MGD 10.1 Personalised medicine I

Context of the Lecture

• From "Molecules, Genes and Disease 2025" by Dr. Anusha Sathyanarayanan.

• Theme: Analyzing patient data for proactive interventions and personalized treatment plans.

Learning Outcomes (Lectures 10.1 & 10.2)

• Concept of personalised medicine: Understand its definition and an explanation of the objective.

• Gene therapy application: Apply gene therapy concepts to clinical scenarios.

• Diagnosis and management: Utilize understanding for genetic/congenital disorders, abnormal blood tests, skin lesions, jaundice, visual abnormalities, bowel habit changes, and nausea/vomiting.

• Adverse Drug Reactions (ADRs): Explain improvements personalised medicine can bring to reduce ADRs.

• Rare diseases: Describe how personalised medicine increases treatment options through alternative uses for existing medicines.

• Cost implications: Explain both positive and negative financial viewpoints.

• Personal genome sequencing (PGS): Describe the process and its associated ethical, economic, and social issues.

• Gene and immunotherapy principles: Describe their biological origins.

• Specific therapies: Explain gene and immunotherapies currently in development and clinical practice.

Personalised Medicine: Definition and Aims

• Definition: Also known as precision medicine; it uses an individual's unique genetic material to tailor therapy.

• Aims to achieve the best therapeutic response and ensure safety.

• Goals: Facilitate earlier diagnoses, improve risk assessments, and enable optimal treatments.

• Holds potential to enhance health care quality and reduce costs.

How Personalised Medicine Offers Better Health Outcomes

• Prevention: Enables early disease detection rather than reactive treatment.

• Optimal therapy selection: Reduces trial-and-error prescribing, leading to more effective treatments.

• Reduced ADRs: Minimizes adverse drug reactions.

• Increased patient adherence: Patients are more likely to comply with tailored treatments.

• Improved quality of life: Enhances patient well-being.

• New uses for medicines: Identifies alternative applications for existing drugs and those in trials.

• Cost-effective healthcare: Streamlines treatment pathways and reduces overall healthcare expenditure.

Need for Personalised Medicine

• Variability in drug effectiveness: Clinical studies highlight significant differences in drug responses across patient populations.

• Non-response rates: A notable proportion of patients do not respond to drugs within a given class.

• Example: Variations in drug response across populations are well-documented.

Tailored Approach: Clinical Contexts and Trials

• Example: The CLL206 trial demonstrated high effectiveness of Alemtuzumab + methylprednisolone as an induction regimen for Chronic Lymphocytic Leukemia (CLL) with TP53 deletion.

Personalised Medicine in Practice: Key Ideas

• Vision: Faster diagnoses and personalised treatments with fewer side effects.

• Four Ps Framework:

• Prediction and Prevention: Identifying individuals at risk before symptom onset.

• More Precise diagnoses: Enhancing diagnostic accuracy through deeper understanding of molecular and cellular processes.

• Personalised and targeted interventions: Delivering treatments specifically tailored to individuals.

• A more Participatory role for patients: Empowering patients to be actively involved in their healthcare decisions.

Prediction and Prevention of Disease

• Goal: Utilize $\text{genomic technologies}$ and other diagnostics to identify at-risk individuals before symptoms appear.

• Benefits: Enables new treatment options and informed lifestyle choices.

• Impact: Potential to reduce the burden of long-term conditions such as cardiovascular diseases, cancer, chronic respiratory diseases, and diabetes.

More Precise Diagnoses

• Traditional approach: Relies solely on symptoms and standard tests.

• Enhanced understanding: Achieved by integrating molecular and cellular process insights with clinical and diagnostic information.

• Enabling technologies: Includes diagnostic imaging, digital pathology, genomics, and informatics.

100,000 Genomes Project (UK)

• Overview: Launched in 2012 and completed in December 2018, sequencing $100,000$ genomes from approximately $85,000$ participants.

• Participants: Included NHS patients with rare diseases (and their families) and cancer patients.

• Early diagnoses: Identified conditions such as LEOPARD syndrome, familial breast cancer, and GLUT1 deficiency syndrome.

• Results: Analysis completed and results returned to NHS patients in July $2019$.

• Significance: A world-first study demonstrating that whole genome sequencing (WGS) can uncover new diagnoses across a broad range of rare diseases, with potential benefits for the NHS.

Jessica Case (Illustrative 100,000 Genomes Project Example)

• Challenge: Jessica had a rare, previously hard-to-identify condition.

• Resolution: Her family participated in the 100k Genomes Project, and WGS provided a molecular diagnosis, allowing for informed treatment decisions.

Personalised and Targeted Interventions

• Current variability: Only about $30\%$ - $60\%$ of patients effectively respond to many pharmaceutical interventions.

• Concept: Utilizes pharmacogenomic profiling via genetic variants to identify the optimal treatment for an individual.

• Example study: $CYP2C9$ and $VKORC1$ polymorphisms influence warfarin dose variability in long-term anticoagulation patients (Santos et al., 2013).

• Practical implication: Tailors drug choice and dosing based on genetic profile to improve safety and efficacy.

Preventing Dangerous Side Effects

• Variant analysis: Can predict the risk of adverse drug reactions (ADRs).

• ADRs impact: Contribute to approximately $\frac{1}{15}$ of hospital admissions in the UK.

• Benefits: Predicting and preventing ADRs can reduce the burden on emergency departments and improve patient experience.

Is a Variant Benign or Pathogenic?

• Classification: Variants are classified using a 5-point scale, ranging from benign to pathogenic.

• Resources for interpretation: ClinVar (https://www.ncbi.nlm.nih.gov/clinvar/), OMIM (http://omim.org/), and Genomics England 100,000 Genomes project resources.

A More Participatory Role for Patients

• Public awareness: Drives the deployment and adoption of personalised medicine.

• Patient initiative: A 2015 Inspire survey showed $52\%$ of new treatment discussions were initiated by patients.

• Engagement: Approximately two-thirds of patients bring notes or questions to consultations, indicating active participation.

Summary Framework (The University of Buckingham Slide)

• Core pillars: Patients, Information, Government, Precision medicine, Analysis, Data, Regulation.

Potential Impact on Outcomes

• Personalised medicine offers significant advantages for individuals, populations, the NHS, scientific research, and the wider economy.

Cancer as a Model for Personalised Medicine

• Heterogeneity: Cancer is highly diverse, with over $200$ known types.

• Treatment challenge: There is no single universal cancer treatment; no "magic bullet" or one-size-fits-all solution.

• Response rates: Some cancers exhibit response rates as low as $\frac{1}{5}$ ($20\%$).

Cancer Biomarkers: Definition and Uses

• Definition: A biological molecule that indicates a normal or abnormal process, or a disease state (e.g., cancer) within blood, bodily fluids, or tissues (according to NCI).

Potential Uses for Cancer Biomarkers (Examples)

• Estimate cancer risk: BRCA1 germline mutation for screening.

• Prostate cancer risk: Prostate-Specific Antigen (PSA) for screening.

• Differential diagnosis: Immunohistochemistry to determine tissue of origin.

• Prognosis: 21-gene recurrence score (Oncotype) to predict recurrence.

• Therapy response: K-Ras mutation and anti-EGFR in Colorectal Cancer (CRC); HER2 expression and anti-HER2 therapies in breast/gastric cancer; Estrogen receptor expression in breast cancer.

• Disease monitoring: CEA (colorectal), AFP, LDH, $\beta \text{HCG}$ (germ cell tumors).

Breast Cancer Subtypes (Intrinsic/Molecular)

• Luminal A (approximately $40\%$): Hormone Receptor-positive (ER+ and/or PR+), HER2-negative, low Ki-67; targeted therapy: Tamoxifen; best prognosis.

• Normal-like (approximately $2\%-8\%$): HR-positive, HER2-negative; similar therapy considerations; slightly worse prognosis than Luminal A.

• Luminal B (approximately $20\%$): HR-positive, HER2-positive or negative, high Ki-67; indicates fast cancer cell growth; targeted therapy: Tamoxifen.

• HER2-enriched (approximately $10\%-15\%$): HR-negative, HER2-positive; faster growth; targeted therapy: Herceptin (Trastuzumab).

• Triple Negative (approximately $15\%-20\%$): HR-negative, PR-negative, HER2-negative; most aggressive subtype; higher association with BRCA1 mutations.

Breast Cancer Therapies

• Tamoxifen: Standard treatment for ER-positive early-stage breast cancer (about $80\%$ of cases).

• Metabolized by $CYP2D6$ into its active form, endoxifen; genetic variants of $CYP2D6$ can affect its activity and metabolism.

• Trastuzumab (Herceptin): A monoclonal antibody targeting HER2; used for HER2-positive breast cancer (found in about $20\%-30\%$ of cases); prognosis varies with HER2 status.

Breast Cancer Testing: Oncotype DX

• Description: A genomic test designed for early-stage, ER-positive, HER2-negative breast cancers.

• Analyzes the expression of $16$ cancer-related genes to predict tumor behavior and treatment response.

• NICE approval: Approved in 2013 for NHS England/Wales as a cost-effective method to determine recurrence risk and guide treatment decisions.

Oncotype DX Recurrence Score (RS) and Chemotherapy Benefit

• Recurrence Score (RS): The assay provides a score on a scale, typically interpreted in bands such as RS 0-10, RS 11-15, RS 16-20, RS 21-25, RS 26-100.

• Example data (for RS 26-100, all ages): Shows an absolute chemotherapy (CT) benefit of approximately $32\%$\%; distant recurrence risk with Tamoxifen (Tam) alone is $20\%$\%

• Gene components: Includes genes like Estrogen receptor (ER), Progesterone receptor (PR), HER2, Ki-67, GRB7, STK15, BC12, Survivin, BAG1, among others (total 21 genes, with 16 relevant to breast cancer in the assay).

Breast Cancer Prevention

• Molecular markers: Can indicate risk before symptoms, guiding preventive actions.

• Preventive steps: Include lifestyle modifications, increased mammography surveillance, elective surgery, and chemoprevention.

• Angelina Jolie example: Her high BRCA mutation risk led to bilateral mastectomy and oophorectomy due to estimated risks (breast $\sim 90\%$, ovarian $\sim 60\%$).

Cost of Healthcare and Case Study

• Increased efficiency: Personalised medicine can reduce healthcare costs by minimizing trial-and-error dosing, decreasing hospitalizations due to ADRs, and avoiding late diagnoses and reactive treatments.

• Case study (Epstein et al., 2010): Reported $31\%$\%

• Fewer hospitalizations overall for warfarin dosing: With up to $48\%$\%

• Fewer hospitalizations for bleeding or thromboembolism.

Barriers to Personalised Medicine

• Costs: High expenses associated with diagnostic tests and potentially treatments.

• Guideline adoption: Challenges in integrating personalised medicine into established guidelines from bodies like NICE (UK) and FDA (USA).

• Knowledge and understanding: Gaps in knowledge among medical professionals and patients.

• Data requirements: Requires massive data integration from genomic, transcriptomic, and microbiomic sources.

How Personalised Medicine Offers Better Health Outcomes (Revisited)

• Key benefits: Reinforces prevention via early detection, selection of optimal therapy to reduce trial-and-error, decreased ADRs, increased patient adherence, improved quality of life, identification of new uses for medicines, and more cost-effective healthcare.

Drug Repurposing (Drug Repositioning)

• Definition: The process of identifying new therapeutic uses for existing or available drugs.

• Bases: Relies on the understanding that diseases often share common biological targets and that pleiotropic drugs can affect multiple biochemical pathways.

Drug Repurposing Examples (Common Examples Table)

• Aspirin: Originally an analgesic; new indication includes colorectal cancer (CRC).

• Azathioprine: Originally for rheumatoid arthritis; new indication for renal transplant.

• Cycloserine: Originally for tuberculosis; new indication for depression.

• Duloxetine: Originally for depression; new indication for stress urinary incontinence.

• Galantamine: Originally for polio-related paralysis; new indication for Alzheimer's disease.

• Gemcitabine: Originally an antiviral; new indication for cancer.

• Finasteride: Originally for benign prostatic hyperplasia; new indication for hair loss.

• Imatinib: Originally for chronic myelogenous leukemia; new indication for gastrointestinal stromal tumors (GIST).

• Sildenafil: Originally for angina; new indications for erectile dysfunction and pulmonary arterial hypertension (PAH).

• Thalidomide: Originally a sedative/antiemetic with teratogenicity concerns; repositioned for leprosy complications, then multiple myeloma, and potentially for COVID-19.

• Zidovudine: Originally for HIV/AIDS; new indication for cancer.

• Benefits: Drug repurposing can shorten development time, reduce costs, and extend the utility of shelved drugs to new patient populations.

Drug Repurposing – Aspirin (Details)

• History: Marketed by Bayer in 1899 as an analgesic; repositioned in the 1980s at a low-dose as an anti-platelet agent for cardiovascular prevention.

• Potential oncology role: May prevent the development of CRC through anti-platelet activity.

• Mechanisms: Includes reduced platelet-tumor interactions, suppression of $PGE2$ in tumor cells, and roles of $COX-1$ and $COX-2$ enzymes, leading to $PGE2$ reduction and effects on angiogenesis.

Drug Repurposing – Thalidomide (History and Repurposing)

• History: Banned by WHO in 1962 due to teratogenicity.

• Repositioned: In 1998 for leprosy complications through $TNF-\alpha$ inhibition; later, in 2006, as a first-line treatment for multiple myeloma.

• Potential: Under consideration for severe COVID-19 cases.

• Term: Often categorized with orphan drug status, used to treat rare diseases with government support.

Drug Repurposing – Sildenafil (Viagra)

• Initial investigation: Initially studied for hypertension and angina.

• Unexpected side effect: Observation of penile erections during trials led to its repositioning as Viagra leading to sales exceeding $2$ billion annually.

• Further repositioning: Subsequently used for pulmonary arterial hypertension (PAH) at a lower dose.

Anastrozole (Recent Repurposing Example)

• IBIS-II study: Demonstrated that anastrozole reduces long-term breast cancer rates in high-risk postmenopausal women.

• Recommendation: Suggested as a preventive drug-of-choice over tamoxifen in some guidelines.

• Impact: A 2019 QMUL announcement indicated nearly $300,000$ women in England would be offered the drug to reduce breast cancer risk.

Drug Repurposing in Cancer: Targets and Benefits

• Targets: Focuses on inhibiting tumor invasion & metastasis and implementing anti-angiogenesis strategies.

• Examples: Includes compounds like Niclosamide, Minocycline, Esoteric EGFR antagonists, Bisphosphonates (Zoledronic Acid), Itraconazole, Curcumin, Ivermectin, Ritonavir, Doxycycline, Statins, Metformin, and Leflunomide, among others.

• Benefits: Leads to reduced costs, faster development timelines, broadened patient access, and provides an opportunity to market shelved drugs.

• Concept: Synergy between combination therapy and personalised medicine.

Direct-to-Consumer (DTC) Genetic Testing

• Accessibility: DNA sequencing is now cheap and fast, though data interpretation remains challenging.

• Companies: Many companies offer personal genome analysis (e.g., 23andMe).

• Example offerings: 23andMe provides risk assessments for late-onset Alzheimer’s and certain BRCA mutations (some FDA-approved).

• Consumer marketing: Includes at-home genetic test packs offering multiple reports (ancestry, nutrigenetics, pharmacogenetics, etc.).

• Price points (example): A 7-report bundle advertised at $£399.00$, discounted to $£299.00$.

Points to Consider for DTC Genetic Testing

• Ethical, economic, legal, and social issues: These are central considerations.

• Integration: The challenge of integrating personal/family medical history with traditional tests and genomics for medical decisions.

• Validity of risk: Assessing the validity of risks associated with SNPs or mutations.

• Ownership of DNA: Legal considerations regarding the ownership and use of samples and data after collection.

• Role of genetic counselling: The importance of professional guidance in interpreting results.

Genetic Testing: Ethical Considerations (Who Cares About Your Genome?)

• Potential interested parties: Family, spouse, doctors, government, police, schools, and insurance companies.

• Key questions: Do meaningful interventions exist from this information? Is there potential for discrimination based on genetic data?

Ethical Debate Prompts (Self-directed Work)

• Government agencies: Should patients’ DNA sequences be held by government agencies?

• Selective termination: Should doctors make decisions on selective termination based on genetic information?

• Patent mutations: Should drug discovery companies be allowed to patent novel mutations identified during drug discovery efforts?

• Incidental findings: Should all incidental findings be disclosed to patients when performing personal genome analysis?

Practical Notes and References

• Abbreviations used: ER (Estrogen Receptor), PR (Progesterone Receptor), HER2 (human epidermal growth factor receptor 2), CK (Cytokeratin), Ki-67 (a marker for cell proliferation), CT (Chemotherapy), ADR (Adverse Drug Reaction).

• Key sources cited: Include NICE, Genomics England, NEJM (New England Journal of Medicine), Lancet, Mol Oncol (Molecular Oncology), and various government reports.

• Emphasis: Throughout the expansion of personalised medicine, ethical, social, and economic considerations are emphasized as