Q-omics provides the consensus-scored SPATA16 profile across patient tissues and cancer cell-line models. SPATA16 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SPATA16 is differentially expressed in 8, with the highest sampling consensus in KIRC. Additionally, SPATA16 RNA expression shows 5,602 significant pathway-activity associations, with the highest sampling consensus in UCEC. Together, these results highlight MESO, KIRC, and UCEC as cancer lineages where SPATA16 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 SPATA16 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATA16 survival associations across molecular data types. SPATA16 RNA expression shows survival associations in the most cancer types (21), 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 SPATA16 RNA expression–survival associations across cancer types. High SPATA16 expression shows unfavorable associations in MESO, KICH, KIRC, UCEC, BRCA and CHOL. 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 SPATA16 RNA expression.
This table summarizes SPATA16 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SPATA16. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATA16 shows lower tumor expression in KIRC, KIRP and KICH and higher tumor expression in BRCA, LUSC and LIHC. The KIRC box plot shows higher SPATA16 RNA expression in normal versus tumor tissue (log2 FC = −0.181, t-test p < 0.001).
This table shows molecular features associated with SPATA16 in patient tissues and cancer cell lines. In patient samples, SPATA16 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPATA16 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BONE, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and OVARY.
