Q-omics provides the consensus-scored ZNF350 profile across patient tissues and cancer cell-line models. ZNF350 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ZNF350 is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, ZNF350 RNA expression shows 20,886 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, COAD, and ACC as cancer lineages where ZNF350 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 ZNF350 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZNF350 survival associations across molecular data types. ZNF350 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZNF350 RNA expression–survival associations across cancer types. High ZNF350 expression shows unfavorable associations in LGG, LUSC, ACC and UVM, but favorable associations in KIRC and BLCA. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for ZNF350 RNA expression.
This table summarizes ZNF350 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in COAD for RNA.
This table ranks reproducible tumor–normal expression differences for ZNF350. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZNF350 shows lower tumor expression in COAD, THCA and READ and higher tumor expression in BRCA, LIHC and KIRC. The COAD box plot shows higher ZNF350 RNA expression in normal versus tumor tissue (log2 FC = −0.897, t-test p < 0.001).
This table shows molecular features associated with ZNF350 in patient tissues and cancer cell lines. In patient samples, ZNF350 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, ZNF350 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in BREAST and BLOOD_Lymphoma.
