Q-omics provides the consensus-scored SPATA32 profile across patient tissues and cancer cell-line models. SPATA32 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SPATA32 is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, SPATA32 RNA expression shows 18,649 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and BLCA as cancer lineages where SPATA32 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 SPATA32 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATA32 survival associations across molecular data types. SPATA32 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (2) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPATA32 RNA expression–survival associations across cancer types. High SPATA32 expression shows unfavorable associations in UVM, LGG and READ, but favorable associations in SKCM, BLCA and KIRC. The UVM 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 UVM as the clearest survival context for SPATA32 RNA expression.
This table summarizes SPATA32 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 1. The strongest signals are observed in BLCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPATA32. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATA32 shows lower tumor expression in KICH and higher tumor expression in BLCA, STAD, KIRC, CHOL and LUAD. The BLCA box plot shows higher SPATA32 RNA expression in tumor versus normal tissue (log2 FC = +0.379, t-test p = .002).
This table shows molecular features associated with SPATA32 in patient tissues and cancer cell lines. In patient samples, SPATA32 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SPATA32 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 LARGE_INTESTINE and BLOOD_Leukemia.
