Serum tumour associated trypsin inhibitor, as a biomarker for survival in renal cell carcinoma

Background: We studied the role of tumor-associated trypsin inhibitor (TATI) in serum and in tumor tissues among human papillomavirus (HPV)-positive and HPV-negative OPSCC patients. Materials and methods: The study cohort included 90 OPSCC patients treated at the Helsinki University Hospital (HUS), Helsinki, Finland, in 2012–2016. TATI serum concentrations (S-TATIs) were determined by an immunofluorometric assay. Immunostaining was used to assess tissue expression. HPV status was determined with a combination of p16 immunohistochemistry and HPV DNA PCR genotyping. The survival endpoints were overall survival (OS) and disease-specific survival (DSS). Results: A significant correlation was found between S-TATI positivity and poor OS (p < 0.001) and DSS (p = 0.04) in all patients. In HPV-negative cases, S-TATI positivity was linked to poor OS (p = 0.01) and DSS (p = 0.05). In HPV-positive disease, S-TATI positivity correlated with poor DSS (p = 0.01). S-TATI positivity was strongly associated with HPV negativity. TATI serum was negatively linked to a lower cancer stage. TATI expression in peritumoral lymphocytes was associated with favorable OS (p < 0.025) and HPV positivity. TATI expression in tumor and in peritumoral lymphocytes correlated with lower cancer stages. Conclusion: Our results suggest that S-TATI positivity may be a biomarker of poor prognosis in both HPV-positive and HPV-negative OPSCC.

Section: Discussionsupporting

confidence: 90%

Tumor-Associated Trypsin Inhibitor (TATI) as a Biomarker of Poor Prognosis in Oropharyngeal Squamous Cell Carcinoma Irrespective of HPV Status

Sjöblom

Stenman

Hagström

et al. 2021

Cancers

Self Cite

“…Numerous meta-analyses (e.g., [7][8][9]) have tried to identify the gene biomarkers whose altered sequence and/or expression may serve to diagnose the KC form, and whose restoration may help to cure it. Among others, the 27.0 release (29 October 2020) of the Genomic Data Commons Data Portal [10] includes 59,612 mutations detected in 20,426 genes sequenced from 3295 (2110 male and 1185 female) KC cases.…”

Section: Introductionmentioning

confidence: 99%

Genomic Fabric Remodeling in Metastatic Clear Cell Renal Cell Carcinoma (ccRCC): A New Paradigm and Proposal for a Personalized Gene Therapy Approach

Mgbemena

et al. 2020

Cancers

Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma samples were analyzed from the genomic fabric paradigm (GFP) perspective to identify the best targets for gene therapy. GFP considers the transcriptome as a multi-dimensional mathematical object constrained by a dynamic set of expression controls and correlations among genes. Every gene in the chest wall metastasis, two distinct cancer nodules, and the surrounding normal tissue of the right kidney was characterized by three independent measures: average expression level, relative expression variation, and expression correlation with each other gene. The analyses determined the cancer-induced regulation, control, and remodeling of the chemokine and vascular endothelial growth factor (VEGF) signaling, apoptosis, basal transcription factors, cell cycle, oxidative phosphorylation, renal cell carcinoma, and RNA polymerase pathways. Interestingly, the three cancer regions exhibited different transcriptomic organization, suggesting that the gene therapy should not be personalized only for every patient but also for each major cancer nodule. The gene hierarchy was established on the basis of gene commanding height, and the gene master regulators DAPK3,TASOR, FAM27C and ALG13 were identified in each profiled region. We delineated the molecular mechanisms by which TASOR overexpression and ALG13 silencing would selectively affect the cancer cells with little consequences for the normal cells.

“…Numerous meta-analyses (e.g. : [7][8][9]) tried to identify the gene biomarkers whose altered sequence or/and expression may serve to diagnose the kidney cancer form, and whose restoration may help to cure it. Among others, the 26.0 release (September 08, 2020) of the Genomic Data Commons Data Portal [10] 2.67%) were mutated in more than 2% of cases.…”

Section: Introductionmentioning

confidence: 99%

Genomic Fabric Remodeling in Metastatic Clear Cell Renal Cell Carcinoma (ccRCC): A New Paradigm and Proposal for a Personalized Gene Therapy Approach

Mgbemena

et al. 2020

Preprint

Published transcriptomic data from surgically removed metastatic clear cell renal cell carcinoma (ccRCC) samples were re-analyzed from the Genomic Fabric Perspective that considers the transcriptome a multi-dimensional mathematical object, constrained by a dynamic set of expression correlations among genes. Every gene in the chest wall metastasis (MET), two primary tumors (PTA, PTB) and the surrounding normal tissue (NOR) of the right kidney was characterized by three independent measures: average expression level (AVE), relative expression variation (REV) and expression correlation (COR) with each other gene. AVE was used to determine the regulation of the genomic fabrics of ccRCC, apoptosis, chemokine and VEGF signaling pathways. REV quantified the alteration of the transcripts’ abundances control, while COR determined the remodeling of the transcriptomic networks of chemokine signaling and oxidative phosphorylation genes. The gene hierarchy was established in based on Gene Commanding Height and the Gene Master Regulators (GMR) TASOR (PTA), FAM27C (PTB) and ALG13 (MET) and DAPK3 (NOR) were identified in each profiled region. We predict that TASOR overexpression would block transcription in PTA but not in PTB, while slightly stimulating it in NOR. Silencing of ALG3 would slow-down the cell-cycle in all three cancer regions with practically no effect in NOR.