Q-omics provides the consensus-scored SPNS2 profile across patient tissues and cancer cell-line models. SPNS2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SPNS2 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SPNS2 RNA expression shows 16,744 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight MESO, HNSC, and THYM as cancer lineages where SPNS2 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 SPNS2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPNS2 survival associations across molecular data types. SPNS2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPNS2 RNA expression–survival associations across cancer types. High SPNS2 expression shows unfavorable associations in MESO and BRCA, but favorable associations in LIHC, KIRC, SARC and HNSC. The MESO 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 MESO as the clearest survival context for SPNS2 RNA expression.
This table summarizes SPNS2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 2. The strongest signals are observed in KIRC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SPNS2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPNS2 shows lower tumor expression in HNSC, KIRC, KICH, LUSC and KIRP and higher tumor expression in COAD. The HNSC box plot shows higher SPNS2 RNA expression in normal versus tumor tissue (log2 FC = −3.058, t-test p < 0.001).
This table shows molecular features associated with SPNS2 in patient tissues and cancer cell lines. In patient samples, SPNS2 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, SPNS2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in SOFT_TISSUE and LUNG_NSCLC_LUAD.
