Q-omics provides the consensus-scored C9orf106 profile across patient tissues and cancer cell-line models. C9orf106 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, C9orf106 is differentially expressed in 10, with the highest sampling consensus in BRCA. Additionally, C9orf106 RNA expression shows 18,793 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight UVM, BRCA, and GBM as cancer lineages where C9orf106 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 C9orf106 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C9orf106 survival associations across molecular data types. C9orf106 RNA expression shows survival associations in the most cancer types (23), 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 C9orf106 RNA expression–survival associations across cancer types. High C9orf106 expression shows unfavorable associations in UVM and COAD, but favorable associations in HNSC, SARC, CESC 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 C9orf106 RNA expression.
This table summarizes C9orf106 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for C9orf106. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C9orf106 shows lower tumor expression in UCEC, KIRP and PRAD and higher tumor expression in BRCA, THCA and LIHC. The BRCA box plot shows higher C9orf106 RNA expression in tumor versus normal tissue (log2 FC = +0.430, t-test p < 0.001).
This table shows molecular features associated with C9orf106 in patient tissues and cancer cell lines. In patient samples, C9orf106 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, C9orf106 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma.
