Q-omics provides the consensus-scored CLTB profile across patient tissues and cancer cell-line models. CLTB expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in LUAD. Among the 18 cancer types available for tumor–normal comparison, CLTB is differentially expressed in 8, with the highest sampling consensus in LIHC. Additionally, CLTB protein abundance shows 28,473 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight LUAD, LIHC, and GBM as cancer lineages where CLTB 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 CLTB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CLTB survival associations across molecular data types. CLTB RNA expression shows survival associations in the most cancer types (28), followed by mutation status (4) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CLTB RNA expression–survival associations across cancer types. High CLTB expression shows unfavorable associations in LUAD, KICH, UCS and LAML, but favorable associations in MESO and SARC. The LUAD Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify LUAD as the clearest survival context for CLTB RNA expression.
This table summarizes CLTB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8, while mass-spec protein shows differences in 6. The strongest signals are observed in LIHC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CLTB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CLTB shows lower tumor expression in KICH and COAD and higher tumor expression in LIHC, THCA, CHOL and LUSC. The LIHC box plot shows higher CLTB RNA expression in tumor versus normal tissue (log2 FC = +1.153, t-test p < 0.001).
This table shows molecular features associated with CLTB in patient tissues and cancer cell lines. In patient samples, CLTB 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, CLTB 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 BLOOD_Lymphoma and BONE.
