Q-omics provides the consensus-scored SGO2 profile across patient tissues and cancer cell-line models. SGO2 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SGO2 is differentially expressed in 17, with the highest sampling consensus in HNSC. Additionally, SGO2 RNA expression shows 21,512 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, HNSC, and GBM as cancer lineages where SGO2 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 SGO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SGO2 survival associations across molecular data types. SGO2 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SGO2 RNA expression–survival associations across cancer types. High SGO2 expression shows unfavorable associations in ACC, KIRP, LIHC, MESO, KICH and LGG. 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 SGO2 RNA expression.
This table summarizes SGO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 17, while mass-spec protein shows differences in 1. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for SGO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SGO2 shows higher tumor expression in HNSC, BLCA, LUAD, KIRP, KIRC and LIHC. The HNSC box plot shows higher SGO2 RNA expression in tumor versus normal tissue (log2 FC = +1.410, t-test p < 0.001).
This table shows molecular features associated with SGO2 in patient tissues and cancer cell lines. In patient samples, SGO2 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, SGO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in LIVER and BLOOD_Leukemia.
