Q-omics provides the consensus-scored C22orf46 profile across patient tissues and cancer cell-line models. C22orf46 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, C22orf46 is differentially expressed in 11, with the highest sampling consensus in HNSC. Additionally, C22orf46 RNA expression shows 20,101 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight HNSC, and ACC as cancer lineages where C22orf46 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 C22orf46 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C22orf46 survival associations across molecular data types. C22orf46 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C22orf46 RNA expression–survival associations across cancer types. High C22orf46 expression shows unfavorable associations in LUAD, ACC and UVM, but favorable associations in HNSC, ESCA and UCS. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for C22orf46 RNA expression.
This table summarizes C22orf46 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for C22orf46. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C22orf46 shows lower tumor expression in THCA, KIRC and BRCA and higher tumor expression in HNSC, LIHC and STAD. The HNSC box plot shows higher C22orf46 RNA expression in tumor versus normal tissue (log2 FC = +1.152, t-test p < 0.001).
This table shows molecular features associated with C22orf46 in patient tissues and cancer cell lines. In patient samples, C22orf46 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, C22orf46 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in STOMACH and LARGE_INTESTINE.
