YTH domain family member 2 pseudogene 1Genealiases: HGRG8 · NY-REN-2 · YTHDF2P
Q-omics provides the consensus-scored YTHDF2P1 profile across patient tissues and cancer cell-line models. YTHDF2P1 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, YTHDF2P1 is differentially expressed in 9, with the highest sampling consensus in KICH. Additionally, YTHDF2P1 RNA expression shows 18,902 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, KICH, and ACC as cancer lineages where YTHDF2P1 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 YTHDF2P1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes YTHDF2P1 survival associations across molecular data types. YTHDF2P1 RNA expression shows survival associations in the most cancer types (28). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible YTHDF2P1 RNA expression–survival associations across cancer types. High YTHDF2P1 expression shows unfavorable associations in LIHC, KICH, ACC, UCEC and SARC, but favorable associations in KIRC. The LIHC 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 LIHC as the clearest survival context for YTHDF2P1 RNA expression.
This table summarizes YTHDF2P1 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 KICH for RNA.
This table ranks reproducible tumor–normal expression differences for YTHDF2P1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. YTHDF2P1 shows lower tumor expression in KICH and COAD and higher tumor expression in HNSC, LIHC, BRCA and CHOL. The KICH box plot shows higher YTHDF2P1 RNA expression in normal versus tumor tissue (log2 FC = −0.542, t-test p < 0.001).
This table shows molecular features associated with YTHDF2P1 in patient tissues and cancer cell lines. In patient samples, YTHDF2P1 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set.
