scholarly journals Understanding the unimodal distributions of cancer occurrence rates: it takes two factors for a cancer to occur

2020 ◽  
Author(s):  
Shuang Qiu ◽  
Zheng An ◽  
Renbo Tan ◽  
Ping-an He ◽  
Jingjing Jing ◽  
...  
Keyword(s):  
Occurrence Rate ◽  
Cancer Drug ◽  
Proliferative Potential ◽  
Cancer Type ◽  
Cancer Occurrence ◽  
Important Relationship ◽  
Age Regression ◽  
Age Dependent ◽  
Two Factors ◽  
Realistic Possibility

Abstract Data from the SEER reports reveal that the occurrence rate of a cancer type generally follows a unimodal distribution over age, peaking at an age that is cancer-type specific and ranges from 30+ through 70+. Previous studies attribute such bell-shaped distributions to the reduced proliferative potential in senior years but fail to explain why some cancers have their occurrence peak at 30+ or 40+. We present a computational model to offer a new explanation to such distributions. The model uses two factors to explain the observed age-dependent cancer occurrence rates: cancer risk of an organ and the availability level of the growth signals in circulation needed by a cancer type, with the former increasing and the latter decreasing with age. Regression analyses were conducted of known occurrence rates against such factors for triple negative breast cancer, testicular cancer and cervical cancer; and all achieved highly tight fitting results, which were also consistent with clinical, gene-expression and cancer-drug data. These reveal a fundamentally important relationship: while cancer is driven by endogenous stressors, it requires sufficient levels of exogenous growth signals to happen, hence suggesting the realistic possibility for treating cancer via cleaning out the growth signals in circulation needed by a cancer.

scholarly journals Aspirin Decreases Hepatocellular Carcinoma Risk in Hepatitis C Virus Carriers: A Nationwide Cohort Study

2019 ◽  
Author(s):  
Yen-Hsiang Liao ◽  
Wen-Lin Hsu ◽  
Tzu-Hwei Wang ◽  
Chen-Ta Wu ◽  
Sheng-Yao Huang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Cohort Study ◽  
Hepatitis C Virus ◽  
Hepatitis C ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Incidence Rate ◽  
Occurrence Rate ◽  
Control Group ◽  
Cancer Occurrence

Abstract Background Aspirin lowered some cancer occurrence rate, through the inhibition of the cyclooxygenase enzyme. The association of aspirin-use and hepatocellular carcinoma (HCC) occurrence rate in hepatitis B virus (HBV) carriers is well known. However, the association in hepatitis C virus (HCV) carriers is not known. Our purpose is comparing the HCC occurrence rate in HCV carriers with or without Aspirin treatment. Methods In this retrospective cohort study, the participants were ones newly-diagnosed with HCV from 2000 to 2012 in Taiwan. These HCV carriers with aspirin treatment were defined as the control group, whereas those without aspirin were defined as a compared cohort. We used a 1:1 propensity score matching by age, sex, comorbidities, drugs, diagnosis year and index year with covariate assessment. Results Our study sample consisted of 2980 aspirin-treated HCV carriers and 7771 non-aspirin-treated HCV carriers. After propensity score matching, each cohort consisted of 1911 HCV carriers. The adjusted hazard ratio (aHR) of HCC incidence in aspirin users (aHR=0.56, 95% CI=0.43-0.72, p < 0.001 ) was significantly lower than that in non-aspirin users. The Kaplan-Meier curves show that among the HCV carriers, aspirin users had a lower cumulative incidence rate of HCC in the first 10-year aspirin treatment course ( p < 0.0001 ). Conclusions The HCC incidence rate was lower in the aspirin users than non- aspirin users among HCV carriers, supporting the aspirin effect may be acting through inhibition of the cyclooxygenase enzyme pathway. Moreover, the patients got HCC protection by aspirin within 1-year treatment course and had best HCC prevention during 1- to 2-year aspirin treatment course. We encourage aspirin treatment to prevent HCC in HCV carriers.

scholarly journals Mir-125a rs12976445 is Associated with Susceptibility to Thyroid Cancer: A Case-control Study

2020 ◽  
Author(s):  
Nima Nima Montazeri-Najafabady ◽  
Mohammad Hossein Dabbaghmanesh ◽  
Abbas Ghaderi ◽  
Nazanin Chatrabnous ◽  
Mohammad Reza Arabnezhad ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Case Control ◽  
Occurrence Rate ◽  
Cancer Type ◽  
Dominant Model ◽  
Allele Distribution ◽  
Genotype Frequencies ◽  
Significant Difference ◽  
Pcr Rflp ◽  
Cancer Types

Abstract Background: Thyroid cancer is the fifth communal cancer type in females and its occurrence rate continues to rise rapidly worldwide. Latest data demonstrated mir-125 is down-regulated in various cancer types. Methods: a case-control (179 cases, 165 controls) study in order to explore the association of mir-125 rs12976445 with the risk of thyroid cancer in the Iranian population was performed. In order to investigate rs12976445 C/T polymorphisms, polymerase chain reaction restriction–fragment length polymorphism (PCR–RFLP) was done. Logistic regression analyses were done to find the association of mir-125 rs12976445 C/T polymorphisms with thyroid cancer and its stages. Results: The genotype frequencies for patients was [(CC: 81(45.2%), CT: 75(41.9%), TT: 23 (12.9%)], and for controls was [(CC: 100 (60.1%), CT: 53(32.2%), TT: 12 (6.7%)]. The T allele distribution was significantly altered between patients and controls (P=0.002) with the odds ratio of 1.68. In the co-dominant model CC genotype was set as reference and compared with CT, and TT genotypes. In the dominant model, there was a significant difference between CC vs CT genotypes (adjusted OR = 1.69, 95% CI= 1-2.8, P = 0.026), and slightly significant differences between CC vs TT genotypes (adjusted OR = 2.18, 95% CI= 1-4.7, P = 0.047). we compared CT/TT genotype to the reference genotype (CC) and found a highly significant difference (adjusted OR = 1.78, 95% CI= 1.15-2.74, P = 0. 0.009).Conclusion: as the first study, our findings suggest that miR-125a rs12976445 is a possible prognostic biomarker for thyroid cancer patients.

scholarly journals Nelfinavir and other protease inhibitors in cancer: mechanisms involved in anticancer activity

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 9 ◽  
Author(s):  
Tomas Koltai
Keyword(s):  
Cancer Treatment ◽  
Anticancer Activity ◽  
Protease Inhibitors ◽  
Mode Of Action ◽  
Fatty Acid Synthase ◽  
Molecular Mechanisms ◽  
Cancer Drug ◽  
Cancer Type ◽  
Anti Cancer ◽  
Cancer Activity

Objective:To review the mechanisms of anti-cancer activity of nelfinavir and other protease inhibitors (PIs) based on evidences reported in the published literature.Methods:We extensively reviewed the literature concerning nelfinavir (NFV) as an off target anti-cancer drug and other PIs. A classification of PIs based on anti-cancer mode of action was proposed. Controversies regarding nelfinavir mode of action were also addressed.Conclusions:The two main mechanisms involved in anti-cancer activity are endoplasmic reticulum stress-unfolded protein response pathway and Akt inhibition. However there are many other effects, partially dependent and independent of those mentioned, that may be useful in cancer treatment, including MMP-9 and MMP-2 inhibition, down-regulation of CDK-2, VEGF, bFGF, NF-kB, STAT-3, HIF-1 alfa, IGF, EGFR, survivin, BCRP, androgen receptor, proteasome, fatty acid synthase (FAS), decrease in cellular ATP concentration and upregulation of TRAIL receptor DR5, Bax, increased radiosensitivity, and autophagy. The end result of all these effects is slower growth, decreased angiogenesis, decreased invasion and increased apoptosis, which means reduced proliferation and increased cancer cells death.PIs may be classified according to their anticancer activity at clinically achievable doses, in AKT inhibitors, ER stressors and Akt inhibitors/ER stressors.Beyond the phase I trials that have been recently completed, adequately powered and well-designed clinical trials are needed in the various cancer type settings, and specific trials where NFV is tested in association with other known anti-cancer pharmaceuticals should be sought, in order to find an appropriate place for NFV in cancer treatment.The analysis of controversies on the molecular mechanisms of NFV hints to the possibility that NFV works in a different way in tumor cells and in hepatocytes and adipocytes.

Examining the relationship between the clinical benefit of oncology drug indications and the time from pan-Canadian Oncology Drug Review (pCODR) recommendation to public reimbursement.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e19360-e19360
Author(s):  
Sasha Thomson ◽  
Louis Everest ◽  
Noah Witzke ◽  
Seanthel Delos Santos ◽  
Matthew C. Cheung ◽  
...  
Keyword(s):  
Clinical Benefit ◽  
Multivariable Analysis ◽  
Cancer Drug ◽  
Cancer Type ◽  
Inclusion Criteria ◽  
Oncology Drug ◽  
The Mean ◽  
American Society ◽  
The Relationship ◽  
Drug Review

e19360 Background: We examined if publicly reimbursed oncology drug indications with evidence of high clinical benefit, as measured by the American Society of Clinical Oncology Value Framework v2 (ASCO-VF), and European Society for Medical Oncology Magnitude of Clinical Benefit Scale v1.1 (ESMO-MCBS), received reimbursement status faster than those with lower clinical benefit from the time of pCODR recommendation. Methods: Oncology drug indications that received pCODR recommendations between Jan 2012 and July 2018 were identified. Indications that did not receive provincial reimbursement, without notice of compliance, or received a negative pCODR recommendation were excluded. The relationship between clinical benefit, as measured by ASCO-VF and ESMO-MCBS, and the time to reimbursement was evaluated using Spearman correlation coefficient, univariable, and multivariable linear regression analyses. Results: Overall, 84 indications met inclusion criteria yielding 80 ASCO-VF and 66 ESMO-MCBS scores. The mean ASCO-VF and ESMO-MCBS scores were 38.8 (SD = 23.8) and 3.0 (SD = 1.1) respectively. Higher ASCO-VF and ESMO-MCBS scores had low correlation with shorter time to provincial funding, (rho = -0.15, 95%CI -0.24, -0.06) and (rho = -0.25, 95%CI -0.34, -0.16) respectively. Univariable analyses showed that manufacturer reported incremental cost effectiveness ratio (ICER) values, year of pCODR recommendation, province and cancer type were associated with time to public reimbursement (all p < 0.0001). After adjusting for potential confounders in the respective multivariable analysis, ASCO-VF (p = 0.29) and ESMO-MCBS (p = 0.15) scores were not significantly associated with time to public reimbursement. Year of pCODR recommendation remained associated with time to public reimbursement (p < 0.001). Earlier years (2012-2014) had a shorter time to reimbursement (mean = 10.4 months) than later years (2015-2018) (mean = 14.5 months). Other factors that were associated with time to reimbursement in multivariable analysis were province (p < 0.001) and cancer type (p < 0.001). Conclusions: Currently, oncology drug indication with evidence of high clinical benefit do not appear to be funded faster than those with low clinical benefit. This suggests the need to prioritize cancer drug indications based on clinical benefit in order to allow for timely public reimbursement of cancer drugs with higher clinical benefit to patients.

scholarly journals Survival Prediction Score: A Simple but Age-Dependent Method Predicting Prognosis in Patients Undergoing Palliative Radiotherapy

ISRN Oncology ◽  
2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Kent Angelo ◽  
Astrid Dalhaug ◽  
Adam Pawinski ◽  
Ellinor Haukland ◽  
Carsten Nieder
Keyword(s):  
Cancer Patients ◽  
Poor Prognosis ◽  
Performance Status ◽  
Palliative Radiotherapy ◽  
Good Prognosis ◽  
Prediction Score ◽  
Survival Prediction ◽  
Cancer Type ◽  
Age Dependent ◽  
Prognosis Group

Purpose. Validation of a Canadian three-tiered prognostic model (survival prediction score, SPS) in Norwegian cancer patients referred for palliative radiotherapy (PRT), and evaluation of age-dependent performance of the model. Patients and Methods. We analyzed all 579 PRT courses administered at a dedicated PRT facility between 20.06.07 and 31.12.2009. SPS was assigned as originally described, That is, by taking into consideration three variables: primary cancer type, site of metastases, and performance status. Results. Patients with poor prognosis (non-breast cancer, metastases other than bone, and Karnofsky performance status (KPS) ≤ 60) had median survival of 13 weeks. Those with intermediate prognosis (two of these parameters) survived for a median of 29 weeks, and patients with good prognosis for a median of 114 weeks, P<0.001. While this model performed well in patients who were 60 years or older, it was less satisfactory in younger patients (no significant difference between the good and intermediate prognosis groups). Conclusion. SPS should mainly be used to predict survival of elderly cancer patients. However, even in this group accuracy is limited because the good prognosis group contained patients with short survival, while the poor prognosis group contained long-term survivors. Thus, improved models should be developed.

scholarly journals A virtual-hybrid approach to launching a cardio-oncology clinic during a pandemic

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Sherry-Ann Brown ◽  
Sahishnu Patel ◽  
David Rayan ◽  
Svetlana Zaharova ◽  
Mingqian Lin ◽  
...  
Keyword(s):  
Retrospective Review ◽  
Information Seeking ◽  
De Novo ◽  
Hybrid Approach ◽  
Cancer Drug ◽  
Cancer Type ◽  
Cancer Therapies ◽  
Preventive Cardiology ◽  
Cardiovascular Diagnosis ◽  
Virtual Resources

Abstract Background As cardiovascular disease is a leading cause of death in cancer survivors, the new subspecialty of Cardio-Oncology has emerged to address prevention, monitoring, and management of cardiovascular toxicities to cancer therapies. During the coronavirus disease of 2019 (COVID-19) pandemic, we developed a Virtual-Hybrid Approach to build a de novo Cardio-Oncology Clinic. Methods We conceptualized a Virtual-Hybrid Approach including three arms: information seeking in locations with existing Cardio-Oncology clinics, information gathering at the location for a new clinic, and information sharing to report clinic-building outcomes. A retrospective review of outcomes included collection and synthesis of data from our first 3 months (at pandemic peak) on types of appointments, cancers, drugs, and cardiotoxicities. Data were presented using descriptive statistics. Results A de-novo Cardio-Oncology clinic was developed structured from the ground up to integrate virtual and in-person care in a hybrid and innovative model, using the three arms of the Virtual-Hybrid Approach. First, we garnered in-person and virtual preparation through hands-on experiences, training, and discussions in existing Cardio-Oncology Clinics and conferences. Next, we gleaned information through virtual inquiry and niche-building. With partners throughout the institution, a virtual referral process was established for outpatient referrals and inpatient e-consult referrals to actualize a hybrid care spectrum for our patients administered by a multidisciplinary hybrid care team of clinicians, ancillary support staff, and clinical pharmacists. Among the multi-subspecialty clinic sessions, approximately 50% were in Cardio-Oncology, 20% in Preventive Cardiology, and 30% in General Cardiology. In the hybrid model, the Heart & Vascular Center had started to re-open, allowing for 65% of our visits to be in person. In additional analyses, the most frequent cardiovascular diagnosis was cardiomyopathy (34%), the most common cancer drug leading to referral was trastuzumab (29%), and the most prevalent cancer type was breast cancer (42%). Conclusion This Virtual-Hybrid Approach and retrospective review provides guidance and information regarding initiating a brand-new Cardio-Oncology Clinic during the pandemic for cancer patients/survivors. This report also furnishes virtual resources for patients, virtual tools for oncologists, cardiologists, and administrators tasked with starting new clinics during the pandemic, and innovative future directions for this digital pandemic to post-pandemic era.

scholarly journals Breast Cancer: Treatment Effects on Fertility and Subsequent Pregnancy Outcomes

2021 ◽  
Vol 8 (8) ◽  
pp. 442-447
Author(s):  
Antigoni Sarantaki ◽  
Kyriaki Perisaki
Keyword(s):  
Breast Cancer ◽  
Pregnancy Outcomes ◽  
Subsequent Pregnancy ◽  
Reproductive Age ◽  
Cancer Type ◽  
Women Of Reproductive Age ◽  
Breast Cancer Therapy ◽  
Common Cancer ◽  
Cancer Occurrence ◽  
Common Cancer Type

Objective: Breast cancer is the most common cancer type in women of reproductive age. Given that most women postpone childbearing, breast cancer occurrence possibly perplexes their plans for starting a family. The treatment for breast cancer can affect their fertility and have adverse effects on a pregnancy that occurs during that period. The aim of this narrative review is primarily to explore the influence of breast cancer therapy on the ability of a woman diagnosed with breast cancer to gestate. Moreover, to determine the safer timing for childbearing after being treated for breast cancer and investigate the pregnancy outcome when conception is succeeded. Childbearing after treatment for breast cancer is considered safe and pregnancy outcomes are favorable if conception happens 1 year after chemotherapy or at least 2 years after chemotherapy and radiation therapy. Counseling is of great significance and fertility preservation methods should be thoroughly discussed with women diagnosed with breast cancer, even prior to commencement of the treatment

scholarly journals Pan-Cancer Integrative Analysis of Whole-Genome De novo Somatic Point Mutations Reveals 17 Cancer Types

2021 ◽  
Author(s):  
Amirreza Kazemi ◽  
Amin Ghareyazi ◽  
Kimia Hamidieh ◽  
Hamed Dashti ◽  
Maedeh Tahaei ◽  
...  
Keyword(s):  
Cancer Patients ◽  
Molecular Mechanisms ◽  
High Throughput Sequencing ◽  
Specific Treatment ◽  
Cancer Drug ◽  
Cancer Type ◽  
Cancer Subtypes ◽  
Genotypic Analysis ◽  
Cancer Types ◽  
Pan Cancer

The advent of high throughput sequencing has enabled researchers to systematically evaluate the genetic variations in cancer, resulting in identifying many cancer-associated genes. Although cancers in the same tissue are widely categorized in the same group, they demonstrate many differences concerning their mutational profiles. Hence there is no &ldquo;silver bullet&rdquo; for the treatment of a cancer type. This reveals the importance of developing a pipeline to identify cancer-associated genes accurately and re-classify patients with similar mutational profiles. Classification of cancer patients with similar mutational profiles may help discover subtypes of cancer patients who might benefit from specific treatment types. In this study, we propose a new machine learning pipeline to identify protein-coding genes mutated in a significant portion of samples to identify cancer subtypes. We applied our pipeline to 12270 samples collected from the International Cancer Genome Consortium (ICGC), covering 19 cancer types. Here we identified 17 different cancer subtypes. Comprehensive phenotypic and genotypic analysis indicates distinguishable properties, including unique cancer-related signaling pathways, in which, for most of them, targeted treatment options are currently available. This new subtyping approach offers a novel opportunity for cancer drug development based on the mutational profile of patients. We also comprehensive study the causes of mutations among samples in each subtype by mining the mutational signatures, which provides important insight into their active molecular mechanisms. Some of the pathways we identified in most subtypes, including the cell cycle and the Axon guidance pathways, are frequently observed in cancer disease. Interestingly, we also identified several mutated genes and different rates of mutation in multiple cancer subtypes. In addition, our study on &ldquo;gene-motif&rdquo; suggests the importance of considering both the context of the mutations and mutational processes in identifying cancer-associated genes. The source codes for our proposed clustering pipeline and analysis are publicly available at: https://github.com/bcb-sut/Pan-Cancer.

scholarly journals The Multifaceted Glioblastoma: From Genomic Alterations to Metabolic Adaptations

2021 ◽  
pp. 59-76
Author(s):  
Addison Quinones ◽  
Anne Le
Keyword(s):  
Genetic Alterations ◽  
Proliferative Potential ◽  
Low Grade ◽  
Cancer Type ◽  
Advanced Stage ◽  
Microvascular Proliferation ◽  
Current Therapies ◽  
Metabolic Properties ◽  
Advanced Stage Cancer ◽  
Temporal And Spatial Heterogeneity

AbstractGlioblastoma multiforme (GBM) develops on glial cells and is the most common as well as the deadliest form of brain cancer. As in other cancers, distinct combinations of genetic alterations in GBM subtypes induce a diversity of metabolic phenotypes, which explains the variability of GBM sensitivity to current therapies targeting its reprogrammed metabolism. Therefore, it is becoming imperative for cancer researchers to account for the temporal and spatial heterogeneity within this cancer type before making generalized conclusions about a particular treatment’s efficacy. Standard therapies for GBM have shown little success as the disease is almost always lethal; however, researchers are making progress and learning how to combine therapeutic strategies most effectively. GBMs can be classified initially into two subsets consisting of primary and secondary GBMs, and this categorization stems from cancer development. GBM is the highest grade of gliomas, which includes glioma I (low proliferative potential), glioma II (low proliferative potential with some capacity for infiltration and recurrence), glioma III (evidence of malignancy), and glioma IV (GBM) (malignant with features of necrosis and microvascular proliferation). Secondary GBM develops from a low-grade glioma to an advanced-stage cancer, while primary GBM provides no signs of progression and is identified as an advanced-stage glioma from the onset. The differences in prognosis and histology correlated with each classification are generally negligible, but the demographics of individuals affected and the accompanying genetic/metabolic properties show distinct differentiation [3].

Introduction: the study of European Union relations with Mercosur

2017 ◽  
Author(s):  
Arantza Gomez Arana
Keyword(s):  
European Union ◽  
Economic Integration ◽  
Decision Makers ◽  
Association Agreement ◽  
Eu Policy ◽  
Important Relationship ◽  
Two Factors ◽  
The Common ◽  
Council Of Ministers ◽  
High Degree

This monograph seeks to examine the motivations behind the European Union’s (EU) policy towards the Common Market of the South (Mercosur), the EU’s most important relationship with another regional economic integration organisation. In order to investigate the motivations (or lack there of), this monograph will examine the contribution of the main policy and decision-makers, the European Commission and the Council of Ministers, as well as the different contributions within both institutions. By doing so, it will be possible to show the degree of “involvement”/”engagement” reflected in the EU’s policy towards Mercosur, which is the dependent variable in this study. The analysis offered here examines the development of EU policy towards Mercosur in relation to three key stages: The non-institutionalized relations (1986-1990), official relations (1991-1995), and the negotiations of an association agreement (1996-2007 and 2010-present). This degree of engagement will be measured using a scale of low, medium and high degree. The outcome of the measure is created by analysing two factors, the level of “ambition” and “commitment”.

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