Q-omics provides the consensus-scored SERTM2 profile across patient tissues and cancer cell-line models. SERTM2 expression is associated with patient survival in 27 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SERTM2 is differentially expressed in 13, with the highest sampling consensus in KICH. Additionally, SERTM2 RNA expression shows 13,682 significant gene co-expression associations, with the highest sampling consensus in TGCT. Together, these results highlight KIRP, KICH, and TGCT as cancer lineages where SERTM2 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 SERTM2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERTM2 survival associations across molecular data types. SERTM2 RNA expression shows survival associations in the most cancer types (27). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERTM2 RNA expression–survival associations across cancer types. High SERTM2 expression shows unfavorable associations in KIRP, LUSC, BLCA and DLBC, but favorable associations in MESO and CESC. The KIRP 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 KIRP as the clearest survival context for SERTM2 RNA expression.
This table summarizes SERTM2 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 BRCA for RNA.
This table ranks reproducible tumor–normal expression differences for SERTM2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERTM2 shows lower tumor expression in UCEC, BRCA, LIHC, CHOL and LUSC and higher tumor expression in KICH. The KICH box plot shows higher SERTM2 RNA expression in tumor versus normal tissue (log2 FC = +2.395, t-test p < 0.001).
This table shows molecular features associated with SERTM2 in patient tissues and cancer cell lines. In patient samples, SERTM2 shows the broadest associations at the RNA and protein expression levels, with TGCT recurring as the lineage with the largest associated feature set. In cancer cell lines, SERTM2 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 BLOOD_Leukemia.
