Q-omics provides the consensus-scored ZSWIM3 profile across patient tissues and cancer cell-line models. ZSWIM3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, ZSWIM3 is differentially expressed in 14, with the highest sampling consensus in HNSC. Additionally, ZSWIM3 RNA expression shows 19,779 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight HNSC, and UVM as cancer lineages where ZSWIM3 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 ZSWIM3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ZSWIM3 survival associations across molecular data types. ZSWIM3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (8) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ZSWIM3 RNA expression–survival associations across cancer types. High ZSWIM3 expression shows unfavorable associations in LIHC, UVM, LUSC and CESC, but favorable associations in HNSC and KIRC. The HNSC 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 HNSC as the clearest survival context for ZSWIM3 RNA expression.
This table summarizes ZSWIM3 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 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ZSWIM3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ZSWIM3 shows lower tumor expression in UCEC and higher tumor expression in HNSC, LIHC, STAD, CHOL and COAD. The HNSC box plot shows higher ZSWIM3 RNA expression in tumor versus normal tissue (log2 FC = +0.528, t-test p < 0.001).
This table shows molecular features associated with ZSWIM3 in patient tissues and cancer cell lines. In patient samples, ZSWIM3 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ZSWIM3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
