immunoglobulin heavy constant deltaGenealiases: []
Q-omics provides the consensus-scored IGHD profile across patient tissues and cancer cell-line models. IGHD expression is associated with patient survival in 19 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IGHD is differentially expressed in 8, with the highest sampling consensus in STAD. Additionally, IGHD RNA expression shows 10,076 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight HNSC, STAD, and TGCT as cancer lineages where IGHD 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 IGHD — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGHD survival associations across molecular data types. IGHD RNA expression shows survival associations in the most cancer types (19), 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 IGHD RNA expression–survival associations across cancer types. High IGHD expression shows unfavorable associations in UVM, but favorable associations in HNSC, BRCA, SKCM, LUAD and SARC. The HNSC 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 HNSC as the clearest survival context for IGHD RNA expression.
This table summarizes IGHD 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 3. The strongest signals are observed in BRCA for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGHD. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGHD shows lower tumor expression in LIHC, BRCA, COAD and KICH and higher tumor expression in STAD and KIRC. The STAD box plot shows higher IGHD RNA expression in tumor versus normal tissue (log2 FC = +1.257, t-test p = .032).
This table shows molecular features associated with IGHD in patient tissues and cancer cell lines. In patient samples, IGHD 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, IGHD RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in LUNG_SCLC and NCI60_ALL.
