Q-omics provides the consensus-scored PLEKHA8 profile across patient tissues and cancer cell-line models. PLEKHA8 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PLEKHA8 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, PLEKHA8 RNA expression shows 20,180 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where PLEKHA8 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 PLEKHA8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PLEKHA8 survival associations across molecular data types. PLEKHA8 RNA expression shows survival associations in the most cancer types (25), 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 PLEKHA8 RNA expression–survival associations across cancer types. High PLEKHA8 expression shows unfavorable associations in ACC, BLCA, LIHC, LGG and MESO, but favorable associations in KIRC. 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 PLEKHA8 RNA expression.
This table summarizes PLEKHA8 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for PLEKHA8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PLEKHA8 shows higher tumor expression in HNSC, BLCA, COAD, LUAD, LIHC and LUSC. The HNSC box plot shows higher PLEKHA8 RNA expression in tumor versus normal tissue (log2 FC = +0.997, t-test p < 0.001).
This table shows molecular features associated with PLEKHA8 in patient tissues and cancer cell lines. In patient samples, PLEKHA8 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, PLEKHA8 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 BREAST and UPPER_AERODIGESTIVE_TRACT.
