Q-omics provides the consensus-scored SNCA profile across patient tissues and cancer cell-line models. SNCA expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in STAD. Among the 18 cancer types available for tumor–normal comparison, SNCA is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, SNCA protein abundance shows 25,146 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight STAD, THCA, and GBM as cancer lineages where SNCA 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 SNCA — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNCA survival associations across molecular data types. SNCA RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SNCA RNA expression–survival associations across cancer types. High SNCA expression shows unfavorable associations in STAD, HNSC, OV and UCEC, but favorable associations in PAAD and UVM. The STAD 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 STAD as the clearest survival context for SNCA RNA expression.
This table summarizes SNCA tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 7. The strongest signals are observed in THCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SNCA. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNCA shows lower tumor expression in THCA, LUAD, BLCA, KIRC, COAD and UCEC. The THCA box plot shows higher SNCA RNA expression in normal versus tumor tissue (log2 FC = −1.637, t-test p < 0.001).
This table shows molecular features associated with SNCA in patient tissues and cancer cell lines. In patient samples, SNCA 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, SNCA 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 BONE and SKIN.
