Q-omics provides the consensus-scored AGBL4-IT1 profile across patient tissues and cancer cell-line models. AGBL4-IT1 expression is associated with patient survival in 13 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, AGBL4-IT1 is differentially expressed in 2, with the highest sampling consensus in KICH. Additionally, AGBL4-IT1 RNA expression shows 6,827 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KICH, and LSCC as cancer lineages where AGBL4-IT1 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 AGBL4-IT1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AGBL4-IT1 survival associations across molecular data types. AGBL4-IT1 RNA expression shows survival associations in the most cancer types (13). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AGBL4-IT1 RNA expression–survival associations across cancer types. High AGBL4-IT1 expression shows unfavorable associations in HNSC, ACC, ESCA, LGG and THYM, but favorable associations in PAAD. The HNSC 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 HNSC as the clearest survival context for AGBL4-IT1 RNA expression.
This table summarizes AGBL4-IT1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 2. The strongest signals are observed in KICH for RNA.
This table ranks reproducible tumor–normal expression differences for AGBL4-IT1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AGBL4-IT1 shows lower tumor expression in KICH and higher tumor expression in BRCA. The KICH box plot shows higher AGBL4-IT1 RNA expression in normal versus tumor tissue (log2 FC = −0.038, t-test p = .009).
This table shows molecular features associated with AGBL4-IT1 in patient tissues and cancer cell lines. In patient samples, AGBL4-IT1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set.
