Q-omics provides the consensus-scored CHRNB2 profile across patient tissues and cancer cell-line models. CHRNB2 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, CHRNB2 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, CHRNB2 RNA expression shows 18,278 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, KICH, and GBM as cancer lineages where CHRNB2 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 CHRNB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CHRNB2 survival associations across molecular data types. CHRNB2 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CHRNB2 RNA expression–survival associations across cancer types. High CHRNB2 expression shows unfavorable associations in SKCM, COAD and DLBC, but favorable associations in UVM, LGG and PAAD. The UVM 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 UVM as the clearest survival context for CHRNB2 RNA expression.
This table summarizes CHRNB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for CHRNB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CHRNB2 shows lower tumor expression in KICH, HNSC and BRCA and higher tumor expression in LUSC, KIRP and LIHC. The KICH box plot shows higher CHRNB2 RNA expression in normal versus tumor tissue (log2 FC = −0.344, t-test p < 0.001).
This table shows molecular features associated with CHRNB2 in patient tissues and cancer cell lines. In patient samples, CHRNB2 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, CHRNB2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in PANCREAS and BLOOD_Leukemia.
