Q-omics provides the consensus-scored SPOPL profile across patient tissues and cancer cell-line models. SPOPL expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, SPOPL is differentially expressed in 12, with the highest sampling consensus in HNSC. Additionally, SPOPL RNA expression shows 20,866 significant gene co-expression associations, with the highest sampling consensus in ACC. Together, these results highlight KIRC, HNSC, and ACC as cancer lineages where SPOPL 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 SPOPL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPOPL survival associations across molecular data types. SPOPL RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPOPL RNA expression–survival associations across cancer types. High SPOPL expression shows unfavorable associations in ACC, UVM, HNSC and UCEC, but favorable associations in KIRC and SKCM. 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 SPOPL RNA expression.
This table summarizes SPOPL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 12. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for SPOPL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPOPL shows lower tumor expression in THCA and higher tumor expression in HNSC, BRCA, LIHC, KIRC and BLCA. The HNSC box plot shows higher SPOPL RNA expression in tumor versus normal tissue (log2 FC = +1.059, t-test p < 0.001).
This table shows molecular features associated with SPOPL in patient tissues and cancer cell lines. In patient samples, SPOPL shows the broadest associations at the RNA and protein expression levels, with ACC recurring as the lineage with the largest associated feature set. In cancer cell lines, SPOPL 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 PANCREAS and UPPER_AERODIGESTIVE_TRACT.
