Q-omics provides the consensus-scored PRXL2CP1 profile across patient tissues and cancer cell-line models. PRXL2CP1 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PRXL2CP1 is differentially expressed in 6, with the highest sampling consensus in HNSC. Additionally, PRXL2CP1 RNA expression shows 11,241 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRP, HNSC, and ESCA as cancer lineages where PRXL2CP1 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 PRXL2CP1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PRXL2CP1 survival associations across molecular data types. PRXL2CP1 RNA expression shows survival associations in the most cancer types (13). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PRXL2CP1 RNA expression–survival associations across cancer types. High PRXL2CP1 expression shows unfavorable associations in KIRP, CESC, PCPG and PRAD, but favorable associations in HNSC and COAD. 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 PRXL2CP1 RNA expression.
This table summarizes PRXL2CP1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for PRXL2CP1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PRXL2CP1 shows lower tumor expression in THCA, LUSC and KIRP and higher tumor expression in HNSC, READ and KIRC. The HNSC box plot shows higher PRXL2CP1 RNA expression in tumor versus normal tissue (log2 FC = +0.018, t-test p = .024).
This table shows molecular features associated with PRXL2CP1 in patient tissues and cancer cell lines. In patient samples, PRXL2CP1 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set.
