Q-omics provides the consensus-scored ZGRF1 profile across patient tissues and cancer cell-line models. ZGRF1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, ZGRF1 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, ZGRF1 RNA expression shows 21,254 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KICH, HNSC, and GBM as cancer lineages where ZGRF1 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 ZGRF1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZGRF1 survival associations across molecular data types. ZGRF1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (7). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZGRF1 RNA expression–survival associations across cancer types. High ZGRF1 expression shows unfavorable associations in KICH, KIRC, MESO, ACC and LGG, but favorable associations in READ. The KICH 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 KICH as the clearest survival context for ZGRF1 RNA expression.
This table summarizes ZGRF1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for ZGRF1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZGRF1 shows higher tumor expression in HNSC, KIRC, BLCA, LUSC, STAD and COAD. The HNSC box plot shows higher ZGRF1 RNA expression in tumor versus normal tissue (log2 FC = +0.770, t-test p < 0.001).
This table shows molecular features associated with ZGRF1 in patient tissues and cancer cell lines. In patient samples, ZGRF1 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZGRF1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OVARY, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia and LUNG_NSCLC_LUAD.
