Q-omics provides the consensus-scored IGLV2-23 profile across patient tissues and cancer cell-line models. IGLV2-23 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, IGLV2-23 is differentially expressed in 9, with the highest sampling consensus in COAD. Additionally, IGLV2-23 RNA expression shows 15,370 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, COAD, and LSCC as cancer lineages where IGLV2-23 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 IGLV2-23 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes IGLV2-23 survival associations across molecular data types. IGLV2-23 RNA expression shows survival associations in the most cancer types (25), 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 IGLV2-23 RNA expression–survival associations across cancer types. High IGLV2-23 expression shows unfavorable associations in UVM, but favorable associations in HNSC, SKCM, BRCA, UCEC 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 IGLV2-23 RNA expression.
This table summarizes IGLV2-23 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 3. The strongest signals are observed in COAD for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for IGLV2-23. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. IGLV2-23 shows lower tumor expression in COAD, BRCA, LIHC and READ and higher tumor expression in LUAD and KIRC. The COAD box plot shows higher IGLV2-23 RNA expression in normal versus tumor tissue (log2 FC = −4.542, t-test p < 0.001).
This table shows molecular features associated with IGLV2-23 in patient tissues and cancer cell lines. In patient samples, IGLV2-23 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
