Isolation of functional human islets from pancreatectomy remnants: Determinants of yield and functionality

Abstract

Human pancreatic islets are essential for studies in β-cell biology, cell transplantation, and tissue engineering, yet access to viable human islets remains limited because conventional isolation protocols primarily rely on whole pancreases from deceased donors. Surgical pancreatectomy specimens may represent an accessible alternative source, but factors influencing successful isolation and functional preservation remain poorly defined. In this study, we evaluated a standardized method for isolating human islets from pancreatic tissue obtained from surgical pancreatectomy specimens and investigated patient-, specimen-, and surgery-related factors affecting islet yield and functionality. Between March and October 2024, 50 consecutive islet isolations were performed from pancreatic specimens obtained during surgical resections. Following enzymatic digestion, tissue fractions were cultured for 24 h before handpicking of morphologically intact islets. Islet yield was quantified as islet equivalents (IEQ), and functional integrity was assessed by glucose-stimulated insulin secretion assays on culture days 1, 3, and 5. A mean yield of 6690 IEQ/g pancreatic tissue was obtained (range 0–56,500 IEQ/g). Exploratory analyses suggested potential associations between islet yield and factors such as younger patient age, shorter surgical duration, and preserved pancreatic parenchyma. However, these findings should be interpreted cautiously given the variability of the specimens and the exploratory design of the study. These findings support the feasibility of using surgical pancreatectomy specimens as an accessible source of functional human islets for experimental and translational research.

Graphical Abstract

Keywords

islets of Langerhans human islet isolation islet transplantation beta cells tissue engineering

Introduction

Diabetes mellitus type 1 (T1DM) is one of the most prevalent chronic diseases in childhood. In 2022, 8.75 million individuals worldwide were diagnosed with the disease¹. This condition arises from a deficiency in insulin production due to the destruction of the beta cells within the pancreas. The current gold standard therapy for these patients is the regular application of synthetic subcutaneous insulin. While this therapy is life-saving, it demands stringent patient compliance, rendering long-term optimal glucose control difficult to achieve, particularly in patients with hypoglycemia unawareness, severe hypoglycemic episodes, and glycemic lability^1,2. Untreated, the disease can lead to severe secondary complications, including diabetic peripheral neuropathy, diabetic retinopathy, coronary artery disease, and end-stage kidney failure. To improve glycemic control and reduce long term complications, ß-cell replacement strategies such as pancreas and islet transplantation have been developed^3,4. However, their broader clinical application remains limited by donor organ availability, variability in islet quantity, and the need for immunosuppression^4,5. Beyond their clinical use, human islets are a critical resource for experimental and translational research, including studies on ß-cell biology, disease mechanisms and the development of tissue engineering approaches. In particular, efforts to recreate the islet microenvironment have focused on key components such as the extracellular matrix (ECM), vascularization and functional ß-cells^6,7.

Indeed, various groups have focused on engineering the endocrine pancreatic tissue by recellularizing the decellularized rat pancreas, lung, and liver ECM with xenogenous vascular cells and islets of rat or porcine origin^8–11. However, it is well-established that islets from different species exhibit different characteristics regarding isolation and functionality^12–14. To ensure better translatability, these tissue-engineered constructs need to be tested using human islets. While several protocols for human islet isolation exist, they are all adaptations of the widely known Ricordi method, which is feasible for large amounts of pancreatic tissue, like whole pancreases of multi-organ donors¹⁵. To address the limited availability of viable human islets for experimental research, we focused on the isolation of islets from pancreatic tissue obtained during routine surgical procedures. In contrast to established protocols relying on whole pancreata from deceased donors, these specimens are smaller, more heterogeneous and of variable quality, requiring adapted isolation strategies. Here, we present a novel method for isolating human islets from surgical pancreatectomy specimens and evaluate the feasibility of this approach. In addition, we explore patient-, specimen-, and surgery-related factors that may influence islet yield and functionality.

Methods

Ethical approval

Approval for islet isolation from pancreatic tissue obtained from surgical pancreatectomy specimens of patients undergoing a surgical procedure in the Department of Surgery, Charité – Universitätsmedizin Berlin, Germany, was given by the local ethical board (Ethikkomission der Charité, EA2/154/22). Informed written consent from all patients involved in this study was present before isolation.

Patient inclusion

The study was designed as a retrospective observational analysis of prospectively collected data from consecutive human islet isolations performed on pancreatic tissue obtained from surgical pancreatectomy specimens.

From March 7, 2024, to October 2, 2024, a total of 84 pancreatic surgery procedures were performed. In 32 cases (38%), tissue for isolation was not provided by the pathologists due to inadequate sample size, and in two cases (2%) the surgical procedure was aborted due to inoperability. Tissue samples were obtained from 51 patients (60.7%). The first isolation was performed as a proof of concept using a nonstandardized protocol, and was therefore excluded from further analysis. The final study cohort comprised 50 consecutive isolations.

A retrospective analysis was conducted on the following patient-related factors, as documented in the patient’s medical records: age, sex, weight, height, body mass index (BMI), history of diabetes mellitus, history of pancreatitis, diagnosis leading to pancreatic surgery, and neoadjuvant chemotherapy, if applicable. The final pathology reports were reviewed with regard to tumor diagnosis and histological characteristics of the pancreatic parenchyma. In addition, the following surgery-related factors were evaluated: type of surgery (open or minimally invasive), duration of surgery, and warm ischemia time. Specimen-related factors such as cold ischemia time, tissue weight, and parenchymal quality were also assessed.

A total of 84 pancreatic surgical procedures were screened for eligibility. Tissue samples were obtained from 51 patients. One initial nonstandardized isolation was excluded, resulting in 50 consecutive isolations included in the final analysis. Functional testing via glucose-stimulated insulin secretion test (GSIS) was performed in a subset of 15 isolations, and histological evaluation was available for 13 cases.

Isolation protocol

After retrieval from the pathologist, the specimen was stored in Hanks’ solution (HBSS, Bio & Sell GmbH, Feucht, Germany) at 4°C and transported to the laboratory. The pancreatic specimen was dissected free of surrounding fat and vascular tissue.

A standardized isolation protocol was applied to all specimens. Due to the small size of pancreatic samples, ductal cannulation was not performed. Instead, the tissue was distended by injecting HBSS directly into the parenchyma to remove residual blood.

Collagenase solution was prepared by diluting 60 mg collagenase in 10 ml HBSS for tissue samples weighing less than 2 g and 120 mg in 20 l HBSS for samples weighing more than 2 g (Collagenase Type V, Sigma Aldrich, St. Louis, Missouri, United States). The solution contained 1% HEPES (4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid) and was prewarmed to 39°C.

The pancreatic tissue was dissected into small fragments and incubated in the collagenase solution at 39°C for 12 min with intermittent gentle shaking. Digestion was stopped by rapid cooling with cold HBSS (4°C) up to a total volume of 100 ml. The suspension was centrifuged at 277 × g for 1 min, and the supernatant was discarded. This washing step was repeated twice.

The final pellet was resuspended in cold Connaught Medical Research Laboratories (CMRL) medium (CMRL-1066 supplemented with 10% fetal bovine serum, 10 mM nicotinamide, 2mM L-glutamine, and 1% penicillin/streptomycin). The tissue was transferred into culture dishes and incubated at 37°C in an atmosphere of 95% O₂ and 5% CO₂.

During the initial phase of the study (first 20 isolations), contamination was observed despite sterile handling. Therefore, an additional antibiotic preincubation step was introduced, consisting of incubation with gentamicin (100 µg/ml for 10 min) prior to isolation. This modification reduced contamination rates from approximately 40 to 3% and was applied to all subsequent isolations. Due to the small sample size, gradient purification was not performed in this protocol.

Islet picking, counting and viability staining

Following a 24-hour incubation period, islets were handpicked under an inverted microscope based on morphological criteria. Collected islets were pooled and quantified as islet equivalents (IEQ) after dithizone (DTZ) staining, as previously described. Briefly, islets were categorized into diameter classes (in 50 µm increments), and counts were normalized to a standard islet size of 150 µm using established conversion factors.

Islet viability was assessed using fluorescein diacetate (FDA) and propidium iodide (PI) staining. Viable cells were identified by green fluorescence, whereas nonviable cells were identified by red fluorescence. Viability was evaluated qualitatively based on the proportion of live and dead cells within each islet.

Glucose-stimulated insulin secretion test

Islet functionality was assessed by measuring static insulin secretion in response to glucose stimulation by adapting a protocol previously described¹⁶. Islets were exposed to low (3.3 mM) and high (16.4 mM) glucose conditions, and insulin secretion was measured on culture days 1, 3 and 5. Only isolations with sufficient numbers of viable islets for triplicate measurements were included in the analysis (n = 15). Due to contamination and limited islet availability in some isolations, functional testing could only be performed in a subset of cases. Only isolations with sufficient numbers of viable islets to perform triplicate measurements under both low and high glucose conditions were included in the GSIS analysis. This resulted in a final subgroup of 15 isolations.

Islet cultivation, appearance of islet stromal cells (ISC) and staining

After picking, human islets were cultivated over a period of 5 days. After 3 days of culture, cells adhering to islets and radially spreading over the culture plate around the islets were detected. Initially, the cells exhibited a round shape, subsequently changing to an elongated shape. On day 5 of cultivation, these cells resulted in islets becoming attached to the bottom of the cell culture plate. For staining, these cells were first trypsinized with 6 ml Trypsin, then placed on coverslips pretreated with 0.02% gelatin. After an overnight incubation to ensure cell adhesion the cells were fixated with 4% PFA for 15min. Finally, staining was performed as described below.

Correlation of the consistency of the parenchyma with islet yield

To objectify tissue quality, pancreatic specimens were retrospectively evaluated by two pathologists in consensus. The analysis consisted of evaluating pancreatic parenchyma regarding fibrosis, lipomatosis and pancreatitis. Hematoxylin and eosin staining were performed. For evaluating pancreatic fibrosis an established grading system as described by Schawkat et al.¹⁷ was implemented: F0 = normal pancreatic parenchyma; F1 = mild fibrosis with thickening of periductal fibrous tissue; F2 = moderate fibrosis with marked sclerosis of interlobular septa and no evidence of architectural changes; and F3 = severe fibrosis with detection of architectural destruction. Based on another grading system also developed from Schawkat et al. fat content of the pancreatic specimen was graded as: L1 = 0 to 10% fat deposition, L2 = 11 to 30%, and L3 = greater than 30%. Lastly, the specimens were also retrospectively investigated for pancreatitis, and were separated into mild, moderate and severe pancreatitis based on a score for evaluation of pancreatitis used in the Department of Pathology, Charité – Universitätsmedizin Berlin, Germany. The parameters for the acute pancreatitis involve edema, inflammatory infiltration (neutrophils and granulocytes) and necrosis; the parameters for chronic pancreatitis involve the evaluation of the lymphocytic inflammatory infiltration.

Immunohistochemical analysis

Immunohistochemical staining for insulin, CD31, and CD90 was performed using standard protocols to assess endocrine function and characterize islet-associated stromal cells.

Statistical analysis

All quantitative data analyses were conducted and visualized using GraphPad Prism version 10.00 (GraphPad Software, La Jolla, California, USA). The Gaussian distribution was calculated using the Shapiro-Wilk normality test, and data are expressed as the mean ± standard error of the mean (SEM). Two-way ANOVA followed by multiple comparisons (Tukey’s multiple comparisons test) was performed to compare the results of the glucose-stimulated insulin secretion test. Student’s paired t-test was performed to compare the different parameters between the low yield and the high yield group. Pearson’s correlation coefficient (r) or nonparametric Spearman’s correlation coefficient were used to investigate the association between patient-, specimen- and surgical procedure-related factors, islet yield, and islet functionality. A P-value of <0.05 was considered significant.

Given the exploratory nature of the study and the limited sample size, multivariable analysis were not performed to avoid model overfitting and unstable estimated. Therefore, the statistical analysis was primarily univariable and hypothesis-generating. Effect sized, including correlation coefficients, are reported alongside P-values where applicable to provide a more comprehensive interpretation of the results.

Missing data were not imputed. Analyses were performed using available-case data, and the number of observations (n) is reported for each analysis where applicable. Cases with unavailable histological or functional data were excluded from the respective sub-analyses. Given the exploratory nature of the study, and the limited sample size, multivariable analyses were not performed to avoid model overfitting.

The study design and reporting were aligned with Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) recommendations were applicable.

Results

In this study we primarily evaluated the feasibility and variability of isolating human islets from surgical pancreatectomy specimens. In addition, we performed exploratory analyses to assess potential associations between patient-, specimen-, and surgery-related factors and islet yield and functionality. To facilitate interpretation and comparison of outcomes, isolations were categorized into two groups based on total islet yield: a low-yield group (LY, <2000 IEQ) and a high-yield group (HY > 2000 IEQ). This threshold was chosen pragmatically to distinguish between isolations yielding sufficient material for downstream experimental applications and those with limited usability. Given the exploratory nature of the study, this categorization was intended to support descriptive comparisons rather than to imply a strict biological cutoff.

Islet yield

Human islet isolation

Islet yield ranged from 0 to 56,500 IEQ/g pancreatic tissue (mean 6690 IEQ/g). The low yield group (n = 31) and high-yield group (n = 19) differed significantly in total islet yield (P < 0.0001, Figure 1a).

Figure 1.

Isolation protocol. (a) The pancreatectomy specimen was received from the operation room, treated with gentamicin and was weighed. Based on the weight, digestion was performed either with 60 mg or with 120 mg collagenase type V. After centrifugation, islets were placed in culture. On the next day, picking, staining and counting followed. Finally, islets were cultivated over 5 days, with functional analysis performed on days 1, 3, and 5 of cultivation. (b) A total of n = 50 isolations were performed, and the isolations were separated into low yield (< 2000 IEQ, n = 31) and high yield (> 2000 IEQ, n = 19). The difference between both groups in islet yield was statistically significant (292.5 ± 477.08 vs 23209 ± 21113.8, P < 0.0001). (c) The cold ischemia time calculated as the time from receiving the specimen to islet isolation was slightly longer in the high yield group (55.16 ± 54.83 vs 91.58 ± 73.81 min, P = 0.06). (d) Living human islets and (e) dead human islets as stained with FDA/PI. FDA, fluorescein diacetate; PI, propidium iodide.

Islet isolation was performed at varying time points after sample receipt, with a mean cold ischemia time of 70.8 ± 64.1 min (0–270 min). Although the time to isolation was longer in the high-yield group, this difference was not statistically significant (Figure 1c). Viability staining was performed on the same day, with green-stained islets considered viable and red-stained islets nonviable. Representative examples included isolation #2 (21,000 IEQ, all viable; Figure 1d) and isolation #15 (0 IEQ; Figure 1e). In the latter case, initially intact islets were observed but lost viability by the following day. This observation may be related to prolonged warm ischemia time and challenging surgical conditions; however, causality cannot be established based on a single case.

Age, sex, and BMI did not differ significantly between LY and HY groups (Table 1). However, patients with diabetes mellitus type II and pancreatitis were more frequent in the LY group (P = 0.02, Table 1). Benign diagnoses were similarly distributed (LY: n = 8 [26%] vs HY: n = 10 [52%]), whereas malignant diagnoses were more common in the LY group (n = 23 [74%] vs n = 9 [48%], P = 0.07). Neoadjuvant chemotherapy (n = 11) was similarly distributed between groups.

Table 1.

Patient-related factors and isolation outcome.

Patient characteristics	IEQ < 2000	SD	IEQ > 2000	SD	P
Age (Median)	63 (37–84)	11.3	58 (30–76)	12.1	0.18
Sex (Male), n (%)	20 (65%)		7 (36%)		0.08
Body mass index (BMI)	25.3	4.2	25.3	4.6	0.98
Comorbidities, n (%)					0.03
Diabetes mellitus, type 2	9 (29%)		1 (6%)
Acute pancreatitis	0 (0%)		2 (10%)
Chronic pancreatitis	7 (23%)		2 (10%)
None	15 (48%)		14 (74%)
Diagnosis, n (%)					0.07
Benign	8 (26%)		10 (52%)
Malignant	23 (74%)		9 (48%)
Neoadjuvant chemotherapy, n (%)					0.99
Yes	8 (35%)		3 (33%)
No	15 (65%)		6 (67%)
Histological diagnosis, n (%)					0.058
SPN	2 (7%)		0 (0%)
MCN	0 (0%)		3 (16%)
IPMN	5 (17%)		3 (16%)
Pancreatitis	1 (3%)		2 (11%)
PDAC	16 (51%)		4 (21%)
Other	7 (22%)		7 (36%)
T Classification, n (%)					0.57
T1	3 (16%)		1 (17%)
T2	11 (58%)		2 (33%)
T3	4 (21%)		3 (50%)
T4	1 (5%)		0 (0%)
N Classification, n (%)					0.39
N0	6 (32%)		2 (33%)
N1	7 (37%)		3 (50%)
N2	6 (31%)		0 (0%)
G Classification, n (%)
G1	0 (0%)		1 (17%)
G2	11 (58%)		3 (50%)
G3	6 (32%)		2 (33%)
R Classification, n (%)					0.54
R0	15 (79%)		6 (100%)
R1	4 (21%)		0 (0%)

Depiction of patient characteristics separated into two groups based on islet yield. Patients with < 2000 IEQ had significantly more comorbidities such as diabetes mellitus type 2 (DMT2), acute and chronic pancreatitis (P = 0.03). These patients also showed more malignant diagnosis with PDAC than patients yielding > 2000 IEQ. IEQ: islet equivalent; SD: standard deviation; BMI: body mass index; SPN: solid pseudopapillary neoplasm; MCN: mucinous cystic neoplasm; IPMN: intraductal papillary mucinous neoplasm; PDAC: pancreatic ductal adenocarcinoma. Values in bold p < 0.05.

Histopathological analysis showed that pancreatic ductal adenocarcinoma (PDAC) was significantly more frequent in the LY group (LY vs HY: n = 16 [51%] vs n = 4 [21%], P = 0.0058; Table 1). Other diagnoses included retroperitoneal cysts, extrahepatic bile duct carcinoma, and neuroendocrine tumors (NETs) in the HY group, and duodenal carcinoma, extrahepatic bile duct carcinoma, papillary carcinoma, pancreatic intraepithelial neoplasia (PanIN), NET, and renal cell carcinoma metastasis in the LY group. Among patients with malignant disease (n = 24), postoperative T, N, G, and R status was similarly distributed between groups.

Specimen-related factors and isolation outcome

Prior to isolation, sample weight and anatomical origin (head, corpus, or tail) were recorded. Although sample weight was higher in the HY group, the difference was not statistically significant (Table 2). Specimen origin was similarly distributed between groups (P = 0.95).

Table 2.

Specimen characteristics and isolation outcome.

Specimen characteristics	IEQ < 2000	SD	IEQ > 2000	SD	P
Mean weight (g)	1.33	1.02	1.9	1.3	0.17
Localization, n (%)					0.95
Head	11 (35%)		6 (31%)
Corpus	5 (16%)		4 (21%)
Tail	14 (245%)		8 (42%)
Unknown	1 (3%)		1 (6%)
Fibrosis, n (%)					0.001
F0	3 (10%)		1 (6%)
F1	5 (18%)		12 (70%)
F2	7 (25%)		4 (24%)
F3	13 (46%)		0 (0%)
Lipomatosis, n (%)					0.39
L0	0 (0%)		1 (6%)
L1	23 (82%)		12 (70%)
L2	4 (14%)		2 (12%)
L3	1 (4%)		2 (12%)
Pancreatitis, n (%)					0.005
None	4 (14%)		10 (59%)
Mild	8 (29%)		5 (29%)
Moderate	6 (21%)		0 (0%)
Severe	10 (36%)		2 (12%)

Specimens from isolations with < 2000 IEQ were subjectively significantly more fatty and hard than the ones from isolations yielding >2000 IEQ (P = 0.0001). Histological examination of the specimens revealed that specimens from isolations yielding < 2000 IEQ were significantly more fibrotic (P = 0.001) and pancreatitic (P = 0.005) than specimens yielding > 2000 IEQ. IEQ: islet equivalent; SD: standard deviation. Values in bold p < 0.05.

Histological evaluation of the unaffected pancreatic parenchyma revealed marked differences between groups. Six specimens were excluded due to insufficient tissue. Severe fibrosis was significantly more frequent in the LY group (F3: LY vs HY, 13 vs 0 patients, P = 0.001), whereas mild fibrosis was more common in the HY group (F1: LY vs HY, 5 vs 12). Similarly, moderate and severe pancreatitis were more prevalent in the LY group, while absence of pancreatitis predominated in the HY group (Table 2).

Surgery-related factors and isolation outcome

Surgery type and related characteristics were compared between LY and HY groups. Total pancreatectomy was most frequent in the LY group (LY vs HY: n = 13 vs n = 4), whereas pylorus-preserving pancreatoduodenectomy (PPPD; LY vs HY: n = 9 vs n = 6) and robotic-assisted distal pancreatectomy (LY vs HY: n = 5 vs n = 6) were more common in the HY group. However, surgery type did not differ significantly between groups (P = 0.33, Table 3). Surgical duration was longer in the LY group (287 ± 86 min vs 242 ± 92 min), although this difference was not statistically significant (P = 0.13, Table 3). Warm ischemia time was further analyzed in minimally invasive procedures (n = 15; 14 robotic-assisted, 1 laparoscopic). All procedures in the HY group were robotic-assisted, whereas the LY group included six robotic-assisted and one laparoscopic case (P = 0.33, Table 4). Sample weight and macroscopic quality were comparable between groups. Both total surgery time and warm ischemia time were longer in the LY group, but without statistical significance (Table 4).

Table 3.

Relationship between surgical procedure and isolation outcome.

Surgical procedures	IEQ < 2000	SD	IEQ > 2000	SD	P
Surgery, n (%)					0.33
Open total pancreatectomy	13 (42%)		4 (21%)
Open PPPD	9 (29%)		6 (32%)
Robotic-assisted distal pancreatectomy	6 (10%)		6 (32%)
Robotic-assisted Appleby procedure	1 (3%)		1 (5%)
Open Appleby Procedure	0 (0%)		2 (10%)
Laparoscopic distal pancreatectomy	1 (3%)		0 (0%)
Open distal pancreatectomy	1 (3%)		0 (0%)
Duration of surgery, min	282	87	242	92	0.13

Depiction of surgery-related characteristics separated into two groups based on islet yield, in which no statistically significant differences were detected. IEQ: islet equivalent; SD: standard deviation; PPPD: pylorus preserving pancreatoduodectomy.

Table 4.

Characteristics of surgical interventions.

Characteristics of surgical interventions	IEQ < 2000	SD	IEQ > 2000	SD	P
Type of surgery, n (%)					0.47
Robotic-ASSISTED	5 (83%)		7 (100%)
Laparoscopic	1 (17%)		0 (0%)
Localization, n (%)					0.31
Head	0 (0%)		0 (0%)
Corpus	0 (0%)		0 (0%)
Tail	6 (100%)		7 (100%)
Diagnosis, n (%)
Benign	3 (50%)		5 (71%)		0.95
Malignant	3 (50%)		2 (29%)
Weight, g	1.3	1.2	1.3	1.3	0.95
Macroscopic quality, n (%)					0.17
Good	3 (50%)		5 (71%)
Fatty	2 (33%)		0 (0%)
Hard	1 (17%)		2 (29%)
Total surgery time, min	190	73.82	164	25.9	0.41
Warm ischemia time, min	86	53	51	34	0.27

Depiction of impact of warm ischemia time on islet yield. Minimally-invasive surgeries (n = 15) were categorized by isolations with < 2000 IEQ (n = 6) and isolations yielding >2000 IEQ (n = 7). No significant differences were detected between the two groups in terms of type of surgery, localization, diagnosis, weight, macroscopic quality and total surgery time. Finally, no statistically significant changes were detected in warm ischemia time between both groups, whereby it was longer in the low yield than in the high yield group by 35 min (P = 0.27). IEQ, islet equivalent; SD, standard deviation.

Correlation analysis between islet yield and patient-, specimen-, and surgery-related factors

We investigated whether there was any significant correlation between islet yield and patient-, specimen-, and surgery-related factors (Figure 2). An indirect correlation between the patient age and islet yield was shown, suggesting that younger patient age may be associated with higher islet yield (r = −0.32, P = 0.02, Figure 2a). Moreover, an indirect correlation was also detected between duration of surgery and islet yield, suggesting that shorter surgical duration may be associated with higher islet yield (r = −0.309, P = 0.03, Figure 2b). Islet yield did not correlate significantly with neoadjuvant chemotherapy and known diagnosis of pancreatitis or DMT2 (r = −0.07, P = 0.60; r = −0.002, P = 0.99; r = −0.24, P = 0.09, respectively, data not shown).

Figure 2.

Correlation analysis between patient-, specimens-, and surgical characteristics and islet yield. (a) Patient age negatively correlates with islet yield, with younger patients yielding more islets (r = −0.32, P = 0.02). (b) Duration of surgery also negatively correlates with islet yield, whereby patients undergoing longer surgeries yield less islets (r = −0.309; P = 0.028). (c) Finally, tissue weight positively correlates with islet yield, with larger tissues yielding more islets, although the results are not statistically significant (r = 0.27; P = 0.055).

However, islet yield demonstrated a significant negative correlation with grade of fibrosis (r = −0.5206, P = 0.003) and grade of pancreatitis (r = −0.5209, P < 0.0001, Figure 3a and b). Furthermore, no significant correlation was detected between lipomatosis and islet yield (r = 0.14, P = 0.36, Figure 3c).

Figure 3.

Correlation analysis of parenchymal consistency of the specimen and islet yield. (a) Fibrosis of the pancreatic parenchyma as graded from F0 to F3 negatively correlates with islet yield, with severe fibrotic pancreas yielding significantly less islets (r = −0.5306, P = 0.003). (b) Lipomatosis of the pancreatic parenchyma does not significantly correlate with islet yield, whereby most pancreatic samples were graded as L1 (r = 0.14, P = 0.36). (c) Pancreatitis as graded as none, mild, moderate, and severe also negatively correlates with islet yield (r = −0.5709, P < 0.0001). (d–f) Histological Examples of the pancreatic parenchyma with different grades of fibrosis, lipomatosis and pancreatitis.

Islet functionality

General functionality of human islets

Islet functionality was assessed by GSIS under low and high glucose conditions on culture days 1, 3, and 5 (n = 15). Isolations with contamination or insufficient islet numbers for triplicate measurements were excluded. Islets responded to high glucose stimulation with increased insulin secretion, indicating preserved functionality (day 5: LG vs HG, 12.75 ± 18.84 mU/l vs 38.22 ± 71.1 mU/l, P = 0.103; Figure 4a). While insulin secretion under low glucose conditions remained stable over time, stimulated insulin secretion increased from day 1 to day 5 (11.76 mU/l vs 38.22 mU/l, P = 0.07; Figure 4a).

Figure 4.

General Islet functionality and its correlation with patient-, specimens-, and surgery-related characteristics. (a) Islet functionality as tested by measuring the secreted insulin upon glucose stimulation remains intact throughout the 5-day cultivation period and is almost significantly more on day 5 than on day 1 of cultivation. (b) Islets in the low yield group produced significantly more basal insulin on day 5 than did the islets in the high yield group (low glucose stimulation; LY vs HY, 33.5 vs 7.6 mU/l, P = 0.04). The insulin secretion in the high yield group remained stable throughout all cultivation time. (c) On the other hand, insulin secretion upon stimulation with high glucose solution was similar between both groups at all time points. (d–e) Most patient-, specimen-, and surgery-related characteristics did not significantly correlate with islet functionality (P < 0.05). (f) Duration of surgery was the only parameter to negatively correlate with islet functionality, with islets from longer surgeries functioning less than islets from shorter surgeries (r = −0.5576; P = 0.03).

When analyzed by yield group, LY islets showed higher basal insulin secretion on day 5 compared with HY islets (33.5 vs 7.6 mU/l, P = 0.04; Figure 4b), whereas basal secretion in the HY group remained stable. Stimulated insulin secretion under high glucose conditions did not differ between groups at any time point (Figure 4c).

Correlation analysis between islet functionality and patient-, specimen-, and surgery-related factors

Correlation analysis was performed in the subset of 15 isolations with available GSIS data. The cohort had a mean age of 58.8 ± 13.4 years, 46% were male, 10 patients had malignant disease and 5 benign disease. None had T2DM, while one patient had acute and three had chronic pancreatitis, and two received neoadjuvant chemotherapy.

Islet functionality was assessed as the difference between insulin secretion under high and low glucose conditions (Δ low/high glucose). No significant correlations were observed between islet functionality and patient-, specimen-, or surgery-related factors on day 3 or day 5 (data not shown). On day 1, a negative correlation between duration of surgery and islet functionality was observed (r = −0.55, P = 0.03, Figure 4f). No other significant associations were detected (Figure 4d, e). Analysis of histological parameters (n = 13) showed no significant correlation between islet functionality and fibrosis (r = −0.25, P = 0.41), lipomatosis (r = 0.09, P = 0.75), or pancreatitis (r = −0.27, P = 0.37) (data not shown).

Histological analysis of islets and islet-derived stromal cells

Insulin staining and correlation with insulin secretion upon glucose stimulation

After GSIS was performed, islets were put in formalin and kept at 4°C. Then, insulin staining of these islets was performed. Here, we depict the results of the insulin staining performed in isolation #29 and isolation #44 on islets after GSIS on days 1 and 3 of cultivation. Images a–f belong to exp. #29, in which 450 IEQ were isolated from an 84-year-old patient suffering from pancreatic ductal adenocarcinoma with a pancreatic consistency of F2/L1/mild pancreatitis. The insulin secretion upon stimulation with low and high glucose was inadequate on both days (day 1 LG vs HG: 0.4 vs 0.4 mU/l; day 3 LG vs HG: 0.4 vs 0.46 mU/l). These results are also represented in the insulin staining, whereby islets are mostly negative for insulin on both culture days (Figure 5a–f). Images G-K belong to exp. #44, in which 17.814 IEQ were isolated from a 64-year old women also suffering from pancreatic ductal adenocarcinoma with a pancreatic consistency of F1/L1/no pancreatitis. The insulin secretion here was adequate (day 1 LG vs HG: 1.47 vs 2.13 mU/l; day 3 LG vs HG: 2.12 vs 27.29 mU/l). These results are also depicted in Figure 5d–k, in which islets have stained positive for insulin.

Figure 5.

Insulin staining. (a–f) Islets from a low-yield isolation staining negative for insulin on days 1 and 3 of cultivation after glucose stimulated insulin secretion test. (g–k) Islets from a high-yield isolation staining positive for insulin on days 1 and 3 of cultivation after glucose stimulated insulin secretion test.

Islet-derived stromal cells

After hand-picking islets were cultivated over 5 days in a cell culture plate and the islet medium was not changed after islet picking on day 1 after isolation. Our observations suggested that with time cells started to grow around the islets, which led to islets eventually attaching to the bottom of the cell culture plate partially at day 3, but almost completely at day 5. Figure 6a to c depict this phenomenon with islets isolated from a patient suffering from an intraductal papillary mucinous neoplasm (IPMN). Moreover, the same phenomenon was seen culture plates based on specimen from a patient suffering from a PDAC (Figure 6d–f). As it can be seen, in both cases morphologically similar cells grow around the islets and eventually covering the entire cell culture plate. To understand their origin, we performed staining with CD31 and CD90 antibodies, respectively. While some cells stained positive for these markers, some cells remained unstained (Figure 6g and h). While further characterization is required to further clarify the origin of these cells, this remains outside the scope of this study.

Figure 6.

Islet-derived stromal cells. (a–c) Cells growing around human islets isolated from a patient with a malignant disease. (d–f) Similar cells growing around islets isolated from a patient with a benign disease. (e and f) These cells stained positive for both CD31 and CD90 antibodies.

Discussion

Importantly, the findings of this study should be interpreted in the context of its exploratory design. The relatively small sample size, heterogeneity of surgical specimens, and variability in clinical conditions limit the ability to draw definitive conclusions regarding factors influencing islet yield and functionality. Observed associations should therefore be considered hypothesis generating rather than causal relationships.

The only available data on patient-, specimen-, and surgery-related factors affecting islet yield from human pancreatectomy specimens derive primarily from studies of autologous islet transplantation performed after pancreatectomy for benign or malignant diseases^18–20. Other studies using pancreatic tissue from living donors have focused mainly on isolating islet RNA from snap-frozen samples to investigate β-cell properties in metabolic disease^21–24. In contrast, xenogeneic islets or islets isolated from whole pancreases of deceased multi-organ donors are typically used for tissue engineering or in vitro functional studies²⁵. A central challenge in research islet isolation remains the limited and unpredictable availability of viable human islets, as most studies depend on deceased donor organs, restricting accessibility and reproducibility. Although commercially available human islets exist, they are rarely accessible on demand and their availability cannot be planned in advance⁹. In addition to commercially available islet sources, several research islet distribution programs have been established to improve accessibility. Notably, some initiatives provide human islets for research purposes free of charge, thereby supporting broader scientific use²⁶. Nevertheless, availability remains unlimited and often unpredictable, underscoring the need for alternative and readily accessible sources such as surgical specimens. In this context, our approach is specifically intended to expand the availability of human islets for research applications, rather than to directly compete with clinical-grade islet isolation protocols.

Studies of human islet isolation for allotransplantation have identified that patient-specific factors such as BMI, donor age, and pancreas weight significantly correlate with islet yield. While these findings are informative, their direct applicability to research-oriented islet isolation from surgical specimens is limited, given the differences in tissue source, scale and intended use. For example, Lakey et al.¹⁴ and Hilling et al.²⁷ found that donor age, local procurement team, and high BMI positively correlated with islet recovery, while hyperglycemia had a negative correlation. By contrast, in our study we found that gender, BMI and a known diagnosis of diabetes mellitus type 2 did not correlate significantly with islet yield (data not shown). However, islet yield was significantly correlated with patient age (Figure 2a) as well as with the duration of surgery (Figure 2b). Importantly all of these studies used whole pancreases from deceased donors as source for islets, which is very different from our research using small pancreatic tissue obtained from surgical pancreatectomy specimens from living donating patients. Interestingly, substantial islet yields were obtained despite deviations from classical procurement conditions. This may be due to immediate processing without prolonged cold storage, reduced cumulative ischemia, and differences in handling of smaller specimens. In addition, requirements for research-grade islets are less stringent than for clinical transplantation, which may further explain this observation.

Next, we investigated whether and how the diagnosis leading to pancreatic surgery affected islet yield. Our analysis suggested that specimens obtained from patients with malignant disease may yield fewer islets. However, this trend did not reach statistical significance and should be interpreted cautiously (P = 0.07, Table 1). In a case report, Förster et al.²⁸ described the isolation of 2636 IEQ/g from the distal pancreatectomy specimen of a patient suffering from adenocarcinoma. Ris et al. reported the isolation of 5455 IEQ/g of pancreatic tissue from patients with benign pancreas disease²⁹. Conversely, isolations of 1457 IEQ/g pancreas have been reported from patients with pancreatitis³⁰. In our cohort, isolations from patients with a malignant disease yielded 4208 IEQ/g pancreatic tissue, isolations from patients with a benign disease yielded 11101.78 IEQ/g and isolations from patients with pancreatitis yielded 5533 IEQ/g – all higher than those reported in the literature. However, all of the groups have performed gradient purification during the isolation process, which is known to significantly affect islet counts³⁰. Finally, isolation from specimens of patients without pancreatitis yielded twice as many islets as from patients with acute or chronic pancreatitis, confirming findings in the literature^31,32.

Overall, because of the higher islet yield and the lack of risk of transferring malignancy, these findings may support the preferential use of specimens obtained from patients with benign disease for research applications. However, further studies are required to confirm this observation. Indeed, the main concern with islet isolation from patients suffering from a pancreatic malignancy is cancer recurrence after resection and islet autotransplantation, especially in the liver^31,33,34. Studies have shown that pancreatic cancer very rarely occurs in the remnant pancreas once the tumor resection margins are negative, but there are cases of metastases that have been described^34–36. The most commonly used approach to prevent this is to purify and cultivate the islets until the patient’s final pathology is available. In our cohort, investigation of final pathology regarding the postoperative tumor formula suggested that while more patients in the low yield group suffered from PDAC (P = 0.056, Table 1), only n = 4 patients from the low yield group showed a positive margin resection (Table 1). Lastly, our analysis suggested that contrary to our expectations, neoadjuvant chemotherapy had no significant effect on islet yield. To our knowledge, there is no data in literature to support or refute this finding.

Next, specimen-related factors and their impact on islet yield were analyzed. In our cohort, the cold ischemia time after sample retrieval until isolation was longer in the high-yield group than in the low-yield group (Figure 1c). In contrast, Lakey et al.¹⁴ and Hilling et al. found a significant negative correlation of longer cold storage duration prior to islet isolation and islet yield. Nano et al.³⁷ reported that good pancreas condition and weight also significantly impacted islet yield but did not clearly define the criteria for a good pancreas. Ponte et al.³⁸ evaluated the impact of pancreas quality regarding fat and texture and found a nonsignificant correlation with islet yield. Our analysis found that an inflamed and fibrotic pancreas yielded significantly fewer islets than an age-appropriate, histologically not further affected pancreas, thus confirming the data from Nano et al. (Table 2, Figure 3a–c). In contrast, we found no correlation between sample weight and islet yield (Figure 2c). In this context, Botticher et al.³⁹ reported that a pancreatic tissue weight greater than 2g is generally required to obtain approximately 1000 islets. While our study included specimens of variable and often smaller size, we observed that comparable or higher yields could still be achieved in selected cases. However, the variability in yield observed in our cohort supports the notion that tissue quantity remains an important, but not exclusive determinant of isolation success. Similarly, another study by Jung et al.⁴⁰ reported satisfactory islet isolation outcome using larger surgical specimens, further supporting importance of tissue quality and quantity. Compared with these studies, our approach demonstrated that even smaller and more heterogenous specimens obtained during routine surgery can serve as a viable source of research-grade islets, albeit with greater variability.

The islet functionality was tested and compared between low yield and high yield groups. Lakey et al.¹⁴ reported that islets from failed isolations showed poorer insulin secretion to high glucose stimulation during islet perfusion in vitro than islets from highly successful isolations. One of the main differences was higher basal insulin secretion in lower islet yields, supporting our findings that the low yield group had significantly higher basal insulin secretion than the high yield group, indicating suboptimal islet functionality (Figure 5b). When investigating the islet functionality of all isolations in our cohort, we found an increase in insulin secretion over time. As shown in Figure 5a, while basal insulin remains stable throughout the culture period, insulin secretion on high glucose stimulation increases with time. Unfortunately, we could not find similar data to support or refute these findings in the literature. However, a study by Niclauss et al.⁴¹ found that islets from young donors had better islet graft function, and that functionality decreased with increasing donor age. While in our analysis donor age and islet functionality were not significantly correlated in our analysis, duration of surgery showed a significant negative correlation (r = −0.47, P = 0.03, Figure 4f).

In addition to improved islet functionality, we also observed cells appearing around the islets over time (Figure 6). Villard et al.⁴² and Ebrahim et al.⁴³ have described morphologically similar cells, named ISCs, that adhere to the islets, have mesenchymal stem cell (MSC) properties such as CD73, CD90, and CD105 expression and secrete ECM proteins such as collagens I, IV, and VI, fibronectin, and laminins. These proteins are known to be present around and within the islets and to support islet preservation⁴⁴. CD90-positive cells, identified as stromal cells, appear around the islets (Figure 6). Based on other studies demonstrating the importance of islet co-culture and islet-ECM, we hypothesize that the presence of these cells affects islet functionality. Further studies to support or refute this hypothesis are ongoing.

Finally, we performed an incomplete purification by omitting gradient separation after isolation but performing hand picking before counting, staining, and culturing islets for further functional testing. The reasons for this were twofold: (1) to maximize islet yield from the small pancreas samples and (2) to see if this affected engraftment. Purification after isolation has become an indisputable step in islet isolation and is widely applied; therefore, few recent studies examine the impact of nonpurification. One review published in 1993 by Gores and Sutherland⁴⁵ discussed whether the reduced immunogenicity upon transplantation after purification is worth the price of islet loss and inferior islet engraftment outcomes. Moreover, several studies have shown that isolated islets with retained native ECM, mainly due to incomplete purification, show a reduced incidence of apoptosis and a significant improvement in islet function^46,47. Indeed, we believe that partial purification also adds to the presence of ISCs as an essential reason why human islets in our study perform better over time, a phenomenon we did not see with rat islets of Langerhans or with purified purchased human islets. Although a standardized isolation protocol was applied, minor modifications during the study period, such as the introduction of antibiotic preincubation, may have influenced isolation outcomes. While the adjustment reduced contamination rates, its potential impact on islet yield and functionality cannot be fully excluded. Furthermore, potential confounding factors, including underlying disease processes, surgical complexity, and tissue handling could not be fully controlled in this study design. The absence of multivariable analysis further limits the ability to account for interactions between variables. Future studies with larger and more homogenous cohorts will be necessary to validate these findings.

Conclusion

In conclusion, this study demonstrates the feasibility of isolating viable and functional human islets from small pancreatectomy specimens and suggests potential clinical and specimen-related factors that may influence isolation outcomes. Younger patient age, shorter surgical duration, and preserved pancreatic parenchyma were associated with higher islet yields, while longer surgical procedures negatively affected islet functionality. These findings support the feasibility of using surgical pancreatic specimens as a source of human islets for experimental and translational research.

Limitations

This study has several limitations. First, gradient purification of the isolated human islets was not performed, limiting conclusions regarding yield after additional purification steps; studies addressing this aspect are ongoing. Second, islet functionality was assessed using static glucose-stimulated insulin secretion assays, while dynamic perifusion assays will be required for more detailed functional characterization. In addition, in vivo functional validation using transplantation into streptozotocin (STZ)-induced diabetic immunodeficient mice represents an important gold-standard approach to assess islet quality. Demonstrating the ability of isolated islets to restore normoglycemia in such models would further strengthen confidence in their functional capacity. However, such experiments were beyond the scope of this study and should be addressed in future investigations. Finally, the cells surrounding the isolated islets were only characterized by immunostaining, and further studies are needed to better define their cellular identity. The statistical analysis in this study was primarily univariable due to the limited sample size and heterogeneity of the specimens, which precluded robust multivariable modeling. As a result, potential confounding factors could not be fully controlled, and the findings should be interpreted as exploratory and hypothesis-generating.

Footnotes

Acknowledgements

Dr Karl Herbert Hillebrandt, Dr Matthäus Felsenstein, Dr Simon Moosburner, and Dr Eriselda Keshi are participants in the BIH-Charité Clinician Scientist Program funded by the Charité – Universitätsmedizin Berlin and the Berlin Institute of Health. The author acknowledges the support of the Cluster of Excellence »Matters of Activity. Image Space Material« funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC 2025–390,648,296.

ORCID iDs

Simon Moosburner

Eriselda Keshi

Ethics Statement

Approval for islet isolation from pancreatic tissue obtained from surgical pancreatectomy specimens of patients undergoing a surgical procedure in the Department of Surgery, Charité – Universitätsmedizin Berlin, Germany, was given by the local ethical board on 9 August 2022 (Ethikkomission der Charité, EA2/154/22).

Consent Statement

Informed written consent from all patients involved in this study was present before isolation.

Author contributions

K.H.H. was involved during all parts of the project, discussed the results and proofread the manuscript. T.L. performed the experiments, the biochemical and histological analysis and contributed to writing the manuscript. L.H. helped establish the protocol, performed some experiments and proofread the manuscript. M.F. discussed the results and proofread the manuscript. S.M. helped with graphics and video and proofread the manuscript L.A.B. performed the staining of the pancreatic specimens and performed the analysis and the grading. A.A. supervised the staining of the pancreatic specimens and performed the grading. A.R.-S. discussed results with us, helped perform and evaluate the statistical evaluation and proofread the manuscript. T.M. discussed the results and proofread the manuscript. J.P. discussed the results and proofread the manuscript. I.M.S. developed the project idea, discussed the results, proofread the manuscript and is the guarantor of this study. E.K. developed the project idea, established the isolation protocol, performed experiments, supervised the whole project and wrote the manuscript. The author(s) read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability statement

Not applicable.

Declaration of AI and AI-assisted technologies in the writing process statement

During the preparation of this work the author used ChatGPT in order to maintain clarity and correct grammatical errors. After using this tool/service, the author reviewed and edited the content as needed and takes full responsibility for the content of the publication.

Statement of human and animal rights

This article does not contain any studies with human or animal subjects.

Statement of informed consent

There are no human subjects in this article and informed consent is not applicable.

Supplemental material

Supplemental material for this article is available online.

References

Shapiro

Pokrywczynska

Ricordi

Clinical pancreatic islet transplantation. Nat Rev Endocrinol. 2017;13:268–77.

Spaans

van Dijk

Groenier

Brand

PLP

Kleefstra

Bilo

HJG

. Healthcare reimbursement costs of children with type 1 diabetes in the Netherlands, a observational nationwide study (young dudes-4). BMC Endocr Disord. 2018;18(1):57.

Berney

Andres

Bellin

de Koning

EJP

Johnson

PRV

Kay

TWH

Lundgren

Rickels

Scholz

Stock

White

, et al. A worldwide survey of activities and practices in clinical islet of Langerhans transplantation. Transpl Int. 2022;35:10507.

Shapiro

Ricordi

Hering

Auchincloss

Lindblad

Robertson

Secchi

Brendel

Berney

Brennan

, et al. International trial of the Edmonton protocol for islet transplantation. N Engl J Med. 2006;355(13):1318–30.

Shapiro

AM.

Islet transplantation in type 1 diabetes: ongoing challenges, refined procedures, and long-term outcome. Rev Diabet Stud. 2012;9(4):385–406.

Citro

Ott

HC.

Can we re-engineer the endocrine pancreas?

Curr Diab Rep. 2018;18(11):122.

Keshi

Sauer

Hillebrandt

KH.

Engineering an endocrine neo-pancreas. Decellularized extracellular matrix: characterization, fabrication and applications. In: Yamaoka

Hoshiba

, editors. Decellularized Extracellular Matrix: Characterization, Fabrication and Applications. Cambridge: The Royal Society of Chemistry; 2020, p. 237–58.

Hillebrandt

Everwien

Haep

Keshi

Pratschke

Sauer

IM.

Strategies based on organ decellularization and recellularization. Transpl Int. 2019;32(6):571–85.

Everwien

Keshi

Hillebrandt

Ludwig

Weinhart

Tang

Beierle

Napierala

Gassner

Seiffert

Moosburner

, et al. Engineering an endothelialized, endocrine neo-pancreas: evaluation of islet functionality in an ex vivo model. Acta Biomater. 2020;117:213–25.

10.

Napierala

Hillebrandt

Haep

Tang

Tintemann

Gassner

Noesser

Everwien

Seiffert

Kluge

, et al. Engineering an endocrine neo-pancreas by repopulation of a decellularized rat pancreas with islets of langerhans. Sci Rep. 2017;7:41777.

11.

Citro

Moser

Dugnani

Rajab

Ren

Evangelista-Leite

Charest

Peloso

Podesser

Manenti

Pellegrini

, et al. Biofabrication of a vascularized islet organ for type 1 diabetes. Biomaterials. 2019;199:40–51.

12.

Mueller

Balamurugan

Cline

Pongratz

Hooper

Weegman

Kitzmann

Taylor

Graham

Schuurman

Papas

KK.

Differences in glucose-stimulated insulin secretion in vitro of islets from human, nonhuman primate, and porcine origin. Xenotransplantation. 2013;20(2): 75–81.

13.

Davalli

Ogawa

Scaglia

Hollister

Bonner-Weir

Weir

GC.

Function, mass, and replication of porcine and rat islets transplanted into diabetic nude mice. Diabetes. 1995;44(1):104–11.

14.

Lakey

Warnock

Rajotte

Suarez-Alamazor

Shapiro

Kneteman

NM.

Variables in organ donors that affect the recovery of human islets of langerhans. Transplantation. 1996;61(7):1047–53.

15.

Kin

Shapiro

AM.

Surgical aspects of human islet isolation. Islets. 2010;2(5):265–73.

16.

Ludwig

Ziegler

Schally

Richter

Steffen

Jabs

Funk

Brendel

Block

Ehrhart-Bornstein

, et al. Agonist of growth hormone-releasing hormone as a potential effector for survival and proliferation of pancreatic islets. Proc Natl Acad Sci U S A. 2010;107(28):12623–28.

17.

Schawkat

Eshmuminov

Lenggenhager

Endhardt

Vrugt

Boss

Petrowsky

Clavien

Reiner

CS.

Preoperative evaluation of pancreatic fibrosis and lipomatosis: correlation of magnetic resonance findings with histology using magnetization transfer imaging and multigradient echo magnetic resonance imaging. Invest Radiol. 2018;53(12):720–27.

18.

Chaouch

Leon

Cassese

Aguilhon

Khayat

Panaro

Total pancreatectomy with intraportal islet autotransplantation for pancreatic malignancies: a literature overview. Expert Opin Biol Ther. 2022;22(4):491–97.

19.

Jablonska

Mrowiec

Total pancreatectomy with autologous islet cell transplantation-the current indications. J Clin Med. 2021;10(12):2373.

20.

Ricordi

Lacy

Finke

Olack

Scharp

DW.

Automated method for isolation of human pancreatic islets. Diabetes. 1988;37(4):413–20.

21.

Solimena

Schulte

Marselli

Ehehalt

Richter

Kleeberg

Mziaut

Knoch

Parnis

Bugliani

Siddiq

, et al. Systems biology of the IMIDIA biobank from organ donors and pancreatectomised patients defines a novel transcriptomic signature of islets from individuals with type 2 diabetes. Diabetologia. 2018;61(3):641–57.

22.

Marchetti

Suleiman

Marselli

Organ donor pancreases for the study of human islet cell histology and pathophysiology: a precious and valuable resource. Diabetologia. 2018;61(4): 770–74.

23.

Barovic

Distler

Schöniger

Radisch

Aust

Weitz

Ibberson

Schulte

Solimena

Metabolically phenotyped pancreatectomized patients as living donors for the study of islets in health and diabetes. Mol Metab. 2019; S27:S1–6.

24.

Wigger

Barovic

Brunner

Marzetta

Schöniger

Mehl

Kipke

Friedland

Burdet

Kessler

Lesche

, et al. Multi-omics profiling of living human pancreatic islet donors reveals heterogeneous beta cell trajectories towards type 2 diabetes. Nat Metab. 2021;3(7):1017–31.

25.

Gloyn

Ibberson

Marchetti

Powers

Rorsman

Sander

Solimena

Every islet matters: improving the impact of human islet research. Nat Metab. 2022;4(8):970–77.

26.

Kin

Contribution of a single islet transplant program to basic researchers in North America, Europe, and Asia through distributing human islets. OBM Transplant. 2024;8(2):212.

27.

Hilling

Bouwman

Terpstra

Marang-van de Mheen

PJ.

Effects of donor-, pancreas-, and isolation-related variables on human islet isolation outcome: a systematic review. Cell Transplant. 2014;23(8):921–28.

28.

Förster

Liu

Adam

Schareck

Hopt

UT.

Islet autotransplantation combined with pancreatectomy for treatment of pancreatic adenocarcinoma: a case report. Transplant Proc. 2004;36(4):1125–26.

29.

Ris

Niclauss

Morel

Demuylder-Mischler

Muller

Meier

Genevay

Bosco

Berney

Islet autotransplantation after extended pancreatectomy for focal benign disease of the pancreas. Transplantation. 2011;91(8):895–901.

30.

Balzano

Maffi

Nano

Zerbi

Venturini

Melzi

Mercalli

Magistretti

Scavini

Castoldi

, et al. Extending indications for islet autotransplantation in pancreatic surgery. Ann Surg. 2013;258(2):210–18.

31.

Tanhehco

Weisberg

Schwartz

Pancreatic islet autotransplantation for nonmalignant and malignant indications. Transfusion. 2016;56(3):761–70.

32.

Wahoff

Papalois

Najarian

Kendall

Farney

Leone

Jessurun

Dunn

Robertson

Sutherland

DE.

Autologous islet transplantation to prevent diabetes after pancreatic resection. Ann Surg. 1995;222(4):562–75.

33.

Jin

Kim

Jung

Choi

Jang

Lee

Kim

Lee

, et al. Diabetes-free survival in patients who underwent islet autotransplantation after 50% to 60% distal partial pancreatectomy for benign pancreatic tumors. Transplantation. 2013;95(11):1396–403.

34.

Dalla Valle

Mancini

Crafa

Passalacqua

. Pancreatic carcinoma recurrence in the remnant pancreas after a pancreaticoduodenectomy. JOP. 2006;7(5):473–77.

35.

Muratore

Zeng

Korc

McElyea

Wilhelm

Bellin

Beilman

Metastatic pancreatic adenocarcinoma after total pancreatectomy islet autotransplantation for chronic pancreatitis. Am J Transplant. 2016;16(9):2747–52.

36.

Andreou

Klein

Schmuck

Lee

Sinn

Denecke

Pratschke

Bahra

Incidence and oncological implications of previously undetected tumor multicentricity following pancreaticoduodenectomy for pancreatic adenocarcinoma in patients undergoing salvage pancreatectomy. Anticancer Res. 2017;37(9):5269–75.

37.

Nano

Clissi

Melzi

Calori

Maffi

Antonioli

Marzorati

Aldrighetti

Freschi

Grochowiecki

Socci

, et al. Islet isolation for allotransplantation: variables associated with successful islet yield and graft function. Diabetologia. 2005;48(5):906–12.

38.

Ponte

Pileggi

Messinger

Alejandro

Ichii

Baidal

Khan

Ricordi

Goss

Alejandro

Toward maximizing the success rates of human islet isolation: influence of donor and isolation factors. Cell Transplant. 2007;16(6):595–607.

39.

Botticher

Sturm

Ehehalt

Knoch

Kersting

Grutzmann

Baretton

Solimena

Saeger

HD.

Isolation of human islets from partially pancreatectomized patients. J Vis Exp. 2011;53:2962.

40.

Jung

Choi

Kim

Lee

Jang

Lee

Jee

Ahn

Lee

, et al. A better yield of islet cell mass from living pancreatic donors compared with cadaveric donors. Clin Transplant. 2007;21(6):738–43.

41.

Niclauss

Bosco

Morel

Demuylder-Mischler

Brault

Milliat-Guittard

Colin

Parnaud

Muller

Giovannoni

, et al. Influence of donor age on islet isolation and transplantation outcome. Transplantation. 2011;91(3):360–66.

42.

Villard

Armanet

Couderc

Bony

Moreaux

Noel

De Vos

Klein

Veyrune

Wojtusciszyn

Characterization of immortalized human islet stromal cells reveals a msc-like profile with pancreatic features. Stem Cell Res Ther. 2020;11(1):158.

43.

Ebrahim

Kondratyev

Artyuhov

Timofeev

Gurskaya

Andrianov

Izrailov

Volchkov

Dyuzheva

Kopantseva

, et al. Human pancreatic islet-derived stromal cells reveal combined features of mesenchymal stromal cells and pancreatic stellate cells. Stem Cell Res Ther. 2024;15(1):351.

44.

Daoud

Petropavlovskaia

Rosenberg

Tabrizian

The effect of extracellular matrix components on the preservation of human islet function in vitro. Biomaterials. 2010;31(7):1676–82.

45.

Gores

Sutherland

DE.

Pancreatic islet transplantation: is purification necessary?

Am J Surg. 1993;166(5):538–42.

46.

Ricordi

Alejandro

Rilo

Carroll

Tzakis

Starzl

Mintz

DH.

Long-term in vivo function of human mantled islets obtained by incomplete pancreatic dissociation and purification. Transplant Proc. 1995;27(6):3382.

47.

Thomas

Contreras

Bilbao

Ricordi

Curiel

Thomas

JM.

Anoikis, extracellular matrix, and apoptosis factors in isolated cell transplantation. Surgery. 1999;126(2):299–304.

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