Q-omics provides the consensus-scored CALR profile across patient tissues and cancer cell-line models. CALR expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, CALR is differentially expressed in 15, with the highest sampling consensus in HNSC. Additionally, CALR protein abundance shows 29,778 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, HNSC, and GBM as cancer lineages where CALR 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 CALR — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes CALR survival associations across molecular data types. CALR RNA expression shows survival associations in the most cancer types (21), followed by mutation status (3) 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 CALR RNA expression–survival associations across cancer types. High CALR expression shows unfavorable associations in BLCA, KIRP, KICH, UVM, LGG and ACC. The BLCA Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify BLCA as the clearest survival context for CALR RNA expression.
This table summarizes CALR tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 15, while mass-spec protein shows differences in 7. The strongest signals are observed in KIRC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for CALR. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. CALR shows lower tumor expression in THCA and higher tumor expression in HNSC, KIRC, BLCA, COAD and STAD. The HNSC box plot shows higher CALR RNA expression in tumor versus normal tissue (log2 FC = +1.261, t-test p < 0.001).
This table shows molecular features associated with CALR in patient tissues and cancer cell lines. In patient samples, CALR 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, CALR RNA and mutation anchors are most strongly linked to RNA-expression features, especially in SKIN, while CRISPR and shRNA rows add functional-dependency signals in LARGE_INTESTINE and BONE.
