Q-omics provides the consensus-scored C8orf44-SGK3 profile across patient tissues and cancer cell-line models. C8orf44-SGK3 expression is associated with patient survival in 29 of 34 cancer types, with the highest sampling consensus in SKCM. Among the 18 cancer types available for tumor–normal comparison, C8orf44-SGK3 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, C8orf44-SGK3 RNA expression shows 17,532 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight SKCM, HNSC, and UVM as cancer lineages where C8orf44-SGK3 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 C8orf44-SGK3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C8orf44-SGK3 survival associations across molecular data types. C8orf44-SGK3 RNA expression shows survival associations in the most cancer types (29), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C8orf44-SGK3 RNA expression–survival associations across cancer types. High C8orf44-SGK3 expression shows unfavorable associations in UVM and COAD, but favorable associations in SKCM, UCS, THYM and BRCA. The SKCM Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .005). Together, the overview and detailed table identify SKCM as the clearest survival context for C8orf44-SGK3 RNA expression.
This table summarizes C8orf44-SGK3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for C8orf44-SGK3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C8orf44-SGK3 shows lower tumor expression in KICH and UCEC and higher tumor expression in HNSC, LIHC, STAD and KIRC. The HNSC box plot shows higher C8orf44-SGK3 RNA expression in tumor versus normal tissue (log2 FC = +0.076, t-test p < 0.001).
This table shows molecular features associated with C8orf44-SGK3 in patient tissues and cancer cell lines. In patient samples, C8orf44-SGK3 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, C8orf44-SGK3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SOFT_TISSUE, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia.
