Q-omics provides the consensus-scored ZBTB17 profile across patient tissues and cancer cell-line models. ZBTB17 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, ZBTB17 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ZBTB17 RNA expression shows 19,149 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where ZBTB17 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 ZBTB17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZBTB17 survival associations across molecular data types. ZBTB17 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (5) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZBTB17 RNA expression–survival associations across cancer types. High ZBTB17 expression shows unfavorable associations in ACC, LIHC, CESC, KIRC, LGG and KICH. The ACC 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 ACC as the clearest survival context for ZBTB17 RNA expression.
This table summarizes ZBTB17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14, while mass-spec protein shows differences in 6. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ZBTB17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZBTB17 shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, LIHC, BLCA and STAD. The HNSC box plot shows higher ZBTB17 RNA expression in tumor versus normal tissue (log2 FC = +0.810, t-test p < 0.001).
This table shows molecular features associated with ZBTB17 in patient tissues and cancer cell lines. In patient samples, ZBTB17 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, ZBTB17 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 KIDNEY and LUNG_SCLC.
