Clinical Applications of Next Generation DNA Sequencing

Slide 1 · Clinical Applications of Next-Generation DNA Sequencing

From sequencing strategy to clinicopathologic decisions

Dr Abu Suraih Sakhri

MBBS, MD (Pathology)

www.abusuraihsakhri.com

Slide 2 · Learning objectives

Explain why massively parallel sequencing accommodates heterogeneous clinical DNA.

Trace the analytical sequence from specimen to clinically interpreted variants.

Select among targeted panels, whole-exome sequencing, and whole-genome sequencing.

Apply sequencing results to inherited disease and cancer evaluation.

Slide 3 · Clinical sequencing begins with a question

Constitutional disease

Tumor profiling

Recurrence / resistance

Inherited disease: Which constitutional change may explain a phenotype?

Cancer: Which somatic alterations have treatment or prognostic relevance?

Recurrence: Have new alterations emerged that could explain drug resistance?

Test scope must be chosen to fit the specific diagnostic question.

Slide 4 · Why next-generation sequencing became clinically useful

Many DNA molecules

Separate readouts

Clinical interpretation

Massively parallel read generation permits broad or deep analysis.

Large-scale sequencing is feasible without separately sequencing every region by Sanger methods.

The analysis can interrogate DNA mixtures containing different molecules.

Slide 5 · Sanger and NGS handle mixtures differently

Sanger: Composite signal from template material

NGS: Sequence reads from separated molecules

Sanger sequencing generally requires a homogeneous DNA template for interpretable output.

Heterogeneous mixtures may obscure the sequence represented in a Sanger trace.

NGS reads DNA molecules separately, enabling analysis of heterogeneous samples.

Slide 6 · Molecular heterogeneity matters in oncology

Schematic alignment of reads (not patient data)

Reference

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A tumor sample contains DNA molecules that need not share identical sequences.

Parallel reads preserve information about different alleles within the sample.

This makes tumor mutation profiling feasible despite sequence heterogeneity.

Slide 7 · The clinical NGS workflow

Sample DNA

Library and sequencing

Alignment / calling

Annotation and reporting

Laboratory preparation and sequencing produce reads.

Computational analysis locates differences from a reference genome.

Clinical review converts annotated variants into a medically interpretable report.

Slide 8 · Library preparation precedes sequencing

Source DNA is reorganized into a sequenceable library

Prepared short fragment

Different genomic segment

Another library fragment

Blue ends: Schematic universal adaptors; Grey center: Sample-derived DNA

The source DNA is prepared as a collection of short DNA fragments.

Regions of interest may be enriched before the sequencing run.

The selected library defines what is available for downstream analysis.

Slide 9 · Fragmentation makes parallel reading possible

Input DNA

Short fragments

Individual reads

An NGS library consists of shorter sequences derived from input DNA.

In the illustrated short-read approach, fragments are prepared for immobilization and sequencing.

Each fragment subsequently yields a corresponding sequence read.

Slide 10 · Capture enrichment focuses the library

Sequence complementarity selects DNA regions of interest

Complementary target

Unselected library region

Captured target region

Original schematic — hybrid capture; Not a laboratory assay image

Hybridization probes recognize sequences complementary to selected genomic regions.

Target enrichment directs analytical capacity toward regions of interest.

Target design is therefore central to the clinical assay’s scope.

Slide 11 · Spatial separation is the first NGS principle

Mixed templates

Spatial separation

Independent locations

Input molecules become physically separated at distinct locations.

Platform details vary; Physical separation permits distinct sequence signals.

The essential concept is that different templates are read separately.

Slide 12 · Local amplification increases signal

Single template

Local copies

Detectable signal

Separated templates undergo localized amplification in the source’s illustrated approach.

Copies at each location improve signal detection.

The amplified cluster remains associated with its starting DNA molecule.

Slide 13 · Parallel sequencing produces many reads

Parallel reactions

Sequence reads

Large read collection

Many spatially separated amplified templates are sequenced simultaneously.

Each original template gives rise to a read.

The source describes typical reads as short, generally under 500 bp.

Slide 14 · Reads require genomic context

Short reads

Reference alignment

Genomic positions

Raw read sequences are not yet equivalent to a diagnosis.

Alignment maps reads to a reference genome.

Mapped reads can then be evaluated for sequence differences at genomic positions.

Slide 15 · Alignment links reads to a reference genome

Schematic alignment of reads (not patient data)

Reference

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A reference genome supplies a common coordinate framework.

Sequenced fragments are mapped to matching reference intervals.

Alignment is a prerequisite for systematic comparison with reference sequence.

Slide 16 · Variant calling identifies sequence differences

Aligned reads

Compare to reference

Candidate variants

The pipeline compares aligned sample reads with a reference sequence.

Differences can then be detected in the intervals covered by the assay.

Calling depends on adequate sequencing coverage and downstream review.

Slide 17 · Depth and breadth answer different questions

Breadth: Number or extent of target regions

Depth: Repeated observation at a position

Breadth describes how much genomic territory is interrogated.

Depth describes the number of reads covering a genomic position.

Greater depth can improve detection of a low-frequency variant in mixed DNA.

Slide 18 · Sequencing depth supports rare-allele detection

Conceptual illustration: Greater overlap increases evidence at a locus

Overlapping reads at one position

Low-frequency alleles may be represented by relatively few template molecules.

More reads at the relevant position increase the opportunity to observe these alleles.

A target outside the assay or without adequate coverage cannot be confidently assessed.

Slide 19 · Variant allele frequency represents a mixture

Schematic alignment of reads (not patient data)

Reference

C G T A C G T C G A T C G T A C

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Variant allele frequency (VAF) refers to the fraction of observations supporting a variant.

The source links higher read depth to detection of variants at low VAF.

VAF should be interpreted in its specimen and assay context—not as a diagnosis on its own.

Slide 20 · Variant annotation adds biological meaning

Candidate variant

Gene / protein annotation

Database evidence

Clinical review

Annotation identifies the affected gene and the sequence or coding change.

Predicted protein effects and reference databases provide interpretation context.

Clinical relevance is assessed rather than inferred from a sequence change alone.

Slide 21 · Variant interpretation is not automatic

A variant must be interpreted with the patient’s disease or tumor context.

Databases include common and disease-associated variants.

A clinical laboratory reviews annotation before final reporting.

Slide 22 · The report connects DNA to a clinical decision

Variant evidence

Laboratory review

Interpretation

Clinical report

Reports describe biologic and clinical significance when it can be established.

Multiple pathogenic changes may need explanation in cancer specimens.

The goal is an intelligible result, not merely a list of sequence differences.

Slide 23 · Mutational patterns provide additional information

Individual variants

Pattern recognition

Biologic associations

Analysis need not stop after counting individual mutations.

Mutation patterns may suggest certain exposures or defects in DNA repair.

The source gives ultraviolet light, smoking, and DNA repair defects as examples.

Slide 24 · Tumor mutational burden can be inferred from NGS

Tumor mutational burden summarizes the burden of detected tumor mutations.

The chapter links high TMB in some tumors to a tendency to respond to checkpoint blockade.

TMB is a context-dependent biomarker; A generic NGS result does not itself guarantee response.

Slide 25 · Microsatellite instability is clinically relevant

Mismatch-repair defect

Microsatellite instability

Cancer biomarker assessment

Acquired mismatch-repair defects can produce microsatellite instability (MSI).

The source associates MSI with responsiveness to immune checkpoint inhibitors in some cancers.

NGS bioinformatics may assess MSI as part of cancer profiling.

Slide 26 · Three principal assay strategies

Targeted sequencing

Whole exome

Whole genome

Targeted panels: Curated genes or exons with substantial sequencing depth.

WES: Capture most protein-coding exons across the genome.

WGS: Sequence across the genome, including noncoding regions.

Slide 27 · Targeted sequencing restricts the interrogated space

Gene panel

Whole exome

Whole genome

Conceptual coverage of selected regions; Blocks are not genomic-scale measurements

A panel focuses on selected exons and genes relevant to the indication.

Concentrating the analysis supports greater depth and practical reporting.

The scope depends on expert selection of panel targets.

Slide 28 · Clinical panels are designed around a phenotype

Clinical phenotype

Select relevant genes

Targeted assay

A targeted assay is appropriate when candidate genes are already established.

An inherited disorder may justify one gene or a panel of disease-related genes.

Tumor testing requires genes relevant to the oncologic management question.

Slide 29 · Hybrid capture uses complementary probes

Sequence complementarity selects DNA regions of interest

Complementary target

Unselected library region

Captured target region

Original schematic — hybrid capture; Not a laboratory assay image

The source describes synthesized biotinylated probes used for hybrid capture.

Probes hybridize to complementary DNA segments in the prepared library.

Enriched fragments are then prioritized for sequencing.

Slide 30 · Why targeted panels offer sequencing depth

Conceptual illustration: Greater overlap increases evidence at a locus

Overlapping reads at one position

Sequencing effort is concentrated on a defined set of regions.

The chapter emphasizes maximal depth alongside reduced expense and interpretation burden.

This depth advantage is particularly useful when the specimen contains variant mixtures.

Slide 31 · Targeted panels limit interpretation workload

Focused targets: Manageable candidate set

Untargeted territory: Outside panel scope

Fewer examined regions usually mean fewer variants requiring clinical review.

Focused assays reduce time and expense associated with interpretation.

The trade-off is that variation outside panel targets is not comprehensively assessed.

Slide 32 · Single-gene testing also uses NGS

Single suspected gene

NGS assay

Gene-level sequence review

NGS is not limited to very large gene panels.

The chapter describes migration from multiple Sanger amplicons to NGS-based analysis.

Comprehensive CFTR sequencing is given as an illustrative single-gene application.

Slide 33 · An inherited-gene panel can fit a defined syndrome

Clinical phenotype

Candidate gene set

Phenotype-linked interpretation

When multiple genes can explain a similar phenotype, a multi-gene panel is attractive.

The textbook specifically mentions cardiomyopathy and congenital deafness.

Clinical phenotype guides the panel choice and interpretation.

Slide 34 · Cardiomyopathy: A panel-based diagnostic model

Cardiomyopathy phenotype

Disease-gene panel

Clinical correlation

The clinical entry point is a phenotype consistent with heritable cardiomyopathy.

A panel interrogates established candidate genes rather than the entire genome.

Detected variants need correlation with disease features and family context.

Slide 35 · Congenital deafness: Genetic heterogeneity

Congenital hearing phenotype

Multi-gene panel

Interpret candidate variants

A single clinical presentation may prompt evaluation of many possible genes.

Panel testing interrogates multiple selected genes in one sequencing strategy.

A technically positive change still requires clinically meaningful interpretation.

Slide 36 · Cancer panels profile somatic alterations

Tumor DNA

Cancer gene panel

Clinical variants

Management context

Each tumor may harbor its own combination of acquired mutations.

NGS panels seek tumor changes with therapeutic or prognostic significance.

A broad readout can inform more individualized oncology decisions.

Slide 37 · Tumor-specific profiles are not interchangeable

Tumor A: One combination of alterations

Tumor B: A different combination

Two tumors of the same broad category need not have the same set of somatic mutations.

Profiling seeks the alterations actually present in the specimen.

This molecular information complements, rather than replaces, the clinicopathologic diagnosis.

Slide 38 · Separate predictive from prognostic information

Predictive: Expected benefit from an intervention

Prognostic: Association with disease course

A treatment-relevant alteration can guide consideration of a targeted therapy.

A prognostically relevant alteration informs anticipated disease behavior.

The same molecular report may contain findings with different clinical roles.

Slide 39 · Mutation detection does not equal drug selection

Variant found

Clinical relevance assessed

Therapeutic decision

Panels aim to detect as many treatable or prognostic mutations as possible.

The presence of a variant requires disease-specific clinical evaluation.

Sequencing informs a decision; It does not provide a complete treatment plan.

Slide 40 · Recurrence is a reason to re-evaluate the genome

Initial tumor profile

Treatment course

Recurrent tumor testing

Tumor molecular features may differ after disease progression or therapy.

The chapter notes increasing use of repeat sequencing at recurrence.

The objective is to understand mechanisms underlying acquired resistance.

Slide 41 · Molecular resistance can alter second-line choices

Progression / recurrence

Assess resistance changes

Reconsider therapy

Newly identified resistance-associated changes may explain therapeutic failure.

Repeat testing can identify information relevant to subsequent treatment.

Results require integration with prior molecular findings and clinical status.

Slide 42 · A negative targeted panel has limited scope

Assayed genes: Evidence available

Genes outside panel: Not comprehensively evaluated

No detected panel variant means none was reported within the assay’s investigated targets.

The result cannot exclude disease-related variants in regions the panel did not capture.

If clinical suspicion persists, the question may warrant a broader sequencing approach.

Slide 43 · Whole-exome sequencing expands the target set

Gene panel

Whole exome

Whole genome

Conceptual coverage of selected regions; Blocks are not genomic-scale measurements

WES uses extensive capture to enrich protein-coding exons before sequencing.

It is broader than a phenotype-selected multi-gene panel.

WES remains a form of targeted sequencing—not whole-genome sequencing.

Slide 44 · The exome occupies a small genomic fraction

Coding exons are a small part of the whole genome

Coding exons ≈1.5% of human genomic sequence (source estimate)

The blocks are schematic—not a proportional depiction of all exons.

The chapter describes protein-coding exons as roughly 1.5% of the genome.

Exome capture focuses analytical resources on these coding regions.

A large amount of noncoding genomic sequence lies outside the WES target.

Slide 45 · WES is relevant when the diagnosis is uncertain

Unresolved genetic phenotype

Exome sequencing

Candidate-gene discovery

A rare inherited disease may lack a clear single candidate gene.

A broader analysis can evaluate coding variants beyond a narrow panel.

The chapter emphasizes diagnoses achieved after prolonged unsuccessful evaluations.

Slide 46 · Ending a diagnostic odyssey has clinical value

Prolonged uncertainty

Molecular diagnosis

Clinical explanation / options

Identifying a molecular basis can convert an unexplained syndrome into a defined diagnosis.

The chapter describes benefits for children with rare orphan diseases.

For some diagnosed conditions, finding the molecular cause can open therapeutic options.

Slide 47 · WES also supports cancer gene discovery

Routine panels: Decision-focused tumor profiling

Exome research: Broader gene discovery

In oncology, WES has been used mainly for research applications discussion.

Its breadth facilitates study of genes that are infrequently mutated.

This is distinct from the routine targeted-panel goal of actionable tumor profiling.

Slide 48 · The exome still misses important territory

Coding exons: Principal WES targets

Noncoding genome: Largely outside target

An exome assay preferentially interrogates protein-coding exons.

Potentially relevant noncoding changes are not comprehensively covered.

Persisting clinical suspicion after a non-diagnostic exome can justify considering WGS.

Slide 49 · Whole-genome sequencing is the broadest DNA scope

Gene panel

Whole exome

Whole genome

Conceptual coverage of selected regions; Blocks are not genomic-scale measurements

WGS examines coding and noncoding genomic regions.

It is the most comprehensive sequencing strategy discussed in this chapter.

Greater breadth increases analysis and interpretation demands.

Slide 50 · After a negative exome, WGS may be useful

Strong phenotype

Non-diagnostic WES

Consider WGS

The chapter places most medical-genetics WGS indications after unsuccessful WES.

The clinical prerequisite is persistently high suspicion of genetic disease.

Broadening assay territory may reveal changes missed by exon-focused testing.

Slide 51 · WGS includes noncoding sequence

Coding exons are a small part of the whole genome

Coding exons ≈1.5% of human genomic sequence (source estimate)

The blocks are schematic—not a proportional depiction of all exons.

A broader genomic assay can evaluate variation outside protein-coding exons.

This matters when a clinically important alteration may not lie in an exonic sequence.

Comprehensive coverage does not automatically confer comprehensive interpretation.

Slide 52 · WGS can detect structural rearrangements

Broad genomic reads

Structural change detection

Clinical assessment

The chapter gives insertions, deletions, and translocations as examples.

At sufficient depth, WGS can characterize novel structural genomic changes.

Such alterations may be relevant to cancer biology or clinical management.

Slide 53 · Cancer WGS may reveal noncoding alterations

Noncoding variants

Structural alterations

Clinical relevance review

A tumor genome includes potentially important changes outside conventional panel regions.

Broad analysis may find noncoding variants and novel structural rearrangements.

The value of a finding still depends on established biologic and clinical meaning.

Slide 54 · WGS is not yet a universal routine replacement

Cost

Turnaround

Informatics burden

The chapter identifies high costs as a barrier.

Longer turnaround and substantial informatics demands also hinder routine implementation.

A broader assay is useful only when it helps answer the clinical question.

Slide 55 · Breadth must be balanced against practical depth

Gene panel

Whole exome

Whole genome

Conceptual coverage of selected regions; Blocks are not genomic-scale measurements

Targeted testing concentrates resources on selected regions.

WES greatly expands the set of exons considered.

WGS provides broad genomic scope but increases the reporting and analysis burden.

Slide 56 · Targeted panel, WES, and WGS compared

Approach

Principal target

Typical purpose

Key trade-off

Gene panel

Selected genes / exons

Focused clinical diagnostics

Limited to chosen targets

WES

Protein-coding exons

Broad coding-variant search

Noncoding DNA largely excluded

WGS

Coding + noncoding genome

Most comprehensive DNA analysis

Cost, time, informatics

Slide 57 · Match test breadth to the clinical indication

Phenotype / clinical question

Choose assay scope

Interpret in context

Known disease-related gene set → targeted panel often provides efficient analysis.

Rare unexplained inherited disease → WES can expand the coding search.

High suspicion after unrevealing WES → WGS may examine broader genomic territory.

Slide 58 · Constitutional and somatic sequencing differ

Constitutional: Explain a hereditary phenotype

Somatic: Characterize a tumor’s alterations

Constitutional disease evaluation asks about inherited or constitutional variation.

Tumor profiling seeks acquired somatic changes relevant to an individual cancer.

Clinical interpretation and reporting priorities follow the indication.

Slide 59 · Illustrative case: Congenital deafness

Clinical reasoning exercise — hypothetical scenario

A child has congenital deafness; A molecular diagnosis is sought.

The clinical question implicates a defined group of genes rather than a single proven gene.

Which sequencing breadth best matches the initial question?

Clinical phenotype

Panel / WES / WGS?

Justify choice

Slide 60 · Case discussion: Choose a hearing-loss panel

Known gene group

Targeted panel

Interpret with phenotype

Targeted sequencing can cover a curated gene set relevant to congenital deafness.

Concentrated depth and focused interpretation are advantages.

If the panel is unrevealing, the residual suspicion and assay scope govern next steps.

Slide 61 · Illustrative case: Tumor recurrence

Clinical reasoning exercise — hypothetical scenario

A patient’s malignancy recurs after treatment.

An earlier molecular profile is available.

What additional question can repeat NGS testing address?

Prior profile

Recurrent tumor

Resistance mechanism?

Slide 62 · Case discussion: Repeat profiling at relapse

Original profile

Repeat NGS

Resistance assessment

Compare the recurrent tumor’s detected changes with the earlier profile.

Look for molecular evidence that could explain acquired resistance.

Review whether newly identified alterations are clinically relevant to later treatment.

Slide 63 · Illustrative case: Exome-negative rare disease

Clinical reasoning exercise — hypothetical scenario

A patient has a convincing genetic syndrome without an established molecular diagnosis.

Whole-exome testing has not identified a cause.

Should the genomic search end, or could it be expanded?

Strong clinical suspicion

Negative WES

What next?

Slide 64 · Case discussion: Broaden beyond coding exons

Exome unrevealing

WGS consideration

Extended interpretation

WGS consideration when WES is unrevealing and suspicion remains high.

WGS offers noncoding coverage and broader structural alteration assessment.

Even a more comprehensive assay requires careful interpretation.

Slide 65 · Interpret a negative result in assay context

A result can only be evaluated in relation to regions actually interrogated.

Sequencing depth and analytical methods influence what can be detected.

An unrevealing result does not negate a strong phenotype or clinical observation.

Slide 66 · Genomic results require clinicopathologic integration

Sequencing evidence

Phenotype / pathology

Clinical synthesis

Sequencing detects and characterizes molecular variation.

The clinician and laboratory determine whether the finding explains the presenting disease.

Cancer assays supplement morphology, diagnosis, treatment history, and other clinical facts.

Slide 67 · What NGS can and cannot establish

NGS can supply

NGS alone does not establish

Sequence differences within assay scope

That every difference is pathogenic

Read-depth and allele information

That every target is adequately covered

Cancer molecular profiling

That a particular therapy will succeed

Expanded genomic searches

That a negative result excludes disease

Slide 68 · Final clinical synthesis

Assay scope

Sequence evidence

Clinical significance

Choose the narrowest assay that adequately answers the clinical question.

Interpret depth, breadth, and target limitations together.

For constitutional disease: Integrate genotype with phenotype.

For cancer: Relate molecular findings to prognosis, therapeutic relevance, and recurrence.

Slide 69 · Principal reference

Robbins, Cotran & Kumar: Pathologic Basis of Disease, 11th edition (2026).

Relevant textbook sections: molecular genetic diagnosis and next-generation sequencing.

Clinical applications: targeted panels, whole-exome and whole-genome sequencing.

NGS principles and bioinformatics are included as foundational context.