Q-omics provides the consensus-scored AXDND1 profile across patient tissues and cancer cell-line models. AXDND1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in LIHC. Among the 18 cancer types available for tumor–normal comparison, AXDND1 is differentially expressed in 13, with the highest sampling consensus in KIRC. Additionally, AXDND1 RNA expression shows 17,425 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight LIHC, KIRC, and UVM as cancer lineages where AXDND1 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 AXDND1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes AXDND1 survival associations across molecular data types. AXDND1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible AXDND1 RNA expression–survival associations across cancer types. High AXDND1 expression shows unfavorable associations in LIHC, KIRC, ACC and UCEC, but favorable associations in READ and SCLC. The LIHC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p < 0.001). Together, the overview and detailed table identify LIHC as the clearest survival context for AXDND1 RNA expression.
This table summarizes AXDND1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for AXDND1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. AXDND1 shows lower tumor expression in KIRC, KICH, KIRP, COAD and THCA and higher tumor expression in HNSC. The KIRC box plot shows higher AXDND1 RNA expression in normal versus tumor tissue (log2 FC = −0.461, t-test p < 0.001).
This table shows molecular features associated with AXDND1 in patient tissues and cancer cell lines. In patient samples, AXDND1 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, AXDND1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in OVARY and LARGE_INTESTINE.
