Q-omics provides the consensus-scored C11orf53 profile across patient tissues and cancer cell-line models. C11orf53 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, C11orf53 is differentially expressed in 14, with the highest sampling consensus in KIRC. Additionally, C11orf53 RNA expression shows 9,445 significant gene co-expression associations, with the highest sampling consensus in ESCA. Together, these results highlight KIRC, and ESCA as cancer lineages where C11orf53 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 C11orf53 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C11orf53 survival associations across molecular data types. C11orf53 RNA expression shows survival associations in the most cancer types (23), 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 C11orf53 RNA expression–survival associations across cancer types. High C11orf53 expression shows unfavorable associations in KIRC, OV, ESCA, READ and PRAD, but favorable associations in MESO. The KIRC 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 KIRC as the clearest survival context for C11orf53 RNA expression.
This table summarizes C11orf53 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 14. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for C11orf53. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C11orf53 shows lower tumor expression in KIRC, KIRP, BRCA and READ and higher tumor expression in KICH and PAAD. The KIRC box plot shows higher C11orf53 RNA expression in normal versus tumor tissue (log2 FC = −0.996, t-test p < 0.001).
This table shows molecular features associated with C11orf53 in patient tissues and cancer cell lines. In patient samples, C11orf53 shows the broadest associations at the RNA and protein expression levels, with ESCA recurring as the lineage with the largest associated feature set. In cancer cell lines, C11orf53 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Myeloma and URINARY_TRACT.
