Ayyappan Nair, Ph.D.
Head, Business Development (Technologies, Discovery Biology), Anthem Biosciences & DavosPharma, New Jersey, USA
Inhibition of NF-κB regulated gene expression by chrysoeriol suppresses tumorigenesis in breast cancer cells
Amrutha K1, Pandurangan Nanjan1, Sanu K Shaji1, Damu Sunilkumar1, Subhalakshmi K1, Rashmi U Nair1, Lakshmi Rajakrishna2, Asoke Banerji1, Ayyappan Ramesh Nair1*,2
- School of Biotechnology, Amrita Vishwa Vidyapeetham, Amritapuri Campus, Clappana P.O., Kollam – 690 525, Kerala, India
- Anthem Biosciences, No 49, Canara Bank Road, Bommasandra Industrial Area, Phase 1, Hosur Road, Bangalore – 560 099, Karnataka, India
Abstract: A large number of effective cancer-preventing compounds inhibit the activation of nuclear factor-κ B (NF-κB). It has been previously demonstrated that some flavonoids that are a vital component of our diet inhibits this pathway. As a consequence, many flavonoids inhibit genes involved in various aspects of tumorigenesis and have thus emerged as potential chemopreventive candidates for cancer treatment. We studied the effect of 17 different flavonoids, including the highly evaluated quercetin on the NF-κB pathway, and on the expression of MMP-9 and COX-2 (two NF-κB regulated genes involved in metastasis) in the highly invasive human breast cancer cell line MDA-MB-231. The findings suggest that not all the quercetin like flavone backbone compounds inhibit the NF-κB pathway, and that the highly hydoxylated flavonols quercetagetin and gossypetin did not inhibit this pathway, nor did it inhibit the expression of MMP-9 and COX-2. This indicates a correlation between inhibition of NF-κB and subsequent suppression of these NF-κB regulated genes. Here, we also report the novel observation that the not so well characterized methoxylated flavone chrysoeriol inhibited the NF-κB pathway, and was most potent in reducing the expression of MMP-9 and COX-2. Based on these observations, the cellular effects of chrysoeriol were evaluated in MDA-MB-231. Chrysoeriol caused cell cycle arrest at G2/M, inhibited migration and invasion, and caused cell death of macrophages that contributed to migration of these cancer cells. These effects of chrysoeriol make it a potential therapeutic candidate for breast cancer metastasis.
![Delegate Talk: AIB1 Mediated Modulation of CXCR4-SDF1 Signaling in Breast Cancer @ Acharya Hall | Vallikavu | Kerala | India](http://www.amritabioquest.org/conference/2013/wp-content/uploads/sites/2/2015/02/gtm.jpg)
Binu K Aa, Jem Prabhakarb, Thara Sc and Lakshmi Sd,∗
aDepartment of Clinical Diagnostics Services and Translational Research, Malabar Cancer Centre, Thalassery, Kerala, India.
bDivision of Surgical Oncology, Division of Pathology
dDivision of Cancer Research, Regional Cancer Centre, Thiruvananthapuram, Kerala, India.
Introduction
AIB1, a member of the nuclear co activators, promotes the transcriptional activity of multiple nuclear receptors such as the ER and other transcription factors. Chemokines produced by stromal cells have potential to influence ERα-positive breast cancer progression to metastasis. CXCR4 is the physiological receptor for SDF1, together shown to stimulate the chemotactic and invasive behavior of breast cancer cells to serve as a homing mechanism to sites of metastasis. We propose that over expression of AIB1 in breast cancer cells leads to increased SDF1 and CXCR4 expression, which induces invasion and metastasis of cancer cells.
Materials and Methods
Breast tumor and normal breast tissues from patients in Regional Cancer Centre, Thiruvananthapuram were used for study. The modulatory effect of AIB1 was studied in MCF-7 cells with AIB1 siRNA transfection along with treatment of 17β-Estradiol (E2), 4-hydroxytamoxifen (4OHT), combinations of E2 and 4OHT. The gene expression pattern and protein localization were assessed by RT-PCR and immunofluorescence microscopy respectively. The metastatic and invasive properties were assessed by wound healing assay. Quantitative colocalization analyses were done to assess the association of proteins using Pearson’s correlation coefficient.
Result and Conclusion
The mRNA and protein level expression of AIB1, CXCR4 and SDF1 were higher in tumor samples than in normal samples. AIB1 was localized to the nuclei whereas CXCR4 and SDF1 immunoreactivity were observed in the cytoplasm and to a lesser extent in the nuclei of tumor epithelial cells. In tumor samples the gene level expressions of AIB1 showed significant positive correlations with SDF1(r = 0.213, p = 0.018). CXCR4 showed significant positive correlation with SDF1 in gene (r = 0.498, p = 0.000) and protein levels(r = 0.375, p = 0.002). Quantitative colocalization analyses showed a marked reduction in expression of CXCR4 and SDF1 in siAIB1MCF-7 cells than MCF-7 cells with different treatment groups. Wound healing assay shows reduced wound healing in siAIB1 treated MCF-7 cells.
In recent years, targeting specific cancer pathways and key molecules to arrest tumor growth and achieve tumor eradication have proven a challenge; due to acquired resistance and homing of cancer cells to various metastatic sites. The present study revealed that silencing AIB1 can prevent the over expression of SDF1 and CXCR4. Co activator levels determine the basal and estrogen-inducible expression of SDF1, a secreted protein that controls breast cancer cell proliferation and invasion through autocrine and paracrine mechanisms (Hall et al. 2003). The effects of CXCR4 overexpression has been correlated with SDF1 mediated activation of downstream signaling via ERK1/2 and p38 MAPK and with an enhancement of ER-mediated gene expression (Rhodes et al. 2011). It is possible that over expression of AIB1 as a stimulant involved in the expression of CXCR4 might up-regulate the expression of prometastatic and angiogenic genes. Thus based on these observations it can be concluded that SDF1/CXCR4 overexpression, with significant association with AIB1 expression, itself contribute to the development of mammary cancer and metastatic progression.
Nader Pourmand, Ph.D.
Director, UCSC Genome Technology Center,University of California, Santa Cruz
Biosensor and Single Cell Manipulation using Nanopipettes
Approaching sub-cellular biological problems from an engineering perspective begs for the incorporation of electronic readouts. With their high sensitivity and low invasiveness, nanotechnology-based tools hold great promise for biochemical sensing and single-cell manipulation. During my talk I will discuss the incorporation of electrical measurements into nanopipette technology and present results showing the rapid and reversible response of these subcellular sensors to different analytes such as antigens, ions and carbohydrates. In addition, I will present the development of a single-cell manipulation platform that uses a nanopipette in a scanning ion-conductive microscopy technique. We use this newly developed technology to position the nanopipette with nanoscale precision, and to inject and/or aspirate a minute amount of material to and from individual cells or organelle without comprising cell viability. Furthermore, if time permits, I will show our strategy for a new, single-cell DNA/ RNA sequencing technology that will potentially use nanopipette technology to analyze the minute amount of aspirated cellular material.
Karmeshu, Ph.D.
Dean & Professor, School of Computer & Systems Sciences & School of Computational & Integrative Sciences, Jawaharlal Nehru University, India.
Interspike Interval Distribution of Neuronal Model with distributed delay: Emergence of unimodal, bimodal and Power law
The study of interspike interval distribution of spiking neurons is a key issue in the field of computational neuroscience. A wide range of spiking patterns display unimodal, bimodal ISI patterns including power law behavior. A challenging problem is to understand the biophysical mechanism which can generate the empirically observed patterns. A neuronal model with distributed delay (NMDD) is proposed and is formulated as an integro-stochastic differential equation which corresponds to a non-markovian process. The widely studied IF and LIF models become special cases of this model. The NMDD brings out some interesting features when excitatory rates are close to inhibitory rates rendering the drift close to zero. It is interesting that NMDD model with gamma type memory kernel can also account for bimodal ISI pattern. The mean delay of the memory kernels plays a significant role in bringing out the transition from unimodal to bimodal ISI distribution. It is interesting to note that when a collection of neurons group together and fire together, the ISI distribution exhibits power law.
Andrey Panteleyev, Ph.D.
Vice Chair, Division of Molecular Biology, NBICS Centre-Kurchatov Institute, Moscow, Russia
The system of PAS proteins (HIF and AhR) as an interface between environment and skin homeostasis
Regulation of normal skin functions as well as etiology of many skin diseases are both tightly linked to the environmental impact. Nevertheless, molecular aspects of skin-environment communication and mechanisms coordinating skin response to a plurality of environmental stressors remain poorly understood.
Our studies along with the work of other groups have identified the family of PAS dimeric transcription factors as an essential sensory and regulatory component of communication between skin and the environment. This protein family comprises a number of hypoxia-induced factors (HIF-alpha proteins), aryl hydrocarbon receptor (AhR), AhR nuclear translocator (ARNT), and several proteins implicated in control of rhythmic processes (Clock, Period, and Bmal proteins). Together, various PAS proteins (and first of all ARNT – as the central dimerization partner in the family) control such pivotal aspects of cell physiology as drug/xenobiotic metabolism, hypoxic and UV light response, ROS activity, pathogen defense, overall energy balance and breathing pathways.
In his presentation Dr. Panteleyev will focus on the role of ARNT activity and local hypoxia in control of keratinocyte differentiation and cornification. His recent work revealed that ARNT negatively regulates expression of late differentiation genes through modulation of amphiregulin expression and downstream alterations in activity of EGFR pathway. All these effects are highly dependent on epigenetic mechanisms such as histone deacetylation. Characterisation of hypoxia as a key microenvironmental factor in the skin and the role of HIF pathway in control of dermal vasculature and epidermal functions is another major focus of Dr. Panteleyev’s presentation.
In general, the studies of Dr. Panteleyev’s laboratory provide an insight into the PAS-dependent maintenance of skin homeostasis and point to the potential role of these proteins in pathogenesis of environmentally-modulated skin diseases such as barrier defects, desquamation abnormalities, psoriasis, etc.
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.