Q-omics provides the consensus-scored SP9 profile across patient tissues and cancer cell-line models. SP9 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SP9 is differentially expressed in 7, with the highest sampling consensus in HNSC. Additionally, SP9 RNA expression shows 10,968 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRP, HNSC, and ESCA as cancer lineages where SP9 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 SP9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SP9 survival associations across molecular data types. SP9 RNA expression shows survival associations in the most cancer types (26). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SP9 RNA expression–survival associations across cancer types. High SP9 expression shows unfavorable associations in KIRP, ACC, KIRC, KICH and MESO, but favorable associations in HNSC. The KIRP 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 KIRP as the clearest survival context for SP9 RNA expression.
This table summarizes SP9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SP9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SP9 shows lower tumor expression in BRCA and higher tumor expression in HNSC, LUSC, LUAD, COAD and PRAD. The HNSC box plot shows higher SP9 RNA expression in tumor versus normal tissue (log2 FC = +0.542, t-test p < 0.001).
This table shows molecular features associated with SP9 in patient tissues and cancer cell lines. In patient samples, SP9 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, SP9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BREAST.
