Pancreatic Cancer Exposome Profile to Aid Early Detection and Inform Prevention Strategies.
Ontology highlight
ABSTRACT:
SUBMITTER: Monroy-Iglesias MJ
PROVIDER: S-EPMC8069449 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:My research seeks to aid in developing approaches to prevent breast cancer. This research evolved from our early empirical studies for discovering natural compounds with anticancer activities, coupled with clinical evaluation to a genetics-driven approach to prevention. This centers on the use of comparative genomics to discover risk-modifying alleles that could help define population and individual risk and also serve as potential prevention drugable targets to mitigate risk. Here, we initially fine map mammary cancer loci in a rat carcinogenesis model and then evaluate their human homologs in breast cancer case-control association studies. This approach has yielded promising results, including the finding that the compound rat QTL Mcs5a's human homologous region was associated with breast cancer risk. These and related findings have the potential to yield advancements both in translation-prevention research and in basic molecular genetics.
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Project description:Endometrial cancer is the most common female genital tract cancer in developed countries. We systematically reviewed the current health-economic evidence on early detection and prevention strategies for endometrial cancer based on a search in relevant databases (Medline/Embase/Cochrane Library/CRD/EconLit). Study characteristics and results including life-years gained (LYG), quality-adjusted life-years (QALY) gained, and incremental cost-effectiveness ratios (ICERs) were summarized in standardized evidence tables. Economic results were transformed into 2019 euros using standard conversion methods (GDP-PPP, CPI). Seven studies were included, evaluating (1) screening for endometrial cancer in women with different risk profiles, (2) risk-reducing interventions for women at increased or high risk for endometrial cancer, and (3) genetic testing for germline mutations followed by risk-reducing interventions for diagnosed mutation carriers. Compared to no screening, screening with transvaginal sonography (TVS), biomarker CA-125, and endometrial biopsy yielded an ICER of 43,600 EUR/LYG (95,800 EUR/QALY) in women with Lynch syndrome at high endometrial cancer risk. For women considering prophylactic surgery, surgery was more effective and less costly than screening. In obese women, prevention using Levonorgestrel as of age 30 for five years had an ICER of 72,000 EUR/LYG; the ICER for using oral contraceptives for five years as of age 50 was 450,000 EUR/LYG. Genetic testing for mutations in women at increased risk for carrying a mutation followed by risk-reducing surgery yielded ICERs below 40,000 EUR/QALY. Based on study results, preventive surgery in mutation carriers and genetic testing in women at increased risk for mutations are cost-effective. Except for high-risk women, screening using TVS and endometrial biopsy is not cost-effective and may lead to overtreatment. Model-based analyses indicate that future biomarker screening in women at increased risk for cancer may be cost-effective, dependent on high test accuracy and moderate test costs. Future research should reveal risk-adapted early detection and prevention strategies for endometrial cancer.
| S-EPMC7408795 | biostudies-literature
Project description:PurposeTo inform recommendations by the Canadian Task Force on Preventive Health Care on screening in primary care for the prevention and early detection of cervical cancer by systematically reviewing evidence of (a) effectiveness; (b) test accuracy; (c) individuals' values and preferences; and (d) strategies aimed at improving screening rates.MethodsDe novo reviews will be conducted to evaluate effectiveness and to assess values and preferences. For test accuracy and strategies to improve screening rates, we will integrate studies from existing systematic reviews with search updates to the present. Two Cochrane reviews will provide evidence of adverse pregnancy outcomes from the conservative management of cervical intraepithelial neoplasia. We will search Medline, Embase, and Cochrane Central (except for individuals' values and preferences, where Medline, Scopus, and EconLit will be searched) via peer-reviewed search strategies and the reference lists of included studies and reviews. We will search ClinicalTrials.gov and the World Health Organization International Clinical Trials Registry Platform for ongoing trials. Two reviewers will screen potentially eligible studies and agree on those to include. Data will be extracted by one reviewer with verification by another. Two reviewers will independently assess risk of bias and reach consensus. Where possible and suitable, we will pool studies via meta-analysis. We will compare accuracy data per outcome and per comparison using the Rutter and Gatsonis hierarchical summary receiver operating characteristic model and report relative sensitivities and specificities. Findings on values and preferences will be synthesized using a narrative synthesis approach and thematic analysis, depending on study designs. Two reviewers will appraise the certainty of evidence for all outcomes using GRADE (Grading of Recommendations Assessment, Development and Evaluation) and come to consensus.DiscussionThe publication of guidance on screening in primary care for the prevention and early detection of cervical cancer by the Task Force in 2013 focused on cytology. Since 2013, new studies using human papillomavirus tests for cervical screening have been published that will improve our understanding of screening in primary care settings. This review will inform updated recommendations based on currently available studies and address key evidence gaps noted in our previous review.
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| S-EPMC3079322 | biostudies-literature
Project description:Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC.
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Project description:Pancreatic adenocarcinoma (PDAC) is associated with poor clinical outcomes and incomplete responses to conventional therapy. Therefore, there is an unmet clinical need to better understand the predisposing factors for pancreatic cancer in hopes of providing early screening to high-risk patients. While select risk factors such as age, race, and family history, or predisposing syndromes are unavoidable, there are several new and established risk factors that allow for intervention, namely by counseling patients to make the appropriate lifestyle modifications. Here, we discuss the best-studied risk factors for PDAC such as tobacco use and chronic pancreatitis, as well as newly emerging risk factors including select nutritional deficits, bacterial infections, and psychosocial factors. As several of these risk factors appear to be additive or synergistic, by understanding their relationships and offering coordinated, multidisciplinary care to high-risk patients, it may be possible to reduce pancreatic cancer incidence and improve clinical outcomes through early detection.
| S-EPMC7313672 | biostudies-literature
Project description:Pancreatic cancer is the fourth leading cause of cancer death. Lack of early detection technology for pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 2.0 Array was used to discover altered gene expression in saliva supernatant. The Human Oral Microbe Identification Microarray (HOMIM) was used to investigate microflora shift in saliva pellet. Biomarkers selected from both studies were subjected to an independent clinical validation using a cohort of 30 early pancreatic cancer, 30 chronic pancreatitis and 30 healthy matched-control saliva samples. Two panels of salivary biomarkers, including eleven mRNA biomarkers and two microbial biomarkers were discovered and validated for pancreatic cancer detection. The logistic regression model with the combination of three mRNA biomarkers (ACRV1, DMXL2 and DPM1) yielded a ROC-plot AUC value of 0.974 (95% CI, 0.896 to 0.997; P < 0.0001) with 93.3% sensitivity and 90% specificity in distinguishing pancreatic cancer patients from healthy subjects. The logistic regression model with the combination of two bacterial biomarkers (Neisseria elongata and Streptococcus mitis) yielded a ROC-plot AUC value of 0.895 (95% CI, 0.784 to 0.961; P < 0.0001) with 96.4% sensitivity and 82.1% specificity in distinguishing pancreatic cancer patients from healthy subjects. Importantly, the logistic regression model with the combination of four biomarkers (mRNA biomarkers, ACRV1, DMXL2 and DPM1; bacterial biomarker, S. mitis) could differentiate pancreatic cancer patients from all non-cancer subjects (chronic pancreatitis and healthy control), yielding a ROC-plot AUC value of 0.949 (95% CI, 0.877 to 0.985; P < 0.0001) with 92.9% sensitivity and 85.5% specificity. This study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. Keywords: Salivary biomarker, pancreatic cancer, early detection, salivary transcriptome, salivary microflora This study, which was approved by the UCLA Institutional Review Board, started sample collection in February 2006 and ended in April 2008. It had a discovery and verification phase, followed by an independent validation phase. All patients with clinically diagnosed early or locally advanced pancreatic cancer, chronic pancreatitis and matched healthy control were recruited from the UCLA Medical Center. The controls were matched for gender, age, ethnicity and smoking history. We chose early and locally advanced pancreatic cancers because they were considered early stage diseases. All patients were recently diagnosed with primary disease, and had not received any prior treatment in the form of chemotherapy, radiotherapy, surgery, or alternative remedies. No subjects had a history of prior malignancy, immunodeficiency, autoimmune disorders, hepatitis, or HIV infection. Written informed consent was obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were collected and processed as previously described. The saliva bank of pancreatic disease at the UCLA Dental Research Institute has collected 283 saliva samples since 2006. Of these, 114 samples, from 42 pancreatic cancer patients, 30 chronic pancreatitis patients and 42 healthy control subjects, met the following eligibility criteria: the disease subjects’ samples were obtained immediately after primary diagnosis from patients without evidence of metastasis; the saliva sample was free of blood (Table 1 in accompanying manuscript). Of the 114 samples, 12 pancreatic cancer samples and 12 healthy control samples were chosen for the discovery and verification phase. The transcriptomic approach profiled the saliva supernatant samples from 12 pancreatic cancer patients and 12 healthy control subjects using the Affymetrix Human Genome U133 Plus 2.0 Array platform.
| S-ECPF-GEOD-14245 | biostudies-other
Project description:Pancreatic cancer is the fourth leading cause of cancer death. Lack of early detection technology for pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 2.0 Array was used to discover altered gene expression in saliva supernatant. The Human Oral Microbe Identification Microarray (HOMIM) was used to investigate microflora shift in saliva pellet. Biomarkers selected from both studies were subjected to an independent clinical validation using a cohort of 30 early pancreatic cancer, 30 chronic pancreatitis and 30 healthy matched-control saliva samples. Two panels of salivary biomarkers, including eleven mRNA biomarkers and two microbial biomarkers were discovered and validated for pancreatic cancer detection. The logistic regression model with the combination of three mRNA biomarkers (ACRV1, DMXL2 and DPM1) yielded a ROC-plot AUC value of 0.974 (95% CI, 0.896 to 0.997; P < 0.0001) with 93.3% sensitivity and 90% specificity in distinguishing pancreatic cancer patients from healthy subjects. The logistic regression model with the combination of two bacterial biomarkers (Neisseria elongata and Streptococcus mitis) yielded a ROC-plot AUC value of 0.895 (95% CI, 0.784 to 0.961; P < 0.0001) with 96.4% sensitivity and 82.1% specificity in distinguishing pancreatic cancer patients from healthy subjects. Importantly, the logistic regression model with the combination of four biomarkers (mRNA biomarkers, ACRV1, DMXL2 and DPM1; bacterial biomarker, S. mitis) could differentiate pancreatic cancer patients from all non-cancer subjects (chronic pancreatitis and healthy control), yielding a ROC-plot AUC value of 0.949 (95% CI, 0.877 to 0.985; P < 0.0001) with 92.9% sensitivity and 85.5% specificity. This study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer. Keywords: Salivary biomarker, pancreatic cancer, early detection, salivary transcriptome, salivary microflora This study, which was approved by the UCLA Institutional Review Board, started sample collection in February 2006 and ended in April 2008. It had a discovery and verification phase, followed by an independent validation phase. All patients with clinically diagnosed early or locally advanced pancreatic cancer, chronic pancreatitis and matched healthy control were recruited from the UCLA Medical Center. The controls were matched for gender, age, ethnicity and smoking history. We chose early and locally advanced pancreatic cancers because they were considered early stage diseases. All patients were recently diagnosed with primary disease, and had not received any prior treatment in the form of chemotherapy, radiotherapy, surgery, or alternative remedies. No subjects had a history of prior malignancy, immunodeficiency, autoimmune disorders, hepatitis, or HIV infection. Written informed consent was obtained from all patients who agreed to serve as saliva donors. Unstimulated saliva samples were collected and processed as previously described. The saliva bank of pancreatic disease at the UCLA Dental Research Institute has collected 283 saliva samples since 2006. Of these, 114 samples, from 42 pancreatic cancer patients, 30 chronic pancreatitis patients and 42 healthy control subjects, met the following eligibility criteria: the disease subjectsâ?? samples were obtained immediately after primary diagnosis from patients without evidence of metastasis; the saliva sample was free of blood (Table 1 in accompanying manuscript). Of the 114 samples, 12 pancreatic cancer samples and 12 healthy control samples were chosen for the discovery and verification phase. The transcriptomic approach profiled the saliva supernatant samples from 12 pancreatic cancer patients and 12 healthy control subjects using the Affymetrix Human Genome U133 Plus 2.0 Array platform.
2008-12-30 | E-GEOD-14245 | biostudies-arrayexpress