Q-omics provides the consensus-scored APPL2 profile across patient tissues and cancer cell-line models. APPL2 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, APPL2 is differentially expressed in 14, with the highest sampling consensus in COAD. Additionally, APPL2 RNA expression shows 21,125 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, COAD, and THYM as cancer lineages where APPL2 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 APPL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APPL2 survival associations across molecular data types. APPL2 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible APPL2 RNA expression–survival associations across cancer types. High APPL2 expression shows unfavorable associations in KICH and MESO, but favorable associations in HNSC, SCLC, BRCA and KIRC. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for APPL2 RNA expression.
This table summarizes APPL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 8. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for APPL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APPL2 shows lower tumor expression in COAD, KICH and READ and higher tumor expression in BLCA, LIHC and CHOL. The COAD box plot shows higher APPL2 RNA expression in normal versus tumor tissue (log2 FC = −1.872, t-test p < 0.001).
This table shows molecular features associated with APPL2 in patient tissues and cancer cell lines. In patient samples, APPL2 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, APPL2 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 BONE and BLOOD_Leukemia.
