Breast Cancer Against Anthracycline Taxane Based Chemotherapy Biology Essay

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This project will primarily focus on the finding of the biomarkers in response to the taxane/anthracycline based chemotherapy. Biomarkers are the basically product of genes whose expression increase or decrease in particular biological state. Chemotherapy is effective way to treat ER negative cancer and show increased death free survival time (D.F.S). But problem associated with chemotherapy is lots of side effects in human and same dose of chemotherapy can't be used for the desired results in each and every patient. In this project I will try to find biomarkers in 161 patient's database 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 and show heightened complete pathological response in patients who takes this therapy. 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:

Biomarkers could be anything which tells us about any particular state of body. But mostly Biomarkers are gene products and their expression increase / decrease in particular state of body. 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 cancer breast cancer is the second diagnosed cancer in the world. ER negative breast cancer cells are more aggressive and unresponsive to hormone therapy. Chemotherapy is the treatment which can control growth of ER negative cancerous cells effectively.

Chemotherapy:

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.

Chemical used in chemotherapy:

Anthracyclin :

These are chemical compound which are produced from streptomycin, various form of anthracyclin like doxorubicin, epirubicin etc. are used in the treatment for cancer and show inhibitory effect on growth of cancerous cells. anthracyclin killed cell by Damaging cell membrane, Damage DNA/RNA of cancerous cell, Inhibit topoisomerase -2 and inhibit transcription and translation(REF A2), Promote apoptosis via P53 DNA damage sensor and cascape mechanism(R MIX 3 COMBINED USE)

Doxorubicin:

Initially doxorubicin was used for treatment of advanced stage of breast cancer which shows great response rate. doxorubicin was used in both ways alone and in combination with other chemicals in adjuvant therapy. Beuzeboc and college report improved survival in high risk in premenopausal breast cancer MMAC combination .it has been shown that women receive doxorubicin having high survival rate and sequential treatment with doxorubicin is more effective then CMF alone. Some Side effects associated doxorubicin are: High dose of doxorubicin cause cardio toxicity, Nausea, vomiting, mucositis occur in high doses range, Not fit for long term use

Epirubicin:

This is the substitute of doxorubicin and less toxic(REF ANTHRACYLIC INRO 1).problem associated with epirubicin was higher dose because in chemotherapy epirubicin dose is 1.5 times then doxorubicin. major advantage with this less cardio toxicity then doxorubicin(REF A2).In combinational therapy cumulative cardio toxicity is lower with epirubicin then doxorubicin(REFA into 3).

Anthracyclins are used in various regimens. Antracyclin in FEC regimens used as neo-adjuvant therapy. FEC used to treat primary and secondary breast cancer and kill cells by interfering in their growth and cell division. Sometimes we can't use FEC combination for cancer patient who have heart disease because epirubicin is not suitable for such group of cancer patients.

Taxane:

These are chemical compound which produce naturally by genre "taxus" and causing less cytotoxicity then anthracyclin. Most commonly used taxane are paciltaxal, dociltaxal etc. taxane report very good in anthracyclin resistant patients. Taxane are radiosenstizing and cause appotosis of cancerous cell in radiotherapy. Taxane cause apoptosis, frozen mitosis. Taxane bind reversibly to beta microtubule to stabilise microtubule complex, this caused microtubule polymerisation, arrest cell cycle and cause apoptosis(REF R MIX 3).paciltaxal used as adjuvant therapy for early and advance state breast cancer?(r mix r2).Taxane can be used alone or in combination of chemotherapeutic agents. Taxane also used in the treatment of metastasis breast cancer in which HER2 gene is over expressed. Response rate is high with paciltaxal 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(r mix r2)

Combination of antracycline and taxane:

Apart from mono therapy, anthracyline and taxane are used in combinations to increase disease free survival in breast cancer. Taxane in combination with anthracyclin have less toxicity and reduce risk of occurrence of operable breast cancer(mix 2). In combinational therapy paciltaxal is less effective then dociltaxal. More use of these anthracyclin/taxane combinations makes these tumour resistant to treatment. So we should use appropriate combination for the treatment.

Dataset E-GEOD-6861:

This dataset is taken from E.M.B.L'S(European Molecular Biology Laboratory) array express and developed by the Potti/Nevins group at Duke University. This database contain transcriptional profiling of 161 needle biopsies of locally advanced or large operable breast tumour patients who were treated with anthracyclin/taxane chemotherapy. in this database was comparison FEC(anthracyclin based) and ET(taxane based).in this six cycles of FEC followed by three cycle of ET and their response was noted 28/65 show pathological complete response (pCR) to FEC arm and27/59 show pathological complete response (pCR) to ET arm in ER negative tumour. Transcriptional profiling of this database was done by Affymetrix microarray.

Dna microarray:

Principle of DNA micro array is"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. Affymetrix microarray was used in database. In which quartz made microarray chips were used and speciality of this microarray is to test the presence of specific gene in to biological sample and we can use thousand of genes in this microarray and check their presence in the cdna. Affymetrix microarray was used to find expression of the various genes in the patients who show complete and incomplete pathological response(pCR) in response to therapy and whole data was generated.

How A.NN was used in breast cancer treatment:

In 1995: 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.

In 1999: 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.

In 2001: 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.

In 2004: 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.

In 2010: a.n.n was used for estimation of tumour parameter in cancerous breast with thermogram. this approach can adopt to retrieve tumour location and radious 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

Recently, a.n.n also used to find biomarkers in the different cancers.

How this technique is going to help:

Different people have different genetic makeup and have different response to therapy according to their genotype. I will try to find biomarker of response to patient in cancer therapy by which one can personalised this chemotherapy treatment according to patient and can give rise to increase complete pathological response. These biomarkers will also help us to find out group of patients on which this therapy will not work and that group of patients may check for another combination of chemotherapy. In this Database E-GEOD-6861 is high accuracy of N.P.V which helps us to screen patients who will not respond to therapy and can prevent from possible side effects of that chemotherapy which are not going to help them in treatment.

These biomarkers will help to reduce diagnosis time of patient because chemotherapy result will come after some time in patient with possible side effects of chemotherapy .if result shows this given chemotherapy was not effective then patient may switch to another one. But we can't do experiment all the time because this depend upon condition of patient whether he is capable for the further treatment with chemotherapy or not. Sometimes side effects of chemotherapy are as much severe that patient can't bear side effect of another experimental chemotherapy and may died due to long time in finding of appropriate chemotherapy.

By performing chemosensitivity of biopsy sample. We can find expression of genes in patient through microarray technique and by the help of A.N.N we can find out whether this therapy will show response to patient or not and help to increase D.F.S time in patient who take this chemotherapy

Technique will use in project:

Artificial neural network (A.N.N):

This is computer based model of human brain which works in similar manner to biological neural network but much faster than the human brain. A.N.N have three layers; input, middle and outer layer. Signal is enter through input layer then come to middle layer and 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 this 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 out put.

http://smig.usgs.gov/SMIG/features_0902/tualatin_ann.fig3.gif

Methodes of learning:

Supervised 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.

Unsupervised learning:

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.

Problem associated with A.N.N

Difficult to interpret how this reach to optimal solution

Suffered from dimensionality problem when used to solve complex problem having large variables.

by the use of A.N.N we will find which set the genes are up/down-regulated. This group of certain gene would be biomarkers which show response it terms of chemotherapy.

Statistic tools:

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.

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