Q-omics provides the consensus-scored ZBTB49 profile across patient tissues and cancer cell-line models. ZBTB49 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ZBTB49 is differentially expressed in 13, with the highest sampling consensus in THCA. Additionally, ZBTB49 RNA expression shows 20,605 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, THCA, and ACC as cancer lineages where ZBTB49 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 ZBTB49 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZBTB49 survival associations across molecular data types. ZBTB49 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZBTB49 RNA expression–survival associations across cancer types. High ZBTB49 expression shows unfavorable associations in ACC, but favorable associations in HNSC, UCS, PAAD, BLCA and READ. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for ZBTB49 RNA expression.
This table summarizes ZBTB49 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 1. The strongest signals are observed in THCA for RNA and PDAC for protein.
This table ranks reproducible tumor–normal expression differences for ZBTB49. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZBTB49 shows lower tumor expression in THCA, BRCA, KICH and UCEC and higher tumor expression in LIHC and CHOL. The THCA box plot shows higher ZBTB49 RNA expression in normal versus tumor tissue (log2 FC = −0.298, t-test p < 0.001).
This table shows molecular features associated with ZBTB49 in patient tissues and cancer cell lines. In patient samples, ZBTB49 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, ZBTB49 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
