Q-omics provides the consensus-scored FAM71B profile across patient tissues and cancer cell-line models. FAM71B expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in MESO. Additionally, FAM71B RNA expression shows 6,286 significant pathway-activity associations, with the highest sampling consensus in STAD. Together, these results highlight MESO, and STAD as cancer lineages where FAM71B 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 FAM71B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes FAM71B survival associations across molecular data types. FAM71B RNA expression shows survival associations in the most cancer types (13), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible FAM71B RNA expression–survival associations across cancer types. High FAM71B expression shows unfavorable associations in MESO, KICH, DLBC, KIRC, ACC and LUSC. The MESO 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 MESO as the clearest survival context for FAM71B RNA expression.
This table shows molecular features associated with FAM71B in patient tissues and cancer cell lines. In patient samples, FAM71B 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, FAM71B 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 KIDNEY and LARGE_INTESTINE.
