Q-omics provides the consensus-scored SH2B1 profile across patient tissues and cancer cell-line models. SH2B1 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, SH2B1 is differentially expressed in 9, with the highest sampling consensus in LIHC. Additionally, SH2B1 RNA expression shows 19,427 significant gene co-expression associations, with the highest sampling consensus in THYM. Together, these results highlight HNSC, LIHC, and THYM as cancer lineages where SH2B1 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 SH2B1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes SH2B1 survival associations across molecular data types. SH2B1 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (3) 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 SH2B1 RNA expression–survival associations across cancer types. High SH2B1 expression shows unfavorable associations in LIHC and PRAD, but favorable associations in HNSC, BLCA, UVM and SKCM. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p = .001). Together, the overview and detailed table identify HNSC as the clearest survival context for SH2B1 RNA expression.
This table summarizes SH2B1 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 7. The strongest signals are observed in THCA for RNA and LUAD for protein.
This table ranks reproducible tumor–normal expression differences for SH2B1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. SH2B1 shows lower tumor expression in THCA, UCEC and BRCA and higher tumor expression in LIHC, KIRP and CHOL. The LIHC box plot shows higher SH2B1 RNA expression in tumor versus normal tissue (log2 FC = +1.450, t-test p < 0.001).
This table shows molecular features associated with SH2B1 in patient tissues and cancer cell lines. In patient samples, SH2B1 shows the broadest associations at the RNA and protein expression levels, with THYM recurring as the lineage with the largest associated feature set. In cancer cell lines, SH2B1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in OESOPHAGUS, while CRISPR and shRNA rows add functional-dependency signals in BONE and BLOOD_Leukemia.
