Q-omics provides the consensus-scored TPCN1 profile across patient tissues and cancer cell-line models. TPCN1 expression is associated with patient survival in 22 of 34 cancer types, with the highest sampling consensus in KICH. Among the 18 cancer types available for tumor–normal comparison, TPCN1 is differentially expressed in 10, with the highest sampling consensus in LIHC. Additionally, TPCN1 RNA expression shows 19,291 significant gene co-expression associations, with the highest sampling consensus in UVM. Together, these results highlight KICH, LIHC, and UVM as cancer lineages where TPCN1 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 TPCN1 — synthetic lethality, tumor antigen, and pembrolizumab response.
This table summarizes TPCN1 survival associations across molecular data types. TPCN1 RNA expression shows survival associations in the most cancer types (22), followed by mutation status (8) and mass-spec protein abundance (5). The rightmost column indicates the cancer type with the highest sampling consensus for each molecular layer.
This table ranks reproducible TPCN1 RNA expression–survival associations across cancer types. High TPCN1 expression shows unfavorable associations in KICH, LIHC, LUAD, ESCA and OV, but favorable associations in SCLC. The KICH Kaplan–Meier curve shows clear separation, with the high-expression group declining faster, consistent with the unfavorable association (log-rank p = .001). Together, the overview and detailed table identify KICH as the clearest survival context for TPCN1 RNA expression.
This table summarizes TPCN1 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 5. The strongest signals are observed in LIHC for RNA and HNSC for protein.
This table ranks reproducible tumor–normal expression differences for TPCN1. A negative fold-change indicates higher expression in normal tissue than in tumor tissue. TPCN1 shows lower tumor expression in HNSC, BLCA, UCEC, LUSC and BRCA and higher tumor expression in LIHC. The LIHC box plot shows higher TPCN1 RNA expression in tumor versus normal tissue (log2 FC = +1.486, t-test p < 0.001).
This table shows molecular features associated with TPCN1 in patient tissues and cancer cell lines. In patient samples, TPCN1 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, TPCN1 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 PANCREAS and BLOOD_Lymphoma.
