Q-omics provides the consensus-scored EMX2 profile across patient tissues and cancer cell-line models. EMX2 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, EMX2 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, EMX2 RNA expression shows 13,852 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, KICH, and KIRP as cancer lineages where EMX2 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 EMX2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EMX2 survival associations across molecular data types. EMX2 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (3) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EMX2 RNA expression–survival associations across cancer types. High EMX2 expression shows unfavorable associations in ACC, READ and LUAD, but favorable associations in KIRC, KIRP and CESC. 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 EMX2 RNA expression.
This table summarizes EMX2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for EMX2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EMX2 shows lower tumor expression in KICH, KIRC, BRCA, UCEC and PRAD and higher tumor expression in PAAD. The KICH box plot shows higher EMX2 RNA expression in normal versus tumor tissue (log2 FC = −1.734, t-test p < 0.001).
This table shows molecular features associated with EMX2 in patient tissues and cancer cell lines. In patient samples, EMX2 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, EMX2 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 BONE and OVARY.
