Q-omics provides the consensus-scored SNPH profile across patient tissues and cancer cell-line models. SNPH expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, SNPH is differentially expressed in 12, with the highest sampling consensus in BLCA. Additionally, SNPH RNA expression shows 19,058 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LUSC, BLCA, and ACC as cancer lineages where SNPH 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 SNPH — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNPH survival associations across molecular data types. SNPH RNA expression shows survival associations in the most cancer types (22), followed by mutation status (4) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SNPH RNA expression–survival associations across cancer types. High SNPH expression shows unfavorable associations in LUSC, STAD, LUAD, CESC and ACC, but favorable associations in PAAD. The LUSC 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 LUSC as the clearest survival context for SNPH RNA expression.
This table summarizes SNPH 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 4. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for SNPH. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNPH shows lower tumor expression in BLCA, THCA, UCEC, COAD and KIRC and higher tumor expression in LIHC. The BLCA box plot shows higher SNPH RNA expression in normal versus tumor tissue (log2 FC = −2.072, t-test p < 0.001).
This table shows molecular features associated with SNPH in patient tissues and cancer cell lines. In patient samples, SNPH shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SNPH RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in SKIN and LARGE_INTESTINE.
