Cancer is considered one of the foremost causes of morbidity and mortality across the world. Cancer causes dysregulation in several signaling pathways linked to cell proliferation, metastasis, resistance to apoptosis evasion, treatment failures in chemotherapy, etc. Current cancer therapies like chemotherapy, radiation therapy, and surgery are found to be only effective for a limited group of certain patients. This is because not all tumors are caused by the same mutations in the genome, and the tumor varies for everyone. Cancer, due to the complexity of its mechanisms and high diversity, demands the need for alternative therapeutic approaches in clinical science.
One of the modern approaches becoming more popular in cancer treatment is Personalized or Precision medicine. In this mode of treatment, genotypic, phenotypic, and environmental characteristics are assessed for a patient, and a ‘tailor-made” therapy is provided, thereby eliminating the constraints, side effects, and costs associated with conventional “one-size-fits-all” treatment. Having advantages over limited sample requirements, cost-effectiveness, and the use of targeted biomarkers have made Next-generation sequencing (NGS) a major leap in personalized medicine. NGS helps in tumor and cell-free DNA profiling, proteome and RNA analysis, better understanding of immunological systems, aiding physicians in precise diagnosis, and selection of cancer treatment choices. Precision therapy involves identifying mutations in signaling pathways and inhibiting existing or newly designed medications based on NGS profiles collected from various malignancies.
So what is this Next Generation Sequencing?
Next-generation sequencing (NGS) refers to a group of technologies that enable rapid and cost-effective sequencing of DNA or RNA. This technology helps scientists sequence many millions of DNA fragments quickly and cost-effectively. This provides information about genome structure, variations in gene activity, and changes in their functions, thereby providing a breakthrough in clinical research settings, pharmaceutical, and clinical diagnostic arenas. The NGS technologies are broadly used in whole-genome sequencing (WGS), whole-exome sequencing (WES), RNA sequencing, and chromatin immunoprecipitation sequencing. Various NGS platforms helped to widen the scope of genomics research, facilitating studies on rare genetic diseases, cancer genomics, microbiome analysis, infectious diseases, and population genetics. Recent advancements in NGS have helped identify disease-causing variants, uncover novel drug targets, and aid in knowing more about the complexity and mechanism of various tumors, etc.
NGS has been categorized as first-, second-, and third-generation technology based on improvements in their chemistry, data depth, and resolution. In first-generation technology, sequencing of DNA and RNA was achieved by chemical degradation or enzymatic cleavage of the molecules to generate fragments and analyze them individually. The second generation included a concept called parallel sequencing, which enables simultaneous sequencing of thousands to millions of DNA fragments simultaneously. Third-generation (current) sequencing technologies represent the latest advancements in DNA sequencing, offering new approaches that overcome the limitations of previous generations. These technologies provide long-read sequencing capabilities, enabling the sequencing of much larger DNA fragments compared to earlier methods within a short period. Third-generation platforms also achieved high levels of resolution, data accuracy, and precision in variant detection & interpretation with the combined application of advanced computing and artificial intelligence.
The three important steps involved in NGS are library preparation and amplification, sequencing, and data analysis. One of the popular NGS platforms is Illumina, which works by bridge amplification. Single molecules of DNA are linked to a flow cell and subsequently amplified locally into a clonal cluster, like how a single bacterium grows into a colony on a medium plate. The complementary DNA is then built one nucleotide at a time by sequencing by synthesis, and its identity is determined by an optical readout of fluorescently labeled nucleotides. Another such platform is Ion Torrent, where single DNA molecules are cloned on a bead within an emulsion using the Ion Torrent platform. After that, the beads are placed on a semiconductor chip containing a matrix of individual pH sensors. A localized pH change identifies the sequenced nucleotide as the DNA clones undergo synthesis and sequencing.
What are the impacts of Next Generation Sequencing in Cancer Diagnosis and Medical Management?
NGS helps in genetic characterization, tumor, and cell-free DNA profiling, detecting immune markers, protein function, and RNA structure analysis. All these pieces of information help the physician diagnose and choose a particular treatment most suitable for the patient with fewer side effects and treatment failures. NGS can currently detect Minor Allele Frequency (MAF) of less than 1%, which helps differentiate the rare mutations in the genome. Molecular barcodes or unique molecular IDs can aid in improving sensitivity and reducing false negatives. With MAF under 0.1%, these approaches can detect 59% of stage I or II lung cancer patients.
Many tumors are initially responsive to chemotherapy, but they can develop resistance over time due to DNA mutations and metabolic changes that enhance drug inhibition and degradation. Reduced drug activation can potentially lead to cancer cells developing resistance to such treatments. In these cases, the mutation could be analyzed, and treatment could be planned according to the genetic analysis in personalized medicine.
Circulating cell-free tumor DNA (ctDNA) is one such promising biomarker that can support personalized treatment. Conventionally, ctDNA can be assessed from various readily available physiological fluids, including blood, urine, and cerebrospinal fluid. The main methodologies for analyzing ctDNA are the detection of tumor-associated mutations, DNA methylation, and chromosome instability evaluation. WGS and WES help the physician to detect specific mutations. Some examples are the detection ofEGFR T790M in non-small-cell lung cancer, KRAS G12V in colorectal cancer, and BRAF V600E/ V600K in melanoma.
NGS has been employed in papillary thyroid cancer molecular tumor classification and molecular prediction of recurrence and metastasis. With the help of NGS, we can now detect and classify somatic mutations, which is a very crucial step in treatment. NGS enabled the detection of many somatic alterations in thyroid and metastatic breast cancer patients who were unresponsive to various chemotherapy treatments. TP53, PIK3CA, and GATA3 genes are common somatic mutations in breast cancer.
Most recently, NGS has been widely used to identify new antigens for Chimeric Antigen Receptor (CAR) T cell therapy, thereby assisting oncologists in developing targeted immunotherapy for cancer patients.
Future Trends in Next-Generation Sequencing
Genome editing is a technique for altering genome sequences at specific sites to cause genetic alterations in organisms’ genome sequences. One such popular technology is clustered regularly interspaced short palindromic repeats (CRISPRs) and CRISPR-associated nuclease 9 (Cas9), also known as the CRISPR/Cas9 system. The integration of CRISPR and NGS enhances precision in gene editing, could facilitate genome-wide screening of various genes, and help study the edited genes and biomarkers to be used successfully in treatments.
One of the still improving areas for NGS platforms is how to collect error-free data and process the huge amount of data to be used for scientific purposes. Just to put it in perspective, the whole genome sequencing of an individual would contain approximately 3.1 billion base pairs! In addition, there could be about 5 million mutations, which is about 0.16% of the 3.1 billion bp. With current technology, it takes about 30 hours to generate a complete report, and thanks to advanced computing technologies, we hope to get this done much shorter in the next few years.
Quantum computing is another major advancement in NGS data analysis & data mining and will be a high-demand career for the next few decades. Quantum computers can optimize genome assembly, reducing computational time and improving accuracy. They also accelerate read alignment, enhancing mapping efficiency. By reducing false positives, Quantum computing improved variant detection accuracy and facilitated rapid genome annotation. Ongoing research aims to develop highly sophisticated bioinformatic pipelines, Hybrid Quantum-Classical Architectures, quantum-inspired Algorithms for NGS, and the use of Quantum computing for Single-Cell RNA sequencing. Some key players in this arena are Google’s Quantum AI Lab, IBM Quantum, and Rigetti Computing.
Artificial intelligence (AI) is now widely applied in NGS analysis to assist with variant and biosecurity threat detection. Edge computing is another approach that is widely popular in this category. This helps faster data processing at a local level, reducing the need for a cloud storage server, and hence improving the efficiency of computing time. In addition, the blockchain model is being used for genomic data security to prevent the misuse of clinical data and improve the transfer speed of data across various platforms.
Challenges and Limitations of NGS
NGS is a powerful tool for analyzing genetic changes correlating to clinical pathologies. There are still certain limitations, like the analytic sensitivity of mutation detection, where it is difficult to identify a low tumor percentage and a lower mutation due to the heterogeneity of the tumor. Systemic errors and sequencing errors are common in NGS systems like Illumina.
Current NGS platforms could be more reliable in identifying homologous genes, GC-rich regions, and repetitive regions. Interpretation of data from NGS is another major issue, and the databases may not always be accurate. Copy number and structural variations require separate bioinformatics programs; hence, many techniques must be combined to read the NGS analysis.
NGS generates massive amounts of genomic data, requiring advanced IT infrastructure and analytics. Some associated challenges are data management and storage, scalability and computing power of various platforms, balancing biosecurity with data sharing, ensuring standardization of various algorithms while maintaining privacy, and addressing ethical and legal concerns.
Ethical, Legal, and Social Concerns of NGS
Biosecurity, data privacy, and next-generation sequencing (NGS) are interconnected concerns. Biosecurity risks are Bioterrorism, Dual-use research (NGS can be misused for harmful purposes), and Synthetic biology, where NGS could facilitate the design and construction of biological agents. Data privacy concerns reflect mainly on how to handle genetic information sensitivity, unauthorized access & misuse of private data, and protecting the privacy and ownership (intellectual property) of health data. Most noticeably, how to prevent genetic discrimination and stigma based on an individual’s genetic characteristics.
Some of the regulations and guidelines put in place to address this are the Health Insurance Portability and Accountability Act (HIPAA), the General Data Protection Regulation (GDPR), and the National Institutes of Health (NIH) Genomic Data Sharing Policy.
The Catholic Church has expressed interest and concerns regarding Next-Generation Sequencing technology, primarily focusing on its ethical implications.
The Pontifical Academy for Life (PAV) has addressed genetic engineering and genomics in various documents. The Catholic Church’s teaching on the human genome is summarized in the “Charter for Health Care Workers” (2016). The Church emphasizes that genetic research must respect human dignity, identity, and the sanctity of life as well as should prioritize the common good of humanity.
The church opposes germline editing for non-therapeutic purposes, considering it a form of eugenics. Personalized medicine is encouraged by the church, with attention to accessibility and equity for all humans. The Church emphasizes the importance of protecting genetic data and obtaining informed consent. Provide support for gene therapy for therapeutic purposes, but caution against “designer babies.” The Church supports responsible use, emphasizing parental counseling. Gene editing for disease treatment is supported but with caution regarding unintended consequences. Genetic enhancement is opposed by the church as it alters human nature. Preimplantation genetic diagnosis (PGD) is opposed, citing concerns about embryo destruction.
Mentioned below are some references for further reading on the ethical aspects of the topic:
1.”Humanae Vitae” (1968): Addresses reproductive ethics.
2.”Veritatis Splendor” (1993): Discusses moral principles.
3. “Evangelium Vitae” (1995): Covers life issues, including genetics
4. “The Charter for Health Care Workers” (2016) – Addresses genetic engineering.
Glossary of Technical Terms
Allele: Multiple alternative forms of a gene at a specific location on a chromosome
Apoptosis evasion: Defines as cellular stress response that allows cells to survive when exposed to stressful stimuli. It’s a hallmark of human cancers and can contribute to tumor formation, progression, and treatment resistance
Apoptosis: Also known as programmed cell death, in which a ‘suicide’ program is activated within the cell, leading to cell death without lysis or damage to neighboring cells. It is a normal phenomenon, occurring frequently in a multicellular organism
Biomarker: A biological molecule found in blood, other body fluids, or tissues that is a sign of a normal or abnormal process, or a condition or disease
Chromosome: DNA molecule that contains the genetic information for an organism
Exome: Collection of exons in a genome, which are the protein-coding regions of DNA
Exon: DNA sequence that codes for amino acids that link together to form a protein
Gene: A sequence of DNA that codes for a specific protein
Genome: The totality of genetic information belonging to a cell or an organism; in particular, the DNA that carries this information.
Genotype: The genetic constitution of an individual cell or organism
Malignancy: Term used to describe cancer, which is a group of diseases that involve the abnormal growth of cells
Metastasis: The process by which cancer cells break away from the original tumor and spread to other parts of the body
Microbiome: Community of microorganisms (such as fungi, bacteria, and viruses) that exists in a particular environment
Nucleotide: Basic structural unit of nucleic acids such as DNA and RNA
Phenotype: Observable characteristics of an organism, such as its appearance, behavior, or development
Proteome: Complete set of proteins expressed by an organism
Sequence: Refers to the specific order of nucleotides in a DNA or RNA molecule, or amino acids in a protein
Somatic Mutation: This is the most common cause of cancer, occurring from damage to genes in an individual cell except for the germ cells (sperm and egg). These mutations won’t get transferred to offspring. Somatic mutations are also known as somatic variants
Variant: An alteration in the DNA sequence of a gene
