Q-omics provides the consensus-scored PLEKHA3 profile across patient tissues and cancer cell-line models. PLEKHA3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, PLEKHA3 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, PLEKHA3 RNA expression shows 20,893 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRP, HNSC, and ACC as cancer lineages where PLEKHA3 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 PLEKHA3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLEKHA3 survival associations across molecular data types. PLEKHA3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 PLEKHA3 RNA expression–survival associations across cancer types. High PLEKHA3 expression shows unfavorable associations in KIRP, ACC, LGG and LIHC, but favorable associations in KIRC and SKCM. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify KIRP as the clearest survival context for PLEKHA3 RNA expression.
This table summarizes PLEKHA3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 5. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for PLEKHA3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLEKHA3 shows lower tumor expression in KICH and UCEC and higher tumor expression in HNSC, LIHC, CHOL and BRCA. The HNSC box plot shows higher PLEKHA3 RNA expression in tumor versus normal tissue (log2 FC = +0.848, t-test p < 0.001).
This table shows molecular features associated with PLEKHA3 in patient tissues and cancer cell lines. In patient samples, PLEKHA3 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, PLEKHA3 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 URINARY_TRACT and BLOOD_Leukemia.
