Autoantibodies in Cancer Patients and in Persons with a Higher Risk of Cancer Development

2000 ◽  
pp. 159-173 ◽  
Author(s):  
Karsten Conrad
Keyword(s):  
Cancer Patients ◽  
Cancer Development ◽  
Risk Of Cancer

scholarly journals Use of cannabis in urological cancer patients: A review to evaluate risk for cancer development, therapeutic use, and symptom management

2021 ◽  
Vol 15 (12) ◽  
Author(s):  
Shipra Taneja ◽  
Jen Hoogenes ◽  
Marissa Slaven ◽  
Anil Kapoor
Keyword(s):  
Cancer Patients ◽  
Full Text ◽  
Symptom Management ◽  
Evaluation Studies ◽  
Cannabis Use ◽  
Cancer Development ◽  
Therapeutic Management ◽  
Therapeutic Effects ◽  
Urological Cancer ◽  
Risk Of Cancer

Introduction: Recent recreational legalization of cannabis has resulted in an increased interest in the therapeutic effects of cannabis use in cancer patients, with reports of its use in symptom management and as a risk factor for cancer development. The objective of this review was to evaluate the literature on the association of cannabis use with the risk of cancer development, symptom management, and therapeutic management in the urological cancer (UC) patient population. Methods: A systematic search of databases and trial registries for papers published to March 2020 on cannabis, symptom and therapeutic management, and cancer development in UC patients was conducted. After screening of full-text articles, data were extracted for evaluation. Studies were eligible if they were in the clinical setting, included ≥5 UC patients, reported use of any cannabis variant, and were written in English. Results: The search retrieved 2456 abstracts, of which 48 full-text articles were reviewed and 21 included in the review. Low-level evidence suggested a correlation between cannabis use and risk for development of testicular cancer. Some support existed for using cannabis for cancer pain and chemotherapy-induced nausea. There was inadequate evidence to substantiate cannabis use as a therapeutic agent for management of UCs. A lack of high-level evidence and robust methodology of the studies limited evaluation of the findings. Conclusions: Given the paucity of data on cannabis use for therapeutic purposes in UC, large, prospective trials with adequate followup times to observe the effect of cannabis use on UCs are warranted to improve the evidence base.

scholarly journals Exercise May Affect Metabolism in Cancer-Related Cognitive Impairment

Metabolites ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 377
Author(s):  
Muhammad Shahid ◽  
Jayoung Kim
Keyword(s):  
Physical Activity ◽  
Cognitive Impairment ◽  
Cancer Patients ◽  
Cancer Progression ◽  
Cancer Metabolism ◽  
Cancer Development ◽  
Direct Effects ◽  
Functional Changes ◽  
Risk Of Cancer ◽  
The Brain

Cancer-related cognitive impairment (CRCI) is a significant comorbidity for cancer patients and survivors. Physical activity (PA) has been found to be a strong gene modulator that can induce structural and functional changes in the brain. PA and exercise reduce the risk of cancer development and progression and has been shown to help in overcoming post-treatment syndromes. Exercise plays a role in controlling cancer progression through direct effects on cancer metabolism. In this review, we highlight several priorities for improving studies on CRCI in patients and its underlying potential metabolic mechanisms.

Biomarkers for Early Detection of Colitis-associated Colorectal Cancer - Current Concepts, Future Trends

2020 ◽  
Vol 22 (1) ◽  
pp. 137-145
Author(s):  
Tomasz Mackiewicz ◽  
Aleksander Sowa ◽  
Jakub Fichna
Keyword(s):  
Colorectal Cancer ◽  
Early Detection ◽  
Cancer Development ◽  
Sporadic Colorectal Cancer ◽  
Future Trends ◽  
Significant Progress ◽  
Current Standard ◽  
Risk Of Cancer ◽  
Histological Testing ◽  
Made In

: Colitis-associated colorectal cancer (CAC) remains a critical complication of ulcerative colitis (UC) with mortality of approximately 15%, which makes early CAC diagnosis crucial. The current standard of surveillance, with repetitive colonoscopies and histological testing of biopsied mucosa samples is burdensome and expensive, and therefore less invasive methods and reliable biomarkers are needed. Significant progress has been made thanks to continuous extensive research in this field, however no clinically relevant biomarker has been established so far. This review of the current literature presents the genetic and molecular differences between CAC and sporadic colorectal cancer and covers progress made in the early detection of CAC carcinogenesis. It focuses on biomarkers under development, which can be easily tested in samples of body fluids or breath and, once made clinically available, will help to differentiate between progressors (UC patients who will develop dysplasia) from non-progressors and enable early intervention to decrease the risk of cancer development.

Long‐term risk of cancer development among anti‐Th/To antibody‐positive systemic sclerosis patients: comment on the article by Mecoli et al.

2021 ◽  
Author(s):  
Yuta Yamashita ◽  
Yasuhiko Yamano ◽  
Yoshinao Muro ◽  
Haruka Koizumi ◽  
Takuya Takeichi ◽  
...  
Keyword(s):  
Systemic Sclerosis ◽  
Cancer Development ◽  
Risk Of Cancer

scholarly journals Physical Comorbidities and Depression in Recent and Long-Term Adult Cancer Survivors: NHANES 2007–2018

Cancers ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 3368
Author(s):  
Dafina Petrova ◽  
Andrés Catena ◽  
Miguel Rodríguez-Barranco ◽  
Daniel Redondo-Sánchez ◽  
Eloísa Bayo-Lozano ◽  
...  
Keyword(s):  
Cancer Survivors ◽  
Cancer Patients ◽  
Cancer Diagnosis ◽  
Depression Symptoms ◽  
Depression Risk ◽  
Adult Cancer Survivors ◽  
Before And After ◽  
Nationally Representative ◽  
Risk Of Cancer

Many adult cancer patients present one or more physical comorbidities. Besides interfering with treatment and prognosis, physical comorbidities could also increase the already heightened psychological risk of cancer patients. To test this possibility, we investigated the relationship between physical comorbidities with depression symptoms in a sample of 2073 adult cancer survivors drawn from the nationally representative National Health and Nutrition Examination Survey (NHANES) (2007–2018) in the U.S. Based on information regarding 16 chronic conditions, the number of comorbidities diagnosed before and after the cancer diagnosis was calculated. The number of comorbidities present at the moment of cancer diagnosis was significantly related to depression risk in recent but not in long-term survivors. Recent survivors who suffered multimorbidity had 3.48 (95% CI 1.26–9.55) times the odds of reporting significant depressive symptoms up to 5 years after the cancer diagnosis. The effect of comorbidities was strongest among survivors of breast cancer. The comorbidities with strongest influence on depression risk were stroke, kidney disease, hypertension, obesity, asthma, and arthritis. Information about comorbidities is usually readily available and could be useful in streamlining depression screening or targeting prevention efforts in cancer patients and survivors. A multidimensional model of the interaction between cancer and other physical comorbidities on mental health is proposed.

scholarly journals Polish Medical Students’ Knowledge Regarding Human Papillomavirus’s Ways of Transmission, Risk of Cancer Development and Vaccination, and Their Intention to Recommend Vaccination

Vaccines ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 776
Author(s):  
Tomasz Milecki ◽  
Maciej Michalak ◽  
Jakub Milecki ◽  
Michał Michalak ◽  
Radosław Kadziszewski ◽  
...  
Keyword(s):  
Medical Students ◽  
Hpv Vaccine ◽  
Hpv Vaccination ◽  
Hpv Infection ◽  
Early Years ◽  
Vaccine Uptake ◽  
Transmission Risk ◽  
Cancer Development ◽  
General Level ◽  
Risk Of Cancer

Introduction: Human papillomavirus (HPV) is associated with six types of cancer in men and women. A vaccine against HPV, preferably administered before initial sexual intercourse, has been proven to be highly effective in preventing these cancers. An effective healthcare provider recommendation has significant influence on HPV vaccine uptake; therefore, it is critical that medical students receive comprehensive training in this area. Aim: The aim of the study was to assess the knowledge of medical students regarding Human Papillomavirus’s (HPV) ways of transmission, risk of cancer development, and vaccination against HPV. This study also investigated factors among medical students that would affect their intention to recommend HPV vaccination to others. Materials and Methods: The study was conducted among 1061 (678 women and 383 men) medical students who filled in our questionnaire. The medical students were divided into two subgroups: (1) pre-clinical medical students (MS pre-clinical; first-to third-year students; n = 683) and (2) clinical medical students (MS clinical; fourth-to six-year students; n = 378). Results: A total259 (24.41%) of the 1061 medical students were vaccinated against HPV. We found a significant improvement in the general level of knowledge in the later years of education (4–6) compared to the early years of education (1–3). However, it was demonstrated that, despite medical education advancements, there are still significant gaps of knowledge about the relationship between HPV infection and cancers other than cervical cancer, as well as in relation to the routes by which HPV is transmitted. Medical students’ intentions to recommend HPV vaccine to others were related to their own HPV-related knowledge and their own vaccination status. Conclusion: Medical students have gaps of knowledge regarding particular issues and aspects of HPV. It is necessary to further educate medical students in the field of prevention and in the treatment of lesions caused by HPV infection. Medical students’ intention to recommend the HPV vaccine can be improved by including them and members of their families in the HPV vaccination program.

Down-regulation of miR-219-5p increase the risk of cancer-related mortality in patients with prostate cancer

2021 ◽  
pp. postgradmedj-2021-139981
Author(s):  
Shimin Tang ◽  
Hao Jiang ◽  
Zhijun Cao ◽  
Qiang Zhou
Keyword(s):  
Prostate Cancer ◽  
Prediction Model ◽  
Cancer Patients ◽  
Cox Regression ◽  
Cox Model ◽  
Risk Of Death ◽  
Kaplan Meier ◽  
Risk Of Progression ◽  
Patient Prognosis ◽  
Risk Of Cancer

IntroductionProstate cancer is a common malignancy in men that is difficult to treat and carries a high risk of death. miR-219-5p is expressed in reduced amounts in many malignancies. However, the prognostic value of miR-219-5p for patients with prostate cancer remains unclear.MethodsWe retrospectively analysed data from 213 prostate cancer patients from 10 June 2012 to 9 May 2015. Overall survival was assessed by Kaplan-Meier analysis and Cox regression models. Besides, a prediction model was constructed, and calibration curves evaluated the model’s accuracy.ResultsOf the 213 patients, a total of 72 (33.8%) died and the median survival time was 60.0 months. We found by multifactorial analysis that miR-219-5p deficiency increased the risk of death by nearly fourfold (HR: 3.86, 95% CI): 2.01 to 7.44, p<0.001) and the risk of progression by twofold (HR: 2.79, 95% CI: 1.68 to 4.64, p<0.001). To quantify each covariate’s weight on prognosis, we screened variables by cox model to construct a predictive model. The Nomogram showed excellent accuracy in estimating death’s risk, with a corrected C-index of 0.778.ConclusionsmiR-219-5p can be used as a biomarker to predict death risk in prostate cancer patients. The mortality risk prediction model constructed based on miR-219-5p has good consistency and validity in assessing patient prognosis.

TGFBR1 Polymorphism and Risk of Breast Cancer in Iranian Women

2015 ◽  
Vol 30 (4) ◽  
pp. 414-417 ◽  
Author(s):  
Elahe Kamali ◽  
Simin Hemmati ◽  
Forouzan Safari ◽  
Manoochehr Tavassoli
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Transforming Growth Factor Beta ◽  
Lower Risk ◽  
Transforming Growth Factor ◽  
Age At Onset ◽  
Epidemiological Studies ◽  
Breast Cancer Patients ◽  
Iranian Women ◽  
Risk Of Cancer

Numerous epidemiological studies have evaluated the association between transforming growth factor beta receptor type 1 ( TGFBR1) polymorphisms and the risk of cancer; however, the results remain inconclusive and controversial. To determine the association between breast cancer risk and the *6A polymorphism of the TGFBR1 gene, a case-control study of 280 breast cancer patients and 280 controls was performed in Iranian women. Our study demonstrates that women who carry the TGFBR1*6A allele are at lower risk of developing breast cancer. The highest protection against breast cancer was observed in 6A/6A homozygotes (OR = 0.32, p = 0.04). A lower frequency of the TGFBR1*6A allele in breast cancer patients may be an important genetic determinant that contributes to a lower risk of breast cancer in Iranian women. The results also showed that the allelic length of TGFBR1 polymorphisms had no significant association with the age at onset or the grade of disease, nor with the expression of progesterone and estrogen receptors and HER2.

scholarly journals Machine Learning Frameworks in Cancer Detection

2021 ◽  
Vol 297 ◽  
pp. 01073
Author(s):  
Sabyasachi Pramanik ◽  
K. Martin Sagayam ◽  
Om Prakash Jena
Keyword(s):  
Machine Learning ◽  
Prediction Models ◽  
Supervised Machine Learning ◽  
Machine Learning Techniques ◽  
Cancer Development ◽  
Support Vector ◽  
Learning Approaches ◽  
Learning Techniques ◽  
Fact Finding ◽  
Risk Of Cancer

Cancer has been described as a diverse illness with several distinct subtypes that may occur simultaneously. As a result, early detection and forecast of cancer types have graced essentially in cancer fact-finding methods since they may help to improve the clinical treatment of cancer survivors. The significance of categorizing cancer suffers into higher or lower-threat categories has prompted numerous fact-finding associates from the bioscience and genomics field to investigate the utilization of machine learning (ML) algorithms in cancer diagnosis and treatment. Because of this, these methods have been used with the goal of simulating the development and treatment of malignant diseases in humans. Furthermore, the capacity of machine learning techniques to identify important characteristics from complicated datasets demonstrates the significance of these technologies. These technologies include Bayesian networks and artificial neural networks, along with a number of other approaches. Decision Trees and Support Vector Machines which have already been extensively used in cancer research for the creation of predictive models, also lead to accurate decision making. The application of machine learning techniques may undoubtedly enhance our knowledge of cancer development; nevertheless, a sufficient degree of validation is required before these approaches can be considered for use in daily clinical practice. An overview of current machine learning approaches utilized in the simulation of cancer development is presented in this paper. All of the supervised machine learning approaches described here, along with a variety of input characteristics and data samples, are used to build the prediction models. In light of the increasing trend towards the use of machine learning methods in biomedical research, we offer the most current papers that have used these approaches to predict risk of cancer or patient outcomes in order to better understand cancer.

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