Q-omics provides the consensus-scored SSX9P profile across patient tissues and cancer cell-line models. SSX9P expression is associated with patient survival in 9 of 34 cancer types, with the highest sampling consensus in KICH. Additionally, SSX9P RNA expression shows 7,859 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KICH, and THYM as cancer lineages where SSX9P 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 SSX9P — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SSX9P survival associations across molecular data types. SSX9P RNA expression shows survival associations in the most cancer types (9), 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 SSX9P RNA expression–survival associations across cancer types. High SSX9P expression shows unfavorable associations in KICH, UCEC, LUSC, HNSC, COAD and LUAD. The KICH 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 KICH as the clearest survival context for SSX9P RNA expression.
This table shows molecular features associated with SSX9P in patient tissues and cancer cell lines. In patient samples, SSX9P shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SSX9P RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in STOMACH.
