PHAR44002 clinical relevance of omics

Precision Oncology and Targeted Therapies

Intended Learning Outcomes

• Understand the basics of "precision oncology."

• Recognize the need for developing molecularly targeted therapies.

• Differentiate between targeted therapy and standard chemotherapy.

• Learn methods of tumor stratification for optimal therapeutic selection.

• Understand Next Generation Sequencing (NGS), epigenomics, proteomics, and their relevance in clinical practice.

• Identify drug responders and non-responders.

• Understand the biological and technical challenges in drug prioritization.

• Recognize the role of pharmacists in optimizing anticancer drug use.

Precision Medicine

• Aims to make tailored prescriptions based on individual omics data.

• Collects, integrates, and computes epidemiological, clinical, and response data from previous patients.

• Creates scores to rank available treatments based on predicted efficacy.

• Bioinformatics tools provide evidence-based guidance for clinicians to prescribe drugs that better match patient characteristics.

• therapy tailored to individual patients, based on needs of pt vs what is statistically used.

Targeted Therapies vs. Standard Chemotherapy

1. Specificity:

   • Targeted therapies act on specific molecular targets associated with cancer.

   • Standard chemotherapies act on all rapidly dividing cells, both normal and cancerous.

2. Design:

   • Targeted therapies are deliberately chosen or designed to interact with their target.

   • Standard chemotherapies were often identified by their ability to kill cells.

3. Mechanism:

   • Targeted therapies are often cytostatic, blocking tumor cell proliferation.

   • Standard chemotherapy agents are cytotoxic, killing tumor cells.

there is huge heterogeneity of cancers.

Due to smokers/non smokers, sex, stage of cancer, tumour microenvironment.

There is no right medication that will suit everyone bc of these factors.

Targeted therapy targets specific molecules associatedwith that type of cancer/microenvironment/ heterogeneity

Standard chemotherapies often chosen bc they kill cells, can be effective but have drawbacks- side effects.

target therapies act more locally on tumour, woth normal cells survivin g- better outcomes.

From Genome Sequencing to Medical Intervention

1. Blood Draw: Obtain blood sample from the patient.

2. DNA Isolation: Isolate DNA from the whole blood.

3. Sequencing Library Construction: Prepare the DNA for sequencing.

4. Exome/Genome Sequencing: Sequence the exome or the entire genome.

5. Library Capture: (If exome sequencing is performed)

6. Read Alignment, Variant Calling, Annotation: Align the sequenced reads, identify variants, and annotate them.

7. Variant Filtration: Filter the identified variants to focus on relevant ones.

8. Identify Pathogenic Variant(s): Pinpoint the disease-causing variant(s).

9. Return of Results: Communicate the findings.

10. Medical Intervention: Apply the information to guide medical decisions.

11. Quality Control

Dilution of tumout cells by stromal cells plus genetic heterogeneity requires WGS which allows identification of gene copy numbers and rearrangements, and changes in noncoding regions impacting transcriptipn.

This is a lot of data- difficult to store and clinically interpret

WGS should be performed on high quality dna that cannot be obtained from FFPE tissues.

WGC unlikely to be used for clinical application in short to mid term.

Next Generation Sequencing (NGS) Technologies

• Genomic Sequencing:

  • Identifies SNVs (Single Nucleotide Variations), indels (insertions or deletions), mutations, translocations, CNVs (copy number variations), and SVs (structural variations).

  • Example sequence: ACCCGTTACGTAAACGTTT G AGATGACGATGACCAAGGTTGACGA

• Transcriptome Sequencing:

  • Analyzes gene expression, novel transcripts, fusion genes, and splice variants.

• Small RNA Sequencing

• ChIP-seq (Chromatin Immunoprecipitation Sequencing):

  • Identifies TF (transcription factor) binding regions.

• Methylation Sequencing:

  • Analyzes DNA methylation patterns.

to identify single nucleotide variants- can decide if these mutations can be reversed to stop disease.

Fusion of 2 genes can sometimes cause cancer- eg BCR and Aabl in some leukemias.

Can understand modifications that occur in the genome like methylation- new tech allows for detection of DNA methylation

Transitions in Biology

• From observational science to molecular science to genomic (data) science.

• The steps taken to use biology to develop new drugs. Histology of tumour looks different to normal tissue- look at why it is different, what proteins are expressed vs normal tissue

• Can isolate DNA too and the DNA of cancer tissue - can crrate some genomic data- can sequence dna that obtain from tummour tissue and see of genes expressed in tumour tissue differ from normal tissue.

Transcriptomics - Concept of a Signature

• Gene expression analysis to differentiate between different states (e.g., State A and State B).

• Compare two states using next gen sequencing and do expression analysis. can either be comparing normal vs cancer tissue or noemal tissue at early bs late stage disease.

• can compare same gene in different states

Gene Expression Profiles

• Serve as surrogates for biological phenotypes.- can inject isolated cells into mice and see if they create same phenotype- can be used to conclude if genotype assessed does or does not confer to development of disease.

• Act as a common currency for in vitro and in vivo phenotypes.

• can isolate cells and get profile from cells to make more precise conclusions.

Clinical Interpretation of Gene Expression Profiles

• Gene expression profiles can predict survival rates and risk of recurrence in diseases like NSCLC (Non-Small Cell Lung Cancer).

• Examples:

  • Low-risk vs. high-risk groups based on gene expression.

  • Survival based on tumor size (T-size < 3.0 cm vs. T-size > 3.0 cm).

  • Survival based on the stage of the disease.

• can make interpretations depending on prognosis of cancer- high/low risk.

• Signature expression of genes which confer to the development of cancer, can tell us id pt at high risk of cancer.

• Can find things out from specific genes and what they mean for survival/ prognosis.

• can see whether the drug we have targets the specific gene expression profile to give favourable results or not- can be plotted.

Clinical Trials in Oncology

• Gene expression profiles can predict recurrence probability.

• Example: Accuracy of prediction is 66/84 (78.5%).

• Survival analysis with and without recurrence (p < 0.001).

The Human Epigenome Project (HEP)

• Aims to identify, catalogue, and interpret genome-wide DNA methylation patterns of all human genes in all major tissues.

• Epigenetic changes are tissue-specific and crucial in regulating gene expression during development.

• epigenetics gained a lot of attention - lifestyle you follow will be inherited by your kids- epigenetics signature will be inherited- smoking, lifestyle etc affects epigenetics.

Epigenetics and Cancer

Common Epigenetic Modifications

• DNA Methylation:

  • Addition of methyl marks to DNA bases, typically repressing gene activity.

  • Occurs at the cytosine bases of DNA strands converting the cytosine bases to 5-methylcytosines.

• Histone Modification:

  • Attachment of different molecules to histone tails, altering DNA activity.

  • Hisrone proteins that DNA is wrapped around have histone tailes that when boud can affect gene expression.

Epgenetic changes have beeb extensively studies- methylation and acetylation. These changes happen on histone tails. When have methylation of cytosines on the DNA of these genes- dna is more tightly packed in cells. When have acetylation - gets more relaxed dna meaning get more open structure.

DNA Methylation

• Definition: Addition of a methyl group to the carbon-5 position of cytosine residues.

• Significance: Epigenetic changes that don't affect the genetic code itself.

Epigenetic Regulation of Gene Expression

Covalent modificaition of histones and DNA key mechanusma in epigenetic regulation of gene expression.

Dna pacjaged into chromatin by wrapping around histome proteins to form nucleosome.

These are further compacted by additional protein factors to form chromatin - degree of compactness depends on post translatinal modification present on the histones.

Acylated - less compace and more accesible to RNA polymerase and transcriptional machinert- enabling transcription of nearby genes. enables the expression of genes. sometimes this is not desirable - eg expressing oncogenes.

Methylated- can be repressive or activating depending on site and degree of methylation. More tight packing of DNA means cannot be accessed by transcription factors- may lead to gene not expressed. So if pt has high dna methylation profile has low expression of tumour suppressors- need to use drugs that prevent histone methylation.

Combination of modifications on each histone and/ or nucelosome establishes code that relarws to transcriptional properties of nearby genes.

Primary protein families that mediate post translatonal modifications:

• Writers: Add epigenetic marks (e.g., methyltransferases, acetyltransferases).

• Erasers: Remove epigenetic marks (e.g., demethylases, deacetylases).

• Readers: Recognize and bind to epigenetic marks (e.g., bromodomains, chromodomains, PHD fingers, Tudor domains, PWWP domains).

Targeting the Cancer Epigenome for Therapy

• Targets include:

  • Cancer testis antigens (CTAs).

  • Tumor suppressor genes.

  • Endogenous retroviruses (ERVs).

  • DNA repair genes.

  • MicroRNAs.

  • Differentiation genes.

  • CTCF sites.

  • Gene body methylation

• DNMT inhibitors

• Remobal of methylation can lead to upregulation of cancer testis antigens (CTAs) and endogenous retroviruses- can help increase immuogenecity of cells, and induce apoptosis of cancer stem cells.

• decreased gene body methylation can lead to decreased transcription factors. DNA methyltransferase inhibitors DNMTi increase expression of tumour suppressor , dna repair and differentiation inducing genes- can restore normal behaviour.

• Reactivating CCCTC binding factor cites can help in response

• wide range of DNMTi makethem true genomic medicines.

Targeting Chromatin for Therapy

• Targets:

  • Immune checkpoints (e.g., PD1).

  • Histone modification.

  • DNA modification.

  • RTK (Receptor Tyrosine Kinase).

  • Cytoplasmic signaling.

  • DNA replication

• Influenced by environmental signals

new area of interest - can develop enzyme inhibitors. can be less toxic than traditional treatments.

allows for interference of actions of transcription factors.

targeting chromatin can enhance actibities of other drugs in combination therapies.

it is not sufficient to use only the inhibition of methylayion or acetylation in cancer therapy.

By affecting histome modification shown in chromatin - can affect immune checkpoimts and therefore affext singnals that stimulate different kinases or growth factors leading to disease development.

Cn have cytoplasmic signalling - proteins which are methylated, phosphorylated or acetylated (located in cytoplasm) may be abke to change subcellularr localisatin which can impact the physiology of the cell changing – with effects on dna, transcriotin , which proteins are expressed/ suppressed etc.

The Challenge of Precision in Cancer Treatment

• Key questions:

  • How to improve prognosis to identify patients needing further treatment?

  • How to identify more effective therapeutic opportunities tailored to the individual patient?

  • Who to treat?

  • How to treat?

Standard-of-Care Limitations

• Only a fraction of patients respond to standard treatments.

• The rest are treated ineffectively.

• Challenge: How to choose the right therapy for the individual patient?

• Examples of standard-of-care regimens:

  • Cisplatin/vinorelbine

  • Cisplatin/gemcitabine

  • Cisplatin/docetaxel

  • Carboplatin/paclitaxel

• need to check expression of relevant genes we can aqcuire before and after treatment.

Herceptin - The Importance of Patient Selection

• All breast cancer patients: < 10% response to Herceptin.

• Her2+ breast cancer patients: 35-50% response to Herceptin.

• Question: Can we achieve similar results for commonly used chemotherapies through patient selection?

• herceptin is effective in subtype of breast can that expresses her 2 as it is her 2 inhibitor.

• therefore pts that dont express her 2 do not responf well.

A Strategy to Predict Response to Cytotoxic Chemotherapies

• Using the NCI-60 Cell Panel.

• Identify resistant and sensitive cells.

• Build an expression predictor of response using drug response data and Affymetrix expression data.

• can identify who will responod well and who will have cytotoxic effects.

An Opportunity to Guide Therapy

• Compare standard-of-care with genomics-guided approaches.

• Move beyond standard of care by directing targeted agents.

• Examples:

  • Cisplatin/gemcitabine

  • Cisplatin/docetaxel

Oncology Pharmacist Practice for Supportive Care

• Patient education and palliative care.

• Adverse drug-reaction prevention and monitoring.

• Discontinuation of drugs.

• Dose adjustments for organ dysfunction, weight, age.

• Switch from intravenous to oral formulations.

• Infectious disease and antibiotic support, including immunization advice.

• Pharmacists need to be knowledgebale of drugs to help educate patients without givng false hope.