Q-omics provides the consensus-scored PCDHA10 profile across patient tissues and cancer cell-line models. PCDHA10 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in LUSC. Among the 18 cancer types available for tumor–normal comparison, PCDHA10 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, PCDHA10 RNA expression shows 14,283 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight LUSC, KIRC, and TGCT as cancer lineages where PCDHA10 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 PCDHA10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PCDHA10 survival associations across molecular data types. PCDHA10 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PCDHA10 RNA expression–survival associations across cancer types. High PCDHA10 expression shows unfavorable associations in LUSC, STAD, TGCT and COAD, but favorable associations in UVM and UCS. The LUSC 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 LUSC as the clearest survival context for PCDHA10 RNA expression.
This table summarizes PCDHA10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for PCDHA10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PCDHA10 shows lower tumor expression in KIRC, LUSC, KICH, KIRP and UCEC and higher tumor expression in CHOL. The KIRC box plot shows higher PCDHA10 RNA expression in normal versus tumor tissue (log2 FC = −0.771, t-test p < 0.001).
This table shows molecular features associated with PCDHA10 in patient tissues and cancer cell lines. In patient samples, PCDHA10 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, PCDHA10 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 BLOOD_Myeloma and BLOOD_Leukemia.
