Q-omics provides the consensus-scored SH3PXD2B profile across patient tissues and cancer cell-line models. SH3PXD2B expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in MESO. Among the 18 cancer types available for tumor–normal comparison, SH3PXD2B is differentially expressed in 13, with the highest sampling consensus in HNSC. Additionally, SH3PXD2B protein abundance shows 22,438 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight MESO, HNSC, and GBM as cancer lineages where SH3PXD2B 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 SH3PXD2B — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SH3PXD2B survival associations across molecular data types. SH3PXD2B RNA expression shows survival associations in the most cancer types (23), followed by mutation status (4) and mass-spec protein abundance (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible SH3PXD2B RNA expression–survival associations across cancer types. High SH3PXD2B expression shows unfavorable associations in MESO, UVM, BLCA, LIHC, OV and LGG. The MESO 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 MESO as the clearest survival context for SH3PXD2B RNA expression.
This table summarizes SH3PXD2B 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 6. The strongest signals are observed in HNSC for RNA and CCRCC for protein.
This table ranks reproducible tumor–normal expression differences for SH3PXD2B. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SH3PXD2B shows higher tumor expression in HNSC, KIRC, COAD, KIRP, LIHC and LUAD. The HNSC box plot shows higher SH3PXD2B RNA expression in tumor versus normal tissue (log2 FC = +1.486, t-test p < 0.001).
This table shows molecular features associated with SH3PXD2B in patient tissues and cancer cell lines. In patient samples, SH3PXD2B 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, SH3PXD2B RNA and mutation anchors are most strongly linked to RNA-expression features, especially in BREAST, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BONE.
