Q-omics provides the consensus-scored SPATA33 profile across patient tissues and cancer cell-line models. SPATA33 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SPATA33 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, SPATA33 RNA expression shows 18,903 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight ACC, COAD, and KIRP as cancer lineages where SPATA33 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 SPATA33 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATA33 survival associations across molecular data types. SPATA33 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPATA33 RNA expression–survival associations across cancer types. High SPATA33 expression shows unfavorable associations in ACC, LGG, SARC and LIHC, but favorable associations in UCEC and UVM. 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 SPATA33 RNA expression.
This table summarizes SPATA33 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for SPATA33. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATA33 shows lower tumor expression in KICH and THCA and higher tumor expression in COAD, HNSC, STAD and LIHC. The COAD box plot shows higher SPATA33 RNA expression in tumor versus normal tissue (log2 FC = +1.222, t-test p < 0.001).
This table shows molecular features associated with SPATA33 in patient tissues and cancer cell lines. In patient samples, SPATA33 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, SPATA33 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 BLOOD_Leukemia and BREAST.
