Q-omics provides the consensus-scored SPATA45 profile across patient tissues and cancer cell-line models. SPATA45 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, SPATA45 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, SPATA45 RNA expression shows 11,935 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and KICH as cancer lineages where SPATA45 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 SPATA45 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATA45 survival associations across molecular data types. SPATA45 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPATA45 RNA expression–survival associations across cancer types. High SPATA45 expression shows unfavorable associations in UVM, READ and ACC, but favorable associations in OV, KIRP and LUAD. 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 SPATA45 RNA expression.
This table summarizes SPATA45 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for SPATA45. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATA45 shows lower tumor expression in KICH, THCA, KIRC and COAD and higher tumor expression in LIHC and LUAD. The KICH box plot shows higher SPATA45 RNA expression in normal versus tumor tissue (log2 FC = −0.520, t-test p < 0.001).
This table shows molecular features associated with SPATA45 in patient tissues and cancer cell lines. In patient samples, SPATA45 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, SPATA45 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in OESOPHAGUS and BLOOD_Leukemia.
