telomere repeat binding bouquet formation protein 1Genealiases: CCDC79 · SPGF60
Q-omics provides the consensus-scored TERB1 profile across patient tissues and cancer cell-line models. TERB1 expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in DLBC. Among the 18 cancer types available for tumor–normal comparison, TERB1 is differentially expressed in 8, with the highest sampling consensus in READ. Additionally, TERB1 RNA expression shows 14,887 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight DLBC, READ, and UVM as cancer lineages where TERB1 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 TERB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TERB1 survival associations across molecular data types. TERB1 RNA expression shows survival associations in the most cancer types (21), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TERB1 RNA expression–survival associations across cancer types. High TERB1 expression shows unfavorable associations in DLBC, UVM, KIRP, KIRC and THCA, but favorable associations in PAAD. The DLBC 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 DLBC as the clearest survival context for TERB1 RNA expression.
This table summarizes TERB1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in READ for RNA.
This table ranks reproducible tumor–normal expression differences for TERB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TERB1 shows lower tumor expression in KICH and higher tumor expression in READ, BLCA, CHOL, COAD and ESCA. The READ box plot shows higher TERB1 RNA expression in tumor versus normal tissue (log2 FC = +0.091, t-test p < 0.001).
This table shows molecular features associated with TERB1 in patient tissues and cancer cell lines. In patient samples, TERB1 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, TERB1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LARGE_INTESTINE, while CRISPR and shRNA rows add functional-dependency signals in LIVER and LUNG_SCLC.
