Q-omics provides the consensus-scored CEPT1 profile across patient tissues and cancer cell-line models. CEPT1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in SCLC. Among the 18 cancer types available for tumor–normal comparison, CEPT1 is differentially expressed in 11, with the highest sampling consensus in BLCA. Additionally, CEPT1 protein abundance shows 24,290 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight SCLC, BLCA, and PDAC as cancer lineages where CEPT1 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 CEPT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CEPT1 survival associations across molecular data types. CEPT1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (9). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CEPT1 RNA expression–survival associations across cancer types. High CEPT1 expression shows unfavorable associations in SCLC, ACC and LGG, but favorable associations in KIRC, READ and CHOL. The SCLC 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 SCLC as the clearest survival context for CEPT1 RNA expression.
This table summarizes CEPT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 10. The strongest signals are observed in BLCA for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CEPT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CEPT1 shows lower tumor expression in THCA, LUAD, KICH and LUSC and higher tumor expression in BLCA and STAD. The BLCA box plot shows higher CEPT1 RNA expression in tumor versus normal tissue (log2 FC = +0.706, t-test p < 0.001).
This table shows molecular features associated with CEPT1 in patient tissues and cancer cell lines. In patient samples, CEPT1 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, CEPT1 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_Leukemia and LARGE_INTESTINE.
