Q-omics provides the consensus-scored BLM profile across patient tissues and cancer cell-line models. BLM expression is associated with patient survival in 30 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, BLM is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, BLM RNA expression shows 25,743 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where BLM 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 BLM — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BLM survival associations across molecular data types. BLM RNA expression shows survival associations in the most cancer types (30), followed by mutation status (4) 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 BLM RNA expression–survival associations across cancer types. High BLM expression shows unfavorable associations in ACC, MESO, KIRP, LIHC, KICH and KIRC. 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 BLM RNA expression.
This table summarizes BLM tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for BLM. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BLM shows higher tumor expression in HNSC, BLCA, KIRC, COAD, KIRP and LUAD. The HNSC box plot shows higher BLM RNA expression in tumor versus normal tissue (log2 FC = +1.632, t-test p < 0.001).
This table shows molecular features associated with BLM in patient tissues and cancer cell lines. In patient samples, BLM shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, BLM RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BONE.
