Q-omics provides the consensus-scored PLEKHA4 profile across patient tissues and cancer cell-line models. PLEKHA4 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PLEKHA4 is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, PLEKHA4 RNA expression shows 16,237 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and KICH as cancer lineages where PLEKHA4 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 PLEKHA4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLEKHA4 survival associations across molecular data types. PLEKHA4 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (9) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PLEKHA4 RNA expression–survival associations across cancer types. High PLEKHA4 expression shows unfavorable associations in ACC, LGG and HNSC, but favorable associations in BRCA, THCA and SKCM. The ACC 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 ACC as the clearest survival context for PLEKHA4 RNA expression.
This table summarizes PLEKHA4 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 5. The strongest signals are observed in KICH for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for PLEKHA4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLEKHA4 shows lower tumor expression in KICH, BLCA, BRCA and UCEC and higher tumor expression in KIRP and KIRC. The KICH box plot shows higher PLEKHA4 RNA expression in normal versus tumor tissue (log2 FC = −1.934, t-test p < 0.001).
This table shows molecular features associated with PLEKHA4 in patient tissues and cancer cell lines. In patient samples, PLEKHA4 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, PLEKHA4 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Leukemia, while CRISPR and shRNA rows add functional-dependency signals in SKIN and CNS.
