Biomarkers in Cancer Prognosis & Treatment
Background
Lung cancer is the most common cause of neoplasia-related death worldwide. It is classified into two major subtypes, small-cell (SCLC) and non-small cell lung cancer (NSCLC). NSCLC constitutes 75% of lung cancer cases and is subdivided further into three major histological subtypes: adenocarcinoma (AC), squamous-cell carcinoma (SCC) and large-cell carcinoma. Three new entities with a poor prognosis have been included recently: large-cell neuroendocrine carcinoma (LCNEC), basaloid carcinoma (BC) and pleiomorphic carcinoma. The AC and SCC subtypes represent >85% of all cases of NSCLC.
Despite advances in surgery and treatment, the five year survival rate for lung cancer has not improved significantly during the last 15 years, remaining at about 15% for all stages. The major reason for the low survival is that at the time of diagnosis most of the patients are beyond effective treatment.
Transformation of a normal phenotype into a malignant phenotype is a consequence of accumulation of multiple genetic and epigenetic changes, each conferring one or another type of growth advantage.
Essential alterations in cell physiology that collectively dictate malignant growth are:
- self-sufficiency in growth signals
- insensitivity to growth-inhibitory (antigrowth) signals
- evasion of programmed cell death (apoptosis)
- limitless replicative potential
- sustained angiogenesis and
- tissue invasion and metastasis
Additionally, malignant transformation is characterized by genomic instability, chromosome instability (CIN) and microsatellite instability (MIN), which represents the means that enables evolving populations of premalignant cells to reach these biological endpoints.
Transformation of a normal into a malignant phenotype
Mutations of oncogenes and tumor suppressor genes lead to transformation of a normal into a malignant cell, which in most cases is destroyed in the body by immune surveillance and other mechanisms (dark cells). Some malignant cells might escape the immune system and expand to a microscopic mass consisting of a few hundreds of cells (green cells). These cell populations can no longer grow beyond the sizes of 2-3 mm3 without recruitment of new blood vessels. However, tumor cells might still actively divide in the microscopic dormant tumor until they become angiogenic tumor cells (red cells). Once an angiogenic phenotype is switched on, tumor growth and progression is exponential.
Scheme modified from: Cao Y. Tumor angiogenesis and molecular targets for therapy, Frontiers in Bioscience 2009; 14: 3962-3973
Genomic instability, also referred to as the mutator phenotype, designates the increased mutation rate that occurs in neoplastic cells. The induction of the genomic instability phenotype is emerging to be a crucial early event in carcinogenesis that enables an initiated cell to evolve into a cancer cell by achieving a greater proliferative capacity and genetic plasticity which can overcome host immunological resistance, localized toxic environments and a suboptimal supply of micronutrients.
The high incidence of genomic instability in lung cancers is well established and in some cases it was associated with prognosis. Microsatellite instability (MIN) in lung cancer ranges from 45-76% for SCLC and from 2-34% for NSCLC. In lung cancer, MIN is probably the result of inactivation of mutation repair genes and less common than in cancers of the digestive tract. Chromosomal instability (CIN) is a common feature in lung cancer cell lines and it is associated with the presence of significant aneuploidy. CIN was also detected in surgical specimens from patients with NSCLC and was correlated with poor prognosis.
Microsatellite instability
Microsatellites are short, repetitive DNA sequences that are scattered throughout the genome. Microsatellite instability (MSI), is a marked difference in the number of repeated sequences between tumor and normal tissue. MSI is a hallmark of hereditary nonpolyposis colorectal cancer (HNPCC) tumors, and it is caused by errors in DNA replication due to mutations in DNA repair genes.
Scheme modified from: www.jamesline.com
Currently, lung cancer staging rests on histopathological and clinical criteria that have only limited power to predict relapse and survival. Moreover, our ability to predict responses to chemotherapy or targeted agents is extremely limited based on tumor histology alone. Improving the survival rate for lung cancer patients requires the comprehension of all molecular events leading to lung cancer development and progression. Identification of such biomarkers could enable the identification of patients at risk for developing NSCLC, improve the early detection of lung cancer in high-risk patients and provide clinicians the molecular profile of a given tumor to help them predict patient outcome and response to chemotherapy.
Economic Burden
The rapid increase in the cancer burden represents a real crisis for public health and health systems worldwide. A major issue for many countries, even among high-resource countries, will be how to find sufficient funds to treat all cancer patients effectively and provide palliative, supportive and terminal care for the large numbers of patients, and their relatives, who will be diagnosed in the coming years. According to Lance Armstrong Foundation cancers have already progressed to where they are incurable in 80 % of patients in developing countries. Evidence shows that only 5 % of global resources for cancer are spent in the developing world. Low and lower-middle income countries will make up 46 % of new cancer cases in 2009.
The costs of illness are the monetary and non-monetary losses from cancer, and economic costs are those that can be expressed in monetary units. The National Institutes of Health – National Cancer Institute estimate overall costs of cancer in USA in 2007 at $219.2 billion. Direct medical costs of $89.0 billion result from the use of resources for medical care to prevent, diagnose and treatment and for the continuing care, rehabilitation and terminal care of patients. Indirect morbidity costs of $18.2 billion come from the loss of resources – the time and productivity lost or foregone by the patient, family, friends and others from employment, volunteer activities, leisure and housekeeping. Psychosocial or indirect mortality costs of $112.0 billion come from reduced quality of life from disability, suffering and pain which force undesirable changes in lifestyle such as economic dependence, social isolation, changes or loss of job opportunities or changed conditions of living. Considering all cancers, the human capital loss is considerable lower than the value of life lost from cancer deaths ($116 billion to $232 billion vs. $961 billion, respectively, as indicated by National Cancer Institute).
The way to reduce the value of years of life lost due to cancer is to find better prevention, screening, and treatment modalities and to make sure those technologies are applied comprehensively and cost-effectively. Clearly, the value of human capital loss and life lost from cancer far exceeds the research investment (the National Cancer Institute's budget for 2008 is about $4.8 billion).
The Need
Each year 10.9 million people worldwide are diagnosed with cancer and there are 6.7 million deaths from the disease. It is estimated that there are 24.6 million people alive who have received a diagnosis of cancer in the last five years. Cancer rates could further increase by 50% to 15 million new cases in the year 2020.
According to a new World Cancer Report from the International Agency for Research on Cancer, cancer is expected to overtake heart disease as the number one killer of people around the world by the year 2010. By 2030, the number of new cancer cases is expected to rise to 27 million, with 17 million cancer deaths.
Cancer is one of the leading causes of death worldwide (12.5%) and in the EU. The European Cancer Leagues states that 2 million Europeans are diagnosed with cancer every year. In addition, the European Cancer Patient Coalition says that:
- There are more than 1.1 million cancer deaths in Europe each year;
- Every day 5,214 Europeans are diagnosed with cancer and 3,185 die from their disease;
- Lung cancer is the most common form of cancer, followed closely by colorectal cancer;
- Lung, colorectal and breast cancer account for two-fifths of the entire European population living with cancer;
- The number of Europeans with cancer will increase dramatically over the next 20 years.
According to Eurostat 2006, the age group 45-64 years (41%) is especially at risk of developing cancer. In this age group, the most common cancers in males are of the respiratory system, i.e. lung or throat cancer. Amongst women, the most common type is breast cancer, accounting for 48 deaths per 100,000 women in the EU. The highest cancer rates in the EU are found in Belgium, the Netherlands, and Luxembourg; the lowest rates are in Portugal, Greece, and Spain.
Current Approaches
The diagnostic evaluation of patients with suspected lung cancer includes tissue diagnosis; a complete staging work-up (how far has the tumor advanced), including evaluation of metastasis; and a functional patient evaluation. Treatment and prognosis are closely tied to the type and stage of the tumor identified. For stages I through IIIA non-small cell carcinoma, surgical resection is preferred. Advanced NSCLC is treated with a multimodality approach that may include radiotherapy, chemotherapy and palliative care. Chemotherapy (combined with radiotherapy for limited disease) is the mainstay of treatment for SCLC.
There has been an immense progress in the elucidation of the molecular and cellular pathobiology of lung cancer in the last 10 years as well as the advent of the third generation of cytotoxic chemotherapeutic agents (such as paclitaxel, docetaxel, gemcitabine, vinorelbine). Despite this progress, the median life expectancy of patients with lung cancer is less than 5% 10 years after diagnosis, but it increases to 60% when treatment is started at stage I. Early detection of disease by spiral CT scanning and autofluorescence bronchoscopy can certainly detect lung cancer that is curable, but there are enormous selection and follow-up logistical issues and cost-effectiveness considerations to solve.
The focus of intense research is now on molecular targeted therapeutic agents and biological agents that exploit unique vulnerabilities of cancers based on unique signaling pathways unrelated to DNA synthesis and repair. Our ability to predict responses to chemotherapy or targeted agents is extremely limited based on tumor histology alone. More accurate staging of patients using genetic, epigenetic and proteomic technologies may completely change our approach to treating lung cancer. The most compelling argument for response prediction based on molecular markers is the use of epithelial growth factor tyrosine kinase inhibitors (EGFR-TKIs), like gefitinib in lung cancer. A series of mutations in the epidermal growth factor receptor (EGFR) renders the tumors highly sensitive to this form of therapy, and detection of these mutations can accurately predict the response to these agents.
The role of EGFR in cancer
The epidermal growth factor receptor (EGFR) is one of four receptors in the HER (human epidermal growth factor receptor) signaling pathway. EGFR and other components of the HER signaling pathway interact in a complex and tightly regulated manner to regulate cell growth. Alterations in the amount or activity of HER family members may cause or support the inappropriate cell growth that leads to proliferation, migration, and survival of cancer cells. Because the signaling pathway works as a cascade that amplifies the growth signal at each step, small changes in the amount or activity of EGFR may significantly drive the development, or progression, of cancer by promoting cell growth and metastasis (cell migration) and inhibiting apoptosis (programmed cell death).
Scheme modified from: www.cancercell.org
Defining molecular biomarkers for lung cancer will have applications for establishing disease predisposition, early detection, cancer staging, therapy selection, identifying whether or not a cancer is metastatic, therapy monitoring, assessing prognosis, and advances in the adjuvant setting.
Our Solution
Our aim was to measure the frequency of gene mutations and chromosomal aberrations (frequency of genomic instability) in genomes of patients with NSCLC and to identify genes that are altered during NSCLC promotion and progression because we expect that some of them might show to be good prognostic biomarkers for NSCLC patients and therapy targets that would enable the application of personalized treatment. Multiple DNA fragments from anonymous regions of the complete genome were amplified without any previous knowledge of DNA sequences.
DNA isolation methods
Many different methods and technologies are available for the isolation of genomic DNA. In general, all methods involve disruption and lysis of the starting material followed by the removal of proteins and other contaminants and finally recovery of the each patient DNA.
Scheme modified from: www.agen.ufl.edu
DNA was extracted from paired tumor and normal tissue samples obtained from patients with NSCLC who underwent surgery. Frequency of gene mutations was determined comparing the DNA profiles of paired normal and tumor DNA samples of the same patient. Comparing DNA profiles we detected mutated genes in all cases. Gene mutations (changes in the DNA sequence) can be seen as a band present in tumor vs. healthy tissue. Altered band intensities represent the manifestations of amplifications or deletions of existing chromosomal material.
DNA profiles of tumor (T) and normal (N) tissues of patients with NSCLC presented on polyacrilamyde gels
Numbers: 15, 16, 17, 22, 23, and 24 represent patient. Each band represents part of a genome. Arrows indicate bands that were retrieved from the gel and identified. Names of the identified genes are denoted above the arrows: E2F transcription factor 4 (E2F4), killer cell immunoglobulin-like receptor (KIR) and cytochrome P450, family 4, subfamily Z, polypeptide 1 (CYP4Z1).
In an attempt to identify some of these DNA changes, twenty one unique bands present only in tumor but not in normal tissue were retrieved from the gels and identified. Following mutated genes were detected: tetraspanin 14 (TSPAN14), cadherin 12 (CDH12), retinol dehydrogenase 10 (RDH10), cytochrome P450, family 4, subfamily Z, polypeptide 1 (CYP4Z1), killer cell immunoglobulin-like receptor (KIR), E2F transcription factor 4 (E2F4), phosphatase and actin regulator 3 (PHACTR3), PHD finger protein 20 (PHF20), PRAME (preferentially expressed antigen in melanoma) family member and solute carrier family 2 (facilitated glucose transporter), member 13 (SLC2A13).
Moreover, we were able to identify types of mutations in detected genes. Some mutations most probably produce severely altered and potentially non-functional proteins while other might yield inactivated or functionally altered proteins which all would provide a good background for cancerogenesis.
Correlating frequency of gene mutations observed in all patients with their gender, the age at the time of diagnosis, the NSCLC subtype, histological grade and stage of the tumor, necrosis presence in the tumor and lymph node invasion we found that it was significantly higher in patients with adenocarcinoma than in patients with squamous-cell carcinoma. Most importantly, it decreased as the tumor grade increased. Also, better survival was observed in patients with higher frequency of gene mutations, i.e. with well differentiated tumors. Our results suggest that the high frequency of gene mutations in the early stages of cancer development may be involved in NSCLC progression, and may be a marker of NSCLC prognosis (Markovic et al, 2008).
Kaplan-Meier survival curves
(click the image to see a high resolution version)
- Patients with mutated TSPAN14 lived shorter (a); patients without mutated CDH12 lived shorter (b); patients without mutated CYP4Z1 lived shorter (c); patients with mutated RDH10 lived shorter (d); patients with mutated KIR lived shorter (e);
- Patients with mutated E2F4 lived significantly shorter (f); patients with mutated PHF 20 lived shorter (g); patients without mutated PRAME family member lived shorter (h); patients with mutated PHACTR3 lived significantly shorter(i); patients without SLC2A13 lived shorter (j).
When examining the mutated genes in relation to NSCLC subtype, histological grade and stage of the tumor, lymph node invasion and patients’ survival we observed that some of them were associated with promotion, some with progression and some with non-small cell lung cancer genesis (Bankovic et al, 2009). We expect that some of them might show to be a good prognostic biomarker for NSCLC patients or targets for therapy. This would enable the administration of personalized treatment which, as is expected, would improve the survival rate of patients with NSCLC.
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