Day 1 :
- Types of Breast Cancers | Reconstruction of breast cancer
Tsinghua University School of Medicine, Beijing, China
Zheng Shuo Jin study in Tsinghua University Beijing China since 2014 majoring in the 8-year MD program in School of medicine. Since 2015 I joined professor Dong Wang’s Lab at Tsinghua University, research in breast cancer and epigenetics.
Breast cancer is a disease in which malignant cells form in the tissues of the breast. The most common type of breast cancer is ductal carcinoma, which begins in the cells of the ducts. Cancer that begins in the lobes or lobules is called lobular carcinoma and is more often found in both breasts than are other types of breast cancer. Tamoxifen is a type of estrogen- suppressant, in several cases patients treated by Tamoxifen increased the risk rate for breast cancer, therefore, we hope to reduce the complications of endometrial cancer while treating breast cancer. Breast cancer is a disease in which malignant cells form in the tissues of the breast. The most common type of breast cancer is ductal carcinoma, which begins in the cells of the ducts. Cancer that begins in the lobes or lobules is called lobular carcinoma and is more often found in both breasts than are other types of breast cancer. Tamoxifen is a type of estrogen- suppressant, in several cases patients treated by Tamoxifen increased the risk rate for breast cancer, therefore, we hope to reduce the complications of endometrial cancer while treating breast cancer.
In the early experiment we used High throughout screening technology select compounds from the drug library and sensitive to gene signature which related to T cell associated genes CXCL9, CXCL10, CXCL11. We discover that MDA-MB-231 human triple negative breast cancer cell treated by RSC001 can induce chemokines also affect expression of STAT genes, classic pathway JAK-STAT will affect chemokines expression, chemokines CXCL10 and CXCL11 will recruit CD8+ T cell for attacking tumor cell. Therefore, though the interconnections between the pathway and chemokines, we need to explore more about RSC001 target point in TNBC cell also the relationship with STAT pathways.
University of Latvia, Latvia
Janis Eglitis is Head Of Department with a demonstrated history of working in the medical practice industry and Doctor of Philosophy (PhD) focused in Oncology and hematology from University of Latvia
Introduction & Aim: Breast cancer is the most common cancer type among women and also the most common cause of cancer related death in women worldwide, including Latvia. During the period from 2009 until 2016, the mortality rates in Latvia have increased from 20,7 to 23,3 per 100,000 inhabitants. Metastatic axillary lymph nodes are one of the important factors predicting prognosis of breast cancer patients. The aim of this study was to determine the effect of the N ratio on patient survival.
Method: The study included 100 patients that had underwent mastectomy or breast conserving surgery with lymphadenectomy in the Oncology Centre of Latvia, from January-2010 until December-2011 with a diagnosis of breast cancer with positive axillary lymph nodes. Patients were divided into two groups according to the N ratio: N ratio 0,2 or ≥0,2.
Results: Comparing the five years overall survival a statistically significant difference between groups was found (p=0,033). In the group where the N ratio was <0,2, 5-year overall survival rate was 85%, as opposed to 64% in the group where the N ratio was ≥0,2. When comparing the 5-year relapse free period, a statistically significant difference between the two groups was also found (p=0,039), showing a relapse-free 5-year period in 83% of the patients in the group with N ratio <0,2 and 64% of the patients with N ratio ≥0,2.
Conclusion: Patients with lower N ratio have a greater overall survival and relapse free period compared to patients with higher N ratio. Therefore, N ratio is a significant factor influencing the survival prognosis of breast cancer patients
I am a wife, mother of 3 young adult sons and now ex-Headteacher. Retiring from my post as a result of my secondary diagnosis 2 and a half years ago. My future is uncertain and many family landmarks I had hoped to experience are a faint, unlikely hope rather than probability.
I was first diagnosed with this disease when I was 37 and had hoped that as the 10 year landmark came and went that I was not going to revisit this disease. I was wrong, at the age of 51 I suffered excruciating pain to my spine and was told that my cancer had returned and was now incurable. Previous visits to my GP with my deteriorating back condition had not considered a recurrence of my disease instead the GP thought I was suffering from acute muscle spasms!
I have lived with cancer as a young woman and mother. My initial diagnosis was delayed by 6 months as my female GP considered me to be too young and despite my mother’s diagnosis, she felt I was unlikely to fall victim of this disease. Only pressurising the system resulted in my eventual mammogram and diagnosis. I pursued a clinical negligence claim 3 years after my diagnosis and won.
Arriving home to three very young children (3, 6 and 8) was one of the most difficult things I have ever done. Terrified myself, but unable to show this emotion to my children. How do you tell your children what is happening to their mummy? How do you reassure them when you don’t feel reassured yourself? Financially? How do you cope when you are off work for such a long time?
The fear of recurrence influenced many decisions I made as a parent. Perpetually scared that I would not be there for them; I was always considering the life skills that I was imparting to them trying to prepare them for life without me without them being aware.
Personally, as a woman, an early surgical menopause and all that it brings tested my relationship with my husband. My self-image has never been good since diagnosis.
My secondary diagnosis was given to me and I was sent home with pain killers and an appointment to see an oncologist. No other support. I was broken. It turned my life upside down and I have spent the past 3 and a half years trying to adjust to the huge uncertainties that the diagnosis presents me with.
I do now advocate on behalf of patients, I have appeared on BBC World News and have been in dialogue with key stakeholders in this world. Access to drugs and trials being key issues that I feel very passionate about.
I would feel very honoured to speak at the summit. I have a wealth of experience as a patient as a young woman, mother, wife and also as a middle- aged woman with secondary breast cancer. who has had to give up her career and life as it was to live with this disease.
Tehran University of Medical sciences
I am Dr. Mojtaba Mafi M.D., Medical Doctor/ Physician, graduated from Tehran university, School of Medicine with honor. I studied in neurosurgery ward and graduated with A score with thesis on Meningioma Brain Tumor for 6 years. With continuing my practice with special consideration on psychosomatic disorders, I completed many post graduate courses on health psychology, addiction medicine, sexual disorders therapy successfully. I passed many post graduate courses in Neuro, approved by Medical sciences university. As well, I have been passed post graduate courses on Nutrition, Gastroenterology and hepatology, Obesity treatment and diabetes approved by Tehran University of Medical sciences.
I successfully passed more than 10 programs with certificates and membership in Iranian Association of Gastroenterology and Hepatology.
Breast cancers classified as below types:
A: (DCIS): Ductal Carcinoma B: (LCIS): Lobular Carcinoma
In this article I decided to describe Non-Invasive types of Breast cancer and to compare clinical, radiological and pathological characteristics of two types of Non-Invasive Breast cancers.
Ductal Carcinoma In Situ (DCIS):
Palpable mass is not common in early presentation of this type of tumor in physical examination and radiography, but in late diagnosis, we can find mass and discharge.
This type, specially, when is well differentiated shows Estrogen receptors and the prognosis of Ductal carcinoma in situ is very good. We can find calcifications in radiography of this type of Breast cancer.
Lobular Cell Carcinoma (LCIS):
Pathology shows mono morph cells with Homogenous pattern. We can see mucinous Intracellular vacuoles. (Signet Ring Cells)
Calcifications is rare in radiography, we should know that this type of Breast cancer does not change lobular pattern of Breast.
In lobular cell carcinoma mass is not seen.
We dedicate breast cancers clinical and radiological concepts in detail at oral presentation time.
Sanford University and UC Berkeley University, USA
Jaleel Kareem Ahmed has completed his PhD from Baghdad University. He is the Dean of the Institute of Foundry and Hammering. He has registered 8 patents with 40 published papers and 3 books. He is a member in Who is Who network. He is a reviewer in Jon Wily and Sons and Editorial Board Member of Science Publishing Group and a member in Encyclopedia of Chemistry Scientists. He has got the Iraqi Scientist Medal. Currently, he is a Professor of physical chemistry in the College of Materials Engineering , Babylon University, Iraq.
The interactions between Polymethyl Methacrylate (PMMA), Polyvinyl Alcohol (PVA) Polyethylene Glycol (PEG) as industrial biopolymers and chitosan, cellulose, starch as natural biopolymers with iodine mixed by diethyl ether for homogenous solid mixture show a clear depression in the glass Transition Temperature (Tg) for all polymers as well as new colors appear except cellulose unaffected. It appears that cellulose molecules coated with a film prevent iodine to diffuse through the network structure of cellulose thus no effected its color or its Tg which indicates that molecular structure of cellulose quite different from that of starch and for this fact cellulose not soluble by a solvent and undigested in the human body. The depression in the Tg values of polymers indicate that iodine ruptures the engineering bonds of the polymers. The most effected Tg is of chitosan (lowered by 40.23˚C, this mean that iodine ruptures both hydrogen bonding through nitrogen and oxygen atoms in chitosan molecule. From Tg values it seems that iodine can acts as moderate plasticizer, by diffusing through the net of biopolymers and natural biopolymers ruptures their secondary bonds result in depression of their Tg except in case of cellulose. The order of Tg depressionchitosan>PMMA=starch>PVA>PEG>cellulose. From Tg values calculation of the energy given by the addition of iodine to the polymers was done. These energies are a function of iodine cause a depression in the original Tg of pure biopolymers 27.394>18.442=18.414>9.316>4.315>0 (kJ mol-1).
Seoul National University, Republic of Korea
Endosulfan sulfate (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9 methano-2,3,4-benzodioxathiepin-3,3-dioxide) is a major oxidized metabolite of endosulfan which is a broad-spectrum chlorinated cyclodiene insecticide. In this study, we used a GC-MS/MS based targeted metabolomic approach using MRM of metabolite to elucidate the toxicological effects of endosulfan sulfate in adult zebrafish. Zebrafish were exposed to endosulfan sulfate at concentrations of 1/10 LC50 and LC50 for 24 and 48 hours. After exposure, the fish was homogenized with liquid N2, extracted with 50% MeOH solution and dried before TMS derivatization (MSTFA+1% TMCS). On GC-MS/MS (Shimadzu TQ8040) MRM library of 381 metabolites were used for screening to detect overall 170 metabolites in zebrafish whole body. The PLS-DA score plot (SIMCA-P+) showed a good separation between the three experimental groups (control, 1/10 LC50, LC50) of 48 hours samples. Based on the VIP and ANOVA results, 60 metabolites were identified for contributing significantly to the differences in the metabolic profile. Metabolic pathway analysis using MetaboAnalyst 4.0 revealed that those identified metabolites were important for the organism response to endosulfan sulfate. Several pathways were reported by metabolic pathway analysis included aminoacyl-tRNA biosynthesis, valine/leucine/isoleucine biosynthesis, alanine/aspartate/glutamate metabolism, glycerolipid metabolism, arginine/proline metabolism, citrate cycle (TCA cycle), glycine/serine/threonine metabolism, glyoxylate/dicarboxylate metabolism and pentose phosphate pathway. These results suggest that these pathways underwent significant perturbations over the exposure period. This study highlights the application of GC-MS/MS (MRM mode) based targeted metabolomics to understand molecularlevel toxicity of persistent organochlorine pesticides and the results will contributed to the environmental risk assessment of endosulfan sulfate in zebrafish.
Nueva Granada Military University, Colombia
Math-Physical Medicine approach (MPM) utilizes mathematics, physics, engineering models and computer science in medical research. Initially, the author spent four years of self-studying six chronic diseases and food nutrition to gain in-depth medical domain knowledge. During 2014, he defined metabolism as a nonlinear, dynamic and organic mathematical system having 10 categories with 500 elements. He then applied topology concept with partial differential equation and nonlinear algebra to construct a metabolism equation. He further defined and calculated two variables, metabolism index and general health status unit. During the past few years, he has collected and processed 1.5 million data. Since 2015, he developed prediction models, i.e. equations for both Postprandial Plasma Glucose (PPG) and Fasting Plasma Glucose (FPG). He identified 19 influential factors for PPG and five factors for FPG. He developed the PPG model using optical physics and signal processing. Furthermore, by using both wave and energy theories, he extended his research into the risk probability of heart attack or stroke. In this risk assessment, he applied structural mechanics concepts, including elasticity, dynamic plastic and fracture mechanics, to simulate artery rupture and applied fluid dynamics concepts to simulate artery blockage. He further decomposed 12,000 glucose waveforms with 21,000 data and then re-integrated them into three distinctive PPG waveform types which revealed different personality traits and psychological behaviors of type-2 diabetes patients. Furthermore, he also applied fourier transform to conduct frequency domain analyses to discover some hidden characteristics of glucose waves. He then developed an AI Glucometer tool for patients to predict their weight, FPG, PPG and A1C. It uses various computer science tools, including big data analytics, machine learning and artificial intelligence to achieve very high accuracy (95% to 99%).