outer dense fiber of sperm tails 2 likeGenealiases: []
Q-omics provides the consensus-scored ODF2L profile across patient tissues and cancer cell-line models. ODF2L expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, ODF2L is differentially expressed in 10, with the highest sampling consensus in HNSC. Additionally, ODF2L RNA expression shows 20,466 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KIRC, HNSC, and UVM as cancer lineages where ODF2L 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 ODF2L — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes ODF2L survival associations across molecular data types. ODF2L RNA expression shows survival associations in the most cancer types (22), 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 ODF2L RNA expression–survival associations across cancer types. High ODF2L expression shows unfavorable associations in KIRC, LGG, ACC, SARC and KICH, but favorable associations in BLCA. The KIRC Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .002). Together, the overview and detailed table identify KIRC as the clearest survival context for ODF2L RNA expression.
This table summarizes ODF2L tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10, 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 ODF2L. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. ODF2L shows lower tumor expression in KICH and higher tumor expression in HNSC, BLCA, CHOL, STAD and COAD. The HNSC box plot shows higher ODF2L RNA expression in tumor versus normal tissue (log2 FC = +0.655, t-test p < 0.001).
This table shows molecular features associated with ODF2L in patient tissues and cancer cell lines. In patient samples, ODF2L shows the broadest associations at the RNA and protein expression levels, with UVM recurring as the lineage with the largest associated feature set. In cancer cell lines, ODF2L RNA and mutation anchors are most strongly linked to RNA-expression features, especially in URINARY_TRACT, while CRISPR and shRNA rows add functional-dependency signals in BLOOD_Lymphoma and BLOOD_Leukemia.
