Metformin boosts antitumor immunity and improves

prognosis in upfront resected pancreatic cancer: an

observational study

Casper W.F. van Eijck, Msc,1,2,‡,� Disha Vadgama, Msc,2,‡ Casper H.J. van Eijck , MD, PhD,1 Johanna W. Wilmink, MD, PhD3

; for the

Dutch Pancreatic Cancer Group (DPCG)

1

Department of Surgery, Erasmus University Medical Centre, Rotterdam, the Netherlands 2

Erasmus MC Cancer Institute, Erasmus University Medical Centre, Rotterdam, the Netherlands 3

Department of Medical Oncology, Amsterdam University Medical Centre, Amsterdam, the Netherlands

�Correspondence to: Casper W.F. van Eijck, Msc, Department of Surgery, Erasmus University Medical Centre, Dr Molenwaterplein 40, 3015GD, Rotterdam,

the Netherlands (e-mail: c.w.f.vaneijck@erasmusmc.nl).

†

Both authors contributed equally and share the first authorship.

Abstract

Background: Beyond demographic and immune factors, metabolic considerations, particularly metformin’s recognized impact in

oncology, warrant exploration in treating pancreatic cancer. This study aimed to investigate the influence of metformin on patient

survival and its potential correlation with distinct immune profiles in pancreatic ductal adenocarcinoma (PDAC) tumors.

Methods: We included 82 upfront resected and 66 gemcitabine-based neoadjuvant chemoradiotherapy (nCRT)-treated patients from

the PREOPANC randomized controlled trial (RCT). Transcriptomic NanoString immunoprofiling was performed for a subset of 96

available resected specimens.

Results: Disparities in survival outcomes and immune profiles were apparent between metformin and non-metformin users in

upfront resected patients but lacking in nCRT-treated patients. Compared to non-metformin users, upfront resected metformin

users showed a higher median overall survival (OS) of 29 vs 14months and a better 5-year OS rate of 19% vs 5%. Furthermore, metformin use was a favorable prognostic factor for OS in the upfront surgery group (HR ¼ 0.56; 95% CI ¼ 0.32 to 0.99). Transcriptomic data

revealed that metformin users significantly underexpressed genes related to pro-tumoral immunity, including monocyte to M2 macrophage polarization and activation. Furthermore, the relative abundance of anti-inflammatory CD163þ MRC1þ M2 macrophages in

non-metformin users and immune-activating CD1Aþ CD1Cþ dendritic cells in metformin users was heightened (P < .001).

Conclusion: This study unveils immune profile changes resulting from metformin use in upfront resected pancreatic cancer

patients, possibly contributing to prolonged survival outcomes. Specifically, metformin use may decrease the abundance and activity

of pro-tumoral M2 macrophages and increase the recruitment and function of tumor-resolving DCs, favoring antitumor immunity.

[PREOPANC trial EudraCT: 2012-003181-40]

In pancreatic ductal adenocarcinoma (PDAC), mortality rates

closely parallel its incidence. Projections anticipate PDAC to

become the second leading cause of cancer-related death by 2030

(1,2). Despite improvements in survival outcomes among 13% of

localized PDAC cases, primarily attributed to surgical resection

(3,4), the substantial risk of disease recurrence keeps overall survival suboptimal, with only 4% of resected patients surviving

beyond 10 years (5,6). Integrating neoadjuvant and adjuvant

chemo(radio)therapies has emerged as a strategic approach to

enhance further survival outcomes in resectable and borderline

resectable PDAC patients (7,8).

Diabetes mellitus (DM), a prominent PDAC risk factor, is a

chronic condition involving dysregulated glucose metabolism

due to insufficient insulin or impaired insulin action, leading to

elevated blood glucose levels and metabolic disturbances.

Increasing the risk of various cancers, including PDAC, by twofold (9), DM may also be a symptom of PDAC (10). Notably,

approximately 50% of PDAC patients exhibit either type 2 DM,

the most prevalent form (11), or impaired glucose tolerance in

the early stages (10,12).

In DM patients, metformin is the most prescribed drug to mitigate hyperglycemia. This hypoglycemic agent suppresses hepatic

glucose production, lowers blood glucose levels, and increases

insulin sensitivity by promoting glucose uptake in skeletal

muscles (13-15). Metformin may play an important role in oncology. Metformin suppressed the proliferation of PDAC cells by

inhibiting the mammalian target of rapamycin (mTOR) activation

and insulin-like growth factor (IGF-1) receptor signaling pathway

(16), and metformin use was associated with improved survival

outcomes in various cancers, including PDAC (17,18). However,

Received: January 9, 2024. Revised: February 12, 2024. Accepted: March 4, 2024

# The Author(s) 2024. Published by Oxford University Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs licence (https://creativecommons.org/

licenses/by-nc-nd/4.0/), which permits non-commercial reproduction and distribution of the work, in any medium, provided the original work is not altered or

transformed in any way, and that the work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

JNCI: Journal of the National Cancer Institute, 2024, 116(8), 1374–1383

https://doi.org/10.1093/jnci/djae070

Advance Access Publication Date: March 26, 2024

Early Career Investigator Research

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caution is warranted due to the generally low quality of evidence

linking metformin to reduced PDAC mortality, attributed to

methodological shortcomings in retrospective analyses (19-22).

Additionally, two phase II trials in patients with advanced PDAC

reported no improved survival with metformin use (23,24). Given

these inconsistencies and methodological limitations of existing

studies, further research with prospective designs is crucial to

elucidate the impact of metformin on survival in PDAC patients.

Examinations of the immunomodulatory effects of metformin

have unveiled its multifaceted impact on both innate and adaptive immune systems (25). The immune system plays a complex

role in controlling PDAC progression. Inflammation is associated

with PDAC development, growth, and invasion (26), while the

immunosuppressive tumor microenvironment is a hallmark of

pancreatic cancer (27). This microenvironment allows tumor

cells to evade adaptive T-cell responses, conferring protection

against the immune system and resisting immunotherapy (28).

Notably, a comprehensive exploration of metformin’s exact

immunological role in PDAC remains elusive.

In this study, we conducted a post hoc analysis examining the

influence of metformin on survival outcomes and tumor immunity in a prospective randomized controlled trial (RCT) cohort of

resected PDAC patients. Our emphasis on resected PDAC

patients, with available tumor samples, enabled a comprehensive exploration of the multifactorial nature of the disease,

encompassing interactions among metabolic factors, the

immune system, stromal cells, and tumor cells.

Methods

Patient cohort

This study included patients with pathologically confirmed PDAC

who underwent surgical resection as part of the PREOPANC

phase III RCT (EudraCT number 2012-003181-40) across 16 highvolume pancreatic surgery centers from the Dutch Pancreatic

Cancer Group (DPCG). This trial was conducted according to the

guidelines of the Declaration of Helsinki and approved by the

Ethics Committees of Erasmus MC (MEC-2012-249; December 11,

2012). Written informed consent was obtained from all patients.

Patients were randomly assigned to either upfront surgery or

gemcitabine-based neoadjuvant chemoradiotherapy (nCRT).

Detailed eligible criteria and clinical procedures are outlined in

the protocol (29) and the Supplementary Methods (available

online). The long-term results have been previously published

(30). This study further stratified patients based on metformin

use. Patients prescribed metformin at the time of random assignment for at least six months, adhering to standard metformin

dosages ranging from 500 to 2000mg per day as recommended

by their treating physicians, were considered “metformin users.”

Patients without any history of metformin use were considered

“non-metformin users.” Overall survival (OS), calculated from

PDAC diagnosis (histologically or cytologically confirmed) to

death, was considered the primary survival outcome, with censoring for patients alive at the last follow-up. Demographic data

were obtained through investigator observation.

Transcriptomic immunoprofiling using

NanoString technologies

To elucidate tumoral immunological landscapes associated with

metformin use, we reanalyzed targeted gene expression profiles

of the formalin-fixed and paraffin-embedded (FFPE) surgical

specimens tissue that were previously fabricated using

NanoString technologies (7) (Supplementary Tables 1 and 2,

available online). Detailed descriptions of the NanoString measurements are available in the Supplementary Methods (available

online).

Statistical analyses

R Statistical Software (v4.1.2) was used for downstream data

exploration, statistical analyses, and visualizations, with detailed

descriptions in the Supplementary Methods (available online).

P values less than .01 were considered statistically significant,

denoted as follows: � P value less than .05, �P value less than .01,

��P value less than .001.

Results

Patient characteristics

Between April 2013 and July 2017, 164 out of 248 patients with

borderline resectable or resectable PDAC in the phase III

PREOPANC RCT underwent surgical resection. This study focused

on 148 patients after the exclusion of 12 patients without pathologically confirmed PDAC and 4 patients who did not complete

the full course of gemcitabine-based nCRT. The distribution of

metformin use was comparable between the 82 upfront resected

(21 metformin, 61 non-metformin) and 66 nCRT patients (18 metformin, 48 non-metformin). No significant differences were

observed in preoperative clinical characteristics or postoperative

pathological and surgical outcomes within the metformin subgroups. The median age was higher in the non-metformin group

(70 years) compared to the metformin users (60 years) in the

nCRT group (P ¼ .021) (Table 1).

Metformin users with upfront resected PDAC

exhibit prolonged survival outcomes compared to

those not using metformin

The median follow-up among all patients was 73 months. In the

upfront surgery group, non-metformin users experienced more

progression or death events than metformin users (Table 2).

Survival disparities were evident, with metformin users showing

a higher median OS of 29 months (95% CI ¼ 23 to 46) and a 5-year

OS rate of 19% (95% CI ¼ 8 to 46), compared to non-metformin

users with a median OS of 14 months (95% CI ¼ 11 to 19) and a 5-

year OS rate of 5% (95% CI, ¼ 2 to 15) (Figure 1, A). This survival

difference was not observed in the nCRT group, with a comparable median OS of 32 months (95% CI ¼ 16 to 53) for metformin

users and a median OS of 30 months (95% CI ¼ 21 to 95) for nonmetformin users (Figure 1, A).

Univariate Cox proportional hazard models investigating

covariates associated with OS in both treatment groups corroborated earlier observations (Supplementary Table 3, A, available

online). The use of metformin favored OS in the upfront surgery

group (hazard ratio [HR] ¼ 0.46; 95% CI ¼ 0.26 to 0.79; P.

adj ¼ 0.010) but not in the nCRT group (HR ¼ 1.67; 95% CI ¼ 0.92 to

3.05; P.adj ¼ 0.53) (Figure 1, B). Multivariate analysis, correcting

for the potential confounders of “resection classification (R)” and

“the number of received adjuvant gemcitabine cycles,” confirmed

metformin as a favorable prognostic factor for OS in the upfront

surgery group (HR ¼ 0.56; 95% CI ¼ 0.32 to 0.99; P.adj ¼ 0.047)

(Figure 1, B). Similar results were found in the survival analysis

for progrerssion-free survival (PFS), with an even more pronounced favorable impact of metformin on PFS in upfront

resected patients (Supplementary Figure 1, Supplementary Table

3, B, available online). Given the importance of age and body

mass index (BMI) as prognostic biological factors, we repeated

the multivariate Cox regression models for the upfront surgery

C.W.F. van Eijck et al. | 1375

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Table 1. Preoperative clinical characteristics of 148 resected PDAC patients

Treatment group

Upfront surgery (n ¼ 82) nCRT (n ¼ 66)

Non-metformin Metformin

P

Non-metformin Metformin

(n ¼ 61) (n ¼ 21) (n ¼ 48) (n ¼ 18) P

Sex

Female 25 (41) 10 (48) .62 24 (50) 7 (39) .58

Male 36 (59) 11 (52) 24 (50) 11 (61)

Age at diagnosis (years)

Median [min, max] 68 [40, 80] 65 [45, 78] .25 67 [42, 80] 64 [51, 76] .14

BMI (kg/m2

)

Median [min, max] 25 [18, 43] 25 [18, 35] .41 25 [19, 44] 25 [19, 32] .54

Diabetes mellitus, no. (%)

No 40 (66) 15 (71) .79 38 (79) 14 (78) >.99

Yes 21 (34) 6 (29) 10 (21) 4 (22)

Hypercholesterolemia, no. (%)

No 55 (90) 19 (90) >.99 41 (85) 16 (89) >.99

Yes 6 (10) 2 (10) 7 (15) 2 (11)

Hypertension, no. (%)

No 46 (75) 15 (71) .78 34 (71) 13 (72) >.99

Yes 15 (25) 6 (29) 14 (29) 5 (28)

History of cardiovascular disease, no. (%)

No 44 (72) 16 (76) .78 32 (67) 11 (61) .77

Yes 17 (28) 5 (24) 16 (33) 7 (39)

History of cancer, no. (%)

No 53 (87) 21 (100) >.99 41 (85) 16 (89) >.99

Yes 8 (13) 0 (0) 7 (15) 2 (11)

History of pancreatitis, no. (%)

No 58 (95) 21 (100) .11 45 (94) 14 (78) .082

Yes 3 (5) 0 (0) 3 (6) 4 (22)

Resectability, no. (%)

Borderline resectable 25 (41) 10 (48) .70 22 (46) 5 (28) .26

Resectable 36 (59) 11 (52) 26 (54) 13 (72)

CA19-9, preoperative (U/mL)

Median [min, max] 263 [1, 12000] 227 [1, 4274] .69 147 [2, 4114] 98 [8, 1460] .29

Missing (% of total) 10 (16) 5 (24) 5 (10) 2 (11)

Involvement of the SMA, no. (%)

Absent 58 (95) 19 (90) .60 42 (88) 17 (94) .66

Present 3 (5) 2 (10) 6 (12) 1 (6)

Tumor diameter, before nCRT (mm)

Median [min, max] 30 [15, 60] 35 [20, 55] .14 31 [13, 64] 28 [17, 40] .46

Missing (% of total) 2 (3) 0 (0) 2 (4) 0 (0)

Tumor diameter, after nCRT (mm)

Median [min, max] 30 [15, 60] 35 [4, 55] .18 27 [13, 62] 27 [14, 50] .81

Missing (% of total) 2 (3) 0 (0) 2 (4) 0 (0)

Regional suspicious lymph nodes, no. (%)

Absent 49 (80) 13 (62) .14 32 (67) 15 (83) .23

Present 12 (20) 8 (38) 16 (33) 3 (17)

Tumor location, no. (%)

Corpus or tail 7 (11) 3 (14) .71 10 (21) 2 (11) .49

Head 54 (89) 18 (86) 38 (79) 16 (89)

WHO performance status, no. (%)

WHO 0 18 (30) 9 (43) .28 27 (56) 12 (67) .40

WHO 1 41 (67) 11 (52) 20 (42) 5 (28)

Missing (% of total) 2 (3) 1 (5) 1 (2) 1 (6)

Response to nCRT (RECIST 1.1), no. (%)

Progressive disease 0 (0) 0 (0) – 6 (12) 0 (0) –

Partial response 0 (0) 0 (0) 29 (60) 14 (78)

Stable disease 0 (0) 0 (0) 3 (6) 2 (11)

Missing (% of total) 61 (100) 21 (100) 10 (21) 2 (11)

Institute, no. (%)

Academical hospital 43 (70) 16 (76) .78 33 (69) 16 (89) .12

General hospital 18 (30) 5 (24) 15 (31) 2 (11)

BMI ¼ body mass index; CA19-9 ¼ carbohydrate antigen 19-9; nCRT ¼ neoadjuvant chemoradiotherapy; PDAC ¼ pancreatic ductal adenocarcinoma; RECIST ¼

Response Evaluation Criteria in Solid Tumors; SMA ¼ superior mesenteric artery; WHO ¼ World Health Organization.

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group, incorporating these covariates. These analyses revealed

consistent results, with metformin retaining its significance as a

prognostic factor (Supplementary Figure 2, available online).

Metformin use is associated with unique

transcriptomic alterations in upfront resected but

not in nCRT-treated PDAC tumors

Among the 148 PDAC patients included in our study, RNA isolation succeeded for 125 surgical specimens. After stringent quality

control of tissue RNA and NanoString data, we conducted immunoprofiling analysis on a subset comprising 46 upfront resected

patients (13 metformin and 33 non-metformin users) and 50

gemcitabine-based nCRT-treated patients (15 metformin and 35

non-metformin users). Within the NanoString patient subset,

preoperatively, a lower incidence of DM, hypercholesterolemia,

and hypertension was noted in non-metformin users across both

upfront surgery and nCRT groups (Supplementary Table 4, available online). Cox proportional hazard models applied to the

NanoString subset exhibited a trend akin to the total cohort,

although statistical significance was not achieved, likely due to

the smaller sample size (Supplementary Table 5, available

online).

The transcriptomic NanoString expression data, encompassing 730 immuno-oncology-related genes, underwent visual

exploration using t-distributed Stochastic Neighbor Embedding

(t-SNE) dimensionality reduction analysis. Upfront resected

patients exhibited distinct clustering based on metformin use,

implying that metformin usage prompts a unique transcriptomic

profile (Figure 2, A). Correspondingly, differentially expressed

(DE) gene analysis (Supplementary Table 6, available online)

uncovered that metformin users exhibited significant overexpression of one gene and significant underexpression of 20 genes

(P < .01; Figure 2, B). In contrast, gemcitabine-based nCRT-treated

patients did not cluster based on metformin use, and only three

genes (BCL6, CD99, and MICA) were significantly overexpressed in

metformin users (P < .01; Figure 2, B).

Transcriptomic alterations in upfront resected

PDAC tumors of metformin users promote

anticancer (immunological) properties

The DE genes underwent pathway overrepresentation analysis to

unravel the immune and biological processes associated with

metformin use in the upfront surgery group (Supplementary

Table 7, available online). The hypoglycemic function of metformin was corroborated by the significant enhancement of the lowTable 2. Postoperative clinical characteristics of 148 resected PDAC patients

Treatment group

Upfront surgery (n ¼ 82) nCRT (n ¼ 66)

Non-metformin Metformin

P

Non-metformin Metformin

(n ¼ 61) (n ¼ 21) (n ¼ 48) (n ¼ 18) P

Nodal status (N) postoperative, no. (%)

N0 12 (20) 3 (14) .75 33 (69) 11 (61) .57

N1 49 (80) 18 (86) 15 (31) 7 (39)

Perineural invasion postoperative, no. (%)

Absent 10 (16) 4 (19) >.99 23 (48) 9 (50) >.99

Present 48 (79) 17 (81) 22 (46) 8 (44)

Missing 3 (5) 0 (0) 3 (6) 1 (6)

Resection classification (R) postoperative,

no. (%)

R0 25 (41) 10 (48) .62 35 (73) 13 (72) >.99

R1 36 (59) 11 (52) 13 (27) 5 (28)

SAE reported (any grade), no. (%)

No 35 (57) 11 (52) .80 19 (40) 6 (33) .78

Yes 26 (43) 10 (48) 29 (60) 12 (67)

Tumor grade, postoperative, no. (%)

Moderately differentiated 33 (54) 10 (48) .84 18 (38) 10 (56) .31

Poorly differentiated 14 (23) 4 (19) 16 (33) 3 (17)

Well differentiated 6 (10) 3 (14) 5 (10) 1 (6)

Missing 8 (13) 4 (19) 9 (19) 4 (22)

Tumor stage (T) postoperative, no. (%)

T1/T2 2 (3) 0 (0) >.99 12 (25) 5 (28) >.99

T3/T4 59 (97) 21 (100) 36 (75) 13 (72)

Type of resection, no. (%)

Pancreas body and tail resection 2 (3) 1 (5) .39 7 (15) 1 (6) .58

Pancreatoduodenectomy 57 (93) 18 (86) 40 (83) 17 (94)

Total pancreatectomy 2 (3) 2 (10) 1 (2) 0 (0)

Vascular invasion postoperative, no. (%)

Absent 22 (36) 7 (33) >.99 27 (56) 12 (67) .40

Present 37 (61) 12 (57) 20 (42) 5 (28)

Missing 2 (3) 2 (10) 1 (2) 1 (6)

Adjuvant gemcitabine completed, no. (%)

No 41 (67) 14 (67) >.99 32 (67) 13 (72) .77

Yes 20 (33) 7 (33) 16 (33) 5 (28)

Adjuvant gemcitabine cycles

Median [min, max] 4 [0, 6] 4 [0, 6] .62 3 [0, 4] 3 [0, 4] .38

nCRT ¼ neoadjuvant chemoradiotherapy; SAE: serious adverse event.

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density lipoprotein (LDL) Gene Ontology (GO) pathway in nonmetformin compared to metformin users (P.adj <.01; Figure 3, A).

Metformin may exert an indirect upregulating effect on peripheral

LDL levels by diminishing glucose production and enhancing insulin

sensitivity (31). Furthermore, various GO pathways related to immunity were significantly altered. In non-metformin users, pathways

linked to positive regulation of macrophage processes (activity, differentiation, and migration) and T helper 2 cell differentiation were significantly enhanced, whereas that related to CD4 T cell

differentiation was significantly diminished (P.adj <.01; Figure 3, A).

The significant enhancement in the IgG binding pathway in nonmetformin users further underscores the macrophage’s heightened

levels of opsonization and phagocytosis facilitated through the signaling of IgG antibodies (P.adj <.01). Intriguingly, BioCarta interleukin (IL)

pathways associated with M2 macrophage polarization (IL-4 and IL-6)

and anti-inflammation (IL-10) were heightened in non-metformin

users (Figure 3, A, P.adj <.01), indicating that the amplification in

macrophage-related pathways predominantly involved M2 phenotypic processes.

Gene expression-based immune cell type profiling was conducted to quantify the abundance of intra-tumoral immune cells

(Supplementary Figure 3, available online). In upfront resected

patients, the abundance of pro-tumoral and anti-inflammatory

CD163þ MRC1þ M2 macrophages (P < .001) was significantly

lower in the tumor microenvironment (TME) of metformin users,

with a similar trend toward decreased abundance of CD14þ

CD33þ monocytes (P < .05, Figure 3, B). Correspondingly, genes

related to monocyte recruitment to inflammatory sites (CCL2,

CCR2, CXCR4, ITGB2) were significantly underexpressed in metformin users (P < .01; Figure 3, C). The abundant monocytes in

non-metformin users were also more likely to polarize into M2

macrophages, evident from the significant overexpression of

CSF1, CSF1R, IL13, IL13RA1, IL34, IL10RA, IL4R, IL6, JAK3, and

VEGFA, all associated with M2 macrophage polarization (P < .01,

Figure 3, D). Additionally, intra-tumoral M2 macrophages in nonmetformin users were more active, suggested by the overexpression of ANXA1, AXL, CD33, FCGR2A, and TNFAIP3 (P < .01,

Figure 3, E).

Furthermore, the abundance of immune-activating CD1Aþ

CD1Cþ DCs (Figure 3, B) and the expression of FLT3 (Figure 3, F),

crucial in the development and function of DCs, were significantly higher in metformin-using upfront resected patients

(P < .01). Lastly, LAG3 and STAT3, genes involved in immune

checkpoint inhibitory processes, were significantly underexpressed in metformin-using upfront resected patients (P < .01),

with a similar trend toward underexpression of the gene encoding the immune checkpoint inhibitor CD96 (P < .05; Figure 3, G).

Cox proportional hazard models exploring the prognostic impact

of the relative immune cell counts yielded no significant results

(Supplementary Table 8, available online).

To validate that the observed immunological effects were due

to metformin rather than differences in BMI (or cachexia), we

Meormin use:

Kaplan-Meier curves

Upfront surgery 82

66

+ +

+++

Meormin use: +

++++

+ ++ ++

+

+ +

+++ +

Upfront surgery 82

Meormin

35

to

to

to

Meormin

35

to

to

to

Meormin

35

3

to

to

53

66

Figure 1. Survival analysis of metformin and non-metformin users. (A) Kaplan-Meier curves stratified by treatment illustrate different OS in months

associated with metformin use in treatment-naive patients but not in nCRT-treated patients. Treatment-naive patients using metformin (green) show

prolonged OS compared to non-metformin users (red). The x-axis displays the overall survival (months), and the y-axis displays the survival probability

(%). (B) Forest plots, stratified by treatment, visualize univariate and multivariate Cox proportional hazard models highlighting metformin use as an

independent prognostic factor for OS in treatment-naive patients but not in nCRT-treated patients. Squares highlighted in green denote statistical

significance (P.adj < .05) for the respective covariate. CI ¼ confidence interval; nCRT ¼ neoadjuvant chemoradiotherapy; OS ¼ overall survival;

P.adj ¼ adjusted P value.

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compared immune profiles between patients with BMI ≤ median

and those with BMI more than median (Supplementary Table 9,

available online). In the upfront surgery group, we found no significant differences in immune cell presence based on BMI.

Furthermore, there was no overlap in differentially expressed

genes between the BMI and metformin analyses, suggesting that

BMI had minimal impact on the reported immunological effects

of metformin.

These immunological findings collectively support the concept of a metformin-induced antitumoral immune response in

upfront resected PDAC patients, a phenomenon not observed in

nCRT-treated tumors.

Discussion

Conflicting findings surround the impact of metformin on survival outcomes in PDAC patients. This study introduces a post

hoc analysis investigating the influence of metformin use, either

pre-resection or during the follow-up period, on survival outcomes in resected PDAC patients enrolled in the PREOPANC RCT.

Metformin use was associated with prolonged OS and PFS in the

upfront surgery group, but this association was absent in

the gemcitabine-based nCRT group. Motivated by established

connections between immune responses and glycemic balances

(32-34), on which metformin exerts its effect, we hypothesize

that metformin influences tumor immunity, potentially contributing to the observed favorable survival outcomes.

Transcriptomic immunoprofiling revealed an immunostimulatory pancreatic TME in metformin users, characterized by

reduced infiltration of pro-tumoral CD163þ MRC1þ M2 macrophages and enhanced infiltration of immune-activating CD1Aþ

CD1Cþ DCs. The potential of metformin to enhance antitumor

immunity highlights its promise as an adjunctive therapeutic

intervention for PDAC patients.

In PDAC patients with DM, retrospective studies present conflicting results on the therapeutic benefits of metformin

(22,35,36). Chaiteerakij et al. (22) already emphasized that divergent findings may arise from methodological limitations.

Additionally, variations in study design, such as exclusively

focusing on PDAC patients with DM or those with advanced

PDAC (23,36), could contribute to differing observations (19-21).

This underscores the significance of careful patient selection and

appropriate statistical methods in investigating metformin’s

impact on survival. Unlike previous studies comparing PDAC

patients with DM, our study evaluated the benefits of metformin

use irrespective of DM status in resected patients. The distribution of patients with and without DM was equal between metformin user groups in the upfront surgery cohort, with 15 (71%) and

(n = ) Upfront surgery (n = )

− − − −

Upfront surgery

Gemcitabine based nCRT

Me!ormin use

Upfront surgery

A

B

THBS1 CXCR4 FCER1G

IL4R

CSF1R

ITGAX

Figure 2. Exploration analysis of the transcriptomic NanoString expression data from the 96 PDAC specimens. (A) t-SNE biplots illustrating the

expression profile of 730 immune-related genes, stratified by treatment and grouped by metformin (green) and non-metformin (red) users. Clear

clusters of patients based on metformin use are observed in the treatment-naive group, whereas no such clustering is present in gemcitabine nCRTtreated patients. Each dot represents a patient, and the x-axis and y-axis represent the first and second t-SNE dimensions. (B) Volcano plots, stratified

by treatment, illustrate the DE genes between metformin (green) and non-metformin (red) users. The treatment-naive group exhibits a greater number

of DE genes compared to the nCRT-treated group. The x-axis displays the log2 fold of change, while the y-axis displays the -log10 P value. Each dot

represents a gene, and gene names indicate that they have exceeded the significance threshold of P less than .01. Genes on the right (positive) are

overexpressed in metformin users, whereas genes on the left are overexpressed in non-metformin users. DE ¼ differentially expressed; nCRT ¼

neoadjuvant chemoradiotherapy; PDAC ¼ pancreatic ductal adenocarcinoma; t-SNE ¼ t-distributed stochastic neighbor embedding.

C.W.F. van Eijck et al. | 1379

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CCR2

z

CD33 A

DC

development and func!on

Rela!ve a

CD1A CD1C CD163 MRC1 CD14 CD

IL-10 pathway

LDL pathway

MSP pathway

STAT3 pathway

IL-4 pathway

IL-6 pathway

Pathways in

BioCarta (MsigDB c2)

0 1 2 3 4

Enrichment

P.adj (-log10)

Overlapping genes

in gene set (%)

30 20 10 5

Enhanced in

g

Pathways in

Gene Ontology (MsigDB c2)

0 1 2 3 4

Enrichment

P.adj (-log10)

Overlapping genes

in gene set (%)

30 20 10 5

:

Upfront surgery

No (n = 33)

Yes (n = 13)

A B

C D

E F G

P < .05

* P < .01

** P < .001

:

Figure 3. Detailed analysis of the transcriptomic NanoString expression data from the 46 upfront resected PDAC specimens. (A) Bar plots illustrate the

results of the overrepresentation analysis for pathways characterized by a gene set size of ≤40. Only pathways exhibiting a proportional overlap of ≥

10% (left of the x-axis) and an enrichment P.adj < .01 (right of the x-axis) are presented. Each bar represents a unique pathway, and all pathways are

enhanced in non-metformin users (ie, diminished in metformin users). (B) Boxplots illustrating the mRNA-based immune cell score (y-axis) of tumorinfiltrating cells (x-axis). The relative abundance of DCs, M2 macrophages, and monocytes was higher in non-metformin (red) than in metformin

(green) users. (C-G) Boxplots, stratified by metformin (green) and non-metformin (red) users, illustrate the log2 gene expression count (y-axis) of DE

genes (P < .01) and several genes with trends (P < .05) (x-axis). In metformin compared to non-metformin users, genes related to monocyte recruitment

(C), M2 macrophage polarization (D), M2 macrophage activation (E), and immune checkpoints (F) are overexpressed, whereas a gene related to DC

development and function (G) were underexpressed. In panels A and C to G, each dot represents a patient. DC ¼ dendritic cell; DE ¼ differentially

expressed; GOBP ¼ gene ontology biological processes; nCRT ¼ neoadjuvant chemoradiotherapy; PDAC ¼ pancreatic ductal adenocarcinoma;

�P value less than .05, �P value less than .01, ��P value less than .001.

1380 | JNCI: Journal of the National Cancer Institute, 2024, Vol. 116, No. 8

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6 (19%) patients in the metformin-using group and 40 (66%) and

21 (34%) patients in the non-metformin group, with and without

DM, respectively. In this cohort of upfront resected PDAC

patients scheduled for adjuvant gemcitabine, metformin use

emerged as a favorable prognosticator for OS and PFS.

Intriguingly, this association was absent in patients who received

gemcitabine-based nCRT. Conversely, a phase II trial investigating the benefits of adding metformin to gemcitabine and erlotinib

for advanced PDAC reported no survival improvements when

patients were assessed irrespective of DM status (23). However,

this conflicting result may be explained by the notion that the

survival benefits of metformin are evident primarily in patients

with early-stage cancer (34).

Our transcriptomic immunoprofiling analysis revealed that

metformin might modulate the immune landscape in the pancreatic TME, potentially inhibiting tumor progression. Metformin

appears to shift the immunosuppressive TME toward an

immune-active state with antitumoral properties. First, metformin users exhibited an increased abundance of CD1Aþ CD1Cþ

DCs in the pancreatic TME. DCs are crucial in initiating immune

responses against malignancies by presenting tumor antigens to

T cells, subsequently activating CD4þ T helper cells or CD8þ

cytotoxic T cells in PDAC (37). Second, the infiltration of CD14þ

CD33þ monocytes and immunosuppressive CD163þ MRC1þ M2

macrophages decreased in the TME of metformin-treated

patients. This observation aligns with the underexpression of

genes related to the CCL2-CCR2 and CSF1-CSF1R axes, key

immune pathways facilitating the recruitment and polarization

of monocytes toward the M2 phenotype (38-41). Notably,

increased peripheral levels of CCL2 correlated with reduced survival in PDAC patients (42). Furthermore, the underexpression of

genes encoding IL-4, IL-13, and IL-34 may contribute to enhanced

M2 macrophage infiltration, given their important role in promoting monocyte-to-M2 macrophage polarization (39-41).

Finally, the underexpression of ANXA1, crucial for the acquisition of anti-inflammatory M2-phenotype (43), along with the

underexpression of genes related to immune checkpoint inhibitory processes such as CD96, LAG3, and STAT3, further supports

the idea that metformin may enhance immune activity in the

pancreatic TME of metformin users (44,45). Our findings support

previous research echoing diverse antitumor effects of metformin in different cancers. In head and neck squamous cell carcinoma, metformin enhances the activity of CD4þ and CD8þ

T cells and natural killer cells (46). Moreover, in squamous cell

carcinoma patients, metformin exerts an antitumor response by

mitigating the abundance of tumor-promoting macrophages (47).

The lack of significant associations between metformin use

and survival outcomes or distinct immune landscapes in the

nCRT group may stem from potential interactions and masking

effects of gemcitabine-based nCRT on metformin’s mechanisms

of action. Neoadjuvant treatments such as chemotherapy, radiotherapy, or combination therapies could directly impact the TME,

immune responses, and survival outcomes in PDAC (7), complicating the assessment of metformin’s independent effects.

Furthermore, individual differences in tumor biology, immune

profiles, and treatment responses add complexity to discerning

consistent associations. Further research is needed to unravel

the molecular, immunological, and prognostic interplay between

metformin and gemcitabine-based nCRT in pancreatic cancer.

Although our study benefits from using samples from an RCT,

bolstering the credibility of our findings through temporal clarity,

consistent data collection, control over confounding variables,

and long-term follow-up, we acknowledge several limitations.

First, the distribution of patients with and without metformin

was unbalanced, potentially impacting the robustness of our

statistical analysis. Nevertheless, this distribution accurately

reflects real-world prevalence. Additionally, due to limited tissue

availability and the quality of tissue RNA or gene expression

data, not all resected patients in our survival analyses (n ¼ 148)

underwent NanoString profiling (n ¼ 96). Second, detailed clinical

data regarding the durations or dosages of metformin were lacking. Patients were stratified based on their metformin usage at

randomization, prompting an investigation into whether metformin influences tumor aggressiveness during its development or

provides advantages as an adjuvant therapy. However, all

patients received at least six months of standard metformin dosages between 500 and 2000 mg per day as recommended by their

treating physicians. Moreover, some patients with DM who did

not receive metformin used different hypoglycemic drugs, potentially influencing their immune profile or survival outcomes.

Third, our immunoprofiling analyses were confined to transcriptomic data, and incorporating protein-based or spatial data could

have aided in understanding metformin-induced immune alterations in specific TME compartments. Lastly, our study included

patients receiving gemcitabine-based nCRT, but the optimal neoadjuvant approach for borderline resectable and resectable

PDAC remains unclear. Exploring whether metformin induces

differences in survival outcomes or immune profiles after alternative treatment approaches, as opposed to the observed lack of

differences after gemcitabine-based nCRT, may provide further

insights into its therapeutic benefit.

In conclusion, our study emphasizes metformin’s therapeutic

potential in extending survival for upfront resected PDAC

patients. Notably, this benefit appears diminished after

gemcitabine-based nCRT. We propose that the improved survival

may be linked to metformin’s capacity to enhance antitumor

immunity. Specifically, metformin impeded the infiltration of

immunosuppressive M2 macrophages while concurrently

increasing the presence of immune-activating DCs within the

pancreatic TME. Future investigations should explore

metformin’s impact after various neoadjuvant treatments and

its effects on the peripheral immune system.

Data availability

The datasets used and analyzed during the current study are

available, with permission of the Erasmus Medical Centre

Rotterdam, from the corresponding author on reasonable

request.

Author contributions

Casper W.F. van Eijck, MSc (Conceptualization; Formal analysis;

Investigation; Methodology; Resources; Software; Validation;

Visualization; Writing – original draft; Writing – review & editing),

Disha Vadgama, MSc (Conceptualization; Formal analysis;

Investigation; Methodology; Resources; Software; Validation;

Visualization; Writing – original draft; Writing – review & editing),

Casper H.J. van Eijck, MD, PhD (Conceptualization; Funding

acquisition; Methodology; Project administration; Supervision;

Writing – original draft; Writing – review & editing), Johanna W.

Wilmink, MD, PhD (Conceptualization; Funding acquisition;

Methodology; Project administration; Supervision; Writing – original draft; Writing – review & editing).

C.W.F. van Eijck et al. | 1381

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Funding

This work was financially supported by the Survival With

Pancreatic Cancer Foundation (www.supportcasper.nl) [grant

number OVIT17-06].

Conflicts of interests

The authors declare that they have no competing interests.

Acknowledgements

The funder had no role in the design of the study; the collection,

analysis, or interpretation of the data; or the writing of the manuscript and decision to submit it for publication.

References

01. Malvezzi M, Santucci C, Boffetta P, et al. European cancer mortality predictions for the year 2023 with focus on lung cancer.

Ann Oncol. 2023;34(4):410-419.

02. Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA

Cancer J Clin. 2023;73(1):17-48.

03. Chakraborty S, Singh S. Surgical resection improves survival in

pancreatic cancer patients without vascular invasion- a population based study. Ann Gastroenterol. 2013;26(4):346-352.

04. Winter JM, Brennan MF, Tang LH, et al. Survival after resection

of pancreatic adenocarcinoma: Results from a single institution

over three decades. Ann Surg Oncol. 2012;19(1):169-175.

05. Paniccia A, Hosokawa P, Henderson W, et al. Characteristics of

10-year survivors of pancreatic ductal adenocarcinoma. JAMA

Surg. 2015;150(8):701-710.

06. Ferrone CR, Pieretti-Vanmarcke R, Bloom JP, et al. Pancreatic

ductal adenocarcinoma: long-term survival does not equal

cure. Surgery. 2012;152(3 Suppl 1):S43-9.

07. van Eijck CWF, Mustafa DAM, Vadgama D, et al. Dutch

Pancreatic Cancer Group (DPCG). Enhanced antitumour

immunity following neoadjuvant chemoradiotherapy mediates

a favourable prognosis in women with resected pancreatic cancer. Gut. 2023;73(2):311-324.

08. Varadhachary GR, Wolff RA, Crane CH, et al. Preoperative gemcitabine and cisplatin followed by gemcitabine-based chemoradiation for resectable adenocarcinoma of the pancreatic head. J

Clin Oncol. 2008;26(21):3487-3495.

09. George S, Jean-Baptiste W, Yusuf Ali A, et al. The role of type 2

diabetes in pancreatic cancer. Cureus. 2022;14(6):e26288.

10. Duan X, Wang W, Pan Q, et al. Type 2 diabetes mellitus intersects with pancreatic cancer diagnosis and development. Front

Oncol. 2021;11:730038.

11. Sun H, Saeedi P, Karuranga S, et al. IDF Diabetes Atlas: global,

regional and country-level diabetes prevalence estimates for

2021 and projections for 2045. Diabetes Res Clin Pract.

2022;183:109119.

12. Amri F, Belkhayat C, Yeznasni A, et al. Association between

pancreatic cancer and diabetes: insights from a retrospective

cohort study. BMC Cancer. 2023;23(1):856.

13. Musi N, Hirshman MF, Nygren J, et al. Metformin increases

AMP-activated protein kinase activity in skeletal muscle of subjects with type 2 diabetes. Diabetes. 2002;51(7):2074-2081.

14. Madiraju AK, Erion DM, Rahimi Y, et al. Metformin suppresses

gluconeogenesis by inhibiting mitochondrial glycerophosphate

dehydrogenase. Nature. 2014;510(7506):542-546.

15. Herman R, Kravos NA, Jensterle M, et al. Metformin and insulin

resistance: a review of the underlying mechanisms behind

changes in GLUT4-mediated glucose transport. Int J Mol Sci.

2022;23(3):1264.

16. Karnevi E, Said K, Andersson R, et al. Metformin-mediated

growth inhibition involves suppression of the IGF-I receptor signalling pathway in human pancreatic cancer cells. BMC Cancer.

2013;13:235.

17. Yin M, Zhou J, Gorak EJ, et al. Metformin is associated with survival benefit in cancer patients with concurrent type 2 diabetes:

a systematic review and meta-analysis. Oncologist. 2013;18

(12):1248-1255.

18. Zhou PT, Li B, Liu FR, et al. Metformin is associated with survival

benefit in pancreatic cancer patients with diabetes: a systematic review and meta-analysis. Oncotarget. 2017;8

(15):25242-25250.

19. Wei M, Liu Y, Bi Y, et al. Metformin and pancreatic cancer survival: real effect or immortal time bias? Int J Cancer. 2019;145

(7):1822-1828.

20. Yu H, Zhong X, Gao P, et al. The potential effect of metformin on

cancer: an umbrella review. Front Endocrinol (Lausanne).

2019;10:617.

21. Nowicka Z, Matyjek A, Płoszka K, et al. Metanalyses on metformin's role in pancreatic cancer suffer from severe bias and low

data quality—an umbrella review. Pancreatology. 2023;23

(2):192-200.

22. Chaiteerakij R, Petersen GM, Bamlet WR, et al. Metformin use

and survival of patients with pancreatic cancer: a cautionary

lesson. J Clin Oncol. 2016;34(16):1898-1904.

23. Kordes S, Pollak MN, Zwinderman AH, et al. Metformin in

patients with advanced pancreatic cancer: a double-blind,

randomised, placebo-controlled phase 2 trial. Lancet Oncol.

2015;16(7):839-847.

24. Reni M, Dugnani E, Cereda S, et al. (Ir)relevance of metformin

treatment in patients with metastatic pancreatic cancer: an

open-label, randomized phase II trial. Clin Cancer Res. 2016;22

(5):1076-1085.

25. Nojima I, Wada J. Metformin and its immune-mediated effects

in various diseases. Int J Mol Sci. 2023;24(1):755.

26. Hausmann S, Kong B, Michalski C, et al. The role of

inflammation in pancreatic cancer. Adv Exp Med Biol.

2014;816:129-151.

27. Mundry CS, Eberle KC, Singh PK, et al. Local and systemic

immunosuppression in pancreatic cancer: targeting the stalwarts in tumor’s arsenal. Biochim Biophys Acta Rev Cancer.

2020;1874(1):188387.

28. Sharma P, Hu-Lieskovan S, Wargo JA, et al. Primary, adaptive,

and acquired resistance to cancer immunotherapy. Cell.

2017;168(4):707-723.

29. Versteijne E, van Eijck CH, Punt CJ, et al. Dutch Pancreatic Cancer

Group (DPCG). Preoperative radiochemotherapy versus immediate

surgery for resectable and borderline resectable pancreatic cancer

(PREOPANC trial): study protocol for a multicentre randomized controlled trial. Trials. 2016;17(1):127.

30. Versteijne E, Suker M, Groothuis K, et al. Dutch Pancreatic

Cancer Group. Preoperative chemoradiotherapy versus immediate surgery for resectable and borderline resectable pancreatic cancer: results of the Dutch randomized phase III

PREOPANC trial. J Clin Oncol. 2020;38(16):1763-1773.

31. Pentikainen PJ, Voutilainen E, Aro A, et al. Cholesterol lowering

effect of metformin in combined hyperlipidemia: placebo controlled double blind trial. Ann Med. 1990;22(5):307-312.

1382 | JNCI: Journal of the National Cancer Institute, 2024, Vol. 116, No. 8

Downloaded from https://academic.oup.com/jnci/article/116/8/1374/7635164 by guest on 03 September 2024

32. Eikawa S, Nishida M, Mizukami S, et al. Immune-mediated antitumor effect by type 2 diabetes drug, metformin. Proc Natl Acad

Sci U S A. 2015;112(6):1809-1814.

33. Kunisada Y, Eikawa S, Tomonobu N, et al. Attenuation of CD4(þ)

CD25(þ) regulatory T cells in the tumor microenvironment by

metformin, a type 2 diabetes drug. EBioMedicine. 2017;25:154-164.

34. Shi YQ, Zhou XC, Du P, et al. Relationships are between metformin use and survival in pancreatic cancer patients concurrent

with diabetes: a systematic review and meta-analysis. Medicine

(Baltimore). 2020;99(37):e21687.

35. Sadeghi N, Abbruzzese JL, Yeung SC, et al. Metformin use is

associated with better survival of diabetic patients with pancreatic cancer. Clin Cancer Res. 2012;18(10):2905-2912.

36. Hwang AL, Haynes K, Hwang WT, et al. Metformin and survival

in pancreatic cancer: a retrospective cohort study. Pancreas.

2013;42(7):1054-1059.

37. Nouri-Shirazi M, Banchereau J, Bell D, et al. Dendritic cells capture killed tumor cells and present their antigens to elicit tumorspecific immune responses. J Immunol. 2000;165(7):3797-3803.

38. Sierra-Filardi E, Nieto C, Dominguez-Soto A, et al. CCL2 shapes

macrophage polarization by GM-CSF and M-CSF: identification

of CCL2/CCR2-dependent gene expression profile. J Immunol.

2014;192(8):3858-3867.

39. Lankadasari MB, Mukhopadhyay P, Mohammed S, et al. TAMing

pancreatic cancer: combat with a double edged sword. Mol

Cancer. 2019;18(1):48.

40. Yang S, Liu Q, Liao Q. Tumor-associated macrophages in pancreatic ductal adenocarcinoma: origin, polarization, function,

and reprogramming. Front Cell Dev Biol. 2020;8:607209.

41. Kerneur C, Cano CE, Olive D. Major pathways involved in

macrophage polarization in cancer. Front Immunol.

2022;13:1026954.

42. Feng L, Qi Q, Wang P, et al. Serum level of CCL2 predicts outcome of patients with pancreatic cancer. Acta Gastroenterol Belg.

2020;83(2):295-299.

43. Novizio N, Belvedere R, Pessolano E, et al. ANXA1 contained in

EVs regulates macrophage polarization in tumor microenvironment and promotes pancreatic cancer progression and metastasis. Int J Mol Sci. 2021;22(20):11018.

44. Song TL, Nairismagi ML, Laurensia Y, et al. Oncogenic activation of the STAT3 pathway drives PD-L1 expression in natural

killer/T-cell lymphoma. Blood. 2018;132(11):1146-1158.

45. Zou S, Tong Q, Liu B, et al. Targeting STAT3 in cancer immunotherapy. Mol Cancer. 2020;19(1):145.

46. Crist M, Yaniv B, Palackdharry S, et al. Metformin increases natural killer cell functions in head and neck squamous cell carcinoma through CXCL1 inhibition. J Immunother Cancer. 2022;10

(11):e005632.

47. Wang S, Lin Y, Xiong X, et al. Low-dose metformin reprograms

the tumor immune microenvironment in human esophageal

cancer: results of a phase II clinical trial. Clin Cancer Res. 2020;26

(18):4921-4932.

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JNCI: Journal of the National Cancer Institute, 2024, 116, 1374–1383

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