAAD as the clearest survival context for FAM243A RNA expression.
This table shows molecular features associated with FAM243A in patient tissues and cancer cell lines. In patient samples, FAM243A shows the broadest associations at the RNA and protein expression levels, with STAD recurring as the lineage with the largest associated feature set. In cancer cell lines, FAM243A RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and UPPER_AERODIGESTIVE_TRACT.
