Q-omics provides the consensus-scored SPRY3 profile across patient tissues and cancer cell-line models. SPRY3 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, SPRY3 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, SPRY3 RNA expression shows 20,801 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight UVM, and LIHC as cancer lineages where SPRY3 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 SPRY3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SPRY3 survival associations across molecular data types. SPRY3 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (13) and mass-spec protein abundance (3). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SPRY3 RNA expression–survival associations across cancer types. High SPRY3 expression shows unfavorable associations in UVM and BRCA, but favorable associations in KIRC, MESO, PAAD and UCEC. The UVM Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .003). Together, the overview and detailed table identify UVM as the clearest survival context for SPRY3 RNA expression.
This table summarizes SPRY3 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, while mass-spec protein shows differences in 2. The strongest signals are observed in THCA for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for SPRY3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SPRY3 shows lower tumor expression in THCA, BRCA and LUSC and higher tumor expression in LIHC, UCEC and CHOL. The LIHC box plot shows higher SPRY3 RNA expression in tumor versus normal tissue (log2 FC = +0.252, t-test p < 0.001).
This table shows molecular features associated with SPRY3 in patient tissues and cancer cell lines. In patient samples, SPRY3 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, SPRY3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in PANCREAS, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Leukemia.
