calcitonin receptor like receptorGenealiases: CGRPR · CRLR · LMPHM8
Q-omics provides the consensus-scored CALCRL profile across patient tissues and cancer cell-line models. CALCRL expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, CALCRL is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, CALCRL protein abundance shows 28,194 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight KIRC, KICH, and LSCC as cancer lineages where CALCRL 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 CALCRL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CALCRL survival associations across molecular data types. CALCRL RNA expression shows survival associations in the most cancer types (19), followed by mutation status (7) 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 CALCRL RNA expression–survival associations across cancer types. High CALCRL expression shows unfavorable associations in UVM, KIRP, BLCA and LAML, but favorable associations in KIRC and LGG. The KIRC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify KIRC as the clearest survival context for CALCRL RNA expression.
This table summarizes CALCRL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 9. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CALCRL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CALCRL shows lower tumor expression in KICH, LUSC and LUAD and higher tumor expression in KIRC, HNSC and LIHC. The KICH box plot shows higher CALCRL RNA expression in normal versus tumor tissue (log2 FC = −2.233, t-test p < 0.001).
This table shows molecular features associated with CALCRL in patient tissues and cancer cell lines. In patient samples, CALCRL 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, CALCRL RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BLOOD_Lymphoma.
