Q-omics provides the consensus-scored WEE2-AS1 profile across patient tissues and cancer cell-line models. WEE2-AS1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, WEE2-AS1 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, WEE2-AS1 RNA expression shows 17,213 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, KICH, and THYM as cancer lineages where WEE2-AS1 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 WEE2-AS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes WEE2-AS1 survival associations across molecular data types. WEE2-AS1 RNA expression shows survival associations in the most cancer types (23). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible WEE2-AS1 RNA expression–survival associations across cancer types. High WEE2-AS1 expression shows unfavorable associations in KICH, but favorable associations in HNSC, UVM, KIRP, BRCA and LUSC. The HNSC 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 HNSC as the clearest survival context for WEE2-AS1 RNA expression.
This table summarizes WEE2-AS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for WEE2-AS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. WEE2-AS1 shows lower tumor expression in KICH, KIRC, THCA, BRCA and KIRP and higher tumor expression in CHOL. The KICH box plot shows higher WEE2-AS1 RNA expression in normal versus tumor tissue (log2 FC = −1.278, t-test p < 0.001).
This table shows molecular features associated with WEE2-AS1 in patient tissues and cancer cell lines. In patient samples, WEE2-AS1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, WEE2-AS1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in BREAST.
