immunoglobulin heavy constant alpha 2 (A2m marker)Genealiases: []
Q-omics provides the consensus-scored IGHA2 profile across patient tissues and cancer cell-line models. IGHA2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IGHA2 is differentially expressed in 10, with the highest sampling consensus in COAD. Additionally, IGHA2 protein abundance shows 15,652 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, COAD, and LSCC as cancer lineages where IGHA2 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 IGHA2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGHA2 survival associations across molecular data types. IGHA2 RNA expression shows survival associations in the most cancer types (23), followed by 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 IGHA2 RNA expression–survival associations across cancer types. High IGHA2 expression shows unfavorable associations in UVM, but favorable associations in HNSC, BRCA, SKCM, LIHC and MESO. 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 IGHA2 RNA expression.
This table summarizes IGHA2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 5. The strongest signals are observed in COAD for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for IGHA2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGHA2 shows lower tumor expression in COAD, LIHC, BRCA and READ and higher tumor expression in KIRC and LUAD. The COAD box plot shows higher IGHA2 RNA expression in normal versus tumor tissue (log2 FC = −4.893, t-test p < 0.001).
This table shows molecular features associated with IGHA2 in patient tissues and cancer cell lines. In patient samples, IGHA2 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
