BICD family like cargo adaptor 1Genealiases: BICDR-1 · BICDR1 · CCDC64 · CCDC64A · H_267D11.1
Q-omics provides the consensus-scored BICDL1 profile across patient tissues and cancer cell-line models. BICDL1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, BICDL1 is differentially expressed in 15, with the highest sampling consensus in COAD. Additionally, BICDL1 RNA expression shows 19,514 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and COAD as cancer lineages where BICDL1 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 BICDL1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes BICDL1 survival associations across molecular data types. BICDL1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 BICDL1 RNA expression–survival associations across cancer types. High BICDL1 expression shows unfavorable associations in UVM, LIHC and COAD, but favorable associations in KIRP, HNSC and STAD. The UVM 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 UVM as the clearest survival context for BICDL1 RNA expression.
This table summarizes BICDL1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for BICDL1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. BICDL1 shows lower tumor expression in KIRC, KICH and THCA and higher tumor expression in COAD, LUAD and BRCA. The COAD box plot shows higher BICDL1 RNA expression in tumor versus normal tissue (log2 FC = +1.299, t-test p < 0.001).
This table shows molecular features associated with BICDL1 in patient tissues and cancer cell lines. In patient samples, BICDL1 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, BICDL1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and BLOOD_Leukemia.
