adenosylhomocysteinase like 2Genealiases: ADOHCYASE3 · IRBIT2
Q-omics provides the consensus-scored AHCYL2 profile across patient tissues and cancer cell-line models. AHCYL2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, AHCYL2 is differentially expressed in 13, with the highest sampling consensus in COAD. Additionally, AHCYL2 RNA expression shows 20,483 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight UVM, COAD, and THYM as cancer lineages where AHCYL2 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 AHCYL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AHCYL2 survival associations across molecular data types. AHCYL2 RNA expression shows survival associations in the most cancer types (23), 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 AHCYL2 RNA expression–survival associations across cancer types. High AHCYL2 expression shows unfavorable associations in UCEC and ESCA, but favorable associations in UVM, HNSC, KIRC and BRCA. The UVM 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 UVM as the clearest survival context for AHCYL2 RNA expression.
This table summarizes AHCYL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 6. The strongest signals are observed in COAD for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AHCYL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AHCYL2 shows lower tumor expression in COAD, THCA, KIRC and LUSC and higher tumor expression in KICH and LIHC. The COAD box plot shows higher AHCYL2 RNA expression in normal versus tumor tissue (log2 FC = −3.125, t-test p < 0.001).
This table shows molecular features associated with AHCYL2 in patient tissues and cancer cell lines. In patient samples, AHCYL2 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, AHCYL2 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 SOFT_TISSUE and BLOOD_Leukemia.
