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Primer/probe
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design and
testing
•
Obtain the drug and
marker/reference gene
transcript sequence.
•
Design at least three
primer probe sets for
therapeutic gene. Use
commercial primer/
probe sets if available for
marker/reference
sequences.
If only therapeutic gene
•
transcript is to be
quantitated, decide on
the inhibition control –
SPUD or other.
Select the probe
•
fluorophores based on
singleplex or multiplex
rT-qPCR.
Preparation of
standard for
quality controls
••
A standard RNA
fragment spanning the
sequence of
amplification. Usually
this will be synthetic
with 2’ O-methyl ribose
modification at least at
some locations for
stability.
•
Prepare QC solutions
HQC, MQC, LQC and
LOD after testing the
sensitivity of the
method. Test the quality
and store. At least 6
standards / calibrators
are made freshly before
each run. Acceptance
criteria are specified.
Selection of tissues for
biodistribution
/biomarker RNA levels
The biodistribution of AAV serotypes
has been extensively studied.
Confirm that the effect of expected
tissue matrices on the accuracy at
different QC levels is within the
acceptance criteria (PK).
•
If the serotype of the virus spreads
to many tissues at the dosage in the
study, select the most appropriate
tissues for method development.
•
Lipid Nanoparticles (LNPs) are
known to accumulate more in the
liver but may change by size of the
LNP.
•
Assay conditions for PD biomarker
and reference RNA with that of drug
target gene transcript need to be
optimized.
RNA extraction
– method
development
•
Mandatory for novel
sample types
Test if the same
•
extraction kit/ method
works best for all tissue
types selected,
specifically blood and
other.
•
Keep the quantification
methodology consistent
throughout.
Test the efficiency of
•
method by recovering
the spiked transcript. In
case of therapeutic
product, IVT RNA or
drug infected cell lysate
may be used.
Prevalidation and validation
with strictly defined criteria,
data transfer/reporting
•
For drug/therapeutic gene transcript,
test assay parameters such as accuracy,
precision, specificity, robustness using
the QCs and STD (Calibrators).
Clearly defined criteria for assay
•
parameters per guidelines need to be
set with an Standard Operating Protocol
and validation checklist.
•
Assay method needs to be verified by
spiking the RNA transcript in expected
tissue matrices to rule out the matrix
effect with clearly defined criteria.
Development of calculation strategies
•
or LIMS for real time PCR data files in
high throughput manner.
•
Design or selection of appropriate
model for relative quantification of
biomarker transcript.
Figure10.2 Guidelines for steps/workflow in practice for quantitation of AAV-based drug target transcripts (mRNA) by RT-qPCR.
10.3 Summary 265
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action and the regulation of expression and to identify biomarkers and correlative
endpoints of a potential new drug. Analysis of RNA and protein provides invaluable information of gene and protein expression within the spatial and morphological tissue context. Although in situ RNA detection techniques have been
around for years, the widely used in situ RNA ISH approach is the RNAscope ISH
based on ACD patented signal amplification and background suppression technology[68]. RNAscope can be used for both conventional chromogenic dyes for
bright‐field microscopy or fluorescence microscopy applications with multiplexing capability. The technology employs a probe design strategy of two independent double Z probes hybridizing to the target sequence in tandem for signal
amplification to occur. On average, ~20 double Z target probe pairs within a 1
target region are designed to specifically hybridize to the target molecule to ensure
selective amplification of target‐specific signals [68, 69]. During development
phase, it is crucial to evaluate probe specificity in the selected tissue type in addition to assay reproducibility. Preanalytical variables as stated previously also apply
as well. Since the ISH and IHC analysis share similar preanalytical workflows,
this allows the possibility to combine in situ hybridization and immunohistochemistry on the same slide. A combination of multiplex ISH and IHC also allows
for the co‐localization of gene and protein evaluation at the single‐cell level and to
understand cell‐by‐cell expression profiles, which is a powerful tool for understanding target engagement.
kb
10.3 Summary
Biomarker analysis has drawn more and more attention from industrial professionals, academic researchers, and regulatory agencies. Biomarker method covers
a wide range of analytical targets, technologies, and platforms; hence, understanding the context of substrate and distal biomarker measurements for gene
therapy is critical to determine the extent of method development, and method
validation work. In the current chapter, we discussed a variety of methodologies
for biomarker quantitation for gene therapy, including LC‐MS, histology and
imaging, functional activity and immunoassays, and mRNA detection assays. The
general overview, challenges for method development and validation, and respective regulatory guidelines were discussed, including selected examples and case
studies. The intention of this chapter is to provide guidance for biomarker quantitation, method selection, development and validation for genomic therapy, standardize practices, and eventually lead to more reliable biomarker data during drug
development.
10 Substrate and Distal Pharmacodynamic Biomarker Measurements forGene Therapy
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266
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11
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Detection ofCellular Immunity toViral Capsids and
Transgene Proteins
Maurus de la Rosa1 and Magdalena Tary-Lehmann
1
Sangamo Therapeutic Allée de la Nertière, Valbonne, France
2
CTL-Contract Laboratory, Cellular Technology Limited, Shaker Heights, OH, USA
2
11.1 Introduction
Gene delivery with recombinant adeno‐associated virus (rAAV) vectors is one of
the most promising gene therapy approaches, but immunity against the vector
capsid or the transgene poses a major challenge to successful long‐term efficacy in
humans. The immunity to rAAV vectors can be divided into humoral antibody‐
mediated immunity and cellular T‐cell‐mediated immune responses.
271
11.1.1 Humoral and Cellular Immune Responses toGene Therapy
A preexisting natural neutralizing antibody (NAb) response against the AAV capsid is a crucial hurdle for successful gene therapy treatments[1–4]. Preexisting
NAb responses against the capsid can efficiently neutralize the application of
gene therapy drug candidates[5]. Antibody responses against AAV serotypes are
mostly switched, indicating the presence of cluster of differentiation CD4
T-cells[2]. This finding suggests a full antiviral immune response against a natural serotype, including cytotoxic CD8 T‐cell responses, that could kill transduced
cells. Patients with preexisting anti‐AAV antibodies are often excluded from clinical trials to avoid any impact on safety and efficacy[1, 2, 6]. Additionally, a NAb
response against the rAAV capsid post treatment in an initially rAAV antibody‐
negative patient may block re‐dosing of the patient with the same vector.
Drug Development for Gene Therapy: Translational Biomarkers, Bioanalysis, and Companion
Diagnostics, First Edition. Edited by Yanmei Lu and Boris Gorovits.
© 2024 John Wiley & Sons, Inc. Published 2024 by John Wiley & Sons, Inc.
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272
Antibody responses against the transgene of an AAV vector have the potential to
limit drug efficacy[6–9]. In hemophilic patients, a persistent anti‐transgene response
could even limit protein replacement therapy. Hence, antibody responses to the AAV
capsid and the transgene are carefully monitored in all rAAV clinical trials.
Although clinical trials have advanced the knowledge of interactions between
rAAV vectors and the immune system, the role of T‐cell immunity against viral capsids is still not fully understood. For AAV liver‐tropic gene therapies, it is considered
that rAAV capsid‐specific cytotoxic CD8 T cells kill rAAV‐transduced cells and are
responsible for liver enzyme elevations and the loss of transgene expression [6].
This suggests a full anti‐capsid T‐cell immune response, where CD8 T cells might be
supported by rAAV‐specific CD4 helper T cells to exert an efficient cytotoxic immune
response. However, a T‐cell‐mediated response in enzyme‐linked immunosorbent
spot (ELISPOT) analyses of peripheral blood mononuclear cells (PBMCs) could
only be detected in some cases[1, 6, 10]. A clear correlation between the T‐cell‐
mediated cellular immune response, an increase in liver enzymes, and a drop in
transgene expression could not be observed for AAV liver‐tropic gene therapies.
However, for other gene therapy approaches like muscle‐targeting gene therapies,
T‐cell immunity is considered a major driver of immunogenicity events and loss of
transduced cells in patients[6, 10]. The lack of reliable predictive animal models
also underlines the need for careful monitoring of T‐cell responses in patients.
The attempt to understand these points by analyzing published clinical trial
data is challenging due to different patient populations, sampling regimes, vector
designs, and application routes. Moreover, the methods used to assess anti‐vector
immune responses in clinical trials are not standardized regarding sensitivity,
methodology, cut‐offs, sampling, sample quality, and reagents, adding additional
complexity in evaluating clinical results from different trials. In fact, these para
meters most likely contributed to the varying data sets described by different groups.
This chapter will focus on methods of detecting and characterizing T‐cell‐
mediated cellular immune responses in clinical trials. We share our view on assay
parameters that are considered relevant for high‐quality data and hence an
improved understanding of a crucial part of the immune response impacting
efficacy and safety.
Noteworthy, we understand T‐cell analytics as only one part of the clinical analytics required to improve the understanding of immune responses toward gene
therapeutic vectors.
-
11.1.2 Selected Clinical Observations Showing theLack
ofUnderstanding About T-Cell-Mediated Immune Responses and
theNeed forSensitive T-Cell Analytics
While some clinical trials of rAAV gene therapy succeeded, even resulting in the
approval of the first gene transfer therapies, others were less successful[1]. Mixed
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results have been obtained so far in gene therapy trials for hemophilia, with some
trials achieving long‐term efficacy, while others observed loss of transgene expression, hypothesized to be due to immune‐mediated loss of transduced cells, often
in conjunction with liver transaminase increases[1, 11]. However, although a correlation between the loss of transgene expression, liver transaminase increases,
and cellular anti‐AAV T‐cell responses could be observed in some patients, this is
not the case in other patients. A clear correlation could not be shown yet.
In the first trial of rAAV‐mediated gene transfer of human FIX in hemophilia B
patients with successful proof of concept, transgene expression was limited to
approximately eight weeks, followed by a gradual decline in FIX expression that
was accompanied by transient, asymptomatic liver transaminase increases[9]. It
was hypothesized that both were caused by the T‐cell‐mediated elimination of
transduced hepatocytes, elicited by capsid antigens. Subsequently, it was demonstrated that AAV‐specific memory CD8 T cells are present in the human population and can be reactivated following rAAV‐mediated gene transfer; prior infection
with wild‐type AAV with generation of capsid‐specific memory T cells was
hypothesized to be the main cause of the observed immune response[8, 12, 13].
In the first trial with long‐term success in hemophilia B, patients with preexisting
natural AAV‐NAbs were excluded[14, 15]. Some patients who received high doses
developed transient increases in liver transaminases that were successfully managed with glucocorticoids to suppress anti‐rAVV T‐cell responses and did not
cause substantial loss of transgene expression.
In other trials, glucocorticoid treatment alleviated liver transaminase increases
but did not prevent the loss of transgene expression. In a trial with six hemophilia
B patients, liver transaminase increases followed by transgene loss were observed
in all but one patient, and transgene loss could not be prevented by glucocorticoid
treatment[16]. Loss of transgene expression was also observed in seven of eight
hemophilia B patients in another trial[10]. In the patients with transgene loss in
the low‐dose cohort, there were neither concomitant transaminase increases nor
signs of T‐cell or antibody responses to the vector or transgene. Concomitant liver
transaminase increases were only observed in the high‐dose cohort, and capsid‐
directed T‐cell activation was only observed in two of these patients by interferon
(IFN)‐gamma ELISPOT assay. While the transaminase increases and T‐cell activation could be managed by glucocorticoid treatment, this did not stop the loss of
transgene expression.
Gene therapy with rAAV vectors has also been explored for other indications,
including delivery to the muscle, eye, or central nervous system[17]. A range of
successful clinical trials have been reported for neuromuscular diseases of genetic
origin, where liver transaminase increases and capsid‐directed T‐cell responses
were often observed, but usually not associated with the loss of transgene [1].
However, in two trials in Duchenne muscular dystrophy, patients experienced
rapid activation of the immune system with T‐cell and antibody responses, and
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