There is great interest in an ability to categorize pancreatic cancer, and understand and classify the significant heterogeneity that exists in this disease. Such classifications based on morphologic, genetic, and immunologic features are emerging, and the application of this information to provide both prognostic and predictive information is highly desired. Clin Cancer Res; 24(18); 4355–6. ©2018 AACR.

See related article by Wartenberg et al., p. 4444

In this issue of Clinical Cancer Research, Wartenberg and colleagues offer a novel approach to classifying patients with pancreatic cancer (1). Traditionally, pancreatic cancer has been considered a disease with a uniformly poor outcome. Nonetheless, as with every other malignancy, there is substantial heterogeneity in its behavior and clinical course. Recent classifications have begun to refine how we stratify this disease based on pathologic, genomic, and, more recently, immunologic criteria. To date, these classifications have limitations and are not used on a day-to-day basis for patient decision-making. A hope for the proximate future is the reality of a usable classification system with an ability to provide both prognostic and predictive information to the treating physician.

Historically, tumor immunologists have classified cancers into those considered immune responsive and those that are not. This distinction was often based on clinical, sometimes anecdotal, observations rather than strict criteria used in immunobiology. As a result, this classification was largely driven by the availability of immunotherapeutics (e.g., IL2 and IFNα) in an era when the efficacy of such agents was mostly modest. Limitations to such a classification came to the forefront in the current era of checkpoint blockade when malignancies traditionally thought not to be immune responsive, such as non–small cell lung cancer, demonstrated sensitivity to anti–PD-1 therapy, manifesting as profound and durable responses in a subset of patients.

Pancreatic cancer has remained in the nonresponsive category, prompting the question of whether this reflects a fixed property of disease biology or merely the constraints in our current treatment armamentarium. In support of the latter possibility, a wealth of preclinical data suggest that pancreatic cancers employ multiple means of immune evasion that are amenable to therapeutic intervention (2). These include the recruitment of regulatory immune cells (e.g., so-called myeloid-derived suppressor cells and M2 macrophages), the secretion of chemical messengers (e.g., the chemokine CXCL12, and the cytokines TGFβ and GM-CSF), and the expression of cell-surface proteins (e.g., PD-L1 and CSF1R) that mediate immunosuppression. Which of these pathways drive tumor progression in humans, and thus offer attractive targets for intervention, is currently under active investigation. To date, treatment with single or combination checkpoint inhibitors in patients with pancreatic cancer has shown very limited efficacy outside of the small subset of individuals with microsatellite unstable/mismatch repair deficiency (1%–2%). Multiple combination strategies to augment immunity are currently being evaluated with checkpoint inhibition, cytotoxic therapy, vaccines, and many other immunomodulatory approaches.

In this issue of Clinical Cancer Research, Wartenberg and colleagues take an important step toward elucidating the role of immune cells in human pancreatic cancer that is not restrained by considering only the efficacy of current cancer immunotherapy (1). By parsing out three ways the immune system can interact with pancreatic cancers, independently of existing immune interventions, the authors shed light on what future immunotherapies might achieve in this disease (Table 1).

Table 1.

Immune characterization of pancreatic cancer

Wartenberg subsetSelected characteristicPotentially analogous biologyReferenceOpen question
Immune escape Low T-cell infiltrate T-cell exclusion Feig et al., Proc Natl Acad Sci U S A, 2013 (6) Are mediators of T-cell exclusion (e.g., CXCL12) present? 
Immune rich Rich T-cell infiltrate Cytolytic phenotype Hamid et al., J Transl Med, 2011 (7) Are cytolytic genes (e.g., granzyme B) expressed? 
Immune exhausted PD-L1 upregulation, or microsatellite instability T-cell exhaustion Wherry et al., Immunity, 2007 (8) Are markers of T-cell exhaustion (PD-1, EOMES) present? 
Wartenberg subsetSelected characteristicPotentially analogous biologyReferenceOpen question
Immune escape Low T-cell infiltrate T-cell exclusion Feig et al., Proc Natl Acad Sci U S A, 2013 (6) Are mediators of T-cell exclusion (e.g., CXCL12) present? 
Immune rich Rich T-cell infiltrate Cytolytic phenotype Hamid et al., J Transl Med, 2011 (7) Are cytolytic genes (e.g., granzyme B) expressed? 
Immune exhausted PD-L1 upregulation, or microsatellite instability T-cell exhaustion Wherry et al., Immunity, 2007 (8) Are markers of T-cell exhaustion (PD-1, EOMES) present? 

Through a combination of morphologic (tumor budding), genetic (50 “cancer-related” genes are interrogated), and immunologic (staining for CD3, CD4, CD8, CD30, PD-L1, and other surface markers is integrated with prior data on FOXP3 expression) studies, the authors segregate pancreatic cancers into three immunologic categories (1). These categories (designated as “immune escape,” “immune rich,” and “immune exhausted”) are found to correlate, in some cases, with clinical outcomes. Using a retrospective dataset, the authors find that patients in the immune-rich category demonstrate superior overall and progression-free survival as compared with patients in the immune-escape category or the immune-exhausted category. In contrast to previous pancreatic cancer classification systems that separate tumors into two (3), three (4), or four (5) subsets based primarily on genetic futures of the malignant cells, Wartenberg and colleagues have focused on immunity, suggesting that their approach may be more useful for guiding the use of immunotherapies rather than genetically targeted therapies.

Important limitations of the current study, which are not unique, include the small set of immunologic, morphologic, and genetic features that were analyzed. For instance, it is possible that if a different set of immune cell markers were studied, alternate classifications may have emerged. Other limitations are the sample size (110 patients) and fact that the entire dataset was derived from patients with resectable disease.

Future studies of interest would link these clinical classifications to the reported biology from preclinical models. For instance, by including markers such as PD-1, TIM3, LAG3, 2B4, and EOMES, one could determine whether tumors in the immune-exhausted subset show evidence of T-cell exhaustion. If that is the case, then many immunotherapies that potentially reverse T-cell exhaustion, including anti-TIM3 and anti-LAG3 mAbs (as will be studied in the upcoming phase I studies NCT03489343 and NCT03489369), may have critical relevance. Alternatively, one can ask whether active T-cell exclusion (2) accounts for the paucity of T cells in the immune-escape subset. If that is the case, then the blockade of pathways that mediate this effect (with CXCR4 antagonists, for example, as in the ongoing phase I/II study NCT03193190) will provide further insight.

From the perspective of the past decade, there is both an abundance of investigational agents being developed for pancreatic cancer, and an abundance of diagnostic tools and putative biomarkers that could distinguish between different subsets based on fundamental biology. The challenge will be in combining these tools in an unbiased and thoughtful a manner as possible. With their current study, Wartenberg and colleagues take an important step forward along this path by proposing three distinct categories to describe the intratumoral immune status of patients with pancreatic cancer (1). The next step will be to broaden the immunologic, genetic, and morphologic variables under consideration. This will allow the field to better associate pathologic findings with specific biological processes, and to discover new pathways relevant in human pancreatic cancer by moving beyond the immune populations and markers that are judged important based on our current knowledge. The ultimate validation of this approach will come when patients treated with therapeutics tailored to their disease biology achieve outcomes surpassing what was possible in the previous generation. On the basis of the above-described study, and on that of many other researchers, we are optimistic that such validation is a tangible future actuality.

No potential conflicts of interest were disclosed.

Conception and design: D.N. Khalil, E.M. O'Reilly

Development of methodology: D.N. Khalil, E.M. O'Reilly

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D.N. Khalil, E.M. O'Reilly

Writing, review, and/or revision of the manuscript: D.N. Khalil, E.M. O'Reilly

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): D.N. Khalil, E.M. O'Reilly

D.N. Khalil and E.M. O'Reilly are funded by Cancer Center Support Grant P30-17 CA008748 (principal investigator: Craig Thompson).

1.
Wartenberg
M
,
Cibin
S
,
Zlobec
I
,
Vassella
E
,
Eppenberger-Castori
S
,
Terracciano
L
, et al
Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance
.
Clin Cancer Res
2018
;
24
:
4444
54
.
2.
Joyce
JA
,
Fearon
DT
. 
T cell exclusion, immune privilege, and the tumor microenvironment
.
Science
2015
;
348
:
74
80
.
3.
Moffitt
RA
,
Marayati
R
,
Flate
EL
,
Volmar
KE
,
Loeza
SG
,
Hoadley
KA
, et al
Virtual microdissection identifies distinct tumor- and stroma-specific subtypes of pancreatic ductal adenocarcinoma
.
Nat Genet
2015
;
47
:
1168
78
.
4.
Collisson
EA
,
Sadanandam
A
,
Olson
P
,
Gibb
WJ
,
Truitt
M
,
Gu
S
, et al
Subtypes of pancreatic ductal adenocarcinoma and their differing responses to therapy
.
Nat Med
2011
;
17
:
500
3
.
5.
Bailey
P
,
Chang
DK
,
Nones
K
,
Johns
AL
,
Patch
AM
,
Gingras
MC
, et al
Genomic analyses identify molecular subtypes of pancreatic cancer
.
Nature
2016
;
531
:
47
52
.
6.
Feig
C
,
Jones
JO
,
Kraman
M
,
Wells
RJ
,
Deonarine
A
,
Chan
DS
, et al
Targeting CXCL12 from FAP-expressing carcinoma-associated fibroblasts synergizes with anti-PD-L1 immunotherapy in pancreatic cancer
.
Proc Natl Acad Sci U S A
2013
;
110
:
20212
7
.
7.
Hamid
O
,
Schmidt
H
,
Nissan
A
,
Ridolfi
L
,
Aamdal
S
,
Hansson
J
, et al
A prospective phase II trial exploring the association between tumor microenvironment biomarkers and clinical activity of ipilimumab in advanced melanoma
.
J Transl Med
2011
;
9
:
204
.
8.
Wherry
EJ
,
Ha
SJ
,
Kaech
SM
,
Haining
WN
,
Sarkar
S
,
Kalia
V
, et al
Molecular signature of CD8+ T cell exhaustion during chronic viral infection
.
Immunity
2007
;
27
:
670
84
.