Q-omics provides the consensus-scored AQP8 profile across patient tissues and cancer cell-line models. AQP8 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, AQP8 is differentially expressed in 12, with the highest sampling consensus in COAD. Additionally, AQP8 protein abundance shows 11,769 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, COAD, and PDAC as cancer lineages where AQP8 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 AQP8 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AQP8 survival associations across molecular data types. AQP8 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AQP8 RNA expression–survival associations across cancer types. High AQP8 expression shows unfavorable associations in KIRC, DLBC and OV, but favorable associations in SCLC, COAD and UCS. The KIRC 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 KIRC as the clearest survival context for AQP8 RNA expression.
This table summarizes AQP8 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 COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AQP8. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AQP8 shows lower tumor expression in COAD, READ and LUSC and higher tumor expression in KIRC, THCA and LIHC. The COAD box plot shows higher AQP8 RNA expression in normal versus tumor tissue (log2 FC = −8.077, t-test p < 0.001).
This table shows molecular features associated with AQP8 in patient tissues and cancer cell lines. In patient samples, AQP8 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, AQP8 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Lymphoma.
