HIV Sequence Variation, Drug Resistance, and Laboratory Testing

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HIV Sequence Variation, Drug Resistance, and
Laboratory Testing

• Robert Shafer, MD
• Division of Infectious Diseases
• Stanford University
• (10/23/04)

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Outline

• HIV-1 genetic variation and drug resistance
• Molecular targets of therapy and drug resistance
  testing
• Drug resistance surveillance
• New drugs
• New laboratory markers

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32 yo man with drug-resistant HIV infection - 1

• 32 man diagnosed with HIV in 1989
• 1992 AZT 1994 AZT ddC
• Sept 1994 Phase I/II trialSQV 1800 mg TID
• 8 wk CD4 229 gt 472, HIV RNA 180,000 gt
  12,000
• 24 wk CD4 and HIV RNA back to baseline
• Sept 1994 to Sept 1996 patient took 3 different
  HAART regimens including d4T 3TC IDV then d4T
  ddI RTV SQV then AZT ddI 3TC
• Each time HIV RNA decreased 1-1.5 logs but never
  lt400 and eventually increased to 10,000-20,000.
  CD4 stable at about 240

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32 yo man with drug-resistant HIV infection - 2

• RT M41L, D67N, L210W, T215Y, K219N M184V
  E44D, V118I
• Protease G48V, I54T, V82A L10I, L63H, A71V,
  V77I
• PBMC susceptibility assay
• AZT, 3TC gt100-fold resistant
• ddI, ddC, d4T 3- to 5-fold resistant
• SQV, IDV, RTV, NFV 30- to 100-fold resistant
• NVP susceptible
• Patient asked for advice on drug therapy

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32 yo man with drug-resistant HIV infection - 3

• 1/97 Patient D/Cd HAART regimenHIV RNA
  increased 10,000 gt 250,000 CD4 stayed the same
  at about 240 cells
• Patient restarted HAART d4T 3TC RTV SQV

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32 yo man with drug-resistant HIV infection - 4

• 1998 to 1999 EFV, ABC, APV, and PMEA became
  available
• CD4 180-200 HIV RNA 20,000-30,000

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32 yo man with drug-resistant HIV infection - 5

• 1998-1999 HIV RNA ? to 300,000 and CD4 ? to 105
• June 1999, patient enrolled in a Phase I/II study
  of T20. Eligibility criteria must be NNRTI
  naive
• Began T20 EFV ABC RTV/APV
• Sept 1999 HIV RNA lt50 CD4 260
• May 2000 HIV RNA lt50 CD4 260
• Jan 2002 HIV RNA lt50 CD4 300

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Drug Resistance in the HAART Era

• Many heavily-treated persons already have highly
  drug-resistant viruses
• Primary drug resistance is common
• Margin of success is narrow

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HIV Genetic Variation

• Generation of variation
• No RT proofreading 1 error per 104 - 105
  nucleotides
• High replication rate
• Recombination
• Proviral DNA archive
• Selection of variants
• Chance (neutral substitutions)
• Host immune system
• Anti-HIV drugs

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Two Types of RNA Virus Variability
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HIV Genetic Variation
0.10
Korber et al. 2001
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Primate Immunodeficiency Viruses

• HIV-1 is one of gt 5 primate lentiviruses (PIV)
  that share similar genomic structures and
  phylogenetic relatedness.
• HIV-1 and HIV-2 infect humans.
• Each of the viruses infect old world primates.
  Primate infection is generally species-dependent.
• HIV-1 and HIV-2 cause disease in humans. HIV-1,
  HIV-2, and the other PIV rarely cause disease in
  primates.

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Origin of HIV-1

• The HIV-1 pandemic resulted from a single
  cross-species transmission that took place
  sometime prior to 1959 probably within this
  century (Group M).
• HIV-1 was probably transmitted to humans from a
  Common chimpanzee (Pan troglodytes).
• At least 2 other cross-species transmissions have
  occurred (Group O, Group N).

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HIV-1 Groups

• Group M (main) viruses are responsible for the
  HIV-1 pandemic. They resulted from a single
  cross-species transmission sometime this century
  and have evolved into 6-10 subtypes.
• Group O (outlier) resulted from a separate
  cross-species transmission and less widespread.
• Group N (non-M, non-O) was identified in 1998 and
  represents a third cross-species transmission.

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HIV-1 Subtypes

• HIV-1 Group M has evolved into 9 different pure
  subtypes (A, B, C, D, F, G, H, J, K), two common
  recombinant forms (A/E, A/G), and countless other
  recombinant and mosaic forms.
• Subtypes differ from each other by 10-30 in
  different parts of the HIV genome.
• There are no proven biological differences
  between the different subtypes.

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Timing the Ancestor of the HIV Pandemic Strains.
Korber et al. Science 2000
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Evidence of HIV-1 adaptation to HLA-restricted
immune responses at a population level
Moore et al. Science 2002
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Intrahost Evolution

• Evading host immune response
• Developing drug resistance
• Change in co-receptor utilization
• NSI (CCR5) ? SI (CXCR4)

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Leading Causes of Death Among Persons 25-44,
USA, 1982-1998
Preliminary 1998 data
National Center for Health Statistics National
Vital Statistics System
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Targets of Drug Therapy

• Reverse transcriptase
• Nucleoside analogs (8)
• Non-nucleoside inhibitors (3)
• Protease
• Protease inhibitors (7)
• Cell entry
• Fusion inhibitor (1)
• Chemokine receptor inhibitors

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HIV-1 Protease Bound to an Inhibitor
Active site
Substrate Cleft
Indinavir
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HIV-1 Protease Drug Resistance Mutations
Active site
Substrate Cleft
Major mutations
Indinavir
Minor mutations
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Conserved
Known resistance mutation
Treatment-associated mutation
Polymorphic, not associated with Rx
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HIV-1 RT with RNA Template, DNA primer, and
Catalytic Complex
p66
p51
Active site
Incoming nucleotide
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HIV-1 RT Active Site and Nucleoside Analog Drug
Resistance Mutations
Active site
Drug resistance mutations
Incoming nucleotide
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HIV-1 RT Bound to a Non-Nucleoside RT Inhibitor
(NNRTI)
Active site
Nevirapine
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NNRTI-Associated Drug Resistance Mutations
Active site
Nevirapine
Drug resistance mutations
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Types of HIV Drug Susceptibility Assays
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Advantages of Recombinant Virus Assays

• Can test cryopreserved samples including plasma,
  serum
• Assesses circulating virus
• Culture unnecessary
• Automated

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Creating a Recombinant Virus
PCR fragment (gag/Pro/RT)
Transfect
WT lab strain
Infectious virus
Deleted proviral clone
T-cell
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Region Covered by Phenotyping
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Drug Susceptibility - Dose Response Curves
100
Antiviral Effect ()
Wild type lab strain
50
Patient strain
0
IC50, WT
IC50, pt
Drug Concentration
IC50 50 inhibitory concentration Fold change
IC50, pt / IC50, WT Example IC50, pt 5 µM and
IC50, WT 0.5 µM ? 10-fold change
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Drug susceptibility cut-offs

• Technical cut-offs are derived from the
  reproducibility of the assay on an individual
  sample
• Biological cut-offs are derived by testing large
  numbers of wildtype isolates from untreated
  persons
• Clinical cut-offs are derived from data
  correlating drug susceptibility to a drug and
  virologic response to that drug

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Genotype vs Phenotype
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HIV-1 Quasi-Species Distribution of Genetic
Variants
21 clones of HIV-1 protease from the plasma of a
heavily treated patient
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Sequence Mixtures
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Gene Sequencing

• Research Identify new drug-resistance mutations
• Clinical Identify known drug resistance
  mutations.
• --------------------------------------------------
  ----------------------------
• Plasma is ultracentrifuged and RNA is extracted
• Extracted RNA is reverse transcribed to cDNA
• Nested PCR generates 1.3 kb amplicon containing
  protease and 1st 300 residues of RT
• Dideoxynucleoside cycle sequencing
• Reaction products are resolved electrophoretically

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Molecular Targets of HIV Therapy
GAG
POL
ENV
Pr
RT
INT
297 na
1680 na
kb
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Genotypic Resistance Testing - I
CCTCAGATCACTCTTTGGCAACGACCCATAGTCACAATAAAGATAGCGGG
ACAACTAAAGGAAGCTCTATTAGATACAGGAGCAGATGATACAGTATTAG
AAGAAATGAATTTGCCAGGAAAATGGAAACCAAAAATAATAGTGGGAATT
GGAGGGTTTACCAAAGTAAGACAGTATGATCATGTACAAATAGAAATCTG
TGGACATAAAGTTATAGGTGCAGTATTAATAGGACCTACACCTGCCAATA
TAATTGGAAGAAATCTGTTGACTCAGCTTGGCTGTACTTTAAATTTT
PQITLWQRPIVTIKIAGQLKEALLDTGADDTVLEEMNLPGKWKPKIIVGI
GGFTKVRQYDHVQIEICGHKVIGAVLIGPTPANIIGRNLLTQLGCTLNF
Differences from Consensus B L10I, G17R, K20I,
E35D, N37S, M46I, I62V, L63P, A71I, G73S, I84V,
L90M, I93L
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Interlaboratory Reproducibility Sequencing Plasma
from Heavily Treated Pts (Stanford Virco)
DRM drug resistance mutations
J Clin Micro 2001
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Genotypic Resistance Testing - II
Differences from Consensus B L10I, G17R, K20I,
E35D, N37S, M46I, I62V, L63P, A71I, G73S, I84V,
L90M, I93L
Level of resistance to each of the PIs
including dual PIs APV
NFV IDV RTV LPV
SQV ATV
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Drug Resistance Knowledge Base

• Which mutations are selected by treatment?
• In vitro (virus passage experiments)
• In vivo (in patients receiving the treatment)
• Which mutations cause phenotypic resistance in
  vitro?
• Laboratory isolates
• Clinical isolates
• Which mutations interfere with response to a new
  treatment?

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Stanford HIV Drug Resistance Database

• http//hivdb.stanford.edu
• 27,000 virus isolates
• 12,000 individuals
• 24,000 drug susceptibility results
• 520 references

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Mutations Selected by Nelfinavir (NFV)
mutant in subtype B isolates from untreated
persons (n2400)
mutant in subtype B isolates from NFV-treated
persons (n360)
http//hivdb.stanford.edu
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Reduction in Abacavir Susceptibility with RT
Mutations at Positions 41, 184, 210, 215
Wildtype isolates
Mutant isolates
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Virologic Response to Salvage Therapy
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PI Mutation Patterns in 4,183 Persons
Rhee SY et al AAC, 2004
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NRTI Mutation Patterns in 4,183 Persons
Rhee SY et al AAC, 2004
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NNRTI Mutation Patterns in 4,183 Persons
Rhee SY et al AAC, 2004
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Interactions Between HIV-1 RT Drug Resistance
Mutations
Compensatory reduction in AZT, d4T, and
TDF resistance in viruses containing T215Y/F
184 (3TC)
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NRTI-NNRTI Resistance Interactions
NNRTI Mutations (L100I, Y181C)
Compensatory reduction in AZT resistance
NRTI Mutations (41, 215 ...)
Compensatory reduction in NNRTI resistance
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Two Mechanisms of NRTI Resistance

• Loss of affinity of RT for the analog
• Examples M184V, Q151M, K65R, L74V
• Repair of the terminated DNA-chain
• pyrophosphorolysis, nucleotide excision,
  primer unblocking
• Classical AZT resistance mutations (TAMs)41,
  67, 70, 210, 215, 219
• The loss of affinity mutations often interfere
  with the primer unblocking mutations

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NRTI Susceptibility Testing

• Susceptibility testing works best for the PIs and
  NNRTIs.
• In contrast, the NRTIs are prodrugs that must be
  triphosphorylated to become active.
• Triphosphorylation occurs at different rates in
  different cell types and the activated
  lymphocytes used for susceptibility testing do
  not provide the best assessment of drug activity
  or loss of activity in vivo.

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Protease Cleavage Site Mutations

• HIV-1 protease specifically recognizes and
  cleaves 9 protease cleavage sites (8-mers) in gag
  and pol.
• Mutations at these sites often develop as
  compensatory changes to increase the replication
  of viruses that contain PI-resistance mutations.

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Sequence Quality Control

• Molecular epidemiology
• Compare each nucleic acid sequence to all
  sequences generated within the past several
  weeks.
• Compare the sequence to previous sequences from
  the same patient.

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Sequence Analysis Programs HIVseq, HIVdb
Meaningful Results
(1) Quality control (2) Sequence
Interpretation (3) Literature references
Shafer, Jung, Betts Nature Medicine (11/2000)
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HIVdb Program Output - I
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HIVdb Program Output - II
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HIVdb Program Output - III
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HIVdb Program Output - IV

• Each score is a link to data linking the mutation
  to the drug

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Genotypic Resistance Interpretation
Concordance ANRS, HIVDB, Rega, VGI
Ravela et al. JAIDS 2003
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PI-Associated Mutations and Drug Resistance
Surveillance (Subtype B)
K20I is consensus for G and CRF02_AG V11I, L33F,
E35G, P74A/S, and L89I are polymorphic in one or
more non-B subtypes (range 1-4)
Rhee SY et al. submitted
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NRTI-Associated Mutations and Drug Resistance
Surveillance (Subtype B)
K43E is consensus for CRF01_AE E44D and T139M
are polymorphic in one or more non-B subtypes
(range 1-3)
Rhee SY et al. submitted
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NNRTI-Associated Mutations and Drug Resistance
Surveillance (Subtype B)
V179E occurred at a prevalence of 7 in subtype
G F227L occurred at a prevalence of 2 in
subtype F.
Rhee SY et al. submitted
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Subtypes and Drug Resistance

• Each of the current HIV drugs was developed by
  targeting subtype B viruses.
• Most in vitro studies and clinical data suggest
  that current drugs are as active against subtype
  B as they are against non-B viruses.
• But there are few data on the genetic mechanisms
  by which non-B viruses become resistant to
  current HIV drugs.
• Each of the known-drug resistance mutations has
  been reported in at least one non-B isolate.
• The patterns of mutations associated with
  treatment failure may differ between the subtypes

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New Laboratory Tests

• Common
• Therapeutic drug levels (TDM)
• Replication capacity (RC)
• Experimental
• Host genetic factors
• HLA
• Chemokine receptor and chemokine variants
• CYP450 variants
• Other host cellular partners
• Virus tropism (X4, R5)
• Sequencing of PBMCs and minor variants

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Kilby and Eron, NEJM 2003
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Examples of Inhibitors of HIV-1 Cell Entry in
Development
Kilby, J. M. et al. N Engl J Med
20033482228-2238