prostate and testis expressed 2Genealiases: C11orf38 · PATE-M · UNQ3112
Q-omics provides the consensus-scored PATE2 profile across patient tissues and cancer cell-line models. PATE2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PATE2 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, PATE2 RNA expression shows 13,232 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRP, HNSC, and UVM as cancer lineages where PATE2 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 PATE2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PATE2 survival associations across molecular data types. PATE2 RNA expression shows survival associations in the most cancer types (27), 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 PATE2 RNA expression–survival associations across cancer types. High PATE2 expression shows unfavorable associations in KIRP and DLBC, but favorable associations in UCS, ACC, BRCA and LAML. The KIRP 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 KIRP as the clearest survival context for PATE2 RNA expression.
This table summarizes PATE2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PATE2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PATE2 shows lower tumor expression in PRAD and THCA and higher tumor expression in HNSC, LUAD, BRCA and LUSC. The HNSC box plot shows higher PATE2 RNA expression in tumor versus normal tissue (log2 FC = +0.078, t-test p = .006).
This table shows molecular features associated with PATE2 in patient tissues and cancer cell lines. In patient samples, PATE2 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, PATE2 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 KIDNEY and BLOOD_Lymphoma.
