Q-omics provides the consensus-scored SMPD3 profile across patient tissues and cancer cell-line models. SMPD3 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, SMPD3 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SMPD3 protein abundance shows 34,087 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight HNSC, and GBM as cancer lineages where SMPD3 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 SMPD3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SMPD3 survival associations across molecular data types. SMPD3 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (9) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SMPD3 RNA expression–survival associations across cancer types. High SMPD3 expression shows unfavorable associations in KIRC, but favorable associations in HNSC, LGG, UCEC, STAD and THYM. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .002). Together, the overview and detailed table identify HNSC as the clearest survival context for SMPD3 RNA expression.
This table summarizes SMPD3 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 10. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SMPD3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SMPD3 shows lower tumor expression in HNSC, THCA, COAD, LIHC, LUSC and READ. The HNSC box plot shows higher SMPD3 RNA expression in normal versus tumor tissue (log2 FC = −1.040, t-test p < 0.001).
This table shows molecular features associated with SMPD3 in patient tissues and cancer cell lines. In patient samples, SMPD3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SMPD3 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 SOFT_TISSUE and LUNG_SCLC.
