Hypertension, type 2 diabetes, obesity, and p53 mutations negatively correlate with metastatic colorectal cancer patients’ survival
We studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and mutations in metastatic colorectal cancer (CRC) patients. T2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was cal...
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| Published in | Frontiers in medicine Vol. 10; p. 1091634 |
|---|---|
| Main Authors | , , , , , , , , , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
Frontiers Media S.A
23.01.2023
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| Subjects | |
| Online Access | Get full text |
| ISSN | 2296-858X 2296-858X |
| DOI | 10.3389/fmed.2023.1091634 |
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| Abstract | We studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and
mutations in metastatic colorectal cancer (CRC) patients.
T2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was calculated and classified according to the WHO criteria. TruSigt™Oncology 500 kit was applied to construct the genomic libraries for Next Generation Sequencing (NGS) analysis. The Illumina NovaSeq 6000 technological platform and the Illumina TruSight Oncology 500 bioinformatics pipeline were applied to analyze results. Overall survival (OS) was calculated through Kaplan-Meier curves. Univariate and multivariate analyses were performed to assess the relationships between clinical and/or molecular covariates. Associations between HT, T2D, BMI, p53, and clinical variables were evaluated by the χ2 test.
< 0.05 were considered statistically significant.
Two-hundred-forty-four patients were enrolled. One-hundred-twenty (49.2%), 110 (45.1%), and 50 (20.5%) patients were affected by overweight, HT, and T2D, respectively. DC (disease control) was achieved more frequently in patients without T2D (83.1%) compared to the diabetic ones (16.9%) (
= 0.0246). DC,
mutational status, T2D, BMI, and concomitant presence of T2D, BMI, and HT associated with survival (
< 0.05). At multivariate analysis, age (≥65 vs. <65 years), response to first-line chemotherapy (DC vs. no DC), and concomitant presence of T2D, BMI, and HT (HR: 4.56; 95% CI: 2.40-8.67;
= 0.0217) emerged as independent prognostic variables.
was mutated in 31/53 analyzed cases (60.4%). The most frequent gene variants were p.Arg175His and p.Cys135Tyr. High BMI (>25 kg/m
) associated with occurrence of
mutations (
< 0.0001).
mutated patients presented a worse prognosis compared to the wild-type ones (HR: 3.21; 95% CI: 1.43-7.23;
= 0.0047).
Diabetic, hypertensive and overweight metastatic CRC patients are a negative prognostic subgroup deserving specific therapeutic strategies.
mutations associate with prognosis and BMI unrevealing complex and unexplored connections between metabolism and cancer occurrence. |
|---|---|
| AbstractList | We studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and p53 mutations in metastatic colorectal cancer (CRC) patients.IntroductionWe studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and p53 mutations in metastatic colorectal cancer (CRC) patients.T2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was calculated and classified according to the WHO criteria. TruSigt™Oncology 500 kit was applied to construct the genomic libraries for Next Generation Sequencing (NGS) analysis. The Illumina NovaSeq 6000 technological platform and the Illumina TruSight Oncology 500 bioinformatics pipeline were applied to analyze results. Overall survival (OS) was calculated through Kaplan-Meier curves. Univariate and multivariate analyses were performed to assess the relationships between clinical and/or molecular covariates. Associations between HT, T2D, BMI, p53, and clinical variables were evaluated by the χ2 test. P < 0.05 were considered statistically significant.Patients and methodsT2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was calculated and classified according to the WHO criteria. TruSigt™Oncology 500 kit was applied to construct the genomic libraries for Next Generation Sequencing (NGS) analysis. The Illumina NovaSeq 6000 technological platform and the Illumina TruSight Oncology 500 bioinformatics pipeline were applied to analyze results. Overall survival (OS) was calculated through Kaplan-Meier curves. Univariate and multivariate analyses were performed to assess the relationships between clinical and/or molecular covariates. Associations between HT, T2D, BMI, p53, and clinical variables were evaluated by the χ2 test. P < 0.05 were considered statistically significant.Two-hundred-forty-four patients were enrolled. One-hundred-twenty (49.2%), 110 (45.1%), and 50 (20.5%) patients were affected by overweight, HT, and T2D, respectively. DC (disease control) was achieved more frequently in patients without T2D (83.1%) compared to the diabetic ones (16.9%) (P = 0.0246). DC, KRAS mutational status, T2D, BMI, and concomitant presence of T2D, BMI, and HT associated with survival (P < 0.05). At multivariate analysis, age (≥65 vs. <65 years), response to first-line chemotherapy (DC vs. no DC), and concomitant presence of T2D, BMI, and HT (HR: 4.56; 95% CI: 2.40-8.67; P = 0.0217) emerged as independent prognostic variables. P53 was mutated in 31/53 analyzed cases (60.4%). The most frequent gene variants were p.Arg175His and p.Cys135Tyr. High BMI (>25 kg/m2) associated with occurrence of p53 mutations (P < 0.0001). P53 mutated patients presented a worse prognosis compared to the wild-type ones (HR: 3.21; 95% CI: 1.43-7.23; P = 0.0047).ResultsTwo-hundred-forty-four patients were enrolled. One-hundred-twenty (49.2%), 110 (45.1%), and 50 (20.5%) patients were affected by overweight, HT, and T2D, respectively. DC (disease control) was achieved more frequently in patients without T2D (83.1%) compared to the diabetic ones (16.9%) (P = 0.0246). DC, KRAS mutational status, T2D, BMI, and concomitant presence of T2D, BMI, and HT associated with survival (P < 0.05). At multivariate analysis, age (≥65 vs. <65 years), response to first-line chemotherapy (DC vs. no DC), and concomitant presence of T2D, BMI, and HT (HR: 4.56; 95% CI: 2.40-8.67; P = 0.0217) emerged as independent prognostic variables. P53 was mutated in 31/53 analyzed cases (60.4%). The most frequent gene variants were p.Arg175His and p.Cys135Tyr. High BMI (>25 kg/m2) associated with occurrence of p53 mutations (P < 0.0001). P53 mutated patients presented a worse prognosis compared to the wild-type ones (HR: 3.21; 95% CI: 1.43-7.23; P = 0.0047).Diabetic, hypertensive and overweight metastatic CRC patients are a negative prognostic subgroup deserving specific therapeutic strategies. P53 mutations associate with prognosis and BMI unrevealing complex and unexplored connections between metabolism and cancer occurrence.ConclusionDiabetic, hypertensive and overweight metastatic CRC patients are a negative prognostic subgroup deserving specific therapeutic strategies. P53 mutations associate with prognosis and BMI unrevealing complex and unexplored connections between metabolism and cancer occurrence. IntroductionWe studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and p53 mutations in metastatic colorectal cancer (CRC) patients.Patients and methodsT2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was calculated and classified according to the WHO criteria. TruSigt™Oncology 500 kit was applied to construct the genomic libraries for Next Generation Sequencing (NGS) analysis. The Illumina NovaSeq 6000 technological platform and the Illumina TruSight Oncology 500 bioinformatics pipeline were applied to analyze results. Overall survival (OS) was calculated through Kaplan-Meier curves. Univariate and multivariate analyses were performed to assess the relationships between clinical and/or molecular covariates. Associations between HT, T2D, BMI, p53, and clinical variables were evaluated by the χ2 test. P < 0.05 were considered statistically significant.ResultsTwo-hundred-forty-four patients were enrolled. One-hundred-twenty (49.2%), 110 (45.1%), and 50 (20.5%) patients were affected by overweight, HT, and T2D, respectively. DC (disease control) was achieved more frequently in patients without T2D (83.1%) compared to the diabetic ones (16.9%) (P = 0.0246). DC, KRAS mutational status, T2D, BMI, and concomitant presence of T2D, BMI, and HT associated with survival (P < 0.05). At multivariate analysis, age (≥65 vs. <65 years), response to first-line chemotherapy (DC vs. no DC), and concomitant presence of T2D, BMI, and HT (HR: 4.56; 95% CI: 2.40–8.67; P = 0.0217) emerged as independent prognostic variables. P53 was mutated in 31/53 analyzed cases (60.4%). The most frequent gene variants were p.Arg175His and p.Cys135Tyr. High BMI (>25 kg/m2) associated with occurrence of p53 mutations (P < 0.0001). P53 mutated patients presented a worse prognosis compared to the wild-type ones (HR: 3.21; 95% CI: 1.43–7.23; P = 0.0047).ConclusionDiabetic, hypertensive and overweight metastatic CRC patients are a negative prognostic subgroup deserving specific therapeutic strategies. P53 mutations associate with prognosis and BMI unrevealing complex and unexplored connections between metabolism and cancer occurrence. We studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and mutations in metastatic colorectal cancer (CRC) patients. T2D was diagnosed according to the ADA criteria. HT was classified according to the ACC/AHA guidelines. BMI (body-mass index) was calculated and classified according to the WHO criteria. TruSigt™Oncology 500 kit was applied to construct the genomic libraries for Next Generation Sequencing (NGS) analysis. The Illumina NovaSeq 6000 technological platform and the Illumina TruSight Oncology 500 bioinformatics pipeline were applied to analyze results. Overall survival (OS) was calculated through Kaplan-Meier curves. Univariate and multivariate analyses were performed to assess the relationships between clinical and/or molecular covariates. Associations between HT, T2D, BMI, p53, and clinical variables were evaluated by the χ2 test. < 0.05 were considered statistically significant. Two-hundred-forty-four patients were enrolled. One-hundred-twenty (49.2%), 110 (45.1%), and 50 (20.5%) patients were affected by overweight, HT, and T2D, respectively. DC (disease control) was achieved more frequently in patients without T2D (83.1%) compared to the diabetic ones (16.9%) ( = 0.0246). DC, mutational status, T2D, BMI, and concomitant presence of T2D, BMI, and HT associated with survival ( < 0.05). At multivariate analysis, age (≥65 vs. <65 years), response to first-line chemotherapy (DC vs. no DC), and concomitant presence of T2D, BMI, and HT (HR: 4.56; 95% CI: 2.40-8.67; = 0.0217) emerged as independent prognostic variables. was mutated in 31/53 analyzed cases (60.4%). The most frequent gene variants were p.Arg175His and p.Cys135Tyr. High BMI (>25 kg/m ) associated with occurrence of mutations ( < 0.0001). mutated patients presented a worse prognosis compared to the wild-type ones (HR: 3.21; 95% CI: 1.43-7.23; = 0.0047). Diabetic, hypertensive and overweight metastatic CRC patients are a negative prognostic subgroup deserving specific therapeutic strategies. mutations associate with prognosis and BMI unrevealing complex and unexplored connections between metabolism and cancer occurrence. |
| Author | Zappavigna, Silvia Petrillo, Nadia Nasti, Guglielmo Caraglia, Michele Ottaiano, Alessandro Granata, Vincenza Cascella, Marco Savarese, Giovanni Scrima, Marianna Capuozzo, Maurizio Circelli, Luisa Casillo, Marika Perri, Francesco Santorsola, Mariachiara Sabbatino, Francesco Lombardi, Angela Gualillo, Oreste Ianniello, Monica |
| AuthorAffiliation | 5 Department of Precision Medicine, University of Campania “L. Vanvitelli” , Naples , Italy 2 AMES, Centro Polidiagnostico Strumentale srl , Naples , Italy 4 Coordinamento Farmaceutico , Ercolano , Italy 3 Oncology Unit, Department of Medicine, Surgery and Dentistry, University of Salerno , Salerno , Italy 8 IDIS, Instituto de Investigación Sanitaria de Santiago de Compostela, Grupo C027 NEIRID , Santiago de Compostela , Spain 7 Servizo Galego de Saude and Instituto de Investigación Sanitaria de Santiago, Neuroendocrine Interactions in Rheumatology and Inflammatory Diseases, Research Laboratory 9, Santiago University Clinical Hospital , Santiago de Compostela , Spain 1 Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale” , Naples , Italy 6 Laboratory of Molecular and Precision Oncology, Biogem Scarl, Institute of Genetic Research , Ariano Irpino , Italy |
| AuthorAffiliation_xml | – name: 1 Istituto Nazionale Tumori di Napoli, IRCCS “G. Pascale” , Naples , Italy – name: 7 Servizo Galego de Saude and Instituto de Investigación Sanitaria de Santiago, Neuroendocrine Interactions in Rheumatology and Inflammatory Diseases, Research Laboratory 9, Santiago University Clinical Hospital , Santiago de Compostela , Spain – name: 6 Laboratory of Molecular and Precision Oncology, Biogem Scarl, Institute of Genetic Research , Ariano Irpino , Italy – name: 8 IDIS, Instituto de Investigación Sanitaria de Santiago de Compostela, Grupo C027 NEIRID , Santiago de Compostela , Spain – name: 4 Coordinamento Farmaceutico , Ercolano , Italy – name: 5 Department of Precision Medicine, University of Campania “L. Vanvitelli” , Naples , Italy – name: 2 AMES, Centro Polidiagnostico Strumentale srl , Naples , Italy – name: 3 Oncology Unit, Department of Medicine, Surgery and Dentistry, University of Salerno , Salerno , Italy |
| Author_xml | – sequence: 1 givenname: Alessandro surname: Ottaiano fullname: Ottaiano, Alessandro – sequence: 2 givenname: Mariachiara surname: Santorsola fullname: Santorsola, Mariachiara – sequence: 3 givenname: Luisa surname: Circelli fullname: Circelli, Luisa – sequence: 4 givenname: Francesco surname: Perri fullname: Perri, Francesco – sequence: 5 givenname: Marco surname: Cascella fullname: Cascella, Marco – sequence: 6 givenname: Francesco surname: Sabbatino fullname: Sabbatino, Francesco – sequence: 7 givenname: Maurizio surname: Capuozzo fullname: Capuozzo, Maurizio – sequence: 8 givenname: Vincenza surname: Granata fullname: Granata, Vincenza – sequence: 9 givenname: Silvia surname: Zappavigna fullname: Zappavigna, Silvia – sequence: 10 givenname: Angela surname: Lombardi fullname: Lombardi, Angela – sequence: 11 givenname: Marianna surname: Scrima fullname: Scrima, Marianna – sequence: 12 givenname: Nadia surname: Petrillo fullname: Petrillo, Nadia – sequence: 13 givenname: Monica surname: Ianniello fullname: Ianniello, Monica – sequence: 14 givenname: Marika surname: Casillo fullname: Casillo, Marika – sequence: 15 givenname: Oreste surname: Gualillo fullname: Gualillo, Oreste – sequence: 16 givenname: Guglielmo surname: Nasti fullname: Nasti, Guglielmo – sequence: 17 givenname: Michele surname: Caraglia fullname: Caraglia, Michele – sequence: 18 givenname: Giovanni surname: Savarese fullname: Savarese, Giovanni |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36756182$$D View this record in MEDLINE/PubMed |
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| Copyright | Copyright © 2023 Ottaiano, Santorsola, Circelli, Perri, Cascella, Sabbatino, Capuozzo, Granata, Zappavigna, Lombardi, Scrima, Petrillo, Ianniello, Casillo, Gualillo, Nasti, Caraglia and Savarese. Copyright © 2023 Ottaiano, Santorsola, Circelli, Perri, Cascella, Sabbatino, Capuozzo, Granata, Zappavigna, Lombardi, Scrima, Petrillo, Ianniello, Casillo, Gualillo, Nasti, Caraglia and Savarese. 2023 Ottaiano, Santorsola, Circelli, Perri, Cascella, Sabbatino, Capuozzo, Granata, Zappavigna, Lombardi, Scrima, Petrillo, Ianniello, Casillo, Gualillo, Nasti, Caraglia and Savarese |
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| Keywords | type 2 diabetes metastatic colorectal cancer NGS hypertension prognosis obesity p53 |
| Language | English |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 These authors share last authorship Edited by: Heping Yang, Cedars–Sinai Medical Center, United States Reviewed by: Ferdinando Carlo Sasso, University of Campania Luigi Vanvitelli, Italy; Ting Liu, Central South University, China This article was submitted to Precision Medicine, a section of the journal Frontiers in Medicine These authors share first authorship |
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mutations in metastatic colorectal cancer (CRC)... We studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and p53 mutations in metastatic colorectal cancer... IntroductionWe studied the predictive and prognostic influences of hypertension (HT), type 2 diabetes (T2D), weight, and p53 mutations in metastatic colorectal... |
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| Title | Hypertension, type 2 diabetes, obesity, and p53 mutations negatively correlate with metastatic colorectal cancer patients’ survival |
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