Q-omics provides the consensus-scored ZNHIT1 profile across patient tissues and cancer cell-line models. ZNHIT1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ZNHIT1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, ZNHIT1 protein abundance shows 22,969 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, and GBM as cancer lineages where ZNHIT1 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 ZNHIT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZNHIT1 survival associations across molecular data types. ZNHIT1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (4) 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 ZNHIT1 RNA expression–survival associations across cancer types. High ZNHIT1 expression shows unfavorable associations in KIRC, UVM, KICH, ACC, UCS and LGG. The KIRC 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 KIRC as the clearest survival context for ZNHIT1 RNA expression.
This table summarizes ZNHIT1 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 5. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for ZNHIT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZNHIT1 shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, KIRP, COAD and STAD. The KIRC box plot shows higher ZNHIT1 RNA expression in tumor versus normal tissue (log2 FC = +0.627, t-test p < 0.001).
This table shows molecular features associated with ZNHIT1 in patient tissues and cancer cell lines. In patient samples, ZNHIT1 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, ZNHIT1 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 LUNG_NSCLC_LUSC and SOFT_TISSUE.
