Q-omics provides the consensus-scored TELO2 profile across patient tissues and cancer cell-line models. TELO2 expression is associated with patient survival in 23 of 34 cancer types, with the highest sampling consensus in KIRC. Among the 18 cancer types available for tumor–normal comparison, TELO2 is differentially expressed in 16, with the highest sampling consensus in COAD. Additionally, TELO2 protein abundance shows 30,759 significant protein co-abundance associations, with the highest sampling consensus in PDAC. Together, these results highlight KIRC, COAD, and PDAC as cancer lineages where TELO2 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 TELO2 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TELO2 survival associations across molecular data types. TELO2 RNA expression shows survival associations in the most cancer types (23), followed by mutation status (6) and mass-spec protein abundance (12). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TELO2 RNA expression–survival associations across cancer types. High TELO2 expression shows unfavorable associations in KIRC, ACC, LGG, MESO and LAML, but favorable associations in HNSC. 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 TELO2 RNA expression.
This table summarizes TELO2 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 16, while mass-spec protein shows differences in 13. The strongest signals are observed in HNSC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TELO2. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TELO2 shows higher tumor expression in COAD, HNSC, KIRP, KIRC, LIHC and STAD. The COAD box plot shows higher TELO2 RNA expression in tumor versus normal tissue (log2 FC = +1.400, t-test p < 0.001).
This table shows molecular features associated with TELO2 in patient tissues and cancer cell lines. In patient samples, TELO2 shows the broadest associations at the RNA and protein expression levels, with PDAC recurring as the lineage with the largest associated feature set. In cancer cell lines, TELO2 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in LIVER, while CRISPR and shRNA rows add functional-dependency signals in UPPER_AERODIGESTIVE_TRACT and BLOOD_Lymphoma.
