Q-omics provides the consensus-scored BBS9 profile across patient tissues and cancer cell-line models. BBS9 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, BBS9 is differentially expressed in 8, with the highest sampling consensus in KICH. Additionally, BBS9 RNA expression shows 20,225 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight BLCA, KICH, and UVM as cancer lineages where BBS9 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 BBS9 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BBS9 survival associations across molecular data types. BBS9 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (9) and mass-spec protein abundance (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible BBS9 RNA expression–survival associations across cancer types. High BBS9 expression shows unfavorable associations in BLCA, LGG, STAD, KICH and LIHC, but favorable associations in KIRC. The BLCA 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 BLCA as the clearest survival context for BBS9 RNA expression.
This table summarizes BBS9 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for BBS9. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BBS9 shows lower tumor expression in KICH, LUSC and UCEC and higher tumor expression in LIHC, CHOL and BRCA. The KICH box plot shows higher BBS9 RNA expression in normal versus tumor tissue (log2 FC = −1.322, t-test p < 0.001).
This table shows molecular features associated with BBS9 in patient tissues and cancer cell lines. In patient samples, BBS9 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, BBS9 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Leukemia.
