Q-omics provides the consensus-scored ZNF316 profile across patient tissues and cancer cell-line models. ZNF316 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in CESC. Among the 18 cancer types available for tumor–normal comparison, ZNF316 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, ZNF316 protein abundance shows 21,231 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight CESC, COAD, and GBM as cancer lineages where ZNF316 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 ZNF316 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZNF316 survival associations across molecular data types. ZNF316 RNA expression shows survival associations in the most cancer types (23), followed by mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZNF316 RNA expression–survival associations across cancer types. High ZNF316 expression shows unfavorable associations in CESC, OV, ACC and LGG, but favorable associations in THYM and PAAD. The CESC 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 CESC as the clearest survival context for ZNF316 RNA expression.
This table summarizes ZNF316 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 5. The strongest signals are observed in COAD for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for ZNF316. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZNF316 shows higher tumor expression in COAD, LIHC, KIRP, HNSC, STAD and KIRC. The COAD box plot shows higher ZNF316 RNA expression in tumor versus normal tissue (log2 FC = +1.104, t-test p < 0.001).
This table shows molecular features associated with ZNF316 in patient tissues and cancer cell lines. In patient samples, ZNF316 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, ZNF316 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 BLOOD_Lymphoma and BONE.
