Q-omics provides the consensus-scored SPTSSA profile across patient tissues and cancer cell-line models. SPTSSA expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SPTSSA is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, SPTSSA RNA expression shows 19,156 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, and UVM as cancer lineages where SPTSSA 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 SPTSSA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPTSSA survival associations across molecular data types. SPTSSA 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 SPTSSA RNA expression–survival associations across cancer types. High SPTSSA expression shows unfavorable associations in HNSC, STAD, LGG, KIRP, CHOL and PAAD. The HNSC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for SPTSSA RNA expression.
This table summarizes SPTSSA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SPTSSA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPTSSA shows lower tumor expression in KIRC and READ and higher tumor expression in HNSC, LIHC, BRCA and CHOL. The HNSC box plot shows higher SPTSSA RNA expression in tumor versus normal tissue (log2 FC = +0.979, t-test p < 0.001).
This table shows molecular features associated with SPTSSA in patient tissues and cancer cell lines. In patient samples, SPTSSA 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, SPTSSA RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BREAST.
