calcitonin related polypeptide betaGenealiases: CALC2 · CGRP-II · CGRP2
Q-omics provides the consensus-scored CALCB profile across patient tissues and cancer cell-line models. CALCB expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, CALCB is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, CALCB RNA expression shows 10,390 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, KIRC, and TGCT as cancer lineages where CALCB 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 CALCB — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CALCB survival associations across molecular data types. CALCB RNA expression shows survival associations in the most cancer types (22), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible CALCB RNA expression–survival associations across cancer types. High CALCB expression shows unfavorable associations in KIRP, UCEC, COAD, ACC, OV and STAD. The KIRP 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 KIRP as the clearest survival context for CALCB RNA expression.
This table summarizes CALCB tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for CALCB. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CALCB shows lower tumor expression in KIRC and higher tumor expression in LIHC, UCEC, BRCA, LUSC and LUAD. The KIRC box plot shows higher CALCB RNA expression in normal versus tumor tissue (log2 FC = −0.207, t-test p < 0.001).
This table shows molecular features associated with CALCB in patient tissues and cancer cell lines. In patient samples, CALCB shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, CALCB 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 BLOOD_Leukemia and BONE.
