L17- Application of molecular pathology in cancer detection and treatment

whats the process of tumor spread

• Early dissemination from primary tumour

• Late dissemination from primary tumour

• Genetic divergence of primary and metastatic tumours has implications for treatment

what is intra-tumor heterogeneity

• Common and unique mutations

• Varying aggressiveness

• Distinct clinical and biological features

• Different metastatic capabilities

what genomic alterations can occur in cancer

Point mutations

Translocations

Gene amplification

Epigenetic modifications

Deletions

Aberrant RNA splicing

Altered gene expression

what ways can cancer cell survival be promoted die to genomic pertubations

Cell cycle control

DNA repair

Differentiation

Apoptosis

Tumour vascularisation

Metabolism

How is breast cancer classified pathologically?

• Cancer is a complex disease

• Two main categories:

  • Carcinoma (epithelial origin):

    • Ductal carcinoma in situ (DCIS)

    • Lobular carcinoma in situ (LCIS)

    • Invasive ductal carcinoma

      • Rare subtypes: medullary, mucinous (colloid), tubular, papillary

    • Invasive lobular carcinoma

  • Sarcoma (stromal/connective tissue):

    • Phyllodes tumour

    • Angiosarcoma

What are the key features of major breast cancer subtypes?

• Ductal carcinoma in situ (DCIS):

  • Pre-invasive lesion

  • Atypical cells in ducts/lobules

  • Non-invasive but has invasive potential

• Invasive ductal carcinoma:

  • Most common type

  • Cells form small ducts or tubules

• Invasive lobular carcinoma:

  • 2nd most common type

  • Cells form single-file lines or single cells

  • Frequent cytoplasmic vacuoles

what was the main treatment option for breast cancer

Breast is oestrogen dependent organ, remove oestrogen and tumour shrinks  

Why is breast cancer often hormone-dependent and how is this exploited therapeutically?

• Breast is an oestrogen-dependent organ

• Removing oestrogen (e.g. oophorectomy) can cause tumour shrinkage

• ER-positive cancers (~70%) depend on oestrogen signalling

• Treated with tamoxifen (anti-oestrogen) → blocks oestrogen receptor activity

• Prevents oestrogen-driven tumour growth

What are the main breast cancer subgroups based on receptor expression and their treatments?

• ER-positive (~70%)

  • ER⁺ / PR⁺, luminal markers

  • Subtypes: Luminal A, Luminal B

  • Treatment: Tamoxifen

• HER2 (ERBB2) positive (~10%)

  • Overexpression of ERBB2 receptor

  • Treatment: Trastuzumab (targets extracellular domain of ERBB2)

• Triple negative (~15%)

  • Lack ER, PR, HER2

  • Aggressive, heterogeneous

  • No clear target → chemotherapy

What characterises HER2-positive and triple-negative breast cancers?

• HER2-positive:

  • Driven by ERBB2 receptor overexpression

  • Targeted with trastuzumab

• Triple-negative:

  • Do not express ER, PR, or HER2

  • Aggressive and difficult to treat

  • No obvious receptor target → rely on chemotherapy

• Normal-like (~5%)

  • Poorly understood subgroup

  • Underlying defects not well defined

Why is targeting the estrogen receptor (ER) important in breast cancer?

• >70% of breast cancers are ER⁺ (ESR gene)

• Estrogen drives tumour growth and breast development

• Estrogen withdrawal ↓ proliferation (>90%)

• ER⁺ tumours are treated with endocrine therapy (mainstay)

  • Tamoxifen → ER antagonist

  • Aromatase inhibitors → ↓ estrogen production

  • Fulvestrant → destabilises and antagonises ER

    • Prevents estrogen signalling (blocks nuclear activity/dimerisation)

What are the clinical outcomes and limitations of endocrine therapy in ER⁺ breast cancer?

• Typically given for ~5 years post-surgery

• Reduces recurrence and mortality

• However, resistance develops over time

• Many patients eventually relapse with metastatic disease

• Require alternative endocrine therapies after resistance develops

how does fulvestrant work

Fulvestrant-Prevent oestrogen from entering nucleus and cause oestrogen dimerising  

How is genomic information used to identify cancer patient subgroups?

• Genomics helps stratify patients into subgroups with shared genetic alterations

• Discovery phase:

  • Identify biomarkers and therapeutic targets

  • Understand oncogenic mechanisms

• Uses whole genome analysis, including:

  • Copy number & LOH (loss of heterozygosity)

  • Gene expression & alternative splicing

  • Methylation

  • Transcription factor binding

  • Linkage/association studies

  • Mutation analysis

How are genomic findings validated and applied clinically?

• Validation phase:

  • Study larger patient cohorts

  • Statistically validate targets and biomarker signatures

  • Focus on fewer, relevant genes

  • Methods: copy number signatures, targeted genotyping

• Clinical utility:

  • Classify patients by prognosis

  • Stratify based on treatment response

  • Each patient screened for gene alterations/signatures

  • Used in diagnostic assays and clinical decision-making

What is the overall workflow and key principle of using genomics to stratify cancer patients?

• Patients are grouped based on common genetic alterations

• Follows a pipeline:

  • Discovery → Validation → Clinical application

• Trend across stages:

  • Start broad (whole genome, many genes)

  • Move to fewer, highly relevant genes

  • Study larger patient cohorts for validation

• Final step:

  • Develop validated diagnostic assays

  • Apply in routine clinical practice for patient stratification

what does it mean that tumours are heterogenous- what is the clinical importance?

Interactions with different types of stroma and connective tissue etc 

• Need to be able to pick out tumour cells from other types of cells, so we only analyse their cells/DNA 

  • if contain diff populations of clones with mutations in them, also mixes up DNA when analysing samples  

what are genetic array platforms

Tens-hundreds of thousands of oligonucleotide probes spotted onto glass slides

Probes-Against targets in the genome  

• Sample hybridised to slide, see what binds to specific probes 

what are the types of genomic array platforms and what do they detect (4)

1. Expression array – mRNA, microRNA

2. Exon array – alternative splicing of mRNA

3. SNP array – somatic and germline mutation, gene amplification/deletion of DNA

4. DNA methylation array – CpG methylation sites associated with gene activity

what is the method for using expression array platforms

Take sample from cancer patient/tumour and a control sample- equal amounts  

• Isolate mRNA  

• Convert tp cDNA 

• Tagged with fluorescent probe (healthy green, cancer red) 

• mRNAs bind to probe 

• Detect level of fluorescent 

• Can look at the different of expression of healthy and cancer cells (as equal sample amounts were used) 

how is data from gene expression arrays used

Gene expression signatures segregate breast cancer subtypes and predict metastatic spread and patient survival

• Use info to predict how patient will react to therapy and survival time  

What are SNPs and why are they important?

• Single-nucleotide polymorphisms (SNPs) = 1 base-pair DNA changes

• Contribute to genetic variation between individuals (allele status)

• Most SNPs have no effect, some cause subtle differences, others affect disease risk

• ~10⁷ SNPs in the human genome

• ~10⁶ SNPs are relevant to disease

• Can influence risk of diseases (e.g. prostate cancer susceptibility)

What are SNP arrays and how are they used in research?

• Use DNA oligonucleotide probes to detect SNPs across the genome

• Typically ~10⁶ SNPs analysed (~1 SNP per 3 kb)

• Determine whether alleles are homozygous or heterozygous

• Enable large-scale association studies (GWAS)

• Example:

  • ~43,000 prostate cancer cases vs ~43,700 controls

  • Identified 23 susceptibility loci

• Used to link genetic variation to disease risk

What is meant by allele status in SNP analysis and why is it important?

• Allele status = whether a SNP is homozygous or heterozygous

• Determined using SNP arrays

• Reflects individual genetic variation

• Certain 1 bp changes (SNPs) can increase disease susceptibility

• Key for linking genotype → disease risk in GWAS

what is the importance of the MDM2 SNP in cancer

• Naturally occurring polymorphisms may influence individual’s susceptibility to cancer or response to treatment

• SNP identified in a healthy population in MDM2 intronic promoter (SNP309, T to G change)

• In binding site for TF- SP1 

what does the MDM2 SNP cause

• Transcription factor SP1 binds more strongly to promoter

• Increased transcription from MDM2 promoter

• elevated MDM2 mRNA (x8) and protein (x4)

MDM2 negative regulator of p53 and increased MDM2 protein expression attenuates p53 pathway promoting genetic instability

In patients - SNP309 genetic variants show susceptibility to tumour development and frequent metastases

what does next generation sequencing allow for

rapid sequencing of large genomes
1. Detailed sequence information for each individual provides a full genetic profile

• predict development and progression of disease

2. First high quality ‘reference’ sequence of human genome completed in 2003

• Sanger sequencing- used to cost millions

how can sanger sequencing be adapted

Adapted Sanger sequencing technology by miniaturisation

- fluorescent chain terminators and capillary electrophoresis

what do current sequencing strategies use

Current sequencing strategies use Nanopore sequencing

– bases identified as individual DNA strands are pulled through tiny holes in lipid bilayer (pore 2nm).

- one million nanopores running in parallel coan complete full genome sequencing in 1 hour

• now costs less than 1000 pound

how is genome sequencing does using emulsion PCR

DNA taken from patient, made into SS and broken into fragments 

• Adaptor probes added to end of fragments 

• Fragments mixed with beads avg. one fragment to bead 

• Mix with lipid mix- 1 fragment on one bead enclosed in lipid droplet containing PCR mixture 

• PCR in situ in droplet 

• Millions of copies of one fragment in each droplet 

• Into nanopores for sequencing 

• Droplets burst and release beads  

• Sequencing done within each pore 

• Can sequence billions of fragments to be aligned by a computer 

describe molecular profiling of primary breast cancer

correlations of mutations with genomic and clinical features (n=11,500)

What does next-generation sequencing (NGS) reveal about breast cancer subgroups?

• NGS allows stratification of patients into subgroups (broader classification than IHC)

• Identifies >10 distinct breast cancer subgroups

• These subgroups have different clinical outcomes (survival differences)

• Survival curves show clear separation between groups (log-rank P ≈ 1.2 × 10⁻¹⁴)

• Enables more precise prognostic classification beyond traditional subtypes

What characterises the high-risk breast cancer subgroup IntClust5?

• High-risk group → poor prognosis, die quickly after diagnosis

• Luminal tumours

• ER-positive (ER⁺) but with additional tumour alterations

• 11q13/14 amplification (e.g. CCND1, EMSY)

• Associated with steep mortality trajectory

• Key idea:

  • Even ER⁺ cancers can be high risk if additional genomic alterations are present

  • Example: mutations/amplifications on chromosome 11q13 → worse prognosis

What is currently known about driver mutations in cancer from genome sequencing studies?

• ~140 genes (intragenic mutations) are known to drive tumorigenesis

• Typical tumour has 2–8 driver gene mutations

• Remaining mutations are passenger mutations

• Driver genes are grouped into 12 signalling pathways

  • These regulate 3 core processes:

    • Cell fate

    • Cell survival

    • Genome maintenance

How do mutation burdens vary between different tumour types?

• Tumours accumulate different numbers of mutations

• Average ~90 mutant genes per tumour

• Solid tumours: ~33–66 mutations

  • Examples: breast, prostate, pancreatic

• Outliers: melanoma and lung cancers (~200 mutations)

• Paediatric tumours & leukaemia: ~9–10 mutations

how can mutational heterogeneity within and across cancer types be presented

Each spot represents a patient where the average mutations read 

Variation both across tumours and individuals- contribute to complexity and heterogeneity  

What molecular signature tests are used in breast cancer and how are they performed?

• Breast cancer molecular tests:

  • RT-PCR (multiplex): PAM50, Oncotype DX, BCI

  • Microarray: MammaPrint, Curebest 95GC

• PAM50:

  • 50-gene signature for ER⁺ breast cancer

  • Used to predict response to tamoxifen therapy

• Method:

  • RT-PCR on mRNA from FFPE (formalin-fixed paraffin-embedded) tissue samples

What is the clinical utility of PAM50 and molecular signatures in breast cancer?

• Provides a prognostic score (0–100)

  • Predicts risk of recurrence (ROR) over 10 years

• Compares patient gene expression to 4 breast cancer subtypes:

  • Luminal A

  • Luminal B

  • HER2-enriched

  • Basal-like

• Correlates with outcomes:

  • Recurrence-free survival

  • Disease-specific survival

• Enables individualised (personalised) treatment decisions

describe estrogen receptor signalling in breast epithelial cells

• Estrogen (E2) activates ER → drives tumour growth (cell cycle progression)

• Tamoxifen blocks ER, Fulvestrant degrades ER → inhibit signalling

• ER signalling regulates:

  • Cell cycle (proliferation)

  • Apoptosis (BCL-2 vs BAX balance)

  • Autophagy & stress response (UPR)

• Overall: ER network controls growth vs survival vs death of cancer cells

How do ER mutations cause resistance to endocrine therapy in breast cancer?

• Mutations in ER (ESR gene) strongly drive signalling

• Occur mainly in ligand-binding domain (e.g. Tyr537, Asp538)

• Mutated ER is constitutively active without estrogen

• Causes reduced sensitivity to anti-estrogens (tamoxifen, fulvestrant)

• Higher drug doses needed for inhibition

• Structural change → mimics active receptor conformation → drugs can’t properly block it

How do ER mutation frequencies differ between primary and metastatic breast cancer?

• Primary disease: ~1% ESR mutation frequency (inherent resistance)

• Metastatic disease: ~20% ESR mutation frequency (acquired resistance)

• Indicates mutations are often selected during treatment

• Explains why resistance develops over time

• Key idea: mutated ER remains active even without ligand (estrogen) → therapy failure

How does the genomic landscape differ between primary and metastatic breast cancer and why is this important?

Analysis of tumours can help when patient has become resistant, compare initial tumour vs altered tumour  

What are the key steps in the PI3K/AKT/mTOR signalling pathway?

• Growth factor (GF) → RTK activation → IRS1 → PI3K activation

• PI3K converts PIP2 → PIP3

• PTEN opposes PI3K (converts PIP3 back to PIP2)

• PIP3 recruits PDK1 and AKT

• AKT activated by:

  • PDK1 (Thr308 phosphorylation)

  • mTORC2 (Ser473 phosphorylation)

• Activated AKT acts as a central pro-survival and growth regulator

What are the downstream effects of AKT activation?

• Promotes cell survival:

  • Inhibits BAD, FOXO → ↓ apoptosis (↓ BIM, FAS ligand)

  • Increases BCL-2/BCL-XL activity

• Promotes cell growth & proliferation:

  • Activates mTORC1 (via TSC2/RHEB) → protein synthesis (S6K, 4EBP1, eIF4E)

  • Increases Cyclin D (via GSK3 inhibition)

• Regulates cell cycle:

  • Inhibits p21, p27

• Affects metabolism & other pathways (eNOS, AS160, etc.)

• Overall: drives cell growth, proliferation, survival, metabolism, and autophagy regulation

What additional regulatory steps and components fine-tune the PI3K/AKT/mTOR pathway?

• Lipid conversions:

  • PtdIns(4,5)P2 → PtdIns(3,4,5)P3 (via PI3K)

  • PTEN reverses this

  • 5-phosphatases convert PIP3 → PtdIns(3,4)P2

• AKT recruited to membrane via PH domain binding to PIP3

• TSC2 inhibits RHEB → regulates mTORC1 activity

• Additional AKT targets:

  • eNOS, AS160, other substrates (metabolism, signalling)

• Pathway tightly regulated at multiple levels (lipid, kinase, protein interactions)

What are the main driver mutations in PI3K signalling alterations in cancer?

• PTEN deletion/mutations

• PI3K activating mutations

• AKT activating mutations

• Upstream RTK activating mutations

What types of agents targeting PI3K signalling are in clinical trials?

• Pan class I PI3K inhibitors

• Isoform-selective PI3K inhibitors

• Rapamycin analogues

• Pan-PI3K–mTOR inhibitors

• Active site mTOR inhibitors

• AKT inhibitors

What are liquid biopsies and how do circulating tumour cells (CTCs) relate to metastasis?

• Liquid biopsies detect circulating tumour cells (CTCs) to evaluate metastasis

• Metastasis process:

  • Tumour cells invade primary site

  • Enter bloodstream (intravasation)

  • Travel and form clusters

  • Exit vessels (extravasation) → secondary tumour

• CTCs provide a non-invasive way to monitor cancer spread

• Can detect ~1 cancer cell among 10⁷ blood cells

How are circulating tumour cells (CTCs) isolated and analysed in liquid biopsies?

Sample sources:

• Blood, lymph, saliva, urine

Isolation method (your notes):

• Use antibodies (Abs) to pull out cancer cells

CTC isolation workflow:

1. Sample collection (blood, lymph, cerebrospinal fluid, urine)

2. Cell enrichment:

   • Microfluidics (microfiltration, inertial sorting, affinity capture, hybrid devices)

   • Macro methods: gradient centrifugation, FACS, MACS

3. Single-cell isolation & analysis:

   • Cell counting (disease progression monitoring)

   • Multi-omics: genomics, transcriptomics, proteomics, metabolomics

• Enables single-cell sequencing and profiling

why can cancer be studies from liquid biopsies

Can look at DNA from tumour cells in liquid 

Cancer cells released into blood stream 

• When cancer cells they release DNA which enters the bloodstream (circulating tumour DNA) 

how can AI be used in medical sensors for clinical decisions

In pathology, with AI can look at 10s of thousands of samples in 24 hrs, overnight as well