Q-omics provides the consensus-scored SGPP2 profile across patient tissues and cancer cell-line models. SGPP2 expression is associated with patient survival in 18 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SGPP2 is differentially expressed in 11, with the highest sampling consensus in THCA. Additionally, SGPP2 RNA expression shows 19,168 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, THCA, and UVM as cancer lineages where SGPP2 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 SGPP2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SGPP2 survival associations across molecular data types. SGPP2 RNA expression shows survival associations in the most cancer types (18), followed by mutation status (3) 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 SGPP2 RNA expression–survival associations across cancer types. High SGPP2 expression shows unfavorable associations in THCA and UVM, but favorable associations in KIRC, ACC, MESO and HNSC. 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 SGPP2 RNA expression.
This table summarizes SGPP2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 11, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SGPP2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SGPP2 shows lower tumor expression in THCA, KICH, KIRC and COAD and higher tumor expression in LUAD and CHOL. The THCA box plot shows higher SGPP2 RNA expression in normal versus tumor tissue (log2 FC = −2.204, t-test p < 0.001).
This table shows molecular features associated with SGPP2 in patient tissues and cancer cell lines. In patient samples, SGPP2 shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, SGPP2 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 CNS and LARGE_INTESTINE.
