Q-omics provides the consensus-scored ZNFX1 profile across patient tissues and cancer cell-line models. ZNFX1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, ZNFX1 is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, ZNFX1 protein abundance shows 21,557 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight SKCM, HNSC, and LSCC as cancer lineages where ZNFX1 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 ZNFX1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZNFX1 survival associations across molecular data types. ZNFX1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (8) 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 ZNFX1 RNA expression–survival associations across cancer types. High ZNFX1 expression shows unfavorable associations in UVM, LGG and PAAD, but favorable associations in SKCM, KIRC and SARC. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify SKCM as the clearest survival context for ZNFX1 RNA expression.
This table summarizes ZNFX1 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 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for ZNFX1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZNFX1 shows lower tumor expression in LUSC and UCEC and higher tumor expression in HNSC, STAD, LIHC and BRCA. The HNSC box plot shows higher ZNFX1 RNA expression in tumor versus normal tissue (log2 FC = +1.687, t-test p < 0.001).
This table shows molecular features associated with ZNFX1 in patient tissues and cancer cell lines. In patient samples, ZNFX1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, ZNFX1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in CNS and BLOOD_Leukemia.
