Q-omics provides the consensus-scored SPATS2L profile across patient tissues and cancer cell-line models. SPATS2L expression is associated with patient survival in 21 of 34 cancer types, with the highest sampling consensus in ACC. Among the 18 cancer types available for tumor–normal comparison, SPATS2L is differentially expressed in 17, with the highest sampling consensus in KIRC. Additionally, SPATS2L protein abundance shows 21,590 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight ACC, KIRC, and GBM as cancer lineages where SPATS2L 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 SPATS2L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPATS2L survival associations across molecular data types. SPATS2L RNA expression shows survival associations in the most cancer types (21), followed by mutation status (6) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPATS2L RNA expression–survival associations across cancer types. High SPATS2L expression shows unfavorable associations in ACC, LIHC, KICH and LGG, but favorable associations in KIRC and UCS. 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 SPATS2L RNA expression.
This table summarizes SPATS2L 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 7. The strongest signals are observed in KIRC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SPATS2L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPATS2L shows lower tumor expression in KICH and higher tumor expression in KIRC, HNSC, THCA, KIRP and LUAD. The KIRC box plot shows higher SPATS2L RNA expression in tumor versus normal tissue (log2 FC = +1.228, t-test p < 0.001).
This table shows molecular features associated with SPATS2L in patient tissues and cancer cell lines. In patient samples, SPATS2L 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, SPATS2L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in KIDNEY, while CRISPR and shRNA rows add functional-dependency signals in OVARY and BONE.
