Q-omics provides the consensus-scored BET1L profile across patient tissues and cancer cell-line models. BET1L expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, BET1L is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, BET1L RNA expression shows 19,648 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KICH, HNSC, and ACC as cancer lineages where BET1L 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 BET1L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BET1L survival associations across molecular data types. BET1L RNA expression shows survival associations in the most cancer types (23), followed by mutation status (2) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BET1L RNA expression–survival associations across cancer types. High BET1L expression shows unfavorable associations in KICH, LIHC, ACC and LGG, but favorable associations in KIRC and CHOL. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KICH as the clearest survival context for BET1L RNA expression.
This table summarizes BET1L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for BET1L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BET1L shows higher tumor expression in HNSC, KIRC, LIHC, STAD, COAD and CHOL. The HNSC box plot shows higher BET1L RNA expression in tumor versus normal tissue (log2 FC = +0.812, t-test p < 0.001).
This table shows molecular features associated with BET1L in patient tissues and cancer cell lines. In patient samples, BET1L 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, BET1L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and UPPER_AERODIGESTIVE_TRACT.
