Q-omics provides the consensus-scored LYPD9P profile across patient tissues and cancer cell-line models. LYPD9P expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in UCEC. Among the 18 cancer types available for tumor–normal comparison, LYPD9P is differentially expressed in 7, with the highest sampling consensus in KIRC. Additionally, LYPD9P RNA expression shows 8,366 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UCEC, KIRC, and GBM as cancer lineages where LYPD9P 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 LYPD9P — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes LYPD9P survival associations across molecular data types. LYPD9P 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 LYPD9P RNA expression–survival associations across cancer types. High LYPD9P expression shows unfavorable associations in UCEC, KIRP, UCS, GBM and KIRC, but favorable associations in ESCA. The UCEC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .021). Together, the overview and detailed table identify UCEC as the clearest survival context for LYPD9P RNA expression.
This table summarizes LYPD9P tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for LYPD9P. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. LYPD9P shows lower tumor expression in KIRC, KICH, THCA and BRCA and higher tumor expression in UCEC and LIHC. The KIRC box plot shows higher LYPD9P RNA expression in normal versus tumor tissue (log2 FC = −0.457, t-test p < 0.001).
This table shows molecular features associated with LYPD9P in patient tissues and cancer cell lines. In patient samples, LYPD9P shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set.
