Q-omics provides the consensus-scored SH3GLB2 profile across patient tissues and cancer cell-line models. SH3GLB2 expression is associated with patient survival in 26 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, SH3GLB2 is differentially expressed in 9, with the highest sampling consensus in KIRC. Additionally, SH3GLB2 protein abundance shows 26,551 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight BLCA, KIRC, and GBM as cancer lineages where SH3GLB2 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 SH3GLB2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SH3GLB2 survival associations across molecular data types. SH3GLB2 RNA expression shows survival associations in the most cancer types (26), followed by mutation status (5) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SH3GLB2 RNA expression–survival associations across cancer types. High SH3GLB2 expression shows unfavorable associations in ACC and KIRC, but favorable associations in BLCA, SCLC, CHOL and UVM. The BLCA 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 BLCA as the clearest survival context for SH3GLB2 RNA expression.
This table summarizes SH3GLB2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 9, while mass-spec protein shows differences in 6. The strongest signals are observed in KIRC for RNA and COAD for protein.
This table ranks reproducible tumor–normal expression differences for SH3GLB2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SH3GLB2 shows lower tumor expression in KIRC and LUAD and higher tumor expression in LIHC, COAD, THCA and CHOL. The KIRC box plot shows higher SH3GLB2 RNA expression in normal versus tumor tissue (log2 FC = −0.877, t-test p < 0.001).
This table shows molecular features associated with SH3GLB2 in patient tissues and cancer cell lines. In patient samples, SH3GLB2 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, SH3GLB2 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 BLOOD_Leukemia.
