Personalized Cancer Chemotherapy

An Effective Way of Enhancing Outcomes in Clinics

Da Yong Lu

• Publisher: Woodhead Publishing
• Year: 2014
• ISBN:
  9780081003473
• Topic: Medicine
• Subtopic: Pharmacology

Personalized Cancer Chemotherapy separately describes and addresses "individualized cancer chemotherapy" (ICC) strategies new and old, to provide readers with new insights into their characteristics and techniques, as well as key debates and future trends in this area. The book devotes chapters to drug sensitivity testing, cancer biomarkers and bioinformatics detection, pharmacogenetics, individualized antimetastatic therapy, drug combinations, assistant chemotherapy, and cost-effectiveness considerations.

A major obstacle to controlling cancer growth and metastases in patients is the inappropriate use of anticancer and antimetastatic drugs. Researchers and clinicians are now beginning to focus on ICC also called "personalized cancer chemotherapy" (PCC), to improve therapeutic quality and outcomes by selecting and prescribing the most appropriate and effective drugs. Using genetic, molecular, and bioinformatics data and modern experimental techniques, known tumor genes can be detected more easily than ever before; the average speed of genetic sequencing has increased 15, 000 to 50, 000 times since the Human Geonme Project was completed.

This book will help readers understand the pros and cons of each individualized cancer chemotherapy strategy from different angles so as to make good judgments and predictions of drug responses and clinical outcomes.

• Explores the central components of cancer treatment
• Investigates new developments in cancer treatment
• Discusses the many strategies of individualized cancer chemotherapy

1

Introduction

Abstract

Cancer is the disease with a common pathological feature of unlimited growth and sometimes invasion and metastasis. Some parts of cancer patients are not given proper treatment by conventional cancer treatments. Individualized cancer chemotherapies (ICC) are designed to improve cancer patients’ treatment outcomes.

Present understanding and predictions of drug toxicities and responses to tumor growth or metastases in cancer patients are not well-formed, mostly from doctors’ past experience—empirical. Four types of ICC methodologies are introduced in this book. The advantages and weaknesses and future trends of each ICC are given and highlighted.

Keywords

Individualized cancer chemotherapy; personalized medicine; cancer treatment; drug sensitivity testing; pharmacogenomics; cancer biomarkers; antimetastatic therapy; assistant therapy; biotherapy; drug combination; traditional Chinese medicine; cost-effective strategy; stem cells

Cancer treatment is an unsolved, thorny problem. Cancer is one of the leading causes of human deaths all over the world. Paradoxically, given our expectations, we have achieved very little in this respect, despite the huge amount of money and human resources that have been expended. There is a plethora of reasons for this situation. Two are particularly important:

1. different cancers respond to different anticancer drugs and we cannot accurately predict responses to a given type of anticancer drug;

2. there is up to now no good way of treating tumor metastasis in clinics, especially on formed metastatic nodules.

To solve these two problems, we address, review and discuss many ideas for individualized cancer chemotherapy in clinics in this book with the hope that readers will have in-depth perspectives for these two problems, so as to be ready to find better answers to these and new challenges.

Cancer is a number of different diseases, all with the pathological feature of unlimited growth. The hallmarks of cancer can be many different genes and many different series of stages [1–2]. Since tumors originate from a widely varying background of genotypically or phenotypically abnormal tissues that cause the unlimited growth of cells, different genotypically or phenotypically abnormal tissues ought to be sensitive to and so matched with different anticancer drugs. Thus, most cancer patients are unsuited to the use of ‘uniform’ or ‘standardized’ chemotherapy [3–4]. As no single drug or combination has so far been found to be optimal for cancers of all origins, developing a good and clinically sensitive anticancer drug selection system is no less important than the discovery of new anticancer drugs. ‘Individualized cancer chemotherapy’ (ICC) or ‘personal cancer chemotherapy’ (PCC) is designed and tailored to meet this requirement of improving therapeutic quality by selecting and prescribing well-matched anticancer drugs and avoiding ineffective anticancer drugs by adopting a series of systematic methodologies in clinics [3–4].

The first experiments relating to this issue date back to the early 1950s [5–6]. Those reports hypothesized and testified the experimental basis for evaluating anticancer drug sensitivity to tumor samples obtained from human cancer tissue and offering the most sensitive anticancer drugs to these cancer patients—drug sensitivity testing. Systematic investigations and utilization of drug sensitivity tests in clinics began in the late 1970s [7–9]. Since then, drug sensitivity tests have been the mainstream of ICC strategy up to 2000, and continue to be one of the best means of selecting chemotherapeutic agents for future clinical practice. (Chapter 2)

Cancer is a disease of genetic alteration and abnormalities. The best therapeutic approaches should target these genetic alterations and abnormalities. However, different cancers are caused by different genetic alterations and abnormalities. Thus, before an appropriate therapy can be initiated, the exact genetic alterations and abnormalities of a specific cancer must be known in the treatment clinic. Only genetic, RNA or protein detection of these genetic alterations or abnormalities in tumor cells can offer the useful prediction of possible anticancer drug responses we need for individualized cancer chemotherapy. Genetic, RNA or protein detection of cancer represent the exact sites of oncogenic or metastatic processes and underpin modern individualized cancer chemotherapy. They can be divided into two general categories:

1. Detection of the quantities of tumor biomarkers at subquantitative or quantitative level to predict the use of anticancer drugs targeting the detection of increasing levels of oncogenic and metastatic molecules. We categorize this as ‘detection of cancer biomarkers’;

2. Detection of polymorphism of human or tumor genes to predict the anticancer drugs which will be active to tumor tissues and in human bodies. We categorize it as ‘pharmacogenomics of anticancer drugs’.

In this book, two chapters (3 and 4) address these topics, including many basic rules relating to genetic, RNA, protein or glycol-protein detection for drug choice from detected oncogenic or metastatic sites in tumors and pharmacogenetics to predict drug doses, toxicity and responses to cancers.

Previously, cancer biomarker detections have been focused on one or several molecules (commonly protein or glycoprotein biomarkers such as HER-2) of tumor tissues in one patient. At the start of the 21^st century, the genetic disorders related to cancer etiology and therapeutics have become easier to identify and detect in high throughput ways—cancer bioinformatics [3–4,10–14], and there has been a new trend towards utilizing these high throughput bioinformatics data as drug-selective criteria for ICC [3–4,10–14]. Using bioinformatics data and modern experimental techniques, known tumor gene or protein abnormality can be detected more easily and with higher throughput than ever before. The detected genetic molecules can be determined, at the highest, at as many as 70 genetic alleles in one test [13]. These types of techniques will be used widely in future. (Chapter 3)

Pharmacogenetics also predicts which drug might work in an individual patient, and at what dosage range, and if one type of anticancer drug is suitable for a specific cancer patient to have the drug metabolite in active concentrations [15–18]. These types of research can meet some of the requirements of selecting drugs that are potentially sensitive to an individual, but it is better to use this type of method with other ICC methods, such as drug sensitivity tests or tumor biomarker detections.

90% of cancer patients die of cancer metastasis. Currently, however, cancer chemotherapies are mainly focusing on anticancer drugs targeting the primary tumor, not the metastatic foci. So although primary tumors have been inhibited by sensitive antiproliferative drugs, patients’ survival rates have been increased very little [4]. If we change our focus to the development of effective antimetastatic drugs and individualized cancer metastasis, chemotherapy strategies can be targeted for patients in late stages of cancer. Thus we might expect in future to enhance patients’ survival rates with the use of individualized antimetastatic therapies [19–22]. Chapter 5.

Most cancers have multiple genetic alterations or abnormalities [1–2]. It is seldom very useful to use only one anticancer drug in clinical cancer treatment. Presumably, one of the best strategies is the combinatory use of anticancer drugs, especially combinations of chemicals and biotherapies or combinations of antiproliferative anticancer drugs with antimetastatic agents. If chemical anticancer drugs kill 70% to 90% of tumor cells, the highly specific biotherapies or antimetastatic drugs can kill the rest. It is expected that these strategies will be a paradigm in future cancer chemotherapy [4,23]. Chapter 6.

The causes of death of cancer patients can be multi-factorial in clinics. Apart from direct causes, from tumor progressions, other clinical complications (such as venous thrombosis) or psychiatric factors will speed the death of many cancer patients. So many assistant therapies have been developed, which help the patients who have some clinical complications or psychiatric issues [4] and considerably increase patients’ survival rates. Chapter 7.

Cost-effectiveness is a long-standing medical problem and is also an early concern of mathematics in ICC. Increasing efforts to develop ICC are generally paralleled by rising diagnostic costs. Systematic evaluation of the relationship between the running costs and benefits of ICC is crucial in updating the ICC system and making it available in the long run, since the cost of therapy is a critical matter for patients and doctors to consider. From previous studies, many diagnostic methods can be shown as cost-effective, because the cost of cancer biomarker detection or gene polymorphism detection is commonly smaller than that of many anticancer drugs, or of time in hospital. If we use the right anticancer drugs, because we know the cancer biomarkers, patients’ survival rates will increase substantially, especially in early stages [24]. Chapter 8.

Further information will be outlined in detail, discussed and concluded in the following sections. Chapters 9 and 10.

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