Q-omics provides the consensus-scored PYROXD2 profile across patient tissues and cancer cell-line models. PYROXD2 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, PYROXD2 is differentially expressed in 10, with the highest sampling consensus in KICH. Additionally, PYROXD2 RNA expression shows 17,528 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight UCEC, KICH, and TGCT as cancer lineages where PYROXD2 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 PYROXD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PYROXD2 survival associations across molecular data types. PYROXD2 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (7) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PYROXD2 RNA expression–survival associations across cancer types. High PYROXD2 expression shows unfavorable associations in LGG, but favorable associations in UCEC, BLCA, MESO, SKCM and SCLC. The UCEC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .006). Together, the overview and detailed table identify UCEC as the clearest survival context for PYROXD2 RNA expression.
This table summarizes PYROXD2 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 5. The strongest signals are observed in KICH for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PYROXD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PYROXD2 shows lower tumor expression in KICH, LUSC, BRCA, UCEC, LIHC and STAD. The KICH box plot shows higher PYROXD2 RNA expression in normal versus tumor tissue (log2 FC = −2.352, t-test p < 0.001).
This table shows molecular features associated with PYROXD2 in patient tissues and cancer cell lines. In patient samples, PYROXD2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, PYROXD2 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 BREAST and LARGE_INTESTINE.
