Q-omics provides the consensus-scored AHCYL1 profile across patient tissues and cancer cell-line models. AHCYL1 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in READ. Among the 18 cancer types available for tumor–normal comparison, AHCYL1 is differentially expressed in 5, with the highest sampling consensus in KICH. Additionally, AHCYL1 protein abundance shows 22,705 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight READ, KICH, and GBM as cancer lineages where AHCYL1 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 AHCYL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AHCYL1 survival associations across molecular data types. AHCYL1 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AHCYL1 RNA expression–survival associations across cancer types. High AHCYL1 expression shows unfavorable associations in BLCA, ACC and LIHC, but favorable associations in READ, KIRC and COAD. The READ Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify READ as the clearest survival context for AHCYL1 RNA expression.
This table summarizes AHCYL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 5, while mass-spec protein shows differences in 7. The strongest signals are observed in KICH for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for AHCYL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AHCYL1 shows lower tumor expression in KICH, KIRC and KIRP and higher tumor expression in LIHC and CHOL. The KICH box plot shows higher AHCYL1 RNA expression in normal versus tumor tissue (log2 FC = −1.313, t-test p < 0.001).
This table shows molecular features associated with AHCYL1 in patient tissues and cancer cell lines. In patient samples, AHCYL1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, AHCYL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
