Q-omics provides the consensus-scored CCDC150 profile across patient tissues and cancer cell-line models. CCDC150 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, CCDC150 is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, CCDC150 RNA expression shows 25,897 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight ACC, HNSC, and LSCC as cancer lineages where CCDC150 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 CCDC150 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CCDC150 survival associations across molecular data types. CCDC150 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (8) and mass-spec protein abundance (2). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CCDC150 RNA expression–survival associations across cancer types. High CCDC150 expression shows unfavorable associations in ACC, MESO, KICH, UCEC, LIHC and CHOL. The ACC 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 ACC as the clearest survival context for CCDC150 RNA expression.
This table summarizes CCDC150 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CCDC150. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CCDC150 shows higher tumor expression in HNSC, KIRC, BLCA, COAD, LUAD and UCEC. The HNSC box plot shows higher CCDC150 RNA expression in tumor versus normal tissue (log2 FC = +0.464, t-test p < 0.001).
This table shows molecular features associated with CCDC150 in patient tissues and cancer cell lines. In patient samples, CCDC150 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, CCDC150 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and BLOOD_Leukemia.
