Q-omics provides the consensus-scored CHRNB1 profile across patient tissues and cancer cell-line models. CHRNB1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, CHRNB1 is differentially expressed in 12, with the highest sampling consensus in KIRC. Additionally, CHRNB1 RNA expression shows 18,965 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SCLC, KIRC, and UVM as cancer lineages where CHRNB1 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 CHRNB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CHRNB1 survival associations across molecular data types. CHRNB1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CHRNB1 RNA expression–survival associations across cancer types. High CHRNB1 expression shows unfavorable associations in LGG, UVM, ACC and UCEC, but favorable associations in SCLC and KIRP. The SCLC 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 SCLC as the clearest survival context for CHRNB1 RNA expression.
This table summarizes CHRNB1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for CHRNB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CHRNB1 shows lower tumor expression in KICH and BRCA and higher tumor expression in KIRC, LUAD, BLCA and STAD. The KIRC box plot shows higher CHRNB1 RNA expression in tumor versus normal tissue (log2 FC = +0.730, t-test p < 0.001).
This table shows molecular features associated with CHRNB1 in patient tissues and cancer cell lines. In patient samples, CHRNB1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, CHRNB1 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 CNS and BLOOD_Leukemia.
