Q-omics provides the consensus-scored ZSCAN30 profile across patient tissues and cancer cell-line models. ZSCAN30 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LGG. Among the 18 cancer types available for tumor–normal comparison, ZSCAN30 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, ZSCAN30 RNA expression shows 21,599 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LGG, LIHC, and UVM as cancer lineages where ZSCAN30 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 ZSCAN30 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZSCAN30 survival associations across molecular data types. ZSCAN30 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZSCAN30 RNA expression–survival associations across cancer types. High ZSCAN30 expression shows unfavorable associations in LGG and ACC, but favorable associations in HNSC, UCS, PAAD and THYM. The LGG 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 LGG as the clearest survival context for ZSCAN30 RNA expression.
This table summarizes ZSCAN30 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 1. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ZSCAN30. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZSCAN30 shows lower tumor expression in COAD, BRCA, THCA and KIRP and higher tumor expression in LIHC and CHOL. The LIHC box plot shows higher ZSCAN30 RNA expression in tumor versus normal tissue (log2 FC = +0.639, t-test p < 0.001).
This table shows molecular features associated with ZSCAN30 in patient tissues and cancer cell lines. In patient samples, ZSCAN30 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZSCAN30 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
