Q-omics provides the consensus-scored TESPA1 profile across patient tissues and cancer cell-line models. TESPA1 expression is associated with patient survival in 24 of 34 cancer types, with the highest sampling consensus in HNSC. Among the 18 cancer types available for tumor–normal comparison, TESPA1 is differentially expressed in 10, with the highest sampling consensus in KIRC. Additionally, TESPA1 RNA expression shows 23,569 significant protein co-abundance associations, with the highest sampling consensus in LSCC. Together, these results highlight HNSC, KIRC, and LSCC as cancer lineages where TESPA1 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 TESPA1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TESPA1 survival associations across molecular data types. TESPA1 RNA expression shows survival associations in the most cancer types (24), followed by mutation status (6) and mass-spec protein abundance (1). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TESPA1 RNA expression–survival associations across cancer types. High TESPA1 expression shows favorable associations in HNSC, SKCM, BRCA, SCLC, CESC and LUAD. The HNSC Kaplan–Meier curve shows clear separation, with the low-expression group declining faster, consistent with the favorable association (log-rank p < 0.001). Together, the overview and detailed table identify HNSC as the clearest survival context for TESPA1 RNA expression.
This table summarizes TESPA1 tumor–normal expression differences by data type. RNA shows broader differences across cancer types, with a lineage consensus of 10. The strongest signals are observed in KIRC for RNA.
This table ranks reproducible tumor–normal expression differences for TESPA1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TESPA1 shows lower tumor expression in COAD, LUSC, LUAD, UCEC and BLCA and higher tumor expression in KIRC. The KIRC box plot shows higher TESPA1 RNA expression in tumor versus normal tissue (log2 FC = +1.282, t-test p < 0.001).
This table shows molecular features associated with TESPA1 in patient tissues and cancer cell lines. In patient samples, TESPA1 shows the broadest associations at the RNA and protein expression levels, with LSCC recurring as the lineage with the largest associated feature set. In cancer cell lines, TESPA1 RNA and mutation anchors are most strongly linked to RNA-expression features, especially in CNS, while CRISPR and shRNA rows add functional-dependency signals in URINARY_TRACT and BLOOD_Leukemia.
