SERTA domain containing 2Genealiases: Sei-2 · TRIP-Br2 · TRIPBR2
Q-omics provides the consensus-scored SERTAD2 profile across patient tissues and cancer cell-line models. SERTAD2 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, SERTAD2 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, SERTAD2 RNA expression shows 20,323 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight KIRC, and KIRP as cancer lineages where SERTAD2 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 SERTAD2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERTAD2 survival associations across molecular data types. SERTAD2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERTAD2 RNA expression–survival associations across cancer types. High SERTAD2 expression shows unfavorable associations in ACC, LGG, UCEC, MESO and PAAD, but favorable associations in KIRC. 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 SERTAD2 RNA expression.
This table summarizes SERTAD2 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for SERTAD2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERTAD2 shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, KIRP, LIHC and LUSC. The KIRC box plot shows higher SERTAD2 RNA expression in tumor versus normal tissue (log2 FC = +0.989, t-test p < 0.001).
This table shows molecular features associated with SERTAD2 in patient tissues and cancer cell lines. In patient samples, SERTAD2 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, SERTAD2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BLOOD_Lymphoma, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BONE.
