Q-omics provides the consensus-scored MS4A10 profile across patient tissues and cancer cell-line models. MS4A10 expression is associated with patient survival in 17 of 34 cancer types, with the highest sampling consensus in BLCA. Among the 18 cancer types available for tumor–normal comparison, MS4A10 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, MS4A10 RNA expression shows 6,206 significant pathway-activity associations, with the highest sampling consensus in UCEC. Together, these results highlight BLCA, HNSC, and UCEC as cancer lineages where MS4A10 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 MS4A10 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes MS4A10 survival associations across molecular data types. MS4A10 RNA expression shows survival associations in the most cancer types (17), followed by mutation status (4). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible MS4A10 RNA expression–survival associations across cancer types. High MS4A10 expression shows unfavorable associations in BLCA, SKCM, TGCT, ACC and DLBC, but favorable associations in STAD. The BLCA 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 BLCA as the clearest survival context for MS4A10 RNA expression.
This table summarizes MS4A10 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 8. The strongest signals are observed in HNSC for RNA.
This table ranks reproducible tumor–normal expression differences for MS4A10. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. MS4A10 shows lower tumor expression in COAD, KIRP, KICH, KIRC and READ and higher tumor expression in HNSC. The HNSC box plot shows higher MS4A10 RNA expression in tumor versus normal tissue (log2 FC = +0.023, t-test p = .002).
This table shows molecular features associated with MS4A10 in patient tissues and cancer cell lines. In patient samples, MS4A10 shows the broadest associations at the RNA and protein expression levels, with UCEC recurring as the lineage with the largest associated feature set. In cancer cell lines, MS4A10 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 LARGE_INTESTINE and SOFT_TISSUE.
