Q-omics provides the consensus-scored SPACA1 profile across patient tissues and cancer cell-line models. SPACA1 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in CHOL. Among the 18 cancer types available for tumor–normal comparison, SPACA1 is differentially expressed in 3, with the highest sampling consensus in KIRC. Additionally, SPACA1 RNA expression shows 11,985 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight CHOL, KIRC, and UVM as cancer lineages where SPACA1 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 SPACA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPACA1 survival associations across molecular data types. SPACA1 RNA expression shows survival associations in the most cancer types (13), followed by mutation status (10). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPACA1 RNA expression–survival associations across cancer types. High SPACA1 expression shows unfavorable associations in CHOL, LGG, ACC, BRCA and READ, but favorable associations in KIRC. The CHOL 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 CHOL as the clearest survival context for SPACA1 RNA expression.
This table summarizes SPACA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 3, while mass-spec protein shows differences in 1. The strongest signals are observed in KIRC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SPACA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPACA1 shows lower tumor expression in KIRC and higher tumor expression in LIHC and LUSC. The KIRC box plot shows higher SPACA1 RNA expression in normal versus tumor tissue (log2 FC = −0.133, t-test p < 0.001).
This table shows molecular features associated with SPACA1 in patient tissues and cancer cell lines. In patient samples, SPACA1 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, SPACA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and OVARY.
