Q-omics provides the consensus-scored C8orf86 profile across patient tissues and cancer cell-line models. C8orf86 expression is associated with patient survival in 16 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, C8orf86 is differentially expressed in 6, with the highest sampling consensus in KIRC. Additionally, C8orf86 RNA expression shows 11,183 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight SCLC, KIRC, and TGCT as cancer lineages where C8orf86 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 C8orf86 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C8orf86 survival associations across molecular data types. C8orf86 RNA expression shows survival associations in the most cancer types (16), 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 C8orf86 RNA expression–survival associations across cancer types. High C8orf86 expression shows unfavorable associations in DLBC, COAD and SKCM, but favorable associations in SCLC, BRCA and PAAD. The SCLC 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 SCLC as the clearest survival context for C8orf86 RNA expression.
This table summarizes C8orf86 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 6. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for C8orf86. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C8orf86 shows lower tumor expression in KIRC, KICH, READ and HNSC and higher tumor expression in BRCA and PRAD. The KIRC box plot shows higher C8orf86 RNA expression in normal versus tumor tissue (log2 FC = −0.038, t-test p < 0.001).
This table shows molecular features associated with C8orf86 in patient tissues and cancer cell lines. In patient samples, C8orf86 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, C8orf86 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LUNG_SCLC, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BONE.
