Q-omics provides the consensus-scored C4orf17 profile across patient tissues and cancer cell-line models. C4orf17 expression is associated with patient survival in 20 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, C4orf17 is differentially expressed in 7, with the highest sampling consensus in KIRP. Additionally, C4orf17 RNA expression shows 8,382 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight UVM, KIRP, and ESCA as cancer lineages where C4orf17 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 C4orf17 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C4orf17 survival associations across molecular data types. C4orf17 RNA expression shows survival associations in the most cancer types (20), followed by mutation status (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C4orf17 RNA expression–survival associations across cancer types. High C4orf17 expression shows unfavorable associations in UVM, KIRC, KIRP and COAD, but favorable associations in UCS and SKCM. The UVM 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 UVM as the clearest survival context for C4orf17 RNA expression.
This table summarizes C4orf17 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 7. The strongest signals are observed in KIRP for RNA.
This table ranks reproducible tumor–normal expression differences for C4orf17. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C4orf17 shows lower tumor expression in BLCA and STAD and higher tumor expression in KIRP, THCA, LUSC and HNSC. The KIRP box plot shows higher C4orf17 RNA expression in tumor versus normal tissue (log2 FC = +0.031, t-test p = .001).
This table shows molecular features associated with C4orf17 in patient tissues and cancer cell lines. In patient samples, C4orf17 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, C4orf17 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 SOFT_TISSUE and BLOOD_Lymphoma.
