Clinical OMICs - Volume 3, Issue 9 - 10
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role in immune suppression. PD-1 is
expressed in most tumor-infiltrating
T cells, including antigen-specific
CD8+ T cells. Moreover, PD-1 expression occurs after T-cell activation and
has been used as a marker of T-cell
exhaustion.
The PD-1 receptor has the capacity to bind two ligands, PD-L1 and
PD-L2. Typically, when PD-1 is bound
to its ligands the result is the elimination of activated effector T-cells
once they have completed their
tasks-thus making PD-1 an immune
checkpoint molecule. When the interaction of PD-1 and PD-L1 is disrupted,
for instance with checkpoint inhibitor antibodies such as nivolumab
(Opdivo), T cells remain activated,
seeking out cancer cells to eliminate.
PD-L1 expression has been detected
in a number of tumor types, including
melanoma, non-small cell lung cancer (NSCLC) renal, and ovarian cancers-underscoring the importance
of checkpoint inhibitor drugs.
Because of its role in immune suppression and expression pattern in
cancerous tissues, PD-L1 has begun
to emerge as a potential prognostic
marker. Reporting in the April issue of
Oncotarget, Chowdhury et al., studied
the effectiveness of using PD-L1 as a
predictive biomarker for papillary thyroid carcinoma (PTC) and its variants.
Using standard immunohistochemical (IHC) staining techniques, the
researchers analyzed "251 archived
formalin fixed and paraffin embedded (FFPE) surgical tissue samples
(66 benign thyroid nodules and 185
10
Clinical OMICs September 2016
PTCs)." The investigators found that
"PD-L1 positive expression in PTC correlates with a greater risk of recurrence
and shortened disease-free survival
supporting its potential application as
a prognostic marker for PTC."
Increased validation of
novel biomarkers that
provide insight into whether
immunotherapies will be
successful for individual
patients, especially when the
timing of treatment is a factor,
as it most often is for cancer,
is essential.
Scheel et al., reporting ahead of print
in August for Pathologe, found similar
results with the use of IHC methods
when surveying for PD-L1 biomarker
expression in NSCLC tissue. "The use of
PD-L1 IHC in NSCLC is suitable for identification of patients with an increased
probability of a clinical benefit from
immunotherapy," the authors wrote.
"The various proportional cut-offs
used to interpret the staining results
can be summarized in a total score,
which can be reproducibly assessed.
The staining patterns of the four assays
investigated were, however, not congruent in all situations."
Different Direction,
Similar Endpoint
The PD-1/PD-L1 molecules aren't the
only high-profile protein biomarkers associated with immunotherapy.
The cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) is a receptor
that also functions as an immune
checkpoint, downregulating immune
responses. CTLA-4 is constitutively
expressed in regulatory T cells (Tregs)
after their activation, serving as an
off switch when bound to its ligands
CD80 or CD86 present on the surface
of antigen-presenting cells (APC).
CTLA-4 transmits an inhibitory signal to Tregs, causing them to deactivate-the disruption of which is the
basis for the development of antagonist drugs such as ipilimumab (Yervoy). Conversely, researchers have
developed CTLA-4 agonist drugs such
as abatacept (Orencia) as potential
therapies for autoimmune disorders.
Previous work done to track the
expression patterns of CTLA-4 have
shown that the receptor is constitutively expressed in a variety of
cancers-in particular, melanoma,
for which ipilimumab has been FDA
approved for treatment of the disease. Due to the remarkable success
of treating melanoma patients with
checkpoint inhibitors that target the
CTLA-4 pathway, investigators are
now attempting to validate CTLA-4 as
a prognostic marker for other tumor
types.
Reporting recently in the Journal
of Thoracic Oncology, Deng et al.,
looked at the roles of CTLA-4 and
PDCD1 (gene responsible for PD-1
production) expression in lung cancer patient samples. "We used a lung
cancer database of 1715 patients
measured by Affymetrix microarrays
to analyze the association of gene
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Table of Contents for the Digital Edition of Clinical OMICs - Volume 3, Issue 9
Contents
Clinical OMICs - Volume 3, Issue 9 - Cover1
Clinical OMICs - Volume 3, Issue 9 - Cover2
Clinical OMICs - Volume 3, Issue 9 - Contents
Clinical OMICs - Volume 3, Issue 9 - 4
Clinical OMICs - Volume 3, Issue 9 - 5
Clinical OMICs - Volume 3, Issue 9 - 6
Clinical OMICs - Volume 3, Issue 9 - 7
Clinical OMICs - Volume 3, Issue 9 - 8
Clinical OMICs - Volume 3, Issue 9 - 9
Clinical OMICs - Volume 3, Issue 9 - 10
Clinical OMICs - Volume 3, Issue 9 - 11
Clinical OMICs - Volume 3, Issue 9 - 12
Clinical OMICs - Volume 3, Issue 9 - 13
Clinical OMICs - Volume 3, Issue 9 - 14
Clinical OMICs - Volume 3, Issue 9 - 15
Clinical OMICs - Volume 3, Issue 9 - 16
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Clinical OMICs - Volume 3, Issue 9 - 18
Clinical OMICs - Volume 3, Issue 9 - 19
Clinical OMICs - Volume 3, Issue 9 - 20
Clinical OMICs - Volume 3, Issue 9 - 21
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Clinical OMICs - Volume 3, Issue 9 - 31
Clinical OMICs - Volume 3, Issue 9 - 32
Clinical OMICs - Volume 3, Issue 9 - 33
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