triggering receptor expressed on myeloid cells like 4Genealiases: TLT-4 · TLT4
Q-omics provides the consensus-scored TREML4 profile across patient tissues and cancer cell-line models. TREML4 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TREML4 is differentially expressed in 8, with the highest sampling consensus in HNSC. Additionally, TREML4 RNA expression shows 14,162 significant protein co-abundance associations, with the highest sampling consensus in GBM. Together, these results highlight KIRC, HNSC, and GBM as cancer lineages where TREML4 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 TREML4 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TREML4 survival associations across molecular data types. TREML4 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TREML4 RNA expression–survival associations across cancer types. High TREML4 expression shows unfavorable associations in KIRC, LIHC, STAD, BLCA and PRAD, but favorable associations in SKCM. The KIRC 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 KIRC as the clearest survival context for TREML4 RNA expression.
This table summarizes TREML4 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 KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for TREML4. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TREML4 shows higher tumor expression in HNSC, KIRC, KIRP, LIHC, BRCA and STAD. The HNSC box plot shows higher TREML4 RNA expression in tumor versus normal tissue (log2 FC = +0.134, t-test p < 0.001).
This table shows molecular features associated with TREML4 in patient tissues and cancer cell lines. In patient samples, TREML4 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, TREML4 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 BREAST and SOFT_TISSUE.
