Transforming Cancer Care: Advances in AI & ML will help in creating personalized treatment strategies

About Author: A leading figure in the India’s pathology industry, Dr Avinash Phadke is the Founder of Agilus Dr Phadke Labs as well as President – Technology of Agilus Diagnostics. He is the Director of India Venture Healthcare Fund; Advisor & Mentor at APPI (Association of Practicing Pathologists of India); Trustee and member of governing board, Cancare Trust Cancer Hospital. He is also a guest faculty member at Tata Institute of Social Science (TISS), Bhabha Atomic Research Centre and Mumbai University.

Precision medicine, also known as personalized medicine, involves the customization of healthcare, with medical decisions, treatments, practices, or products being tailored to the individual patient. By understanding the genetic makeup of both the patient and their cancer, clinicians can devise targeted therapies that are more likely to be effective and less likely to cause adverse effects. This contrasts with the one-size-fits-all approach of traditional medicine, which can result in varied responses among patients.

Role of Diagnostics in Precision Medicine

Diagnostics are at the heart of precision medicine. Advanced diagnostic tools and techniques allow for the detailed analysis of a patient’s genetic information. This includes:

Genomic Sequencing: Technologies such as next-generation sequencing (NGS) can quickly and accurately decode the DNA of cancer cells. This enables the identification of specific genetic mutations driving the cancer, allowing for the selection of targeted therapies. NGS technologies have revolutionized genomic sequencing by allowing rapid and comprehensive analysis of multiple genes simultaneously. NGS can identify a wide array of genetic mutations, including point mutations, insertions, deletions, and gene fusions, which are often responsible for cancer development and progression. This high-throughput technology provides a detailed genetic profile of the tumor, guiding the selection of targeted therapies tailored to the specific mutations present.

Whole-Exome Sequencing (WES): WES focuses on sequencing all the protein-coding regions of the genome, known as exons. Since most disease-causing mutations are found in these regions, WES can provide crucial insights into the genetic alterations driving cancer. This method is particularly useful for identifying novel mutations and understanding the complex genetic architecture of different cancers.

Whole-Genome Sequencing (WGS): WGS involves sequencing the entire genome, including non-coding regions. This comprehensive approach can uncover genetic variants that might be missed by other sequencing techniques, providing a more complete picture of the genetic changes associated with cancer

Biomarkers: Biomarkers are biological molecules found in blood, other body fluids, or tissues, which can indicate the presence of cancer. By identifying these markers, doctors can diagnose the type of cancer, predict its progression, and monitor the effectiveness of treatment. Prognostic biomarkers provide information about the overall outcome or course of the disease, regardless of treatment. For example, the presence of the BRCA1 or BRCA2 gene mutations in breast cancer patients indicates a higher risk of developing the disease and can inform decisions about preventive measures. Predictive biomarkers help identify which patients are likely to benefit from a particular treatment. For instance, the KRAS mutation in colorectal cancer patients can predict a lack of response to certain anti-EGFR therapies, guiding clinicians to choose alternative treatments. Pharmacodynamic Biomarkers indicate the biological response to a treatment, helping to monitor the effectiveness and adjust the treatment regimen accordingly. Changes in levels of specific proteins or other molecules in response to therapy can provide real-time feedback on treatment efficacy.

Liquid Biopsies: This non-invasive diagnostic method involves analyzing circulating tumor DNA (ctDNA) in the blood. Liquid biopsies offer a less invasive alternative to traditional tissue biopsies and can provide real-time insights into the genetic changes in tumors. Exosomes are small vesicles released by cancer cells that contain proteins, lipids, and nucleic acids. MicroRNAs are small non-coding RNA molecules involved in gene regulation. Both exosomes and microRNAs can serve as biomarkers for cancer detection and monitoring, providing insights into tumor biology and the patient’s response to treatment.

Tailoring Cancer Treatment

Precision oncology refers to the application of precision medicine in cancer treatment. This approach involves:

Targeted Therapies: These drugs are designed to target specific genetic mutations within cancer cells. For example, HER2-positive breast cancers can be treated with trastuzumab, a drug that specifically targets the HER2 protein. Similarly, mutations in the EGFR gene in lung cancer can be targeted with drugs like gefitinib and erlotinib.

Immunotherapy: By leveraging the body’s immune system to fight cancer, immunotherapies such as checkpoint inhibitors have shown remarkable success. The use of pembrolizumab for tumors with high microsatellite instability (MSI-H) or mismatch repair deficiency (dMMR) exemplifies how genetic markers can guide immunotherapy.

Combination Therapies: Precision oncology often involves the use of multiple therapies simultaneously or sequentially to overcome resistance mechanisms. By combining targeted therapies, chemotherapy, and immunotherapy, treatment regimens can be tailored to the specific genetic landscape of a patient’s cancer.

Case Studies and Success Stories

The impact of precision medicine in oncology is best illustrated through patient case studies and clinical successes:

Lung Cancer: The identification of specific mutations, such as ALK rearrangements and ROS1 fusions, has led to the development of targeted therapies like crizotinib. These drugs have significantly improved survival rates and quality of life for patients with these genetic alterations.

Melanoma: The discovery of the BRAF V600E mutation in melanoma has resulted in the development of targeted therapies such as vemurafenib and dabrafenib. These drugs have transformed the treatment landscape for patients with metastatic melanoma.

Breast Cancer: Genomic tests like Oncotype DX analyze the expression of a group of cancer-related genes to predict the likelihood of cancer recurrence. This helps in deciding whether chemotherapy is necessary, sparing many patients from unnecessary treatment.

Challenges and Future Directions

Despite its promise, precision medicine faces several challenges. Cancer is a highly heterogeneous disease, with a complex genetic landscape that can vary greatly between patients and even within different areas of the same tumor. High costs and limited availability of advanced diagnostic tools can restrict access to precision medicine, particularly in low-resource settings. The vast amount of genomic data generated requires sophisticated bioinformatics tools and expertise to integrate and interpret, posing a challenge for many healthcare providers.

Looking ahead, the future of precision medicine in oncology holds great promise. Advances in artificial intelligence and machine learning are expected to enhance the analysis of genomic data, leading to more precise and personalized treatment strategies. Moreover, ongoing research into the tumor micro-environment and cancer metabolism may uncover new therapeutic targets.

Precision medicine is fundamentally transforming oncology, offering new hope to cancer patients through tailored treatments based on their unique genetic profiles. As diagnostics continue to advance and our understanding of cancer biology deepens, precision medicine will undoubtedly play an increasingly central role in cancer care, moving us closer to the goal of personalized, effective, and less toxic treatments for all cancer patients.

*Views expressed by the author are his own.