Q-omics provides the consensus-scored ABRAXAS1 profile across patient tissues and cancer cell-line models. ABRAXAS1 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ABRAXAS1 is differentially expressed in 11, with the highest sampling consensus in UCEC. Additionally, ABRAXAS1 RNA expression shows 20,441 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight KIRC, UCEC, and THYM as cancer lineages where ABRAXAS1 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 ABRAXAS1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ABRAXAS1 survival associations across molecular data types. ABRAXAS1 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible ABRAXAS1 RNA expression–survival associations across cancer types. High ABRAXAS1 expression shows unfavorable associations in LIHC and STAD, but favorable associations in KIRC, BRCA, UCS and SKCM. The KIRC 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 KIRC as the clearest survival context for ABRAXAS1 RNA expression.
This table summarizes ABRAXAS1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 3. The strongest signals are observed in UCEC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for ABRAXAS1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ABRAXAS1 shows lower tumor expression in UCEC, BLCA, LUSC, THCA and BRCA and higher tumor expression in LIHC. The UCEC box plot shows higher ABRAXAS1 RNA expression in normal versus tumor tissue (log2 FC = −1.366, t-test p < 0.001).
This table shows molecular features associated with ABRAXAS1 in patient tissues and cancer cell lines. In patient samples, ABRAXAS1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, ABRAXAS1 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 UPPER_AERODIGESTIVE_TRACT.
