sperm protein associated with the nucleus, X-linked, family member A1Genealiases: CT11.1 · CT11.3 · NAP-X · SPAN-X · SPAN-Xa · SPAN-Xb
Q-omics provides the consensus-scored SPANXA1 profile across patient tissues and cancer cell-line models. SPANXA1 expression is associated with patient survival in 8 of 34 cancer types, with the highest sampling consensus in KIRC. Additionally, SPANXA1 RNA expression shows 983 significant gene co-expression associations, with the highest sampling consensus in BRCA. Together, these results highlight KIRC, and BRCA as cancer lineages where SPANXA1 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 SPANXA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPANXA1 survival associations across molecular data types. SPANXA1 RNA expression shows survival associations in the most cancer types (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPANXA1 RNA expression–survival associations across cancer types. High SPANXA1 expression shows unfavorable associations in KIRC, HNSC, BLCA, LUAD, GBM and SARC. The KIRC 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 KIRC as the clearest survival context for SPANXA1 RNA expression.
This table shows molecular features associated with SPANXA1 in patient tissues and cancer cell lines. In patient samples, SPANXA1 shows the broadest associations at the RNA and protein expression levels, with BRCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SPANXA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in CNS.
