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Current
Cancer Therapy Reviews
ISSN: 1573-3947
Current Cancer Therapy Reviews
Volume 4, Number 2, May 2008
Contents
Cancer Biomarkers
Guest Editor: Robert C. Rees
Dedication to Professor Tony Dodi Pp.
i
Editorial Pp. 77-78
Emerging Breast Cancer Biomarkers Pp. 79-85
Stephanie A. Laversin, Amanda K. Miles, Graham R. Ball
and Robert C. Rees
[Abstract]
Overview of Prostate Biomarkers as Potential
Targets for Immunotherapy Pp. 86-95
Amanda K. Miles, Alistair Roger, Richard Parkinson, Robert
C. Rees and Stephanie E.B. McArdle
[Abstract]
Prognostic Biomarkers of Cutaneous Malignancies
– Serological, Immunohistochemical and Proteomic Approaches
Pp. 96-104
Dirk Schadendorf, Jochen Utikal, Balwir Matharoo-Ball,
Robert C. Rees and Selma Ugurel
[Abstract]
HLA Class I Expression, Tumor Escape and Cancer
Progression Pp. 105-110
Natalia Aptsiauri, Teresa Cabrera, Angel Garcia Lora,
Francisco Ruiz Cabello and Federico Garrido
[Abstract]
Monitoring T Cell Responses to Cancer Immunotherapy:
Can We Now Identify Biomarkers Predicting Patients Who will
be Responders Pp. 111-119
Evelyna Derhovanessian, Cécile Gouttefangeas, Sven
Koch and Graham Pawelec
[Abstract]
NK Cell, Monocyte and Non T Cell Biomarkers as Prognostic
Indicators in Cancer Immunotherapy Pp. 120-124
Renu Datta, Catherine L. Riley, Italo A. Dodi and Robert
C. Rees
[Abstract]
Lymphocyte Biomarkers of Clinical Responses to
Adoptive Immunotherapy of Malignant Melanoma Pp.
125-129
Nathalie Labarrière, Brigitte Dreno and Francine
Jotereau
[Abstract]
NK Cell Receptor and MHC Gene Polymorphisms,
Potential Relevance in Malignancies Pp. 130-136
Anastassia Mihaylova Snejina Mihailova and Elissaveta
Naumova
[Abstract]
Application of Proteomics to the Discovery of
Cancer Biomarkers Pp. 137-143
Murrium Ahmad and Balwir Matharoo-Ball
[Abstract]
Protein Glycosylation as Marker of Melanoma Progression
Pp. 144-148
Anna Litynska, Malgorzata Przybylo, Dorota Hoja-Lukowicz,
Ewa Pochec, Marcelina Kremser, Dorota Ciolczyk-Wierzbicka,
Maria Labedz and Piotr Laidler
[Abstract]
Autoantibody Profiles as Biomarkers for Response
to Therapy and Early Detection of Cancer Pp. 149-156
Zane Kalnina, Karina Silina and Aija Line
[Abstract]
Computational & Statistical Methodologies
to Identify Biomarkers in Cancer Pp. 157-160
Graham R. Ball
[Abstract]
Practical Aspects in the Use of Biomarkers for the
Development of Cancer Vaccines Pp. 161-165
Angus G. Dalgleish
[Abstract]
Abstracts
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Dedication to Professor Tony Dodi
Earlier this year our dear friend and colleague Professor
Tony Dodi died suddenly. He was a Scientist of immense integrity
and worked with many of the authors who have contributed to
the current series of articles focussing on Cancer Biomarkers.
His laboratory at Nottingham Trent University (NTU) authored
the article entitled “NK Cells, monocytes and Non T-cell
biomarkers as prognostic indicators in cancer immunotherapy”
in issue 1 and he contributed enormously to the progress and
wellbeing of the ENACT Research programme funded by the EU
under FP6.
During his career, Tony worked with Robert Lachler and Richard
Bachelor at The Royal Postgraduate Medical School, Hammersmith
London, prior to joining Professor Alejandro Madrigal at the
Anthony Nolan Research Institute. In 2005, Tony was appointed
as Professor of Haemato-oncology and Head of Leukaemia Research
at NTU. He also continued to head the Immunotherapy Group
at the Anthony Nolan Research Institute in London.
His legacy exists in the research he undertook in the field
of Cancer Immunotherapy and Transplantation Immunology and
he was recently involved in the development of the Anthony
Nolan Cord Blood Programme, which was developed as a result
of his enthusiasm and energy.
From the outset, I admired his research ability and determination
and consider it to be a distinct privilege as well as pleasure
to have known Tony as a colleague and close friend.
He is sorely missed by all who knew him and we wish to dedicate
this series of papers to his memory. We will not forget Tony’s
contribution to our research endeavours.
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Editorial: Cancer Biomarkers
Cancer is a genetic disorder resulting in a change
in cell growth pattern, cell phenotype and functional traits.
Tissue integrity is challenged as a result of malignancy,
placing the host-cell equilibrium under threat. In particular
the immune system may respond to cancer in several ways: (1)
to the benefit of the host by mediating the destruction of
the malignant cells, (2) provide the tumour with an additional
growth advantage by changing the tissue micro-environment
to enhance tumour cell survival and growth potential or (3)
become tolerant to the presence of the tumour through interaction
with tumour or host cell derived products, thereby allowing
the tumour to develop “unchecked”. Although single
biomarkers have been identified for several cancers, the dynamic
biological relationship between the host and the cancer will
be reflected through extensive and differing genetic, protein
and cell response “signatures”, derived from both
host and tumour cells. Biomarkers may predict the presence
of cancer and associate with diagnosis, prognosis and outcome
of therapy.
The development of advanced bio-molecular techniques for the
interrogation of complex genetic, protein, biological data
and clinical parameters has led to new opportunities for defining
cancer biomarkers. There is a pressing need for more reliable
markers that associate with disease status and importantly
with response to therapy. Many cancers are detected late in
the disease process when more aggressive therapy is required
and although treatment may succeed in eradicating the disease
it is often difficult to predict patient outcome following
treatment. It is well reported that first line treatment may
fail to stem the disease course; thus, providing a more accurate
assessment of the likely outcome of therapy would allow appropriate
treatment options to be administered at an earlier stage.
For these reasons it is important to focus research on the
identification of new cancer biomarkers with predictive capability.
This publication provides an insight into important research
areas of current interest, describing “state of the
art” methods that are being used to identify new, disease
–associated genes / gene products that have utility
as cancer biomarkers. Many of the studies focus on markers
detected in response to immunotherapy, for example, where
a specific immune response can be defined and monitored, which
in some cases may be indicative of patient outcome. This involves
the assessment of adaptive T-cell mediated immunity and innate
immune mechanisms using phenotypic and functional characteristics
or the measurement of soluble serum factors produced either
by leukocyte populations or as a consequence of host cell
– tumour cell interaction (Pawelec et al.,
Dodi et al., Schadendorf et al.). Some of
the many characteristics of cancer cells, for example the
loss of MHC which represents a tumour escape mechanism, have
been recognised as indicators of patient prognosis (Garrido
et al.). Another important area of research focuses on
profiling autoantibody responses against tumour –associated
proteins, many of which have been discovered through screening
cDNA libraries and antigen arrays. Protein micro-arrays in
particular may prove to be beneficial for the rapid screening
of patient sera for antibody responses to onco-proteins and
normal cellular proteins (Miles et al.). Gene arrays
and interrogation for the serum and cancer cell proteome using
currently available separation and analytical methods coupled
with bioinformatic analysis of complex data sets, allows an
integrated approach to be adopted for biomarker discovery.
The combined assessment of proteomic, genetic, immunological
and clinical data may prove to be of greater value in defining
a set of markers with greater accuracy of prediction (Laversin
et al.).
This issue further continues with reviews on cancer diagnosis,
prognosis and predictive responses that are likely to influence
therapeutic intervention in the future. The host-cancer relationship
is complex and the sequel of pathological mechanisms occurring
during progression of the disease will dictate the genetic
and protein expression profile that can be detected. Biomarkers
may be used to predict the presence of cancer, although there
is a continuing need for more reliable indicators of disease
and it is unlikely that single biomarkers will prove to be
accurate and reliable.
The paper by Labarriere et al. describes the current
status of research using adoptive cellular therapy, as developed
by the group of Francine Jotereau in Nantes. They describe
the clinical and biological consequences of adoptive T-cell
transfer and the clonal response and T-cell phenotype / genotype
associating with long term patient survival. Mihaylova et
al. further discusses the role of NK associated ligands
and receptors as potential markers associating with susceptibility
to cancer. The paper includes important concepts of KIR –
HLA interactions and NKG2D –Mic proteins, that impact
on genetic diversity. The application of proteomics using
mass spectrometry techniques combined with bioinformatic analysis
to determine protein and peptide signatures and obtain protein
identity is addressed (Ahmad and Matharoo-Ball) and the complexity
of post-translational protein modifications is highlighted
by Litynska et al. through studies that describe
glycosylation pathways associating with melanoma. Kalnina
and colleagues discuss the use of phage display –based
SEREX analysis and protein micro-arrays for identifying tumour
antigens and autoantibody responses occurring in patients.
We are increasingly aware of the requirements for analysis
of complex data arising from genomic, proteomic and immunological
profiling and the application of statistical methodologies
is recognised as essential for the interrogation of large
data sets. Graham Ball describes the “state of the art”
of bioinformatic approaches, applying statistical algorithms
to the analysis of complex biological data. The final paper
by Angus Dalgleish overviews the status of biomarkers in cancer
as they are currently used in clinical practice and the development
of vaccine strategies for the treatment of disease.
The European 6th Framework
programme “European Network for the identification and
validation of Antigens and biomarkers in Cancer and their
application in clinical Tumour immunology” ENACT (www.enactcancerresearch.org)
has provided a platform to explore the utility of predictive
cancer biomarkers associating with patient response to immunotherapy.
This programme has involved the integration of clinical and
laboratory research and utilised a wide variety of disciplines
which has resulted in a better understanding of how novel
biomarkers can be discovered and applied to medical practice.
Research centres involved in the ENACT programme have contributed
to the series of review papers published in this issue of
the journal.
Robert C. Rees, PhD
Director, the John van Geest Cancer Research Centre
The School of Science and Technology
Nottingham Trent University
Clifton Lane
Nottingham
NG11 8NS
UK
E-mail: robert.rees@ntu.ac.uk
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Emerging Breast Cancer Biomarkers
Stephanie A. Laversin, Amanda K. Miles, Graham R. Ball
and Robert C. Rees
The most common cancer for women in the United Kingdom
is breast cancer and it is well known that genomic modifications
are responsible for breast carcinogenesis. Major developments
in genomics and proteomics have uncovered biomarkers which
have a crucial role in this process. To move towards individualized
and improved breast cancer care, there is a need for tumor
markers that are associated with disease diagnosis, prognosis,
treatment and monitoring. General opinion is that biomarkers
can bring more accurate and sensitive tools to the clinical
settings than conventional approved histopathological parameters.
However, clinical applications of breast tumor markers remain
quite low in numbers because the data regarding these novel
markers for breast cancer is limited and do not allow well-grounded
conclusions. This review presents a non exhaustive selection
of biomarkers published, some validated, and their uses in
breast cancer management.
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Overview of Prostate Biomarkers as Potential Targets for Immunotherapy
Amanda K. Miles, Alistair Roger, Richard Parkinson, Robert
C. Rees and Stephanie E.B. McArdle
Prostate cancer remains one of the most common cancers
in men and treatment options for patients with advanced or
metastatic disease are limited. Immunotherapeutic approaches,
such as passive or active immunotherapy, have been shown to
be successful in treating some cancer patients. These rely
on the identification of cancer specific antigens that can
be targeted by the immune system or used to diagnose as early
as possible and/or to monitor the disease and its progression.
Several prostate cancer antigens have already been identified;
these include Prostate-Specific Membrane Antigen (PSMA), Prostate
Specific Antigen (PSA), Prostatic Acid Phosphatase (PAP),
PAGE-4, PSP 94, differential display 3, prostate androgen-regulated
transcript 1 and six-transmembrane epithelial antigen prostate-restricted
antigens and these represent potential candidate for immunotherapy
against prostate cancer. The following review describes the
importance of these antigens with a particular emphasis to
the PAP antigen and T21, a recently identified prostate cancer
associated antigen, as very promising targets for prostate
therapy.
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Prognostic Biomarkers of Cutaneous Malignancies – Serological,
Immunohistochemical and Proteomic Approaches
Dirk Schadendorf, Jochen Utikal, Balwir Matharoo-Ball,
Robert C. Rees and Selma Ugurel
Biomarkers become more and more important tools in clinical
diagnosis of cutaneous malignancies. Furthermore, after vigorous
validation, biomarkers may have influence on future prognostic
classification systems. Clinical and histopathological parameters
such as anatomic site, type of the primary tumor, tumor size,
invasion depth, ulceration, vascular invasion, lymph node
involvement and others are well established for their prognostic
value. Additionally, an increasing variety of molecular markers
have now been identified and described, providing a potential
powerful platform for a more precise diagnosis and a more
accurate prognostic sub-grouping of tumor entities. This might
lead to future changes in existing classification systems,
and might have consequences for the treatment and outcome
of skin cancer patients. Recently published gene expression
or proteomic profiling data relate to new marker molecules
involved in skin cancer pathogenesis, which may, after validation
by suitable studies, represent future prognostic or predictive
biomarkers in cutaneous malignancies. The aim of this report
is to summarize the currently known serologic and newer immunohistochemical
biomarker molecules in the most common cutaneous malignancies
malignant melanoma, squamous cell carcinoma, and cutaneous
lymphoma, particularly emphasizing their prognostic and predictive
significance.
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HLA Class I Expression, Tumor Escape and Cancer Progression
Natalia Aptsiauri, Teresa Cabrera, Angel Garcia Lora,
Francisco Ruiz-Cabello and Federico Garrido
The progress in genomics and proteomics resulted in increasing
number of tumor-associated antigens (TAA) being discovered
as cancer biomarkers and targets for immunotherapy. The key
role played by HLA class I antigens in immune reactivity against
malignant and virally infected cells via binding to the peptides
of TAA and subsequent presentation to cytotoxic T-lymphocytes
stimulates interest in the characterization of their expression
in tumor cells. Various types of HLA class I alterations with
different underlying molecular mechanisms are found in different
malignancies. Loss or downregulation of tumor HLA class I
antigen expression represents one of the main mechanisms used
by cancer cells to evade immunosurveillance since it limits
the ability of cytotoxic T-cell to eliminate these cells and
reduces the clinical efficacy of T-cell-based cancer therapy.
As a result of the immune selection, HLA class I negative
variants escape and lead to tumor growth and metastatic colonization.
Altered HLA class I expression on malignant cells frequently
correlates with poor survival, disease progression and limited
response to T-cell-based therapy. Early cancer detection and
treatment require more effective cancer biomarkers, or molecular
signatures, for diagnosis, prognosis, and therapeutic efficacy.
Analysis of the tumor expression of HLA class I antigens as
biomarkers of cancer development might help to choose an appropriate
treatment protocol and monitor clinical response to cancer
immunotherapy.
[Back to top]
Monitoring T Cell Responses to Cancer Immunotherapy: Can We
Now Identify Biomarkers Predicting Patients Who will be Responders
Evelyna Derhovanessian, Cécile Gouttefangeas, Sven
Koch and Graham Pawelec
The immune system plays an important role in eliminating
tumors. Accordingly, many immunotherapy protocols have been
developed in attempts to boost anti-tumor immune responses
in cancer patients. These trials most commonly aim at augmenting
T-cell-, especially CD8+ T-cell, responses. In clinical trials
performed to date, however, little correlation has been observed
between parameters measured to assess cellular immune responses
and clinical outcome. Thus, identification of reliable surrogate
predictors for evaluation of cancer vaccine efficacy still
remains to be accomplished and would be crucial for successfully
pursuing clinically significant results. In this review, we
discuss the role of different cellular components of the immune
system in orchestrating and regulating an anti-tumor immune
response, and how to reliably monitor these using polychromatic
flow cytometry (FC). The increasing use of multi-parameter
FC is expected to be as revolutionary for immunomonitoring
as was the introduction of first generation technology. The
application of this novel technology and more standardised
monitoring assays should help identify biomarkers reliably
distinguishing patients who respond to treatment.
[Back to top]
NK Cell, Monocyte and Non T Cell Biomarkers as Prognostic
Indicators in Cancer Immunotherapy
Renu Datta, Catherine L. Riley, Italo A. Dodi and Robert
C. Rees
Identification and characterisation of tumour associated
antigens is a pre-requisite for an effective and targeted
immunotherapy. Tumour antigens are used as markers to improve
diagnosis and to predict the outcome of a cancer. This review
emphasises on a few important cellular target molecules such
as indoleamine 2,3-dioxygenase (IDO), interleukin-15 (IL15),
mucin 1 (MUC1) and Major histocompatibility complex class
I related chain A and B (MICA/B) which are involved in the
downstream pathways of cancer progression. Unique aberrant
and over-expression of these molecular targets modulates the
physiological and immunological micro-environments in the
host tissue. IDO, IL15 and MICA/B provoke NK cell and dendritic
cell mediated anti-tumour responses due to their strong binding
affinity to activator receptors on the immune cells. The application
of these random markers derived from immunological mechanisms
may help to improve and delineate some of the predictive indicators
obtained with random serum profiles.
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Lymphocyte Biomarkers of Clinical Responses to Adoptive Immunotherapy
of Malignant Melanoma
Nathalie Labarrière, Brigitte Dreno and Francine
Jotereau
During the last few years, adoptive cellular therapy
(ACT) — the isolation of antigen-specific lymphocytes,
their ex vivo expansion and activation, and subsequent
autologous administration — has been tested for treatment
of melanoma tumours. Initial ACT used melanoma -infiltrating
lymphocytes (TIL) that often contain tumour reactive lymphocytes,
of diverse, mostly unknown, specificities [1, 2]. Recently,
the identification of melanoma antigens [3] and the development
of techniques for selection and expansion of epitope specific
T cells has opened the way to the use of tumour antigen specific
T cells, and importantly to immune follow up of ACT [4-9].
Despite these advances, several issues remain to address to
achieve the major aims of ACT, as the rapid production of
clinical grade T cells capable of eliciting a significant
destruction of tumour tissue.
[Back to top]
NK Cell Receptor and MHC Gene Polymorphisms, Potential Relevance
in Malignancies
Anastassia Mihaylova Snejina Mihailova and Elissaveta
Naumova
Progress in the field of NK cell receptors (NKRs) and
their ligands has revolutionized our concept of how NK cells
selectively recognize and lyse tumor while sparing normal
cells. Major families of NKRs that inhibit and activate NK
cells to lyse target cells have been characterized, including
killer cell immunoglobulin-like receptors (KIRs), C-type lectins,
and natural cytotoxicity receptors. Identification of NK receptor
ligands such as HLA, MHC class I chain-related genes A and
B – MICA/B, etc. further clarifies the role of NKR/ligand
interactions in NK cell function. Given the extensive genomic
diversity of KIRs, HLA and MIC, it is reasonable to imagine
that genotypes encoding imbalanced inhibitory and activating
interactions may contribute to susceptibility or resistance
to human diseases, including cancers. This review will discuss
two cell-surface receptor/ligand systems involved in NK cell
recognition of tumor targets – KIR/HLA and NKG2D/MIC
and the potential relevance of their genetic polymorphism
in malignancies.
[Back to top]
Application of Proteomics to the Discovery of Cancer Biomarkers
Murrium Ahmad and Balwir Matharoo-Ball
To date, no effective treatment is available for advanced
cancers, which remain a major cause of morbidity and mortality.
Clearly, there is urgent need to unravel novel biomarkers
for early detection. Proteomic approaches for the identification
of novel biomarkers for cancer diagnosis and staging have
traditionally relied on the identification of differentially
expressed proteins between tumour cells and their normal counterparts
based on the patterns of protein expression observed by two-dimensional
gel electrophoresis (2DE-PAGE). Recent advances in mass spectrometry
and bioinformatics and statistical algorithms necessary to
interpret mass spectrometric data have revolutionized the
approach to defining new tumour markers. Proteomics studies
have generated numerous datasets of potential prognostic,
diagnostic and therapeutic significance in human cancer. In
this review we will discuss the available proteomic technologies
their limitations and highlight the key areas of research
required for understanding the aetiology of cancer and how
they have been used to discover cancer biomarkers.
[Back to top]
Protein Glycosylation as Marker of Melanoma Progression
Anna Litynska, Malgorzata Przybylo, Dorota Hoja-Lukowicz,
Ewa Pochec, Marcelina Kremser, Dorota Ciolczyk-Wierzbicka,
Maria Labedz and Piotr Laidler
A lot of experimental data has been produced which suggests
that there is a crucial role for glycans during the different
stages of melanoma progression. Malignant transformation is
associated with various alterations in the glycosylation pattern
of the protein glycans. The most common changes are associated
with the presence of more branched and hypersialylated N-linked
oligosaccharides, re-expression of fetal-type antigens and
premature terminated glycans. Some of these changes may provide
the tumor cells with an advantage in influencing their social
behavior and facilitating metastasis formation so, glycan-target
therapy in combination with existing protocols may have an
important impact in the treatment of melanoma.
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Autoantibody Profiles as Biomarkers for Response to Therapy
and Early Detection of Cancer
Zane Kalnina, Karina Silina and Aija Line
The production of autoantibodies against tumour-derived
proteins has been observed in the most, if not all cancer
patients therefore they seem to be very attractive biomarkers
for the diagnosis or early detection of cancer. Moreover,
even if they by themselves have a minor role in the anti-tumour
immune response, the autoantibody profile likely reflects
the repertoire of activated CD4+
T cells, presumably, including both, the helper cells and
the regulatory T cells. Hence, they may turn out to be valuable
biomarkers for monitoring patient’s response to immunotherapy.
So far, their clinical utility has been hampered by the low
frequency against each antigen, the inability to differentiate
between different types of cancer, large interindividual variations
in autoantibody repertoires and ambiguous biological and clinical
significance. At least partially these limitations could be
overcome by applying high-throughput proteomic techniques
to cancer serology that allows definition of a comprehensive
set of antigens in each type of cancer and analysing the whole
autoantibody profiles in patients’ sera. In this review
we aim to give an insight into the recent advances in applying
various proteomic approaches, including phage display-based
SEREX, SERPA, MAPPing and protein microarrays for the identification
of tumour-associated antigens and autoantibody profiling,
and discuss the relevance of autoantibodies for the early
detection of cancer and monitoring patients’ response
to therapy.
[Back to top]
Computational & Statistical Methodologies to Identify
Biomarkers in Cancer
Graham R. Ball
The advent of post genomic technologies and their application
to biomedical problems resulted in a massive increase the
complexity of data generated. This has resulted in the need
for more refined statistical and computational methods for
analysis of this type of data Through comprehensive analysis
and modelling approaches, structures or classes in the data
can be defined, denovo predictive biomarkers identified
and clinical decision support systems developed. This review
seeks to provide an overview of some of the computational
methodologies that have been used for data-mining complex
high throughput data for the identification of new biomarkers
or improvement of existing biomarkers. Given the literature
is vast within the area of computational algorithms we seek
to present commonly used methods.
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Practical Aspects in the Use of Biomarkers for the Development
of Cancer Vaccines
Angus G. Dalgleish
Biomarkers can be used to aid the diagnosis of a disease
(particularly early detection of occult tumours), to aid in
the staging of disease, to predict outcome of disease, to
act as a surrogate for clinical progression and to monitor
responses to treatment. It is therefore important when referring
to biomarkers to state exactly which of these indications
is being sought. There is a real clinical need for biomarkers
in all these stages, especially where patient stratification
prior to treatment can considerably improve the outcome of
clinical trials. Cancer, being a heterogeneous disease, is
unlikely to respond to any one specific treatment and biomarkers
that could tell us if the patient and their cancer was resistant
to certain drugs would be very useful and, indeed, these are
being sought. In an analogous way these are even more necessary
with regards to vaccines, which would benefit greatly from
patient stratification and early prediction of disease response
[1].
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