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Breast cancer is a tumour related to breast tissues. Out of total cancer patients in UK thirty percent are females suffered from breast cancer and there is possibility that 1 out of 9 women in UK will get breast cancer once in their life. Chemotherapies are well known treatments for cancer. These techniques are effective but having possible side effects, this project will primarily focus on the finding of the biomarkers in clinical and pathologic response of primary tumour treated with neoadjuvant docetaxal-capecitabine (with or without trastuzumab) chemotherapy. Chemotherapy is effective way to treat HER2 positive cells with docetaxal-capecitabine-trastuzumab regimen and HER2 negative cancer with docetaxal-capecitabine regimen (Gluck, McKenna & Royce 2008)and show increased death free survival time (D.F.S). But problem associated with chemotherapy is lots of side effects and same dose of chemotherapy can't be used for the desired results in each and every patient. This project will try to find out biomarkers in EMBL's ARRAYEXPRESS "E-GEOD-22358" dataset in response to chemotherapy by using artificial neural network (A.N.N) technique to analyse this database and try to validate and optimise results statically.
After finding of biomarkers we can personalised this chemotherapy according to individual and screen out group of people on which this therapy will not work effectively. By just taking patient's biopsy sample we can find out whether this therapy is effective and at which level patient will response to therapy.
Background to investigation:
Breast cancer is the state in which uncontrolled growth of breast tissue takes place. Most commonly cancer originates from milk duct's inner linings or lobules of breast. Among all types of cancers, breast cancer is the second diagnosed cancer in the world (Silva Idos et al. 2008). Some cells respond in specific way due to presence of receptor like HER2 receptor, ER receptor on their surface which affects their growth. HER2 is 'human epidermal growth factor' receptor two. This is surface bound receptor help in signal transduction by which cell proliferates and differentiates. But in some cells HER2 gene product (protein) over express and due to which cell grow in uncontrolled manner and become cancerous. HER2 positive status it means cell have overproduction of HER2 GENE and cell shows cancerous growth, if HER2 negative then HER2 not causing cancer.HER2 belongs to the Human Epidermal Growth Factor Receptor (HER) family of tyrosine kinases consisting of EGFR (HER1, erbB1), HER2 (erbB2, HER2/neu), HER3 (erbB3), and HER4 (erbB4) (Moasser 2007).
. 30% of breast cancers are due to over expression of HER2 gene. And inhibition of HER2 would be the best treatment for this type of cancers. Monoclonal antibodies (AB) found to be an effective treatment for HER2 positive cancer, for this purpose thousands of monoclonal antibody (AB) produced and humanised. Some humanised clone of antibody lost their anti-proliferating activity but some retain by selecting from such ABs 'Trastuzumab' was produced.(Carter et al. 1992) This is an AB which binds specifically to HER2 protein and stop growth of uncontrolled cells in breast tissue.
In initial phase it was difficult to detect HER2 positive cells with immunohistochemical methods but this problem resolve by implementation of a 'fluorescence in situ hybridization (FISH) assay', this is fast method to detect HER2 amplification in cells. Trastuzumab show good response if it is used as upfront therapy. Patients with metastatic disease not showing response to Trastuzumab even after long treatment with this drug cancer come back. Trastuzumab is only responsive to HER2 positive cells and can't work against HER2 negative cells.(Mass et al. 2005).trastuzumab show anti proliferating effect By inducing p27 which induce suppression of cell proliferation and cell cycle arrest at g1 phase ,suppresses Akt signalling in tumour cell, downstream PI3K cascade, inhibition of CDK2 activity, inhibit the HER2 ectodomain cleavage(Karagiannis et al. 2009), trastuzumab response effected by PTEN gene low or absence of PTEN in tumour cells make them resistant to trastuzumab (Nagata et al. 2004) Trastuzumab show good response rate and survival time apart from these it have some significant side effects like not suitable for heart patient and risk of chemotherapy increase when combine with anthracycline.
This is specialised term used for treatment of cancer cells. Chemotherapy chemicals introduce in to blood stream and kill cancerous cell by Cell apoptosis, Mutation in DNA /RNA of cell, freezing of mitosis, stopping growth of new blood vessels that supply tumour. Chemotherapy could be given by single or group of chemicals depend upon the type of therapy and stage of cancer.(Silva, Gatenby 2010).Chemotherapy known for tumour size reduction and increase survival in case of breast cancer so it is substitute treatment for hormone therapy resistant cancer .anthracycline used due to high response rate as treatment for cancer but many patient have recurrent disease which already treated with anthracycline and for those type of patients taxane treatment is used.
Chemical used in chemotherapy:
These are chemical compound which produce naturally by genre "Taxus" and causing less cytotoxicity then anthracycline. Most commonly used taxane are paclitaxel, docetaxal etc. taxane report very good in anthracycline resistant patients. Taxane are radiosenstizing and cause apoptosis of cancerous cell in radiotherapy. Taxane cause apoptosis, frozen mitosis and bind reversibly to beta microtubule to stabilise microtubule complex, this caused microtubule polymerisation, cell cycle arrest and cause apoptosis (Moreno-Aspitia, Perez 2009). Taxane also used in the treatment of metastasis breast cancer in which HER2 gene is over expressed. Response rate is high with paclitaxel used in combination or alone and in neo adjuvant therapy. Some Problems associated with taxane: Worse emotional and mental quality of life throughout adjuvant treatment, High risk of psychological problem, Rate of recovery is very slow (Thornton et al. 2008) Ghersi et al research show an comparison between taxane/ non-taxane based regimen and showed that patient treated with taxane regimen show improved overall survival, time of progression and overall response rate and chemotherapy with taxane based regimen show improved overall survival rate . Patient treated with taxane show higher survival rate of 40-68% and in anthracycline resistant patient alone 52- 57%.
capecitabine is oral anticancer drug used for mylosupression.monotherapy with capecitabine is useful to treat advance stage metastatic breast cancer.capecitabine is a thymidine phosphorylase activated fluropyrimidine and used to genrate 5 flurouracil at tumour site. Many chemicals like taxanes,cyclophosphoamidee, mytomycin are used in combination with cepecitabine and show synergic effect, docetaxal and capecitabine is extensively used combination because of low price of treatment as compare to chemotherapeutic agents(Miles 2008).
Capecitabine is useful anticancer agent in breast cancer and show equal cytotoxic effects as like other drugs used for cancer treatment and inhibit growth of cancerous cells by inducing apoptosis. Capecitabine is a drug having fewer side effects as compare to other chemotherapeutic agents (Loo, Sasano & Chow 2007)
Role of TP53 in cancer:
P53 is protein having tumour suppressing activity which is produced by TP53 (Tumour protein 53) gene located on chromosome 17.This protein regulate cell cycle and prevent cancer. This has anti cancer role and cause apoptosis. Cancer occurred due to faulty copy of TP53 by mutation and this could be chemical, radiation or any other mean due to which TP53 lost his activity and cell start to grow in uncontrolled fashion and this is known as primary cause of cancer. (Ryan 2011)
Drugs in combination:
Combination of docetaxal and capecitabine show positive response in locally advance breast cancer. This combination makes surgery possible and increase disease free survival time. docetaxal and capecitabine are highly active combination in metastatic breast cancer(Twelves et al. 2008) and this is good alternative for non-anthracycline based treatments. Study done by Stefan Gluck et al shows that 3 cycles of Docetaxal, capecitabine as neoadjuvant therapy gives hightend pCR(Pathological complete response) (Hornberger, Jamieson & O'shaughnessy 2002). he shows that this is better alternative to non anthracycline based chemotherapy and this study also shows that HER2 positive/ HER2 negative patient should treat with not more than four cycle of this combination
Side effects of Docetaxal, capecitabine are: gastrointestinal side effects and hard foot syndrome.
This combination frequently used in treatment of HER2 positive breast cancer treatment because of less cardio toxicity and can be used with trastuzumab(Bonetti et al. 2007) .Trastuzumab have high clinical and pathological response in treatment of HER2 positive cancer. Some study shows that pre-operative treatment with docetaxal and trastuzumab should be used as standard treatment. Trastuzumab in combination with docetaxal and capecitabine show good response in HER2 positive patient breast cancer patient.
Combination of docetaxal, capecitabine, trastuzumab:
This is good to use this combination because of less cardio toxicity. docetaxal ,capecitabine, trastuzumab combination show more progression free survival time in HER2 positive patients as compare to docetaxal ,capecitabine. Glueket et al study shows more promising result with this combination In locally advanced breast cancer in HER2 positive type cancer and they also show that this combination is less cardio toxic,
(Ishida et al. 2009)Combination of Docetaxal, capecitabine and trastuzumab used as preoperative breast cancer treatment for HER2 positive and Docetaxal, capecitabine for HER negative breast cancer.
Cell proliferation controlled by p53 and p53 mutation status can be taken as predictive indicator in response to therapy. Amplichip method was used to detect this mutation because of incompatibity of immunohistochemical method to accurately find mutation status.
This test work on principle of DNA microarray "affinity and specificity of cDNA molecules to complementary base pairing and involve in the hybridisation of cDNA molecules to the DNA template from which they were originated" and detection is fluorophore based
This is used to find specific gene type of patient and on the basis of that can be predict how patient will respond to specific treatment. This chip is manufactured by affimatrix on the design of R.M.S. this microarray having 228484 probes on a square grid and each probe having multiple copies of specific nucleotide sequence. A single probe set for an interrogating base position includes five probes, one probe to hybridize to the wild type, three probes to detect three possible single base pair mutations, and one probe to detect single deletion analysis of data with detection algorithm can find out single base pair substitution, deletion with respect to wild type p53 DNA probe.
This dataset generated with 158 patient having breast cancer and treated with neoadjuvant docetaxal-capecitabine (with/without trastuzumab)treatment and surgery
Results: In subjects who completed treatment and surgery, the pCR and near-complete response rates were 15.8% in HER2-negative and 50% in HER2-positive subjects. Of 147 patients tested for p53 mutations, 78 variants were detected; 55 were missense. The response rate among TP53 mutated patients was 30%, significantly higher than the rate in TP53 wild-type patients .
How A.N.N was used in breast cancer treatment:
A.N.N was designed in which input was histological data of patient to detect breast cancer and this was best method to detect breast cancer among the existing methods. (Fogel, Wasson & Boughton 1995)
A.N.N was trained on family history of cancer, dietary variable, socio demographic, gyneco-obstetric factors. On this basis this A.N.N was able to separate group of women who have high chance of having breast cancer. (Ronco 1999)
A.N.N was designed to analyse quantitative data from M.R.I(magnetic resolution imaging). In this quantitative parameters from time-intensity profile were used as input. These factors were size of tumour, age, area under time intensity curve etc. and this A.N.N was capable to separate malignant to benign tumour. (Abdolmaleki, Buadu & Naderimansh 2001)
in this A.N.N was used with M.R.A.S(multivarient adopted regression). In this MRAS used in modelling breast cancer diagnostic problem and obtain variable as input of A.N.N, this improve classification efficiency of A.N.N model .this A.N.N input was taken from FNAC database of cancer patient. This A.N.N help to find important predictor variable which may provide information in further diagnostic purpose. (Chou et al. 2004)
A.N.N was used for estimation of tumour parameter in cancerous breast with thermogram. this approach can adopt to retrieve tumour location and radius with reasonable accuracy and patient may refer to higher level treatment or diagnosis like C.T(computerised tomography) scan, M.R.I(magnetic resolution imaging) scan (Mitra, Balaji 2010)
Recently, A.N.N also used to find biomarkers in the different cancers.
Artificial neural network (A.N.N):
This is computer based model of human brain which works in similar manner to biological neural network but having much faster analysis power than the human brain. A.N.N have three layers; input, middle and outer layer. Signal enter through input layer then pass to middle layer at this place processing of the input data take place and finally result from middle layer transfer to output layer and result comes out from outer layer. In A.N.N all nodes are connected with each other and having an assign value or weight. If input signal having that value then this will pass forward and finally come in form of output.(Abbass 2002)
A.N.N work very well with non linear data and rate of data processing is very fast. this is very fast and less error prone method apart from this sometime A.N.N Suffered from dimensionality problem when used to solve complex problem having large linear data.
Methods of learning:
In this type of learning A.N.N is trained by some special programmes to withdraw desired output from given set of data. In this we have the output value which we want and A.N.N adjusts the input values according to that and produce desired value.(Shukla, Raghunath 1999)
In this we don't have any special programme through which our A.N.N learn. In this A.N.N mode of learning based upon previous experience and this will learn as much this will entertain with new type of data for example. If A.N.N found new pattern which belong to previous cluster then this inclusion of this pattern take i to existing cluster and change in weight take place .which will characterise A.N.N. If this pattern does not belong to existing cluster then this will accommodate in to new class. (Sanger 1989)
In this project unsupervised learning will use and try to withdraw result from Dataset. A.N.N will try to find set of genes which are up/down-regulated. This group of certain gene would be biomarkers which show response in terms of chemotherapy.
We will use various statistical tools to validate and optimise results drawn from A.N.N. Tools selection will depend upon data generated from A.N.N . Primarily, these will include correlation, regression, t test and probalistic approach may be used.
These tests are used for
To check cause and effect relationship.
To check whether two variables are associated.
To estimate value of one variable corresponding to another variable.
Time guidelines for project:
This is six month project. In first month data mining take place along with different modelling pathways. In next three months I will do validation of data and finding of the result. In next one month of analysis of result and validation of result the final month will spent in preparing thesis and poster presentation.