Q-omics provides the consensus-scored SNRNP200 profile across patient tissues and cancer cell-line models. SNRNP200 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SNRNP200 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, SNRNP200 protein abundance shows 32,126 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where SNRNP200 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 SNRNP200 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SNRNP200 survival associations across molecular data types. SNRNP200 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (9) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SNRNP200 RNA expression–survival associations across cancer types. High SNRNP200 expression shows unfavorable associations in ACC, MESO, KIRP and LIHC, but favorable associations in KIRC and SCLC. The ACC 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 ACC as the clearest survival context for SNRNP200 RNA expression.
This table summarizes SNRNP200 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SNRNP200. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SNRNP200 shows higher tumor expression in HNSC, COAD, KIRP, LIHC, LUAD and BLCA. The HNSC box plot shows higher SNRNP200 RNA expression in tumor versus normal tissue (log2 FC = +0.870, t-test p < 0.001).
This table shows molecular features associated with SNRNP200 in patient tissues and cancer cell lines. In patient samples, SNRNP200 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, SNRNP200 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
