Q-omics provides the consensus-scored CALB1 profile across patient tissues and cancer cell-line models. CALB1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in COAD. Among the 18 cancer types available for tumor–normal comparison, CALB1 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, CALB1 protein abundance shows 17,321 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight COAD, KIRC, and GBM as cancer lineages where CALB1 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 CALB1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CALB1 survival associations across molecular data types. CALB1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CALB1 RNA expression–survival associations across cancer types. High CALB1 expression shows unfavorable associations in COAD, OV, UVM and KIRC, but favorable associations in CESC and SKCM. The COAD 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 COAD as the clearest survival context for CALB1 RNA expression.
This table summarizes CALB1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 5. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for CALB1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CALB1 shows lower tumor expression in KIRC, KIRP and KICH and higher tumor expression in HNSC, LUSC and STAD. The KIRC box plot shows higher CALB1 RNA expression in normal versus tumor tissue (log2 FC = −5.955, t-test p < 0.001).
This table shows molecular features associated with CALB1 in patient tissues and cancer cell lines. In patient samples, CALB1 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, CALB1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
