As the microprocessor
revolution was sweeping Silicon Valley in the Seventies, and tech giants Apple
and Microsoft came into being, a silent revolution was gathering steam in the
world of molecular biology. In 1976 a team of researchers in Harvard, led by
future Nobel winner Martin Gilbert, was inaugurating the genomic era with a
project that sought to develop a dependable method to sequence DNA. A continent
away, at the University of Cambridge, another team headed by Frederick Sanger
was trying to achieve the same thing. Sanger had won the Nobel Prize in 1953
for sequencing the protein structure of insulin. Computers, which were to play
such a significant part in the history of genetic sequencing, were just making
their appearance in Sanger’s lab, storing the data generated by the
experiments. Both teams achieved their objective in 1977, finding a reliable
and easy method to sequence DNA molecules into its component bases. This won
Sanger his second Nobel Prize for chemistry, which he shared with Gilbert.
The Sanger method for
sequencing DNA was the key that a generation of scientists would use to unlock
the mysterious world of genetic inheritance. It became the driving force behind
scientific efforts to map the genomes of various organisms—bacteria, microbes,
and even human beings. In 1990, an international collaboration of scientists
started sequencing the human genome using Sanger’s method. The human genome
project sequenced the combination of all the 25,500 genes that make up the
human chromosome. It took them 13 years and cost $2.7 billion.
Today, in Bengaluru, just beyond Electronic City, genome sequencing costs a little over ₹1 lakh ($1461), and takes three days. The computer revolution has made it possible to sequence entire genomes with less investment of time and money than Sanger or Gilbert could have fathomed.
MedGenome, an Indian
biotechnological startup which does gene sequencing and clinical diagnostics,
recently became part of the Genome Asia 100 K project, a not-for-profit
international collaboration to sequence 1 lakh human genomes from Asia. The
project will sequence the genomes of Asian populations to map the genetic
variations among various ethnic sub-groups. It will take genome samples from
more than 40 Asian countries and sequence them to create a standard reference
genome. The database will be hosted by the Nanyang Technological University,
Singapore. While members of the consortium will enjoy early access to the data,
it will be released to the public and medical researchers within 36 months of
completion.
Following in the steps
of the 100 K Genome project in the UK, the Asian Genome Project builds on
research which suggests that disease mutations present themselves differently
in various ethnic groups, and aims to identify rare versions of the same gene
associated with different populations. The immediate aim of the project is to
help tailor medicine and healthcare to individual patients.
“Each individual’s
genetic makeup is unique,” says Venkataswamy, a scientist with MedGenome,
“While there is a standard human reference genome, each gene can have various
versions called alleles. Four base pairs (AGCT) that code a particular gene can
have slight variations in their combinations. This is why individuals differ.
But so far drugs and medicalcare targets only the standard population.” In a paper published in the Annual Review
of Genomics and Human Genetics, Isaac Chan and Geoffrey Ginsburg wrote: “A
broad aspiration of the Human Genome Project is the concept of personalised
medicine—a rapidly advancing field of healthcare that is informed by the
uniqueness of the individual. Although this concept is not entirely new, many
clinicians have held great expectations for the development of medical
diagnosis, prognosis, and treatment that could be based on an individual’s
genetic information. This variability of human health has long been recognized,
but only with the advent of the genome sciences have the tools to understand
this diversity become available.”
DNA molecules are
double helix shaped, like two rope ladders that twine around each other. In
most living cells the DNA molecules which carry genetic information are in the
shape of thread-like chromosomes. Human cells have 23 pairs of chromosomes. A
pair comprises parts inherited from both parents, carrying different traits
which determine the physical characteristics of the offspring. A gene is a
small geographical section of the chromosome, like the sub-sections of a long
highway, each marking a different town or city. A gene is the basic unit of
heredity and controls certain traits. Just as computers are coded by zeroes and
ones, genes are coded by 4 nucleobases, adenine, guanine, thymine and cytosine.
The combinations of A, G, T and C make up the genetic code of a particular
gene. When scientists sequence a human genome, they decipher the nucleobases
that make up each gene.
W
The drastic fall in
cost has had two effects: making population-wide sequencing projects possible,
and allowing companies like MedGenome to offer physicians clinical diagnostics
of their patients by analysis of genetic samples.
The Asia Genome
consortium says the first short-term benefits of the data they gather would be
in cancer research, a field directly linked to genomics.
Arathi Khanna Gupta
joined MedGenome after researching the molecular basis of leukemia at Brigham
and Women’s Hospital, Harvard Medical School. It is her interest in cancer
therapy that led her to Bengaluru.
She says: “Medical
care for cancer has so far followed a one-size-fits-all-approach. This is not
necessarily true. There are variations at the genetic level among various
populations, which medical care has to recognise better. Right now,
chemotherapy for lung cancer is like hitting a nail with a sledge hammer.
Chemotherapy kills all fast growing cells. So it also kills hair, nails, skin
cells, etc. Another huge factor is that all drug trials are conducted on
Western populations. We haven’t studied their effectiveness in non-white and
Asian populations. Asian populations also display higher genetic diversity than
the West, because of the higher prevalence of endogamy. India has particularly
high genetic variation because of caste endogamy. Endogamous communities often
develop genetic disorders because weak traits do not get weeded out of the
closed gene pool and stronger genes do not enter it. Thus a genomic population
study is extremely important.”
As we enter the
laboratory wing of MedGenome, Venkataswamy gestures to a rack filled with
plastic floaters of the brightest colours—red, purple, blue. Scientists in
white lab coats slipping in and out, exchange their outdoor footwear for the
funky lab-only floaters. The lab is divided into three areas behind glass wall
partitions—sampling where the DNA is extracted, preparation, and sequencing.
Venkataswamy leads me into the sampling section, where vials of blood tissue
are stored using anti-clotting chemicals. Some are blood samples from various
clinics intended for the genome projects. Others are samples sent for analysis
by doctors for clinical genetic tests.
“Many come from
oncologists or neurologists. When cancer is suspected before there is a tumour,
the presence of mutations in genes associated with a cancer type can be used to
detect it. Many neurological diseases share the same symptoms, so sequencing
genes that cause different diseases is used as a diagnostic tool,” he says. In
some cases, doctors ask for a test on specific genes. But usually, they ask to
screen for a particular disease, and MedGenome’s scientists create a gene panel
associated with that disease to sequence it.
While DNA can be
extracted from all kinds of tissues including saliva and skin, almost all the
2,000 samples collected so far for the Asia Genome project have been blood
tissues, Venkataswamy says. He goes on to explain how DNA is extracted from
the blood samples. Cells, which are
protected by a cell membrane, consist of a cytoplasm in which the nucleus is
immersed, along with other organelles. The DNA is contained as chromosomes in the nucleus.
To isolate the DNA
from a sample, a scientist lyses the blood tissue with a protein and a reagent
grade detergent. The protein and detergent are harmless to the DNA but soon
break down everything else in the cell; dissolving the proteins, fats and
lipids that make up the cell membrane, organelles and cytoplasm. The DNA is
freed. The solution is now transferred into a tube with a column in the middle.
By adding a chemical buffer the DNA gets attracted and stuck to the column.
Dozens of such tubes are now put into a centrifugal machine that rotates at
blinding speed, draining away the solution of cell debris. In minutes, he picks
out the column tubes containing almost pure DNA. This is now transferred to a
sonication machine, where it will be prepared for sequencing. The sonication
device produces waves of ultrasonic sound which fragments the entangled DNA
strands into smaller bits that can be analysed. The scientist adjusts the
strength of the waves on the device, breaking the DNA into fragments of pre-determined size.
The final stage is the
sequencing of the DNA. MedGenome uses NGS sequencing machines from Illumina, a
company that partners in the Asia Genome project, and which pioneered current
NGS methods. The method allows the parallel sequencing of several DNA samples,
with the entire process requiring around three days. A chemical process
attaches oligoneucleotides to the end of the each DNA fragments. Each set of
the oliogonucleotides has copies which are loaded on to the flow-cell of the
sequencing machines. The flow-cell has millions of small perorations where they
attach themselves. When the fragmented DNA is introduced into the flow-plate,
the oligonucleotides bond to their copies and the whole DNA sequence starts
multiplying into large clusters, which can now be identified optically by the
machine. Knowing which oligonucleotide has attached to which kind of DNA, the
sequence can be understood and recorded.
I
n 1977, an unusual pair of virologists in California was cracking open one of medicine’s deepest mysteries—how is cancer caused? Michael Bishop had turned from the study of history to medicine and then virology. An even more colourful character, Harold Varmus, studied mediaeval English literature before becoming a doctor and practising medicine across the world, which included a year’s stint in Bareilly in Uttar Pradesh. His academic wanderlust finally led him to Bishop and the investigation of the Rous Sarcoma Virus, which caused cancer in chickens. Even after decades of research, scientists did not know what caused mutations that turned normal cells cancerous. The two major competing theories pitched virus infections that introduced a cancer gene in the cells of the host organism, against environmental factors like smoking in humans, which caused genetic mutations that led to cancer. The young virologists discovered something entirely different—the Rous Sarcoma Virus did not introduce a new gene into an animal’s body, it shared a gene with the organism, which it activated. In other words, oncogenes, or cancer producing genes, were the internal enemy, part of the genetic map of all living organisms.
Biologists already
knew that cancer cells were different from normal cells in only one respect:
they never stop reproducing. The discovery of oncogenes allowed scientists to
analyse the mechanism behind the genetic mutations that turn healthy cells into
cancer cells. Oncogenes regulate cell growth and reproduction. Mutations in
oncogenes can lead to over-expression of that gene; or mutations can lead to
new oncogenes forming. Another mechanism by which cancer is caused involves
mutations in tumour-suppressing genes. These genes prevent cells from growing
indefinitely. Mutations can switch off the action of the tumour-suppressing
genes or underplay their expression. More than one gene is associated with a
particular kind of cancer and usually mutations in multiple genes happen before
a normal cell becomes a cancer cell.
From 1990 to 2015, the
mortality rate of almost all cancers fell by one per cent a year. By the
mid-Nineties, several oncogenes and tumour-suppressing genes had been
identified. Drugs that target these genes were developed. Unlike chemotherapy,
which uses toxic drugs to destroy cancer cells, targeted drugs focus on cancer
genes and deactivate them. Twenty-four targeted drugs are now available for
cancers, including leukaemia, prostrate, breast, sarcoma and cervical cancers.
More are in the pipeline.
Arathi Gupta believes
the next step in the fight against cancer is evolving from targeted therapy to
personalised or precision medicine, using population genomics. “Your genetic
predisposition can determine therapy in many ways. It can help tailor the drugs
used. In lung cancer, the most common is non-small cell carcinoma. Thirty per
cent of patients with this type of cancer have mutations in the EGFR gene. If
the patient has this mutation, they are receptive to certain drugs, which does
not work in the rest of the patients whose cancer is not caused by EGFR
mutations. It can prolong life by nine months. You might respond to a
particular medicine because of your predisposition. Cancer medicine must move
towards treatment regimes tailored for a particular individual in deciding drug
type, drug dosage and preventive care. For other diseases, too, most of the
drug trials have been carried out on western subjects. Genome sequencing of
Asian populations would help identify different alleles, disease carrying mutations,
associations of genetic sub-groups with various diseases and differing disease
rates.”
Apart from benefits to
medical research, the project expects the data to feed into studies in the
history of population migration as well as future applications that might be
developed. Mahesh Pratapneni, the CEO of the 100 K AsiaGenome project says that
from the samples collected so far, they have identified a set of sub-groups
that will be the basis of further sampling and population analysis. “We are
only interested in genetically unique sub-groups. None of the metadata will be
in the public database. We are stratifying the sub-groups through further
analysis. From an initial set of about 2,000 genomes we have identified 50 plus
sub-groups. We think at least 50 samples are needed from each group for
population genomics analysis. We have a sampling strategy that is being
detailed right now. It is a combination of ethnic diversity discovered through
initial 2,000 sample analysis, clinical conditions of interest and availability.
The (initial) population genomics data is being analysed. We are working
towards a reference resource that can enable drug discovery and precision
medicine initiatives at the least. Just as with any platform project we believe
that many innovative use cases will emerge as we move forward just as we could
not have predicted an Uber 15 years ago when the US government put GPS out of
military use.”
There are scientists
who remain sceptical of the viability of personalised medicine as well as
whether genome sequencing is the way to achieve it. They see it as a case of
the availability of technology overriding research goals. Aswin Sai Narain
Seshasayee, a biologist with the National Centre for Biological Sciences (NCBS)
in Bengaluru, says: “Mutations on a genome do not act alone, and the manner in
which one mutation might affect the effect of another on a cell or organism’s
characteristics is not well understood. This is further complicated by the fact
that any individual genome of a complex organism may not carry just a few
variations with respect to a ‘healthy reference’, but is likely to carry even
thousands or hundreds of thousands of such variations, depending on the size of
the genome. I am not sure that we will be able to achieve a deep understanding
of such genetic interactions in the near future. One could argue that
statistical analysis of big data could overcome the lack of understanding of
genetic interactions; however, I am not convinced that we will have enough
power to get the statistics to the point that it is predictive enough to drive
‘precision’ ‘personalised’ medicine. Biochemical readouts, derived from
metabolic processes, may be a better way to approach this, because these might
mask the complexity arising from such genetic interactions. However, at this
point, genome sequencing works very well as a technology, because it is a lot
easier to do than any biochemical experiments on a large scale.”
Oncologists, however,
are more hopeful. Dr. Santosh Gowda, who heads the oncology department at the
Mazumdar Shaw Cancer Centre in Bengaluru, thinks personalised medicine in
cancer is the way forward. “Though cancer is generated by environmental factors
also, it is mainly germline mutations that cause it. But each individual’s DNA
is unique, like a molecular fingerprint.
Right now, cancer drugs are randomised for the entire population and do
not take into account the 10 per cent or so variation that exists. Metabolic
cancer drugs for prostate cancer are very aggressive (with side effects). Individual
variations are not taken into account, treatment modifications are not in
place. Can we tailor them to respond to genetic reasons? Among Asian women lung
cancer patients, the percentage of non-smokers is 50 per cent, while it is 20
to 25 per cent among Caucasian women. This is why the argument for genetic
sequencing of populations becomes important.”
In the 2016 US Federal
Budget, President Barack Obama allotted $215 million for the Precision Medicine
Initiative (PMI) a programme to promote biomedical research that would help
doctors and healthcare organisations tailor treatment to individual patient
needs. Among many of the projects PMI has launched is one that plans to enlist
a million volunteers to share their medical and genetic details to create a
massive databank. Similar genetic databanks are under construction in other
countries including the UK and China.
PMI allotted $71
million to the National Cancer Institute (NCI) for research into precision
oncology. The NCI has done a series of clinical trials including an ongoing one
where patients are treated on the basis of the genes that are drving their
cancer, rather than the type of cancer. Precision medicine includes not only
genetics and genomics, but also big data and analytics. In the case of cancer,
NCI notes that there are disparities between population groups, with minority
groups showing higher incidence and mortality.
In 2012, a genome
sequencing study of 14,000 Asian women from China, South Korea, Taiwan,
Singapore and Hong Kong found variations in three places in the genome which
predisposed non-smokers to lung cancer. The study found that the molecular
basis of lung cancer can be different for smokers and non-smokers.
A survey released this
year by the SAP and Oxford Economic Survey (not connected with Oxford
University) found healthcare organisations in Europe, Canada and the US
prioritsing precision medicine around diabetes, cancer, neurological diseases,
ageing and autoimmune diseases. For example, some cardiologists reported that they
have moved away from standard doses of medicine for heart attacks since the
metabolism rates for individuals vary.
Pharmacogenetic
testing on how different people’s genetic makeup influence their response to
drugs, allow them to calibrate drug dosage to individual patients. The study,
which surveyed 126 physicians, said that 49 per cent of the doctors surveyed
reported significanct improvement in patient care because of personalised
medicine practices, while 53 per cent expected this to happen in the next two
years. The survey also found that some pharmacuetical companies have started
using biomarkers in their drug testing, identifying patient sub-poulations and
utilising genomic information to understand their responses.
“P
Precision medicine is
in its early stages, and both optimism and scepticism has been expressed about
its potential. Critics of the PMI programme point at the high cost,
uncertainity and concerns over data privacy. The SAP and Oxford Economic Survey
said only 32 per cent of doctors it interviewed expressed confidence in their
ability to protect the genomic information of their patients. In an article in The
New York Times Dr. Michel J. Joyner, a physician at Mayo Clinic, wrote: “Given the general
omertà about researchers’ criticising funding initiatives, you probably won’t
hear too many objections from the research community about President Obama’s
plan for precision medicine. But I am deeply sceptical. Like most moonshot
medical research initiatives, precision medicine is likely to fall short of
expectations. Medical problems and their underlying biology are not linear
engineering exercises, and solving them is more than a matter of vision, money
and will.”
On the other side of
the fence, a prominent scientific voice who has put his weight behind precision
medicine is Harold Varmus, the virologist who discovered that cancer is a
genomic disease. In an article co-authored with Francis Collins (head of the
human genome project) in the New England Journal of Medicine (January
30, 2015) he says about the PMI project: “But the prospect of applying this
concept (precision medicine) broadly has been dramatically improved by the
recent development of large-scale biologic databases (such as the human genome
sequence), powerful methods for characterising patients (such as proteomics,
metabolomics, genomics, diverse cellular assays, and even mobile health
technology), and computational tools for analysing large sets of data… With
sufficient resources and a strong, sustained commitment of time, energy, and
ingenuity from the scientific, medical, and patient communities, the full
potential of precision medicine can ultimately be realised to give everyone the
best chance at good health.”
Towards the end of his
book on the history of cancer, The Emperor of Maladies, Dr. Siddartha
Mukherjee constructs an imaginary journey through time. The time traveller is
Atossa, the Persian Queen who lived around 500 BCE. She is the first known
personality in history to suffer from cancer. Finding a tumour in her breast,
Atossa had her Greek slave perform a primitive mastectomy. It is not known
whether Atossa was able to excise her cancer and for how many years she
survived the surgery. Mukherjee imagines Atossa travelling the temporal
landscape of cancer, arriving at various points in history to receive
treatment. Her chances start to improve as she enters the 20th century and
peaks as she enters the 1990s. She is diagnosed at an early stage and screened
to see if a tumour will appear in her unaffected breast. Her genome is
sequenced and a mutation is detected in BRCA1. Her two daughters are also
tested and given preventive treatment. When one of them develops a tumour,
early surgery saves her life.
But the scenario is
completely different when Mukherjee fast-forwards Atossa to 2050. Mukherjee, so
far the grim chronicler of humanity’s trench warfare against an ever-mutating
foe, allows himself the audacity of hope.
“In 2050, Attosa will
arrive at her breast oncologist’s clinic with a thumb-size flash drive
containing the entire sequence of her cancer’s genome, identifying every
mutation in every gene. The mutations will be organised into key pathways. An
algorithm might identify the pathways that are contributing to the growth and
survival of her cancer. Therapies will be targeted against these pathways to
prevent a relapse of the tumour after surgery. She will begin with one
combination of targeted drugs, expect to switch to a second cocktail when her
cancer mutates, and switch again when the cancer mutates again. She will likely
take some form of medicine whether to prevent, cure, or palliate her illness,
for the rest of her life.” Atossa survives.
is a former staff reporter at Fountain Ink.
