Proposal for a New Pathologic Prognostic Index After Neoadjuvant Chemotherapy in Pancreatic Ductal Adenocarcinoma (PINC).

BACKGROUND: Limited information is available on the relevant prognostic variables after surgery for patients with pancreatic ductal adenocarcinoma (PDAC) subjected to neoadjuvant chemotherapy (NACT). NACT is known to induce a spectrum of histological changes in PDAC. Different grading regression systems are currently available; unfortunately, they lack precision and accuracy. We aimed to identify a new quantitative prognostic index based on tumor morphology. PATIENTS AND METHODS: The study population was composed of 69 patients with resectable or borderline resectable PDAC treated with preoperative NACT (neoadjuvant group) and 36 patients submitted to upfront surgery (upfront-surgery group). A comprehensive histological assessment on hematoxylin and eosin (H&E) stained sections evaluated 20 morphological parameters. The association between patient survival and morphological variables was evaluated to generate a prognostic index. RESULTS: The distribution of morphological parameters evaluated was significantly different between upfront-surgery and neoadjuvant groups, demonstrating the effect of NACT on tumor morphology. On multivariate analysis for patients that received NACT, the predictors of shorter overall survival (OS) and disease-free survival (DFS) were perineural invasion and lymph node ratio. Conversely, high stroma to neoplasia ratio predicted longer OS and DFS. These variables were combined to generate a semiquantitative prognostic index based on both OS and DFS, which significantly distinguished patients with poor outcomes from those with a good outcome. Bootstrap analysis confirmed the reproducibility of the model. CONCLUSIONS: The pathologic prognostic index proposed is mostly quantitative in nature, easy to use, and may represent a reliable tumor regression grading system to predict patient outcomes after NACT followed by surgery for PDAC.

High-protein meals require 30% additional insulin to prevent delayed postprandial hyperglycaemia.

AIM: To determine the amount of additional insulin required for a high-protein meal to prevent postprandial hyperglycaemia in individuals with type 1 diabetes using insulin pump therapy. METHODS: In this randomized cross-over study, 26 participants aged 8-40 years, HbA1c < 65 mmol/mol (8.1%), received a 50 g protein, 30 g carbohydrate, low-fat (< 1 g) breakfast drink over five consecutive days at home. A standard insulin dose (100%) was compared with additional doses of 115, 130, 145 and 160% for the protein, in randomized order. Doses were commenced 15-min pre-drink and delivered over 3 h using a combination bolus with 65% of the standard dose given up front. Postprandial glycaemia was assessed by 4 h of continuous glucose monitoring. RESULTS: The 100% dosing resulted in postprandial hyperglycaemia. From 120 min, ≥ 130% doses resulted in significantly lower postprandial glycaemic excursions compared with 100% (P < 0.05). A 130% dose produced a mean (sd) glycaemic excursion that was 4.69 (2.42) mmol/l lower than control, returning to baseline by 4 h (P < 0.001). From 120 min, there was a significant increase in the risk of hypoglycaemia compared with control for 145% [odds ratio (OR) 25.4, 95% confidence interval (CI) 5.5-206; P < 0.001) and 160% (OR 103, 95% CI 19.2-993; P < 0.001). Some 81% (n = 21) of participants experienced hypoglycaemia following a 160% dose, whereas 58% (n = 15) experienced hypoglycaemia following a 145% dose. There were no hypoglycaemic events reported with 130%. CONCLUSIONS: The addition of 30% more insulin to a standard dose for a high-protein meal, delivered using a combination bolus, improves postprandial glycaemia without increasing the risk of hypoglycaemia.

Young children, adolescent girls and women with type 1 diabetes are more overweight and obese than reference populations, and this is associated with increased cardiovascular risk factors.

AIM: Overweight and obesity are frequently reported in young persons with type 1 diabetes, however its relative magnitude in comparison to the general population is not well understood. This study compared the prevalence of overweight and obesity in young persons with type 1 diabetes to a reference population and explored possible associated factors, including gender, age, HbA1c , insulin regimen, age at diagnosis, diabetes duration, socio-economic status and cardiovascular disease risk factors. METHODS: A cross-sectional review was undertaken of data collected from youth (3-17 years) in 2016 and young adults (18-30 years) in 2015 with a diagnosis of type 1 diabetes for > 3 months attending diabetes centres in Newcastle, Australia. Rates of overweight and obesity were compared with matched population survey results. RESULTS: Data from 308 youth and 283 young adults were included. In girls, significantly higher prevalence of overweight and obesity were seen in the 5-8 (43% vs. 18%), 13-16 (41% vs. 27%), 18-24 (46% vs. 34%) and 25-30 (60% vs. 43%) years age groups; whereas in boys increased prevalence was observed in the 5-8 years age group only (41% vs. 18%). Rates of overweight and obesity increased with age across sexes. In youth, BMI standard deviation score was correlated with socio-economic status, insulin regimen, blood pressure and blood lipids (P < 0.05). In adults, BMI was positively associated with blood pressure, and longer diabetes duration (P < 0.02). CONCLUSIONS: Overweight and obesity are over-represented in young persons with type 1 diabetes, particularly girls. As overweight is associated with other cardiovascular disease markers early intervention is paramount.

Impact of dietary protein on postprandial glycaemic control and insulin requirements in Type 1 diabetes: a systematic review.

AIM: Postprandial hyperglycaemia is a challenge for people living with Type 1 diabetes. In addition to carbohydrate, dietary protein has been shown to contribute to postprandial glycaemic excursions with recommendations to consider protein when calculating mealtime insulin doses. The aim of this review is to identify and synthesize evidence about the glycaemic impact of dietary protein and insulin requirements for individuals with Type 1 diabetes. METHODS: A systematic literature search of relevant biomedical databases was performed to identify research on the glycaemic impact of dietary protein when consumed alone, and in combination with other macronutrients in individuals with Type 1 diabetes. RESULTS: The review included 14 published studies dated from 1992 to 2018, and included studies that researched the impact of protein alone (n = 2) and protein in a mixed meal (n = 12). When protein was consumed alone a glycaemic effect was not seen until ≥ 75 g. In a carbohydrate-containing meal ≥ 12.5 g of protein impacted the postprandial glucose. Inclusion of fat in a high-protein meal enhanced the glycaemic response and further increased insulin requirements. The timing of the glycaemic effect from dietary protein ranged from 90 to 240 min. Studies indicate that the postprandial glycaemic response and insulin requirements for protein are different when protein is consumed alone or with carbohydrate and/or fat. CONCLUSIONS: This systematic review provides evidence that dietary protein contributes to postprandial glycaemic excursions and insulin requirements. These insights have important implications for the education of people with Type 1 diabetes and highlights the need for more effective insulin dosing strategies for mixed macronutrient meals.

The ups and downs of low-carbohydrate diets in the management of Type 1 diabetes: a review of clinical outcomes.

Dietary management has been a mainstay of care in Type 1 diabetes since before the discovery of insulin when severe carbohydrate restriction was advocated. The use of insulin facilitated re-introduction of carbohydrate into the diet. Current management guidelines focus on a healthy and varied diet with consideration of glycaemic load, protein and fat. As a result of frustration with glycaemic outcomes, low-carbohydrate diets have seen a resurgence in popularity. To date, low-carbohydrate diets have not been well studied in the management of Type 1 diabetes. Studies looking at glycaemic outcomes from low-carbohydrate diets have largely been cross-sectional, without validated dietary data and with a lack of control groups. The participants have been highly motivated self-selected individuals who follow intensive insulin management practices, including frequent blood glucose monitoring and additional insulin corrections with tight glycaemic targets. These confounders limit the ability to determine the extent of the impact of dietary carbohydrate restriction on glycaemic outcomes. Carbohydrate-containing foods including grains, fruit and milk are important sources of nutrients. Hence, low-carbohydrate diets require attention to vitamin and energy intake to avoid micronutrient deficiencies and growth issues. Adherence to restricted diets is challenging and can have an impact on social normalcy. In individuals with Type 1 diabetes, adverse health risks such as diabetic ketoacidosis, hypoglycaemia, dyslipidaemia and glycogen depletion remain clinical concerns. In the present paper, we review studies published to date and provide clinical recommendations for ongoing monitoring and support for individuals who choose to adopt a low-carbohydrate diet. Strategies to optimize postprandial glycaemia without carbohydrate restriction are presented.

Dietary protein affects both the dose and pattern of insulin delivery required to achieve postprandial euglycaemia in Type 1 diabetes: a randomized trial.

AIM: To quantify the insulin requirement for a high-protein meal compared with a low-protein meal, controlling for carbohydrate and fat content. METHODS: In this crossover study, young people with Type 1 diabetes were randomized to consume a high- (60 g) or low-protein meal (5 g), each containing 30 g carbohydrate and 8 g fat. A variation of the insulin clamp technique was used to determine the insulin requirements to maintain euglycaemia for the following 5 h. RESULTS: A total of 11 participants (mean ± sd age 16.5 ± 2.7 years, HbA1c 52 ± 8.7 mmol/mol [6.9 ± 0.8%], diabetes duration 6.9±5.1 years) completed the study. The mean insulin requirements for the high-protein meal were higher than for the low-protein meal [10.3 (CI 8.2, 12.57) vs 6.7 units (CI 4.7, 8.8); P=0.001], with inter-individual requirements ranging from 0.9 to six times the low-protein meal requirement. Approximately half the additional insulin [1.1 units/h (CI 0.5, 1.8; P=0.001)] was given in the first 2 h, compared with an additional 0.5 units/h (CI -0.2, 1.2; P=0.148) in the second 2 h and 0.1 units (CI -0.6, 0.8; P=0.769) in the final hour. CONCLUSIONS: A high-protein meal requires ~50% more insulin to maintain euglycaemia than a low-protein meal that contains the same quantity of carbohydrate. The majority is required within the first 2 h. Inter-individual differences exist in insulin requirements for dietary protein.

A randomized comparison of three prandial insulin dosing algorithms for children and adolescents with Type 1 diabetes.

AIM: To compare systematically the impact of two novel insulin-dosing algorithms (the Pankowska Equation and the Food Insulin Index) with carbohydrate counting on postprandial glucose excursions following a high fat and a high protein meal. METHODS: A randomized, crossover trial at two Paediatric Diabetes centres was conducted. On each day, participants consumed a high protein or high fat meal with similar carbohydrate amounts. Insulin was delivered according to carbohydrate counting, the Pankowska Equation or the Food Insulin Index. Subjects fasted for 5 h following the test meal and physical activity was standardized. Postprandial glycaemia was measured for 300 min using continuous glucose monitoring. RESULTS: 33 children participated in the study. When compared to carbohydrate counting, the Pankowska Equation resulted in lower glycaemic excursion for 90-240 min after the high protein meal (p < 0.05) and lower peak glycaemic excursion (p < 0.05). The risk of hypoglycaemia was significantly lower for carbohydrate counting and the Food Insulin Index compared to the Pankowska Equation (OR 0.76 carbohydrate counting vs. the Pankowska Equation and 0.81 the Food Insulin Index vs. the Pankowska Equation). There was no significant difference in glycaemic excursions when carbohydrate counting was compared to the Food Insulin Index. CONCLUSION: The Pankowska Equation resulted in reduced postprandial hyperglycaemia at the expense of an increase in hypoglycaemia. There were no significant differences when carbohydrate counting was compared to the Food Insulin Index. Further research is required to optimize prandial insulin dosing.

Optimizing the combination insulin bolus split for a high-fat, high-protein meal in children and adolescents using insulin pump therapy.

AIMS: To determine the optimum combination bolus split to maintain postprandial glycaemia with a high-fat and high-protein meal in young people with Type 1 diabetes. METHODS: A total of 19 young people (mean age 12.9 ± 6.7 years) participated in a randomized, repeated-measures trial comparing postprandial glycaemic control across six study conditions after a high-fat and high-protein meal. A standard bolus and five different combination boluses were delivered over 2 h in the following splits: 70/30 = 70% standard /30% extended bolus; 60/40=60% standard/40% extended bolus; 50/50=50% standard/50% extended bolus; 40/60=40% standard/60% extended bolus; and 30/70=30% standard/70% extended bolus. Insulin dose was determined using the participant's optimized insulin:carbohydrate ratio. Continuous glucose monitoring was used to assess glucose excursions for 6 h after the test meal. RESULTS: Standard bolus and combination boluses 70/30 and 60/40 controlled the glucose excursion up to 120 min. From 240 to 300 min after the meal, the glucose area under the curve was significantly lower for combination bolus 30/70 compared with standard bolus (P=0.004). CONCLUSIONS: High-fat and high-protein meals require a ≥60% insulin:carbohydrate ratio as a standard bolus to control the initial postprandial rise. Additional insulin at an insulin:carbohydrate ratio of up to 70% is needed in the extended bolus for a high fat and protein meal to prevent delayed hyperglycaemia.

Increasing the protein quantity in a meal results in dose-dependent effects on postprandial glucose levels in individuals with Type 1 diabetes mellitus.

AIM: To determine the glycaemic impact of increasing protein quantities when consumed with consistent amounts of carbohydrate in individuals with Type 1 diabetes on intensive insulin therapy. METHODS: Participants with Type 1 diabetes [aged 10-40 years, HbA1c ≤ 64 mmol/mol (8%), BMI ≤ 91st percentile] received a 30-g carbohydrate (negligible fat) test drink daily over 5 days in randomized order. Protein (whey isolate 0 g/kg carbohydrate, 0 g/kg lipid) was added in amounts of 0 (control), 12.5, 25, 50 and 75 g. A standardized dose of insulin was given for the carbohydrate. Postprandial glycaemia was assessed by 5 h of continuous glucose monitoring. RESULTS: Data were collected from 27 participants (15 male). A dose-response relationship was found with increasing amount of protein. A significant negative relationship between protein dose and mean excursion was seen at the 30- and 60-min time points (P = 0.007 and P = 0.002, respectively). No significant relationship was seen at the 90- and 120-min time points. Thereafter, the dose-response relationship inverted, such that there was a significant positive relationship for each of the 150-300-min time points (P < 0.004). Mean glycaemic excursions were significantly greater for all protein-added test drinks from 150 to 300 min (P < 0.005) with the 75-g protein load, resulting in a mean excursion that was 5 mmol/l higher when compared with the control test drink (P < 0.001). CONCLUSIONS: Increasing protein quantity in a low-fat meal containing consistent amounts of carbohydrate decreases glucose excursions in the early (0-60-min) postprandial period and then increases in the later postprandial period in a dose-dependent manner.

Influence of dietary protein on postprandial blood glucose levels in individuals with Type 1 diabetes mellitus using intensive insulin therapy.

AIM: To determine the effects of protein alone (independent of fat and carbohydrate) on postprandial glycaemia in individuals with Type 1 diabetes mellitus using intensive insulin therapy. METHODS: Participants with Type 1 diabetes mellitus aged 7-40 years consumed six 150 ml whey isolate protein drinks [0 g (control), 12.5, 25, 50, 75 and 100] and two 150 ml glucose drinks (10 and 20 g) without insulin, in randomized order over 8 days, 4 h after the evening meal. Continuous glucose monitoring was used to assess postprandial glycaemia. RESULTS: Data were collected from 27 participants. Protein loads of 12.5 and 50 g did not result in significant postprandial glycaemic excursions compared with control (water) throughout the 300 min study period (P > 0.05). Protein loads of 75 and 100 g resulted in lower glycaemic excursions than control in the 60-120 min postprandial interval, but higher excursions in the 180-300 min interval. In comparison with 20 g glucose, the large protein loads resulted in significantly delayed and sustained glucose excursions, commencing at 180 min and continuing to 5 h. CONCLUSIONS: Seventy-five grams or more of protein alone significantly increases postprandial glycaemia from 3 to 5 h in people with Type 1 diabetes mellitus using intensive insulin therapy. The glycaemic profiles resulting from high protein loads differ significantly from the excursion from glucose in terms of time to peak glucose and duration of the glycaemic excursion. This research supports recommendations for insulin dosing for large amounts of protein.

In children using intensive insulin therapy, a 20-g variation in carbohydrate amount significantly impacts on postprandial glycaemia.

AIM: To determine if an insulin dose calculated for a meal containing 60 g carbohydrate maintains postprandial glycaemic control for meals containing 40, 50, 70 or 80 g carbohydrate. METHODS: Thirty-four young people (age range 8.5-17.7 years) using intensive insulin therapy consumed five test breakfasts with equivalent fat, protein and fibre contents but differing carbohydrate quantities (40, 50, 60, 70 and 80 g of carbohydrate). The preprandial insulin dose was the same for each meal, based on the subject's usual insulin:carbohydrate ratio for 60 g carbohydrate. Continuous glucose monitoring was used to monitor postprandial glucose over 180 min. RESULTS: The 40-g carbohydrate meal resulted in significantly more hypoglycaemia than the other meals (P = 0.003). There was a one in three chance of hypoglycaemia between 120 and 180 min if an insulin dose for 60 g carbohydrate was given for 40 g carbohydrate. The glucose levels of subjects on the 80-g meal were significantly higher than the 60- and 70-g carbohydrate meals at all time points between 150 and 180 min (P < 0.01). Subjects consuming the 80-g meal were more likely to have significant hyperglycaemia (blood glucose levels ≥ 12 mmol/l) compared with the other meals (P < 0.001). CONCLUSIONS: In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g carbohydrate results in postprandial hypoglycaemia or hyperglycaemia for meals containing 40 and 80 g carbohydrate. To calculate mealtime insulin in order to maintain postprandial control, carbohydrate estimations should be within 10 g of the actual meal carbohydrate.

Analysis of Brca1-deficient mouse mammary glands reveals reciprocal regulation of Brca1 and c-kit.

Disruption of the breast cancer susceptibility gene Brca1 results in defective lobular-alveolar development in the mammary gland and a predisposition to breast tumourigenesis in humans and in mice. Recent evidence suggests that BRCA1 loss in humans is associated with an expansion of the luminal progenitor cell compartment in the normal breast and tumours with a luminal progenitor-like expression profile. To further investigate the role of BRCA1 in the mammary gland, we examined the consequences of Brca1 loss in mouse mammary epithelial cells in vitro and in vivo. Here, we show that Brca1 loss is associated with defective morphogenesis of SCp2 and HC11 mouse mammary epithelial cell lines and that in the MMTV-Cre Brca1(Co/Co) mouse model of Brca1 loss, there is an accumulation of luminal progenitor (CD61(+)CD29(lo)CD24(+)) cells during pregnancy. By day 1 of lactation, there are marked differences in the expression of 1379 genes, with most significantly altered pathways and networks, including lactation, the immune response and cancer. One of the most differentially expressed genes was the luminal progenitor marker, c-kit. Immunohistochemical analysis revealed that the increase in c-kit levels is associated with an increase in c-kit positivity. Interestingly, an inverse association between Brca1 and c-kit expression was also observed during mammary epithelial differentiation, and small interfering RNA-mediated knockdown of Brca1 resulted in a significant increase in c-kit mRNA levels. We found no evidence that c-kit plays a direct role in regulating differentiation of HC11 cells, suggesting that Brca1-mediated induction of c-kit probably contributes to Brca1-associated tumourigenesis via another cellular process, and that c-kit is likely to be a marker rather than a mediator of defective lobular-alveolar development resulting from Brca1 loss.

Can children with Type 1 diabetes and their caregivers estimate the carbohydrate content of meals and snacks?

AIMS: Carbohydrate (CHO) counting allows children with Type 1 diabetes to adjust mealtime insulin dose to carbohydrate intake. Little is known about the ability of children to count CHO and whether a particular method for assessing CHO quantity is better than others. We investigated how accurately children and their caregivers estimate carbohydrate, and whether counting in gram increments improves accuracy compared with CHO portions or exchanges. METHODS: One hundred and two children and adolescents (age range 8.3-18.1 years) on intensive insulin therapy and 110 caregivers independently estimated the CHO content of 17 standardized meals (containing 8-90 g CHO), using whichever method of carbohydrate quantification they had been taught (gram increments, 10-g portions or 15-g exchanges). RESULTS: Seventy-three per cent (n = 2530) of all estimates were within 10-15 g of actual CHO content. There was no relationship between the mean percentage error and method of carbohydrate counting or glycated haemoglobin (HbA(1c)) (P > 0.05). Mean gram error and meal size were negatively correlated (r = -0.70, P < 0.0001). The longer children had been CHO counting the greater the mean percentage error (r = 0.173, P = 0.014). Core foods in non-standard quantities were most frequently inaccurately estimated, while individually labelled foods were most often accurately estimated. CONCLUSIONS: Children with Type 1 diabetes and their caregivers can estimate the carbohydrate content of meals with reasonable accuracy. Teaching CHO counting in gram increments did not improve accuracy compared with CHO portions or exchanges. Large meals tended to be underestimated and snacks overestimated. Repeated age-appropriate education appears necessary to maintain accuracy in carbohydrate estimations.

Children and adolescents on intensive insulin therapy maintain postprandial glycaemic control without precise carbohydrate counting.

AIMS: Carbohydrate (CHO) quantification is used to adjust pre-meal insulin in intensive insulin regimens. However, the precision in CHO quantification required to maintain postprandial glycaemic control is unknown. We determined the effect of a +/-10-g variation in CHO amount, with an individually calculated insulin dose for 60 g CHO, on postprandial glycaemic control. METHODS: Thirty-one children and adolescents (age range 9.5-16.8 years), 17 using continuous subcutaneous insulin infusion (CSII) and 14 using multiple daily injections (MDI), participated. Each subject consumed test lunches of equal macronutrient content, differing only in carbohydrate quantity (50, 60, 70 g CHO), in random order on three consecutive days. For each participant, the insulin dose was the same for each meal, based on their usual insulin : CHO ratio for 60 g CHO. Activity was standardized. Continuous glucose monitoring was used. RESULTS: The CSII and MDI subjects demonstrated no difference in postprandial blood glucose levels (BGLs) for comparable carbohydrate loads (P > 0.05). The 10-g variations in CHO quantity resulted in no differences in BGLs or area under the glucose curves for 2.5 h (P > 0.05). Hypoglycaemic episodes were not significantly different (P = 0.32). The 70-g meal produced higher glucose excursions after 2.5 h, with a maximum difference of 1.9 mmol/l at 3 h (P = 0.01), but the BGLs remained within international postprandial targets. CONCLUSIONS: In patients using intensive insulin therapy, an individually calculated insulin dose for 60 g of carbohydrate maintains postprandial BGLs for meals containing between 50 and 70 g of carbohydrate. A single mealtime insulin dose will cover a range in carbohydrate amounts without deterioration in postprandial control.

The mitogenic signaling pathway for fibroblast growth factor-2 involves the tyrosine phosphorylation of cyclin D2 in MCF-7 human breast cancer cells.

Fibroblast growth factor-2 (FGF-2) is mitogenic for the human breast cancer cell line MCF-7; here we investigate some of the signaling pathways subserving this activity. FGF-2 stimulation of MCF-7 cells resulted in a global increase of intracellular tyrosine phosphorylation of proteins, particularly FGF receptor substrate-2, the protooncogene product Src and the mitogen-activated protein kinase (MAP kinase) cascade. A major increase in the tyrosine phosphorylation of a 30-kDa protein species was also found. This protein was identified as cyclin D2 by mass spectrometry after trypsin digestion. Immunoprecipitation of cyclin D2 and immunoblotting with anti-phosphotyrosine antibodies confirmed that the tyrosine phosphorylation of cyclin D2 was indeed induced by FGF-2 stimulation. In addition, pharmacological inhibition of Src (with herbimycin A and PP2), and of the MAP kinase cascade (with PD98059), confirmed that Src activity is required for the FGF-2-induced phosphorylation of cyclin D2 whereas MAP kinase activity is not. Thus, tyrosine phosphorylation of cyclin D2 may be a key regulatory target for FGF-2 signaling.

The proliferative and migratory activities of breast cancer cells can be differentially regulated by heparan sulfates.

To explore how heparan sulfate (HS) controls the responsiveness of the breast cancer cell lines MCF-7 and MDA-MB-231 to fibroblast growth factors (FGFs), we have exposed them to HS preparations known to have specificity for FGF-1 (HS glycosaminoglycan (HSGAG A)) or FGF-2 (HSGAGB). Proliferation assays confirmed that MCF-7 cells were highly responsive to FGF-2 complexed with GAGB, whereas migration assays indicated that FGF-1/HSGAGA combinations were stimulatory for the highly invasive MDA-MB-231 cells. Quantitative polymerase chain reaction for the levels of FGF receptor (FGFR) isoforms revealed that MCF-7 cells have greater levels of FGFR1 and that MDA-MB-231 cells have greater relative levels of FGFR2. Cross-linking demonstrated that FGF-2/HSGAGB primarily activated FGFR1, which in turn up-regulated the activity of mitogen-activated protein kinase; in contrast, FGF-1/HSGAGA led to the phosphorylation of equal proportions of both FGFR1 and FGFR2, which in turn led to the up-regulation of Src and p125(FAK). MDA-MB-231 cells were particularly responsive to vitronectin substrates in the presence of FGF-1/HSGAGA, and blocking antibodies established that they used the alpha(v)beta(3) integrin to bind to it. These results suggest that the clustering of particular FGFR configurations on breast cancer cells induced by different HS chains leads to distinct phenotypic behaviors.

Lysosomotropic agents and inhibitors of cellular transglutaminase stimulate dome formation, a differentiated characteristic of MDCK kidney epithelial cell cultures.

Dome formation is a manifestation of transepithelial fluid transport in cell culture, a differentiated characteristic of transporting epithelia. A dramatic increase in numbers of domes in confluent MDCK kidney epithelial cell cultures was noted after addition of Friend cell inducers such as hexamethylane bisacetamide (HMBA) (Lever, 1979b). In the present study, we show that primary amines such as methylamine, ethylamine, and dansyl cadaverine also stimulate dome formation. These compounds largely prevented the marked decrease in numbers of spontaneously occurring domes which occurred when cultures were switched from medium containing 10% serum to medium containing serum concentrations below 0.2%. Many of these primary amines are not only lysosomotropic agents but also potent inhibitors of transglutaminase activity when assayed in MDCK cell extracts, at concentrations correlating with those effective in stimulation of dome formation. Other lysosomotropic agents such as chloroquine and secondary and tertiary amines stimulated dome formation yet did not inhibit transglutaminase. Induction of domes by HMBA differed in several properties from that stimulated by amines and did not involve fluctuations in transglutaminase activity. These findings suggest that lysosomal functions modulate serum stimulation of dome formation in epithelial cells by a pathway distinct from that triggered by HMBA.

Rubber solvent: a clastogenic agent that fails to induce sister-chromatid exchanges.

Rubber solvent was tested for its ability to induce chromosome aberrations and sister-chromatid exchanges in human whole blood cultures. Following exposure to relatively low rubber solvent concentrations (0.0125% and greater) significant increases in the frequencies of chromatid gaps and breaks were observed. At higher rubber-solvent concentrations (0.05% and greater) there were also significant increases in the frequency of chromosome breaks. In contrast to the increase in chromosome aberrations following rubber-solvent exposure, rubber-solvent concentrations up to the toxic level failed to produce increases in the sister-chromatid exchange frequency.