Q-omics provides the consensus-scored C9orf40 profile across patient tissues and cancer cell-line models. C9orf40 expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, C9orf40 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, C9orf40 RNA expression shows 18,897 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight MESO, HNSC, and ACC as cancer lineages where C9orf40 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 C9orf40 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C9orf40 survival associations across molecular data types. C9orf40 RNA expression shows survival associations in the most cancer types (19), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible C9orf40 RNA expression–survival associations across cancer types. High C9orf40 expression shows unfavorable associations in MESO, KIRP, ACC, UVM, LGG and LUAD. The MESO 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 MESO as the clearest survival context for C9orf40 RNA expression.
This table summarizes C9orf40 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for C9orf40. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C9orf40 shows higher tumor expression in HNSC, LUAD, LUSC, LIHC, STAD and UCEC. The HNSC box plot shows higher C9orf40 RNA expression in tumor versus normal tissue (log2 FC = +1.101, t-test p < 0.001).
This table shows molecular features associated with C9orf40 in patient tissues and cancer cell lines. In patient samples, C9orf40 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, C9orf40 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 BLOOD_Leukemia and LUNG_SCLC.
