Q-omics provides the consensus-scored C10orf88 profile across patient tissues and cancer cell-line models. C10orf88 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, C10orf88 is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, C10orf88 RNA expression shows 20,552 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight LIHC, HNSC, and ACC as cancer lineages where C10orf88 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 C10orf88 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes C10orf88 survival associations across molecular data types. C10orf88 RNA expression shows survival associations in the most cancer types (27), followed by mutation status (1) 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 C10orf88 RNA expression–survival associations across cancer types. High C10orf88 expression shows unfavorable associations in LIHC, ACC, STAD and UVM, but favorable associations in LGG and KIRC. The LIHC 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 LIHC as the clearest survival context for C10orf88 RNA expression.
This table summarizes C10orf88 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for C10orf88. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. C10orf88 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, LUAD, KIRP and STAD. The HNSC box plot shows higher C10orf88 RNA expression in tumor versus normal tissue (log2 FC = +0.933, t-test p < 0.001).
This table shows molecular features associated with C10orf88 in patient tissues and cancer cell lines. In patient samples, C10orf88 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, C10orf88 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in STOMACH, while CRISPR and shRNA rows add functional-dependency signals in LUNG_NSCLC_LUAD and BLOOD_Leukemia.
