Q-omics provides the consensus-scored ALKBH6 profile across patient tissues and cancer cell-line models. ALKBH6 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ALKBH6 is differentially expressed in 14, with the highest sampling consensus in BLCA. Additionally, ALKBH6 RNA expression shows 17,984 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and BLCA as cancer lineages where ALKBH6 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 ALKBH6 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ALKBH6 survival associations across molecular data types. ALKBH6 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (2) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ALKBH6 RNA expression–survival associations across cancer types. High ALKBH6 expression shows unfavorable associations in ACC, KIRC, UCEC and LGG, but favorable associations in HNSC and SKCM. The ACC 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 ACC as the clearest survival context for ALKBH6 RNA expression.
This table summarizes ALKBH6 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 2. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ALKBH6. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ALKBH6 shows higher tumor expression in BLCA, COAD, HNSC, KIRC, LIHC and KIRP. The BLCA box plot shows higher ALKBH6 RNA expression in tumor versus normal tissue (log2 FC = +1.082, t-test p < 0.001).
This table shows molecular features associated with ALKBH6 in patient tissues and cancer cell lines. In patient samples, ALKBH6 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ALKBH6 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 UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
