is part of the Global Exhibitions Division of Informa PLC
This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 3099067.
By Dr Alvin Lim, Deputy Head, Cytogenetics Laboratory, Department of Molecular Pathology,
Division of Pathology, Singapore General Hospital
13 September 2016
Since the announcement of the first working draft of the Human Genome on June 26, 2000, then President of the United States, Mr Bill Clinton had declared, “Genome Science will have a real impact on our lives - and even more, on the lives of our children. It will revolutionise the diagnosis, prevention and treatment of most, if not all, human diseases.” Indeed, the diagnosis, prevention and treatment of genetic diseases since then have seen a remarkable progress in the development of personalised medicine, such as the development of imatinib (Gleevec), a tyrosine-kinase inhibitor used to treat multiple cancers, most notably chronic myelogenous leukaemia (CML) in a targeted manner. The drug has doubled the five-year survival rates of CML patients.
So it is surprising that it was just 60 years ago that the correct number of human chromosomes was identified. Working on human embryonic lung fibroblasts and a modified protocol, Tjio and Levan demonstrated that the number of chromosomes in man was 46 when it was previously thought to be 48. However, the metaphase preparations then were solid stained, so that it was not possible to distinguish the chromosomes beyond classifying them into broad chromosome groupings. The banding era followed in the 70’s. In 1971, Caspersson and his colleagues at the Karolinska Institutet, Sweden, elicited the first chromosome banding technique, Q-banding, allowing all human chromosomes to be identified for the first time. The more widely-used G-banding technique, still employed today, followed shortly, and this enabled Janet Rowley in 1973 to recognise that the Philadelphia chromosome in CML was not a deleted chromosome 21 but was a result of a reciprocal translocation between chromosomes nine and 22. This was the first recognised chromosomal aberration associated with a malignancy and it heralded the discovery of many more recurrent rearrangements in cancers.
G-banded karyotyping is still by large the gold standard in the evaluation of chromosomal abnormalities. It provides for a genome-wide view of all the chromosomes in the metaphase cell with information on the numerical and structural rearrangements in the clonally abnormal cell. Many of the aberrations have prognostic value, which guides the clinician in patient management, such as the type of treatment to administer. These recurrent rearrangements help stratify patients into favourable, intermediate and poor prognosis groupings and move away from standard chemotherapy regimens toward personalised medicine with superior overall survival and progression-free survival rates.
The technique has severe drawbacks though, such as the need for freshly acquired viable tissues, is tedious and labour intensive, is dependent on mitotically active cells, and suffers from a low abnormality detection rate. Consequently, chromosomal analysis cannot be done on frozen or formalin-fixed paraffin embedded (FFPE) archived samples. Karyotyping necessitates a period of cell culture and this translates to a longer result turnaround time. Even with fresh samples, at times normal haematopoietic cells divide preferentially over tumour cells so that a less than helpful normal result is obtained while the clonally abnormal karyotype is missed. In particular, aberrant plasma cells in plasma cell dyscrasias like multiple myeloma are notoriously indolent in tissue cultures so the detection rate of clonal abnormalities is reportedly around just 30%. Subtle rearrangements like small deletions or amplifications, or translocations involving the terminal regions, can be missed as the chromosomal resolution of haematological samples is at best around 400 bands per haploid set (BPHS) or about 20 Mb while genes are in the order of kb in size.
Fluorescence in Situ Hybridization (FISH)
To circumvent many of these limitations, fluorescence in situ hybridization techniques were introduced to the diagnostic laboratory. The FISH era in clinical applications began ω in the 1990s and quickly proved its value in eliciting answers to specific questions. Whereas karyotyping requires a period of cell culture, FISH is a rapid and highly specific assay that is independent of cell culture and which can be applied to both metaphase and interphase cells. It has a high resolution of 100kb or less. In the context of multiple myeloma, FISH can reportedly increase the detection rate to 67-78%. This is over and above the aforementioned karyotyping detection rate of 30%. Additional techniques can be employed to increase the detection rate. This may be accomplished by either identifying the plasma cells during FISH analysis utilising cytoplasmic immunoglobulin-FISH (cIg-FISH) for a targeted analysis or purifying the population of plasma cells through the use of magnetic cell-sorting procedures on CD138+ plasma cells. With such techniques, the abnormality detection rate can be dramatically increased to over 90%.
FISH can also interrogate FFPE specimens to detect gene-specific abnormalities. Depending on the probe construction type (dual fusion, break apart, or locus specific), specific known translocations including cryptic rearrangements, copy gains and losses can be elucidated. Patients with adenocarcinoma type non-small cell lung cancer who are anaplastic lymphoma kinase (ALK) gene-rearranged are highly sensitive to therapy with an ALK-targeted small molecule tyrosine kinase inhibitor such as crizotinib. FISH is considered the gold standard method for detecting ALK rearrangements.
Despite its wide range of applications, the FISH technique suffers from being too specific in that only a few probes can be applied to a single assay. This is due to the limited number of fluorophores available and consequently only a few genes can be detected per assay. The consequence is an exponential increase in costs when a number of tests on different genes / loci need to be performed. Moreover, there also needs to be fore-knowledge of the disease type in order to decide on the type of FISH probes to use.
Chromosome Microarray Analysis (CMA)
Clinical applications of microarray technology began in the new millennium with the International Standards for Cytogenomic Arrays (ISCA) Consortium and the American College of Medical Genetics releasing a consensus statement in 2010 that CMA should be a 1st tier clinical diagnostic test (ahead of karyotyping) for individuals with developmental disabilities or congenital anomalies, including developmental delay, intellectual disability, autism spectral disorders, or multiple congenital abnormalities. This is because CMA combines the genome-wide view of the DNA by karyotyping with the specificity of FISH, enabling the detection of multiple gains and losses of DNA across the entire genome in a single assay, including cryptic ones. It has the added advantage of being totally independent of cell culture or even of viable cells. When single nucleotide polymorphisms (SNPs) are incorporated into the chip, the assay can detect copy-neutral loss of heterozygosity, a common feature in cancer. The technique is however unable to detect balanced rearrangements like reciprocal translocations which are seen frequently in haematological disorders, as well as being unable to detect other chromosomal abnormalities when the abnormal cell population is below 20%.
The cancer consortium equivalent, the Cancer Cytogenomic Microarray Consortium, later renamed the Cancer Genomics Consortium (CGC), had hoped to quickly leverage on the technology and apply it to cancers. Unfortunately, it has taken some time for the medical oncology community to espouse the technique, which until now has been reliant largely upon karyotyping and FISH. In the context of multiple myeloma, CMA performed on an enriched population of CD138+ plasma cells can detect close to 100% of the clonal abnormalities. CMA when combined with karyotyping or FISH becomes a very powerful diagnostic tool. With the recent 2015 CGC publication in Cancer Genetics conclusively demonstrating the clinical utility of CMA on haematological disorders and renal epithelial tumours, perhaps the test might soon find more support from clinicians.
Next Generation Sequencing (NGS)
Hailed as the next breakthrough in genomics testing and a tool for precision medicine, NGS is possibly one of the most significant technological innovations in diagnostic pathology over the past few decades. The technology allows massively parallel sequencing of millions of DNA templates and is thus largely poised to replace the existing Sanger sequencing or PCR-based assays for genetic testing. Compared to Sanger sequencing, NGS has increased the throughput of DNA sequencing by >500,000 times, while at the same time drastically lowering the costs of sequencing. To put into perspective, the Human Genome Project took 13 years to complete at the cost of US$3 billion to sequence the first human genome by Sanger sequencing. Using NGS, sequencing a human genome costs an average of between one to two thousand dollars nowadays and only takes 1-2 days.
The diagnosis and prognosis of cancers will become more dependent on the genomic profiling of individual tumours, which will then drive precision medicine to further reduce cancer mortality rates. The continual discovery of new biomarkers will open avenues for the development of the next generation of small molecule targeted therapies that proffer maximal therapeutic effect with minimal side effects. As cancer is a genetic disease driven by heritable or somatic mutations, newer DNA sequencing technologies will continue to play a significant role in the detection of driver mutations and the management and treatment of the disease. Diagnostic laboratories must be quick to adopt such newer techniques in the ever-changing molecular diagnostics landscape.