Q-omics provides the consensus-scored HNRNPUL2-BSCL2 profile across patient tissues and cancer cell-line models. HNRNPUL2-BSCL2 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, HNRNPUL2-BSCL2 is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, HNRNPUL2-BSCL2 RNA expression shows 18,503 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight ACC, and HNSC as cancer lineages where HNRNPUL2-BSCL2 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 HNRNPUL2-BSCL2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes HNRNPUL2-BSCL2 survival associations across molecular data types. HNRNPUL2-BSCL2 RNA expression shows survival associations in the most cancer types (22). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible HNRNPUL2-BSCL2 RNA expression–survival associations across cancer types. High HNRNPUL2-BSCL2 expression shows unfavorable associations in ACC, CESC, LUAD and PRAD, but favorable associations in KIRC and ESCA. The ACC 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 ACC as the clearest survival context for HNRNPUL2-BSCL2 RNA expression.
This table summarizes HNRNPUL2-BSCL2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for HNRNPUL2-BSCL2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. HNRNPUL2-BSCL2 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, LUSC, KIRC and CHOL. The HNSC box plot shows higher HNRNPUL2-BSCL2 RNA expression in tumor versus normal tissue (log2 FC = +0.329, t-test p < 0.001).
This table shows molecular features associated with HNRNPUL2-BSCL2 in patient tissues and cancer cell lines. In patient samples, HNRNPUL2-BSCL2 shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, HNRNPUL2-BSCL2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Myeloma, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Leukemia.
