Q-omics provides the consensus-scored SH3BGRL profile across patient tissues and cancer cell-line models. SH3BGRL 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, SH3BGRL is differentially expressed in 13, with the highest sampling consensus in BLCA. Additionally, SH3BGRL protein abundance shows 32,865 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight UVM, BLCA, and LSCC as cancer lineages where SH3BGRL 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 SH3BGRL — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SH3BGRL survival associations across molecular data types. SH3BGRL RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (11). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SH3BGRL RNA expression–survival associations across cancer types. High SH3BGRL expression shows unfavorable associations in UVM and SCLC, but favorable associations in KIRC, SKCM, MESO and HNSC. The UVM 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 UVM as the clearest survival context for SH3BGRL RNA expression.
This table summarizes SH3BGRL tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 13, while mass-spec protein shows differences in 10. The strongest signals are observed in BLCA for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SH3BGRL. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SH3BGRL shows lower tumor expression in BLCA, COAD, LUAD, LUSC, THCA and UCEC. The BLCA box plot shows higher SH3BGRL RNA expression in normal versus tumor tissue (log2 FC = −2.400, t-test p < 0.001).
This table shows molecular features associated with SH3BGRL in patient tissues and cancer cell lines. In patient samples, SH3BGRL shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, SH3BGRL 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 LUNG_SCLC and SOFT_TISSUE.
