Q-omics provides the consensus-scored C1orf100 profile across patient tissues and cancer cell-line models. C1orf100 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in PAAD. Among the 18 cancer types available for tumor–normal comparison, C1orf100 is differentially expressed in 6, with the highest sampling consensus in HNSC. Additionally, C1orf100 RNA expression shows 14,534 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight PAAD, HNSC, and UVM as cancer lineages where C1orf100 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 C1orf100 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C1orf100 survival associations across molecular data types. C1orf100 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C1orf100 RNA expression–survival associations across cancer types. High C1orf100 expression shows unfavorable associations in KIRC, LIHC, ACC and LGG, but favorable associations in PAAD and HNSC. The PAAD 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 PAAD as the clearest survival context for C1orf100 RNA expression.
This table summarizes C1orf100 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 HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for C1orf100. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C1orf100 shows lower tumor expression in KICH and higher tumor expression in HNSC, LIHC, BRCA, CHOL and READ. The HNSC box plot shows higher C1orf100 RNA expression in tumor versus normal tissue (log2 FC = +0.268, t-test p < 0.001).
This table shows molecular features associated with C1orf100 in patient tissues and cancer cell lines. In patient samples, C1orf100 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, C1orf100 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in SKIN and BLOOD_Lymphoma.
