Q-omics provides the consensus-scored PTEN profile across patient tissues and cancer cell-line models. PTEN expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, PTEN is differentially expressed in 12, with the highest sampling consensus in KICH. Additionally, PTEN protein abundance shows 23,211 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, KICH, and LSCC as cancer lineages where PTEN 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 PTEN — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes PTEN survival associations across molecular data types. PTEN RNA expression shows survival associations in the most cancer types (21), followed by mutation status (12) and mass-spec protein abundance (8). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible PTEN RNA expression–survival associations across cancer types. High PTEN expression shows unfavorable associations in ACC and SCLC, but favorable associations in SKCM, KIRC, LGG and UCEC. 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 PTEN RNA expression.
This table summarizes PTEN 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 6. The strongest signals are observed in THCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for PTEN. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. PTEN shows lower tumor expression in KICH, THCA, COAD, UCEC and LUAD and higher tumor expression in HNSC. The KICH box plot shows higher PTEN RNA expression in normal versus tumor tissue (log2 FC = −1.404, t-test p < 0.001).
This table shows molecular features associated with PTEN in patient tissues and cancer cell lines. In patient samples, PTEN 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, PTEN RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_NSCLC_LUAD, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LARGE_INTESTINE.
