Personalized onco-genomics

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Personalized onco-genomics (POG) is the field of oncology and genomics that is focused on using whole genome analysis to make personalized clinical treatment decisions. [1] [2] The program was devised at British Columbia's BC Cancer Agency and is currently being led by Marco Marra and Janessa Laskin. [3] Genome instability has been identified as one of the underlying hallmarks of cancer. The genetic diversity of cancer cells promotes multiple other cancer hallmark functions that help them survive in their microenvironment and eventually metastasise. The pronounced genomic heterogeneity of tumours has led researchers to develop an approach that assesses each individual's cancer to identify targeted therapies that can halt cancer growth. Identification of these "drivers" and corresponding medications used to possibly halt these pathways are important in cancer treatment. [2]

Contents

With the oncogenomic databases that currently recognize mutation and abnormalities in the genomic structure of cancer cells, DNA, RNA, and protein analysis can be used to assess these changes and identify drivers of cancer growth. [4] [5] By decoding the genetic information inside cancer cells, researchers gather information which may help understand factors that promote tumour growth and develop strategies to stop it. Ideally, a catalogue of all somatic cancer mutations will be created in the future that can provide insight into the abnormal cellular pathways of cancer cells and the genetic patterns that drive specific cancer phenotypes. This information can help develop effective personalized treatment options for patients with resistant cancers and ideally prevent toxicities related to conventional chemotherapeutics.

History

The novel approach of comparing a patient's tumour versus normal tissue was first identified in 2010 when assessing the genetic evolution of adenocarcinomas of tongue before and after treatment was received. [6] This study presented evidence that the genetic information from these tumours have potential to influence the treatment options for cancers. After identifying the driver mutations of tumour was the RET oncogene, the patient was administered with a RET inhibitor (sunitinib), which stabilized the disease for 4 months. [6] A second round of RET inhibitors (sorafenib and sulindac) administration provided an additional 3 months of disease stabilization before the cancer progressed again. [6] The observed mutations and amplification in the recurring metastasis were identified to be consistent with resistance to the RET inhibitors. [6] The evolution of the adenocarcinoma after treatment with RET inhibitors demonstrated with possibility for personalized cancer therapy. This approach was then successfully replicated in other cancer types and resulted in the formation of the Personalized Onco-Genomics Program at the BC Cancer Agency. This program has now analyzed over 570 adult cancer patients with incurable disease, which were published in a landmark study in 2020. [7]

Data availability

Genomic and transcriptomic sequence datasets from the 2020 Nature publication encompassing the first 570 "POG" patients [7] have been deposited at the European Genome-phenome Archive (EGA, http://www.ebi.ac.uk/ega/) as part of the study EGAS00001001159. Data on mutations, copy changes and expression from tumour samples in the POG program organized by OncoTree classification (http://oncotree.mskcc.org) are also accessible from https://www.personalizedoncogenomics.org/cbioportal/. The complete small mutation catalog and gene expression TPMs are available for download from http://bcgsc.ca/downloads/POG570/.

Rationale

OMICS technologies are high-throughput methods that help evaluate and unbiased investigate characteristics of the genome, epigenome, transcriptome, proteome, and metabolome.

A genome is the complete collection of an organism's DNA sequences, which contains instructions for cellular processes. In human diploid cells, 6 billion DNA base pairs of the genome can be found in the nucleus. The development of all cancers starts with a single cell accumulating enough harmful changes in DNA sequence that allow it to proliferate uncontrollably. Subsequently, the origin cell's fast-growing progeny invade surrounding tissues, migrate to other tissues. [8]

In a typical tumour, several dozens of somatic mutations may be disrupting the normal function of proteins. The majority of somatic mutations are mere byproducts of the unstable cancer genome and do not enhance the tumour cell growth. Usually, between two and eight driver mutations, mutations that gives cancer cells growth advantages, are found amongst all the somatic mutations a tumour sample. [9] Driver mutations may be actionable as they serve as diagnostic and prognostic biomarkers for cancer, and may have therapeutic implications. [10] For instance, kinase inhibitors can be treating tumours associated with driver mutations in kinases. Axitinib, gefitinib, and dabrafenib to are used to treat adult acute lymphoblastic leukemia, non-small-cell lung cancer, and melanoma respectively. [11]

As cancer can arise from countless different genetic mutations and a combination of mutations, it is challenging to develop a cure that is appropriate for all cancers, given the genetic diversity of the human population. To provide and develop the most appropriate genetic therapy for one's cancer, personalized oncogenomics has been developed. By sequencing a cancer patient's genome, a clinical scientist can better understand which genes/part of the genome have been mutated specifically in that patient and a personalized treatment plan can potentially be implemented.

Methods

Whole Genome Analysis

With the advent of next-generation sequencing, the genome-wide sequencing analyses have been made more accessible to thoroughly understand the genetics of each patient's cancer. Genetic material from tumour biopsies can be analyzed by two genome-wide approaches: whole exome sequencing (WES) and whole genome sequencing (WGS). By developing tools to analyze these extensive sequence data, scientists have begun to comprehend how diseases, including cancer, can be attributed by genes and intergenic variants such as single nucleotide polymorphisms (SNPs) and copy number variants (CNVs).

Although more expensive than WES, whole genome sequencing allows clinical scientists to understand how cancer can be caused by alterations in a genome including single nucleotide variants (SNVs), SNPs and CNVs. [12] Since WES samples only the exome (the collection of known coding regions of the genome) alterations in the non-coding region of the genome will not be detected by WES. Non-coding regions, including untranslated regions, introns, promoters, regulatory elements, non-coding functional RNA, repetitive regions, and mitochondrial genomes, make up 98% of the human genome, the function of most regions remains unexplored. [13] Although these methods are useful in finding shorter variants, they are limited by read lengths of sequencing technology and are unable to detect large indels and structural variants.

Though variants in a non-coding region are not uncovered by WES, both approaches identify all mutations that are known to cause cancer in a given patient and have been helpful in identifying low frequency and rare pathogenic (disease-causing) variants. [14] However, the challenge remains in analyzing all the genetic variations in a genome for the clinical significance (whether a mutation is disease-causing as not all mutations are harmful) as much of the genome is not thoroughly understood, and new variants are still being discovered.

To better understand the pathogenicity of all possible genomic variants to interpret WES/WGS data, researchers are systematically studying genome-wide sequencing data across many tumour genomes. Whole exome sequencing has been the conventional data used by international cancer genome research programs such as The Cancer Genome Atlas (TCGA) and The International Cancer Genome Consortium (ICGC). [15] [16] These studies have accumulated WES data for all types of human tumours and have been an open resource for clinical scientists. Systematically analyzing more than 50,000 tumour genomes has elucidated new cancer genes and pathways, opening up new pursuits for pharmaceutical companies. Researchers have also discovered general trends on different types of cancer that may inform public education on proactive preventative measures. For example, more somatic mutations in coding regions are found in carcinogen-exposed cancers than in pediatric tumours and leukemia. Although these systematic studies provide extensive mutational data on coding regions, information is limited on somatic mutations in non-coding regions. [16] [17] Researchers have only recently started to be illuminated on how cancer may be caused by variants in the non-coding regions of the genome. In 2018, Zhang and colleagues analyzed 930 tumour whole genomes with associated transcriptomes (collection of mRNA transcripts) to show mutations in 193 non-coding sequences disrupt normal gene expression. [17] Notably, they repetitively found noncoding mutations affected DAAM1, MTG2, and HYI transcription wherein DAAM1 expression initiate invasive cell migration in the tumour. [17] Since the core somatic gene expression network is defective in 88% tumours, Zhang et al. suggested that noncoding mutation may have a widespread impact in cancer. [17] As the cost of sequencing decreases and sequence analytic pipeline optimizes, researchers are looking to expand cancer genomic knowledge with WGS. Nonetheless, WES may remain effective for clinical diagnosis in the next few years as WES results are obtained faster.

Application

Treatment options for aggressive metastatic cancer typically have a poor response rate to conventional treatments. Through this novel approach, analysis of oncogenic factors is undertaken to identify the unique molecular signatures of the individual's tumour. [18] In most cancers, there are multiple pathways that are altered and lead to disease growth and progression. The pathways can vary from person to person, and even between different sites of disease in a single person. These pathways also have the ability to evolve depending on the various treatment options attempted to halt progression. [19]

The POGs program [20] takes biopsies from metastatic tumours from patients, sequences both the DNA and RNA, and then research what is driving the person's cancer in an attempt to pick the right drug for the right person at the right time. Recognition of specific genetic abnormalities that are promoting cancer progression can help select non-conventional treatment options to target these abnormalities. [1] This approach allows multiple clinicians to work together in a collaborative manner to tackle an aggressive disease. The genetic information collected from the tumour helps health-care professionals make rational clinical decisions regarding treatment strategies. These strategies may be used to target the growth of the tumour, identify potential clinical trials that patients could enrol in, and find more effective and less toxic drug options. [1]

This approach has been successful in treating small subgroups of cancers with medication commonly used to treat chronic myeloid leukemia (CML). Imatinib targets a BCR-ABL translocation that appears in more than 95% of CML cases. [21] The success of this drug in treating CML has highlighted the importance of personalized treatment options and identification of molecular pathways to be targeted. [21] Imatinib is now also used to treat some stomach cancers after identifying the genetic alterations in this cancer type. [22] Repurposing current treatment options that are used for other treatments and can halt cancer progression due to similarities in characteristics.

The success of the POGs program is highlighted by the identification of a novel genetic mutation in a 35-year-old recurrent breast cancer patient. Zuri Scrivens was enrolled in the POGs program at the BC Cancer agency to help devise a personalized novel therapy based on her tumour mutations. [23] From the results of her tumour genome sequencing analysis, a drug that is most commonly used in the treatment of type 2 diabetes was selected to treat her recurrence along with a standard chemotherapy medication. With the combination of these medications, Zuri's cancer quickly returned into remission. [23]

In the future, the use of this personalized onco-genomics approach may be the first step for the treatment of each person's cancer. There is a great depth of genetic information that can be extracted from each individual's cancer. Genomic data can provide valuable information regarding each individuals’ cancer and guide clinical decision-making from health-care professionals.

Challenges

There are multiple challenges that are preventing the adoption of POGs. The largest challenge is the identification of genetic factors that are promoting cancer growth. [18] These “drivers” need to be understood before any actions can be taken against them. [18] Although the costs of genetic testing have decreased significantly, [24] the results can provide an enormous amount of genetic information that scientists haven't truly understood yet. Through the understanding of these “drivers” of the cancer growth, appropriate drug choices can be made to target them. [18] Only a fraction of these drivers have been identified until now and more research is required help uncover many of cancer's characteristics. [18]

Cancer cells are known for the thousands of genetic changes that are occurring within a single cell. Targeting these genetic changes requires a significant amount of research to identify which changes are drivers and which are “passengers”. [18] These passengers do not directly to cancerous growth. Unfortunately, medication is not currently available for every genetic change that may occur within a cancer cell and drive growth. With further research, more medications will be made and identified to target these genetic changes.

Another challenge with POGs is identifying new methods to overcome resistance from drug treatment. [25] Some medications that are used to target cancers containing genetic changes cannot provide sustained benefits. [26] [27] Patients may experience either short-lived or long-term benefits from the medication, but since cancer is constantly evolving, it often develops even more genetic changes that allow it to adapt and survive against the drug. This drug resistance allows the cancers to grow back despite previously effective treatment. This has become a major challenge in treating cancers.

The POGs and other new cancer treatments are generally tested on patients with advanced cancers who have failed previous drug therapy. With time, cancer progresses and evolves based on the previous treatments the individual has received. [28] These cancers are incredibly difficult to treat due to their drug resistance mechanisms. There is a growing acceptance that these new medications need to be tested in individuals much earlier so cancer does not have time to develop with resistance. As mentioned above, the development of liquid biopsies help provide patients with the right drug at the right time. [29] A non-invasive method to help clinicians influence clinical decision making could become the basis of new clinical trials in the future.

The feasibility of undertaking this approach in all cancer centers remains one of the greatest challenges of any personalized program. Until it is feasible for every hospital and cancer center to have the technology required to study the genomics of each individual, it is unlikely that this approach will be adopted. Before many of the tests described above become commonly used, researchers also need to demonstrate that these test can provide benefit when guiding treatment options, and if this approach ultimately increases the survival and prevents recurrence of cancers in patients.

Related Research Articles

<span class="mw-page-title-main">Marco Marra</span> Canadian geneticist

Marco A. Marra is a Distinguished Scientist and Director of Canada's Michael Smith Genome Sciences Centre at the BC Cancer Research Centre and Professor of Medical Genetics at the University of British Columbia (UBC). He also serves as UBC Canada Research Chair in Genome Science for the Canadian Institutes of Health Research and is an inductee in the Canadian Medical Hall of Fame. Marra has been instrumental in bringing genome science to Canada by demonstrating the pivotal role that genomics can play in human health and disease research.

<span class="mw-page-title-main">Pharmacogenomics</span> Study of the role of the genome in drug response

Pharmacogenomics, often abbreviated "PGx," is the study of the role of the genome in drug response. Its name reflects its combining of pharmacology and genomics. Pharmacogenomics analyzes how the genetic makeup of a patient affects their response to drugs. It deals with the influence of acquired and inherited genetic variation on drug response, by correlating DNA mutations with pharmacokinetic, pharmacodynamic, and/or immunogenic endpoints.

<span class="mw-page-title-main">Personalized medicine</span> Medical model that tailors medical practices to the individual patient

Personalized medicine, also referred to as precision medicine, is a medical model that separates people into different groups—with medical decisions, practices, interventions and/or products being tailored to the individual patient based on their predicted response or risk of disease. The terms personalized medicine, precision medicine, stratified medicine and P4 medicine are used interchangeably to describe this concept though some authors and organisations use these expressions separately to indicate particular nuances.

<span class="mw-page-title-main">Oncogenomics</span> Sub-field of genomics

Oncogenomics is a sub-field of genomics that characterizes cancer-associated genes. It focuses on genomic, epigenomic and transcript alterations in cancer.

The Cancer Genome Project is part of the cancer, aging, and somatic mutation research based at the Wellcome Trust Sanger Institute in the United Kingdom. It aims to identify sequence variants/mutations critical in the development of human cancers. Like The Cancer Genome Atlas project within the United States, the Cancer Genome Project represents an effort in the War on Cancer to improve cancer diagnosis, treatment, and prevention through a better understanding of the molecular basis of the disease. The Cancer Genome Project was launched by Michael Stratton in 2000, and Peter Campbell is now the group leader of the project. The project works to combine knowledge of the human genome sequence with high throughput mutation detection techniques.

Personal genomics or consumer genetics is the branch of genomics concerned with the sequencing, analysis and interpretation of the genome of an individual. The genotyping stage employs different techniques, including single-nucleotide polymorphism (SNP) analysis chips, or partial or full genome sequencing. Once the genotypes are known, the individual's variations can be compared with the published literature to determine likelihood of trait expression, ancestry inference and disease risk.

Somatic evolution is the accumulation of mutations and epimutations in somatic cells during a lifetime, and the effects of those mutations and epimutations on the fitness of those cells. This evolutionary process has first been shown by the studies of Bert Vogelstein in colon cancer. Somatic evolution is important in the process of aging as well as the development of some diseases, including cancer.

<span class="mw-page-title-main">Whole genome sequencing</span> Determining nearly the entirety of the DNA sequence of an organisms genome at a single time

Whole genome sequencing (WGS), also known as full genome sequencing, complete genome sequencing, or entire genome sequencing, is the process of determining the entirety, or nearly the entirety, of the DNA sequence of an organism's genome at a single time. This entails sequencing all of an organism's chromosomal DNA as well as DNA contained in the mitochondria and, for plants, in the chloroplast.

Cancer genome sequencing is the whole genome sequencing of a single, homogeneous or heterogeneous group of cancer cells. It is a biochemical laboratory method for the characterization and identification of the DNA or RNA sequences of cancer cell(s).

<span class="mw-page-title-main">Proteogenomics</span>

Proteogenomics is a field of biological research that utilizes a combination of proteomics, genomics, and transcriptomics to aid in the discovery and identification of peptides. Proteogenomics is used to identify new peptides by comparing MS/MS spectra against a protein database that has been derived from genomic and transcriptomic information. Proteogenomics often refers to studies that use proteomic information, often derived from mass spectrometry, to improve gene annotations. The utilization of both proteomics and genomics data alongside advances in the availability and power of spectrographic and chromatographic technology led to the emergence of proteogenomics as its own field in 2004.

<span class="mw-page-title-main">Molecular diagnostics</span> Collection of techniques used to analyze biological markers in the genome and proteome

Molecular diagnostics is a collection of techniques used to analyze biological markers in the genome and proteome, and how their cells express their genes as proteins, applying molecular biology to medical testing. In medicine the technique is used to diagnose and monitor disease, detect risk, and decide which therapies will work best for individual patients, and in agricultural biosecurity similarly to monitor crop- and livestock disease, estimate risk, and decide what quarantine measures must be taken.

Tumour heterogeneity describes the observation that different tumour cells can show distinct morphological and phenotypic profiles, including cellular morphology, gene expression, metabolism, motility, proliferation, and metastatic potential. This phenomenon occurs both between tumours and within tumours. A minimal level of intra-tumour heterogeneity is a simple consequence of the imperfection of DNA replication: whenever a cell divides, a few mutations are acquired—leading to a diverse population of cancer cells. The heterogeneity of cancer cells introduces significant challenges in designing effective treatment strategies. However, research into understanding and characterizing heterogeneity can allow for a better understanding of the causes and progression of disease. In turn, this has the potential to guide the creation of more refined treatment strategies that incorporate knowledge of heterogeneity to yield higher efficacy.

<span class="mw-page-title-main">Circulating tumor DNA</span> Tumor-derived fragmented DNA in the bloodstream

Circulating tumor DNA (ctDNA) is tumor-derived fragmented DNA in the bloodstream that is not associated with cells. ctDNA should not be confused with cell-free DNA (cfDNA), a broader term which describes DNA that is freely circulating in the bloodstream, but is not necessarily of tumor origin. Because ctDNA may reflect the entire tumor genome, it has gained traction for its potential clinical utility; "liquid biopsies" in the form of blood draws may be taken at various time points to monitor tumor progression throughout the treatment regimen.

Clinicogenomics, also referred to as clinical genomics, is the study of clinical outcomes with genomic data. Genomic factors have a causal effect on clinical data. Clinicogenomics uses the entire genome of a patient in order to diagnose diseases or adjust medications exclusively for that patient. Whole genome testing can detect more mutations and structural anomalies than targeted gene testing. Furthermore, targeted gene testing can only test for the diseases for which the doctor screens, whereas testing the whole genome screens for all diseases with known markers at once.

Mutational signatures are characteristic combinations of mutation types arising from specific mutagenesis processes such as DNA replication infidelity, exogenous and endogenous genotoxin exposures, defective DNA repair pathways, and DNA enzymatic editing.

<span class="mw-page-title-main">Cancer pharmacogenomics</span>

Cancer pharmacogenomics is the study of how variances in the genome influences an individual’s response to different cancer drug treatments. It is a subset of the broader field of pharmacogenomics, which is the area of study aimed at understanding how genetic variants influence drug efficacy and toxicity.

<span class="mw-page-title-main">Tumor mutational burden</span>

Tumour mutational burden is a genetic characteristic of tumorous tissue that can be informative to cancer research and treatment. It is defined as the number of non-inherited mutations per million bases (Mb) of investigated genomic sequence, and its measurement has been enabled by next generation sequencing. High TMB and DNA damage repair mutations were discovered to be associated with superior clinical benefit from immune checkpoint blockade therapy by Timothy Chan and colleagues at the Memorial Sloan Kettering Cancer Center.

Serena Nik-Zainal is a British-Malaysian clinician who is a consultant in clinical genetics and Cancer Research UK advanced clinician scientist at the University of Cambridge. She makes use of genomics for clinical applications. She was awarded the Crick Lecture by the Royal Society in 2021. Serena Nik-Zainal was also recognized as one of the 100 Influential Women in Oncology by OncoDaily.

Personalized genomics is the human genetics-derived study of analyzing and interpreting individualized genetic information by genome sequencing to identify genetic variations compared to the library of known sequences. International genetics communities have spared no effort from the past and have gradually cooperated to prosecute research projects to determine DNA sequences of the human genome using DNA sequencing techniques. The methods that are the most commonly used are whole exome sequencing and whole genome sequencing. Both approaches are used to identify genetic variations. Genome sequencing became more cost-effective over time, and made it applicable in the medical field, allowing scientists to understand which genes are attributed to specific diseases.

Precision diagnostics is a branch of precision medicine that involves precisely managing a patient's healthcare model and diagnosing specific diseases based on customized omics data analytics.

References

  1. 1 2 3 Clinical trial number NCT02155621 for "Personalized Oncogenomics (POG) Program of British Columbia" at ClinicalTrials.gov
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