amyloid beta precursor like protein 2Genealiases: APLP-2 · APPH · APPL2 · CDEBP
Q-omics provides the consensus-scored APLP2 profile across patient tissues and cancer cell-line models. APLP2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, APLP2 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, APLP2 RNA expression shows 19,139 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UVM, HNSC, and KIRP as cancer lineages where APLP2 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 APLP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes APLP2 survival associations across molecular data types. APLP2 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (5) 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 APLP2 RNA expression–survival associations across cancer types. High APLP2 expression shows unfavorable associations in UVM, ACC, BLCA and LIHC, but favorable associations in THCA and KIRC. The UVM 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 UVM as the clearest survival context for APLP2 RNA expression.
This table summarizes APLP2 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 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for APLP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. APLP2 shows lower tumor expression in KIRC, LUAD, COAD and LUSC and higher tumor expression in HNSC and LIHC. The HNSC box plot shows higher APLP2 RNA expression in tumor versus normal tissue (log2 FC = +1.668, t-test p < 0.001).
This table shows molecular features associated with APLP2 in patient tissues and cancer cell lines. In patient samples, APLP2 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, APLP2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
