Q-omics provides the consensus-scored EXTL3 profile across patient tissues and cancer cell-line models. EXTL3 expression is associated with patient survival in 25 of 34 cancer types, with the highest sampling consensus in UVM. Among the 18 cancer types available for tumor–normal comparison, EXTL3 is differentially expressed in 9, with the highest sampling consensus in HNSC. Additionally, EXTL3 RNA expression shows 18,894 significant gene co-expression associations, with the highest sampling consensus in KIRP. Together, these results highlight UVM, HNSC, and KIRP as cancer lineages where EXTL3 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 EXTL3 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes EXTL3 survival associations across molecular data types. EXTL3 RNA expression shows survival associations in the most cancer types (25), followed by mutation status (3) and mass-spec protein abundance (6). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible EXTL3 RNA expression–survival associations across cancer types. High EXTL3 expression shows unfavorable associations in LIHC, LGG and BLCA, but favorable associations in UVM, KIRC and UCEC. The UVM 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 UVM as the clearest survival context for EXTL3 RNA expression.
This table summarizes EXTL3 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 3. The strongest signals are observed in HNSC for RNA and LSCC for protein.
This table ranks reproducible tumor–normal expression differences for EXTL3. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. EXTL3 shows lower tumor expression in THCA and higher tumor expression in HNSC, LIHC, COAD, CHOL and LUSC. The HNSC box plot shows higher EXTL3 RNA expression in tumor versus normal tissue (log2 FC = +1.517, t-test p < 0.001).
This table shows molecular features associated with EXTL3 in patient tissues and cancer cell lines. In patient samples, EXTL3 shows the broadest associations at the RNA and protein expression levels, with KIRP recurring as the lineage with the largest associated feature set. In cancer cell lines, EXTL3 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in UPPER_AERODIGESTIVE_TRACT, while CRISPR and shRNA rows add functional-dependency signals in KIDNEY and BLOOD_Leukemia.
