Q-omics provides the consensus-scored SPACA9 profile across patient tissues and cancer cell-line models. SPACA9 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, SPACA9 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, SPACA9 RNA expression shows 19,501 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight UVM, KICH, and ACC as cancer lineages where SPACA9 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 SPACA9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPACA9 survival associations across molecular data types. SPACA9 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (3) 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 SPACA9 RNA expression–survival associations across cancer types. High SPACA9 expression shows unfavorable associations in BLCA, ACC and LIHC, but favorable associations in UVM, KIRC and KIRP. The UVM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify UVM as the clearest survival context for SPACA9 RNA expression.
This table summarizes SPACA9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPACA9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPACA9 shows lower tumor expression in KICH, KIRC, THCA, UCEC and LUAD and higher tumor expression in LIHC. The KICH box plot shows higher SPACA9 RNA expression in normal versus tumor tissue (log2 FC = −2.541, t-test p < 0.001).
This table shows molecular features associated with SPACA9 in patient tissues and cancer cell lines. In patient samples, SPACA9 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPACA9 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 OESOPHAGUS and BLOOD_Leukemia.
