Q-omics provides the consensus-scored SERINC3 profile across patient tissues and cancer cell-line models. SERINC3 expression is associated with patient survival in 28 of 34 cancer types, with the highest sampling consensus in KIRP. Among the 18 cancer types available for tumor–normal comparison, SERINC3 is differentially expressed in 16, with the highest sampling consensus in HNSC. Additionally, SERINC3 protein abundance shows 24,849 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRP, HNSC, and GBM as cancer lineages where SERINC3 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 SERINC3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SERINC3 survival associations across molecular data types. SERINC3 RNA expression shows survival associations in the most cancer types (28), followed by mutation status (6) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SERINC3 RNA expression–survival associations across cancer types. High SERINC3 expression shows unfavorable associations in KIRP, UVM, HNSC, CESC and LUSC, but favorable associations in KIRC. The KIRP Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRP as the clearest survival context for SERINC3 RNA expression.
This table summarizes SERINC3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 7. The strongest signals are observed in HNSC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SERINC3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SERINC3 shows lower tumor expression in UCEC and LUAD and higher tumor expression in HNSC, KIRC, COAD and LIHC. The HNSC box plot shows higher SERINC3 RNA expression in tumor versus normal tissue (log2 FC = +1.134, t-test p < 0.001).
This table shows molecular features associated with SERINC3 in patient tissues and cancer cell lines. In patient samples, SERINC3 shows the broadest associations at the RNA and protein expression levels, with GBM recurring as the lineage with the largest associated feature set. In cancer cell lines, SERINC3 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 BREAST and BLOOD_Leukemia.
