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NA, number of patients for whom data were not available for the specified variable. P values were corrected by the Benjamini- Hochberg procedure for multiple tests. Clinical variables predicting bad patient outcome are associated with the indicated genes in a public mrna expression dataset including tumor tissue GSE and clinical annotations Supplementary Table 6 from patients with HCC treated by surgical resection 9. Preprocessed mrna expression values were split into high and low expression groups according to the 0. P values were corrected by the Benjamini-Hochberg procedure for multiple tests.

Eur J Biochem ; Blocking Wnt signaling by SFRP-like molecules inhibits in vivo cell proliferation and tumor growth in cells carrying active beta-catenin. Inflammatory cytokines promote the retrodifferentiation of tumor-derived hepatocyte-like cells to progenitor cells.

An expression atlas of human primary cells: Highly efficient generation of human hepatocyte-like cells from induced pluripotent stem cells.

A human model of epithelial to mesenchymal transition to monitor drug efficacy in hepatocellular carcinoma progression. Molecular cancer therapeutics ; Increased extracellular matrix remodeling is associated with tumor progression in human hepatocellular carcinomas. A unique metastasis gene signature enables prediction of tumor relapse in early-stage hepatocellular carcinoma patients. De novo HAPLN1 expression hallmarks Wnt-induced stem cell and fibrogenic networks leading to aggressive human hepatocellular carcinomas.

December 01, Accepted: April 22, Published: May 13, AbstrAct Research Paper: Gene expression network, molecular pathology and survival analyses were performed on HCCs and matching non-tumor livers from 70 patients by real-time PCR and tissue micro-array-based immunohistochemistry. Wnt3a reprogrammed liver progenitors to replicating ibrogenic myoibroblast-like cells displaying stem and invasive features. HAPLN1 was independently associated with bad overall and disease-free outcome. In the context of experimental liver regeneration in response to tissue damage, Wnt signals expand transit-amplifying liver progenitor cells but impair hepatocyte diferentiation [13].

We report that Wnt3a reprograms liver progenitors to replicating and invasive ibrogenic myoibroblast-like cells expressing stem cell markers. HAPLN1 links proteoglycans with hyaluronic acid, thereby building growth factor binding platforms [20]. Whereas HAPLN1 appeared de novo in aggressive tumors expressing stem cell markers and in vitro models of epithelial-mesenchymal transition; HAPLN1 knockdown downregulated key markers of mesenchymal cells.

We hypothesize that HAPLN1 can be hijacked by tumor evolution as a selective advantage for cancer progression. Control media led diferentiation to hepatocyte-like cells, as expected [18]. Wnt signals promote commitment of transitamplifying liver progenitor cells to ibrogenic myoibroblast-like cells To look at the gene networks leading to myoibroblastic diferentiation of hepatic progenitors, we treated cells with 7 nm Wnt3a for three days.

This strategy was validated by real-time PCR Oncotarget. Wnt signals diferentiate liver progenitors to myoibroblast-like cells invading Matrigel. Incubation of progenitor HepaRG cells with control or Wnt3a-conditioned medium for 13 days. Cells incubated with Wnt3a are ibroblast-like.

Coimmunodetection of the indicated proteins. Images were acquired with a Cellomics station at 20X. HepaRG cells invading Matrigel. Wnt3a enhances cell proliferation. Ingenuity Pathway Analysis revealed ibrogenesis and myoibroblast activation pathways Figure 2A. Consistently, gene ontology analysis by FuncAssociate 2. Also, gene ontology analysis conirmed that the gene set afected by scrambled sirna was only associated with actin crosslink formation, relecting cytoskeletal rearrangements following electroporation [22].

To strengthen our observations, we compared the Wnt-induced signature in HepaRG cells with the whole genome mrna expression proiles of epithelial 3P and ibroblast-like 3SP human HCC cell lines. By hierarchical clustering, ibroblastlike 3SP cells were unambiguously distinguished from epithelial 3P cells on the basis of the gene expression of Wnt Homepage targets Figure 2C and extracellular Wnt pathway components Figure 2D and associated functions Figure 2: Wnt signals activate a ibrogenic gene expression program in liver progenitors. Gene networks applying Ingenuity pathway analysis on the gene set diferentially regulated by Wnt3a.

Wnt-induced diferentiation of hepatic progenitors into ibrogenic myoibroblast-like cells matches the transcriptome signature of spontaneously emerging EMT in human HCC GSE Moreover, comparison of the mrna signature of transiently mesenchymal-competent cells induced by dediferentiation of hepatocyte-like HepaRG cells [18] with our Wnt3a-induced signature conirmed that Wnt signals speciically promote diferentiation of transit-amplifying liver progenitor cells to ibrogenic myoibroblast-like cells Supplementary Table 6.

In vitro Wnt-induced ibrogenesis activates signaling networks that are functional in HCCs. Tomatidine is a cyclopamine structural analog which does not inhibit the Hedgehog pathway. Networks with a correlation coeicient threshold 0. Thickness of links is proportional to the correlation coeicients. Multiple regression coeicients R are indicated Oncotarget. Whereas LGR5 expression by myoibroblast-like cells suggested that they retained stem cell features Figure 3C ; silencing of LGR5 by speciic sirna upregulated the hepatocyte diferentiation marker aldolase B Figure 3D , suggesting that Wnt-induced LGR5 impairs hepatocyte diferentiation.

Of note, SFRPs 1 and 2 also relect mesenchymal commitment of stem cells [24]. Hyaluronan And Proteoglycan Link Protein 1 HAPLN1 is a cartilage gene that links proteoglycans to hyaluronic acid, thereby playing a key role in extracellular matrix assembly [20]. Moreover, kinetics analysis of gene expression, upon dediferentiation of hepatocyte-like HepaRG cells to transient mesenchymecompetent progenitors, revealed that HAPLN1 became detectable at 24 h and increased by 8 folds at 48 h post plating. Taken together, these indings indicate that HAPLN1 hallmarks mesenchymal commitment of hepatic progenitors.

The clinical and biological features of the HCC patients in our cohort and the lowchart of inclusion criteria for survival analysis are detailed in Supplementary Table 8, A and B. Multivariate analysis after adjustment for alphafetoprotein, vascular invasion, number of resected liver segments and capsular iniltration by the HCC showed that HAPLN1 was independently associated with survival after curative resection, with a mean increase in relative risk of 4.

Images acquired at 20X. Kinetics of mrna expression analyzed by real-time PCR in HepaRG cells along the retrodiferentiation of hepatocytes into liver progenitors and the diferentiation of liver progenitors to hepatocytes. HAPLN1 silencing leads to mesenchymal and stem cell marker loss. Real-time-PCR-assessed mrna expression of the indicated genes in HepaRG progenitor cells transfected with the indicated sirnas. Controls were used as calibrator. Disease-free and overall survival after curative HCC resection.

Multivariate Cox s proportional hazards model after adjustment for alpha-fetoprotein, vascular invasion, number of resected liver segments and capsular iniltration. Moreover, a cluster of biomarkers induced by Wnt3a in HepaRG cells relecting progenitor cells with mesenchymal commitment was associated with high Edmondson-Steiner s score in HCCs, indicating poor tumor diferentiation Supplementary Figure 4.

Taken together, these indings indicate that HAPLN1 emerges in mesenchymal-committed tumor progenitor cells driving tumor aggressiveness and poor outcome in HCC. DIscUssION We show here that Wnt-speciic signals foster ibrogenic, myoibroblast-like populations with stem cell features and impair hepatocyte and biliary lineage commitment of liver progenitors. The pathway crosstalks elicited by Wnt-speciic signals form a tight network in HCCs. Among the genes switched on within this network, HAPLN1 is associated with bad outcome and with the expression of markers of stemness and of tumor aggressiveness Figure 9.

In addition, R-spondin binding of LGR5 receptors enhances Wnt signaling and leads to long-term expansion of bipotent hepatic progenitor cells [13]. Our data suggest that Wnt3a triggers inely-tuned signaling pathway crosstalks, driving progenitor cell reprogramming to replicative, invasive and ibrogenic myoibroblast-like cells. Despite their ibrogenic activity, these myoibroblast-like progenitors kept high levels of the stem cells markers CD44 and LGR5.

Thus, the rates of proliferation and the expression of stem cell markers suggest that these cells are not terminally diferentiated. This phenotype is compatible with the dynamics of cancer progression. Along these lines, Notch signaling leads to biliary lineage commitment [28], but Wnt3a reduced Notch2 expression Figure 1C and upregulated the Notch inhibitor LFNG Figure 3, A , thus impairing biliary lineage commitment.

Consistently, the earliest mesoderm-committed progenitor cells derived from human embryonic stem cells and mesenchymal-competent HepaRG progenitors are EPCAM [18, 26]. Importantly, through activation of diferent gene networks, both works show that the inal output is enhanced tumor aggressiveness. Wnt signals led cells to ectopically express mesenchymal progenitor genes like HAPLN1, which regulates cell growth in developing cartilage [19] and heart valves [36].

Brown color, speciic signal; blue, hematoxylin counterstaining. The three proteins are detected in tumor cells at the tumor-stroma interface black arrows and in cells arranged in Indian iles red arrowheads. Pearson s X2 and Gamma correlation coeicients are shown on the right.

Vascular tumor invasion black squares is associated with the indicated variables. In conclusion, Wnt-speciic signals led hepatic progenitors to specialize into invasive, proliferating myoibroblast-like ibrogenic cells with stem cell features through a subtle equilibrium of signaling pathway crosstalks. Through the ectopic induction of mesenchymal progenitor genes in liver cancer cells, Wnt signals confer a high degree of biodiversity and, ultimately, selective advantages for cancer progression.

Fifty-one were treated by partial hepatectomy and 19 by orthotopic liver transplantation OLT. The microscopic features of tumors diagnosed as HCC were reviewed and annotated by a senior pathologist BT. Combined hepatocellular-cholangiocarcinoma or ibrolamellar HCCs were not included. After resection, patients were followed up every 3 months for the irst 2 years, and every 6 months thereafter.

Follow-up, which was available for 65 patients, included clinical examination, serum AFP alphafetoprotein , ultrasonography and computed tomography. The end of follow-up was set between June and September or at the time of death. Only patients undergoing partial hepatectomy, with a followup 3 months and with complete tumor resection were included in the survival analyses.

Early deaths, unrelated to the HCC, and patients without microscopically tumorfree resection margins, as well as patients treated by OLT, were excluded from survival analyses. Survival analysis lowchart is shown in Supplementary Table 8B. Eightytwo frozen tumors from 70 patients were analyzed. As controls, we included 66 matching non-tumor livers, 5 Figure 9: Upon low density plating, hepatocyte-like cells acquire transient mesenchymal competence within 48 h and dediferentiate to bipotent progenitors that normally re-diferentiate into hepatocyte-like cells.

A cell microenvironment enriched in Wnt signals reprograms liver progenitor cells into invasive ibrogenic myoibroblast-like cells within two weeks. Briely, fresh tissues were frozen at C in N 2 -cooled isopentane and stored at C under quality-controlled conditions. Formalin-ixed, parain-embedded tissue blocks were obtained from the Anatomic Pathology laboratory. The study protocol complied with French laws and regulations and fulilled the requirements of the local institutional ethics committee.

HepaRG cells were expanded as liver progenitors, diferentiated to hepatocytes and retrodiferentiated to liver progenitors [18]. Independent culture experiments were performed in triplicate. Tissue-microarray TMA and immunohistochemistry scoring of human tissues For selection of tissue blocs for TMA construction, the whole set of archival HE-stained sections from formalin-ixed, parain-embedded tissue blocks from each one of the 67 available HCC patients and from ive histologically normal livers were reviewed Nikon 80i microscope to ensure that the selected parain bloc was the mirror lesion of the frozen sample.

A region of interest ROI, 0. ROIs were punched in triplicate. HCC samples were randomly assigned to either one of two punch receiver parain blocks. The ive histologically normal liver controls were included in both array blocs 1 and 2 to control for signal and background intensities. See Supporting Table 2 for antibodies used. A 4-point scale denoting increasing signal intensity was used. The relative importance of focal versus general expression of the proteins under study was weighted using the following formulas, where GS stands for general score and FS stands for focal score: When applied, these formulas yielded scores varying from 3 to Cell growth assays Cells were seeded at low density cells per well in well plates.

BrdU was detected with mouse anti-brdu antibody 1: After ive days of culture following a routine passage, cells were detached, washed with PBS and suspended in serum-free medium supplemented with 0. Then, 1x10 5 cells were seeded in the upper chamber of the Transwell insert. Non-invading cells were gently removed from the upper surface of the insert and images from ive ields per membrane were randomly acquired Axio observer, Carl Zeiss microscopy.

The reaction included a 95 C denaturation step for 3 min followed by 35 cycles consisting of: Indeed, as somatic deletions are heterozygous, the wild-type allele may mask the deletion upon Sanger sequencing [40]. The primer pairs F1-R1 and F1-R2 yielded bp aa and bp aa amplicons, respectively. After puriication using an RNeasy mini kit Qiagen, Hilden, Germany , crna yield and speciic activity were determined using a NanoDrop spectrophotometer, as previously described [10].

Equal amount of Cy3-labeled crna was subjected to fragmentation followed by hr hybridization onto Agilent human 4x44K v2 pangenomic microarrays. Washing and scanning were performed according to the manufacturer s instructions Agilent Technologies. Gene expression data were further processed using Feature Extraction version Filtration of array data resulted in the selection of nonlag-positive and signiicant gene features.

Inter-array normalization was performed by using the 75th percentile signal value. Gene annotations based on gene ontology and enrichment for biological functions were done with the FuncAssociate 2. Gene networks were visually integrated with Cytoscape, with a correlation coeicient threshold 0. Briely, to screen our transcriptomic dataset for biologically relevant genes warranting further studies, we focused on those meeting two criteria: Survival analyses were performed using the Log Rank test and Kaplan-Meier curves and the Cox s proportional hazards method for univariate or multivariate analyses, as indicated.

Real-time PCR results were further normalized by the following equation: To obtain binary values for Kaplan-Meier curves, normalized realtime PCR results were binarized using the median as the cut-of value. TMA-based immunohistochemistry scores were binarized by a 3 cut-of score for focal expression of speciic proteins Oncotarget. Heatmaps showing associations between binary patient data were constructed with Excel Microsoft Oice See Supplementary Materials and Methods for: RNA interference, nucleic acid extraction from human tissues and cells, real-time PCR and immunocytochemistry.

The authors declare no conlicts of interest. Integrative transcriptome analysis reveals common molecular subclasses of human hepatocellular carcinoma. Wnt-pathway activation in two molecular classes of hepatocellular carcinoma and experimental modulation by sorafenib. Clevers H and Nusse R. Signaling pathway cooperation in TGF-beta-induced epithelialmesenchymal transition.

Current opinion in cell biology. Network modeling of TGFbeta signaling in hepatocellular carcinoma epithelialto-mesenchymal transition reveals joint sonic hedgehog and Wnt pathway activation. Wnt signaling and hepatocarcinogenesis: Secreted frizzled related proteins: Biochimica et biophysica acta. Blockade of Wnt signaling inhibits angiogenesis and tumor growth in hepatocellular carcinoma.

Gene expression in ixed tissues and outcome in hepatocellular carcinoma. N Engl J Med. Long-term culture of genome-stable bipotent stem cells from adult human liver. Wnt proteins are lipid-modiied and can act as stem cell growth factors. Molecular dissection of Wnt3a- Frizzled8 interaction reveals essential and modulatory determinants of Wnt signaling activity. Transdiferentiation of hepatocyte-like cells from the human hepatoma HepaRG cell line through bipotent progenitor. Generation of functional cholangiocyte-like cells from human pluripotent stem cells and HepaRG cells.

Inlammatory cytokines promote the retrodiferentiation of tumor-derived hepatocyte-like cells to progenitor cells. Watanabe H and Yamada Y. Mice lacking link protein develop dwarism and craniofacial abnormalities. The diferent roles of aggrecan interaction domains. Next generation software for functional trend analysis. Multiple efects of electroporation on the adhesive behaviour of breast cancer cells and ibroblasts.

A human model of epithelial to mesenchymal transition to monitor drug eicacy in hepatocellular carcinoma progression. Mapping the irst stages of mesoderm commitment during diferentiation of human embryonic stem cells. G-protein-coupled receptor GPR49 is up-regulated in basal cell carcinoma and promotes cell proliferation and tumor formation. Lin28b is suicient to drive liver cancer and necessary for its maintenance in murine models. The four and a half LIM-domain 2 controls early cardiac cell commitment and expansion via regulating beta-catenin-dependent transcription.

Malaguarnera R and Beliore A. The emerging role of insulin and insulin-like growth factor signaling in cancer stem cells. Spatial transcriptional proile of the chick and mouse endocardial cushions identify novel regulators of endocardial EMT in vitro. J Mol Cell Cardiol. Somatic mutations of the beta-catenin gene are frequent in mouse and human hepatocellular carcinomas.

Gene set enrichment analysis: The sva package for removing batch efects and other unwanted variation in high-throughput experiments. Langfelder P and Horvath S. Journal of the National Cancer Institute. Quality control of the extracted nucleic acids. Primary antibodies used are listed in Supporting Table 2.

Nuclei were stained with DAPI. Wnt3a induces fibrogenic myofibroblast-like cells from liver cell progenitors. Cells receiving control media gradually develop the features of a hepatocyte culture see insets for cytological details. Wnt3a treatment leads to the progressive growth of fascicles of spindle cells with elongated nuclei.

Transition from a hepatocyte-like to a fibroblastlike morphology is particularly evident at day 3, when polygonal, elongated hepatocyte-like cells with granular cytoplasm and round nuclei coexist with fusiform cells arranged in parallel fascicles green arrows. At day 7, closely packed spindle cells are arranged in parallel green arrows or intersecting red arrows fascicules.

At day 10, densely packed whorls of spindled fibroblast-like cells show a storiform-like pattern green arrows. At high power insets these cells show clear elongated nuclei, parallel to the cell axis. Coimmunodetection of the indicated proteins in HepaRG cells after 13 days of incubation with Wnt3a-conditioned or control media. Colormerged images were acquired with a Cellomics cellular imaging station at 20X. HSC70 is used as a loading standard. Expression profiles of genes differentially regulated by Wnt3a in cells that were not transfected No transfection left panel , transfected with a control scrambled sirna scr.

Two gene clusters are shown: Expression profiles of genes differentially modulated by Wnt3a. Biomarkers induced by Wnt signals in vitro are associated with low tumor differentiation in HCCs. Gene expression was assessed by real-time PCR. The heatmap plot shows that poor cytoarchitectural differentiation of HCCs high Edmondson-Steiner s scoring, cut-off, 3 is associated with the mrna expression levels of the indicated genes. Pearson s X 2 and Gamma correlation coefficients are shown on the right. Wnt3a induces a fibrogenesis program in progenitor HepaRG cells. Gene ontology GO terms overrepresented in each one of the gene sets were assessed by FuncAssociate 2.

LOD is the log10 of the odds value indicating overrepresentation. Table refers to Supplementary Table 3, A-G were the gene sets can be found. Gene ontology terms overrepresented in each signature. From the rows in the table listing Wnt target genes, we selected non-redundant genes from different species with available human orthologues.

Normalized and filtered entities from the GSE dataset were further filtered by gene symbol, retaining only those matching the non-redundant Wnt target genes from the Wnt Homepage. Differentially expressed genes are listed by decreasing order of fold change. Normalized and filtered entities were further filtered by gene symbol, retaining only those matching the gene Wnt3a-induced signature in HepaRG cells. Matching entities are listed by increasing order of fold change.

Gene ontology enrichment analysis was performed with FuncAssociate 2. Wnt signals promote the differentiation of transitamplifying liver progenitor cells to fibrogenic myofibroblast-like cells. As shown in the cartoon below, we compared two mrna expression signatures: Comparison of overlapping and non-overlapping genes between Wnt3a-induced transcriptome signature b , as described in Supplementary Table 3A, and the transient mesenchymal competent cell transcriptome signature a.

Signature a, obtained at 8; 12 and 16 hours after low-density plating of hepatocytelike cells [4], was reanalyzed from the public dataset GSE, as follows: Raw data were normalized by global scaling. The trimmed mean target intensity of each array was arbitrarily set to Normalized and filtered entities were further filtered by gene symbol, retaining only those matching the gene Wnt3a-induced. Then, fold changes were calculated as the means of the 8 versus 0 h; 12 versus 0 h and 16 versus 0 h ratios as shown above.

One hundred and seven genes which expression was differently modulated in both signatures are listed in the b column, with their corresponding fold changes. Ninetythree genes which were similarly regulated in both signatures are listed in the Common to a and b column, with their respective fold changes. C Overrepresented gene ontology attributes in the 93 gene set common to our Wnt3a and the Retrodifferentiation experiment by Dubois-Pot Scheneider et al.

Gene expression correlations between the indicated genes in 79 human HCCs. Pearson s correlation coefficients 0. Description of the sample population of HCC patients. Flow chart of the HCC population considered for diseasefree and overall survival analyses. Univariate Cox proportional hazards regression analysis. The number of deaths per category does not allow reliable estimates. Hazard ratio per IU over 6. AFP levels above the median 6. Consistently with a recent study [6], dyslipidemia protected from early death. Management of thrombocytopenia due to liver cirrhosis: World journal of gastroenterology: Opposite association between diabetes, dyslipidemia, and hepatocellular carcinoma mortality in the middle-aged and elderly.

Nous avons reparti ces CHCs en 3 bases: Finally, we developed and clinically validated an 8-gene signature, which predicted favorable patient outcome independently of tumor size. Conclusion Liver zonation impacts the phenotypes of well-differentiated HCCs. Significance of this study What is already known on this subject? Hepatocellular carcinomas HCCs are generally difficult to classify, as their highly heterogeneous natural history results in a diversity of molecular phenotypes.

Both showed favorable clinical outcome, with overlapping disease-free and overall survival curves.

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We developed and clinically validated an 8-gene signature predicting favorable patient outcome independently of tumor size. How might it impact on clinical practice in the foreseeable future? Combined assessment of the signature with clinical, pathological and radiological features, could refine the management of HCCs by improving prediction of aggressiveness in early-stage Barcelona stage A cases. HCC is endemic in Asia and Africa, and its incidence has doubled over the past 20 years in Western countries. Projections anticipate a further increase in incidence, despite recent breakthroughs with a virological cure for chronic hepatitis.

We thus hypothesized that an uncharacterized HCC subclass could be hindering survival studies, which led us to refine existing HCC classifications in a large, statistically powerful population. We found two subclasses of well-differentiated HCCs with overlapping survival curves and favorable clinical outcomes: Our results demonstrate that HCCs expressing the signature relate to more favorable patient survival than all other HCC subtypes taken together. Patients and Methods Patients, study design and data management Figure 1 presents the study design, including the development of two tools: A a robust computational method predicting CTNNB1 mutations and B an HCC metadata set combining nine quality-controlled public transcriptomic datasets see online supplementary tables 2 and 3.

Independently, hierarchical cluster analysis was used in this metadata set to identify robust HCC subclasses. Raw data from publically available transcriptome profiling experiments were extracted from Gene Expression Omnibus, normalized and log2 intensity expression values for each probe set were calculated by Robust Multi-array Average. Nine batch-corrected public transcriptomic datasets passing the quality control analyses were thus combined into a metadata set totalizing HCCs and the expression levels of common genes.

Statistical analyses To identify reliable gene predictors of CTNNB1 activating mutations, we applied Sparse Partial Least Squares Discriminant Analysis spls-da with bootstrap subsampling to optimize the identification of stable predictors see supplementary figure 2. Independently, robust HCC subclasses were identified using hierarchical cluster analysis defined by a stepwise algorithm see supplementary materials and methods for details.

Statistical analyses were performed with R version 3. See online supplementary materials and methods for: See also online supplementary figure 3A. In addition, unsupervised hierarchical clustering confirmed association of the five markers with CTNNB1 mutation in the three datasets figure 2B1, B2, B3. As data from non-tumor tissues were not available in the transcriptomic datasets, further predictions of CTNNB1 mutations were performed with tumor samples. By contrast, Huh7 expressed VNN1 at low levels. Hierarchical cluster analysis identified four subgroups see online supplementary figures Thus, we called this subgroup -type HCCs.

Also, they were both associated with early recurrence[37] and metastasis in HCC. Online supplementary table 9 shows expression levels of the genes in the HCC subclasses. The value of the geneset as a classifier was confirmed in the external validation HCC dataset see below. We observed differences in the percentage of samples in each subclass according to the dataset of origin see online supplementary table The sampling technique resections versus 73 biopsy specimens had no impact on tumor classification see online supplementary table Subsequently, network analysis in the patient metadata set revealed that periportal and perivenous genes were negatively correlated and respectively upregulated in PP-type and PV-type HCCs figure 5A.

Anti-VNN1 staining of bile canaliculi was totally suppressed by the immunogen polypeptide figure 5D. Periportal and Perivenous HCCs are two well-differentiated subclasses showing the best clinical outcomes. As these two HCC subclasses are well-differentiated and show similar survival curves figure 6B , the PP-type is likely to be the confounding tumor subgroup that, in previous studies see online supplementary table 1 , obscured the differences in outcome between HCCs carrying mutant versus those carrying wild-type CTNNB1.

Tumor aggressiveness was inferred by AFP serum levels, tumor grade, TNM staging, vascular invasion, TP53 mutation rates, tumor onset in younger patients, as well as survival see online supplementary figure 13, A-C. A minimal 8-gene Periportal signature indicates favorable pathological features and clinical outcome. We identified eight top genes from the mouse liver periportal signature[9]. These genes complied with the following criteria: Thus, the 8-gene Periportal signature figure 6C was associated with favorable overall and disease-free outcome in the HCC transcriptomic dataset [44] figure 6D.

Validation of this Periportal gene signature in the HCC RNAseq dataset from the TCGA consortium figure 6E and F confirmed its association with overall and disease-free survival as well as with clinical and pathological features indicating good prognosis. Moreover, the Periportal signature predicted disease-free survival independently of tumor size after multivariate Cox analysis and identified a favorable outcome subgroup in BCLC stage A patients see online supplementary figure The Periportal signature genes were highly correlated in the RNAseq dataset see online supplementary table In addition, the GSE microarray dataset from 84 tissues,[45][46] showed that these genes were expressed in normal liver at high levels, and six of them were liver-enriched see online supplementary figure Both subclasses show favorable survival and meet the criteria for non-proliferation class HCCs.

Analysis of two independent cohorts consisting of HCC patients revealed that Periportal HCCs show the most favorable clinicopathological features and outcome, compared to all other HCC subclasses taken together figure 6D-F. We discovered the minimal genetic signature that characterizes Periportal HCCs. These data suggest that Periportal HCCs are the first step in hepatocyte dedifferentiation and tumor progression. Perivenous HCCs are well-differentiated and associated with favorable outcome.

HAL is an enzyme that degrades the amino acid histidine[51] and was restricted to periportal hepatocytes in normal liver figure 5C.

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Some of these amino acid degrading enzymes, such as SDS serine dehydratase and GLDC glycine decarboxylase , yield the end-product oxaloacetate, which is used for gluconeogenesis, a periportal metabolic pathway. Along these lines, VNN1 is one of the 59 major proteins in human bile. It is also expressed de novo in other cancers and associated with favorable outcome. In conclusion, we demonstrated that liver zonation impacts the molecular phenotype of welldifferentiated HCC. Moreover, we provide a minimal signature for identification of this subclass.

New tools facilitating the identification of HCCs with relatively lower or higher malignant potential will improve clinical management of these heterogeneous tumors. Major endpoints are indicated by bold arrows. External validation sets are represented by black boxes. Training and validation sets were used to select the most stable markers by spls-da modeling. New biomarkers and a mutation prediction score were tested in our external validation in-house HCC collection.

Nine public transcriptomic datasets A to I were merged into a metadata set. AXIN2 was included as a Wnt pathway activation marker missing in the validation set. Low and high gene expressions using the median as a cut-off value are represented in green and red, respectively. In the independent cohort, gross tumor features are integrated. C Predictive score formula. Images were acquired with a tissue slide scanner at 20X original magnification.

Data are relative to scrambled sirna-transfected cells. Experiments were done in triplicate. B Expression of relevant genes in the HCC metadata set. Color code keys are shown at the bottom of the heatmap. Samples columns are ordered by HCC subclass. Green, low; red, high expression. A Green and red node borders denote mouse periportal and perivenous genes, respectively. Three gene clusters black nodes on the left denote: Red, high expression, green, low expression. Arrows show portal tracts PT and central veins CV.

VNN1 signal is totally suppressed by the immunogen polypeptide. A Clinical features of HCC subclasses in a patient dataset[44]. D Kaplan-Meier plots of overall and disease-free survival of HCC patients with and without the periportal signature. F Kaplan- Meier plots of overall and disease-free survival in HCC patients with and without the periportal signature in the external validation HCC dataset.

Fisher exact test categorical variables ; Student s t test continuous variables and Log-rank test survival analyses. High mutation rate, based on wholegenome sequencing data from the HCCs validation dataset see online supplementary figure Biomarkers, major biomarkers characterizing the HCC subclasses.

Red arrows, strong and orange arrow, moderate modulations of gene expression. We thank the following core facilities: Hepatocellular Carcinoma from Epidemiology to Prevention: Translating Knowledge into Practice. Genetic Landscape and Biomarkers of Hepatocellular Carcinoma. Transcriptome classification of HCC is related to gene alterations and to new therapeutic targets. Clevers H, Nusse R. Wntpathway activation in two molecular classes of hepatocellular carcinoma and experimental modulation by sorafenib. T-cell factor 4 and beta-catenin chromatin occupancies pattern zonal liver metabolism in mice.

Berasain C, Avila MA. Liver-specific hepatocyte nuclear factor-4alpha deficiency: Differential gene expression in periportal and perivenous mouse hepatocytes. The FEBS journal ; Systematic pan-cancer analysis of tumour purity. The sva package for removing batch effects and other unwanted variation in high-throughput experiments. A molecular classification of human mesenchymal stromal cells. Differential effects of inactivated Axin1 and activated beta-catenin mutations in human hepatocellular carcinomas. Integrated analysis of somatic mutations and focal copy-number changes identifies key genes and pathways in hepatocellular carcinoma.

Maintenance of pluripotency in human and mouse embryonic stem cells through activation of Wnt signaling by a pharmacological GSKspecific inhibitor. Nucleic Acids Res ; Gene expression in fixed tissues and outcome in hepatocellular carcinoma. N Engl J Med ; Classification and prediction of survival in hepatocellular carcinoma by gene expression profiling.

Mol Cell Proteomics ; The Journal of biological chemistry ; Gene expression profiles from hypertrophic scar fibroblasts before and after IL-6 stimulation. The Journal of pathology ; Epidermal growth factorinduced hepatocellular carcinoma: Identification of SOX4 target genes using phylogenetic footprinting-based prediction from expression microarrays suggests that overexpression of SOX4 potentiates metastasis in hepatocellular carcinoma.

Module map of stem cell genes guides creation of epithelial cancer stem cells. Cell Stem Cell ;2: EpCAM and alphafetoprotein expression defines novel prognostic subtypes of hepatocellular carcinoma. Gene expression-based recurrence prediction of hepatitis B virus-related human hepatocellular carcinoma. Suppression of hepatocyte proliferation by hepatocyte nuclear factor 4alpha in adult mice. Hepatocyte nuclear factor 4 alpha suppresses the development of hepatocellular carcinoma. Differentiation therapy of hepatocellular carcinoma in mice with recombinant adenovirus carrying hepatocyte nuclear factor-4alpha gene.

Apc tumor suppressor gene is the "zonation-keeper" of mouse liver. New targets of beta-catenin signaling in the liver are involved in the glutamine metabolism. A gene atlas of the mouse and human protein-encoding transcriptomes. Whole-genome sequencing identifies recurrent mutations in hepatocellular carcinoma.

Beta-catenin mutations are associated with a subset of low-stage hepatocellular carcinoma negative for hepatitis B virus and with favorable prognosis. Am J Pathol ; Vanin-1 is a key activator for hepatic gluconeogenesis. Hepatic amino acid-degrading enzyme expression is downregulated by natural and synthetic ligands of PPARalpha in rats. Analysis of vanin-1 upregulation and lipid accumulation in hepatocytes in response to a highfat diet and free fatty acids. J Clin Biochem Nutr ; Journal of hepatology ; PPARalpha regulates the production of serum Vanin-1 by liver. A proteomic analysis of human bile.

Mol Cell Proteomics ;3: Odontogenic ameloblast-associated and amelotin are novel basal lamina components. Histochem Cell Biol ; Kaimala S, Kumar S. An evolutionarily conserved non-coding element in casein locus acts as transcriptional repressor. Sixty-five gene-based risk score classifier predicts overall survival in hepatocellular carcinoma. Geneexpression signature of vascular invasion in hepatocellular carcinoma. Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma. Gene expression in nontumoral liver tissue and recurrence-free survival in hepatitis C virus-positive hepatocellular carcinoma.

Neoangiogenesis-related genes are hallmarks of fast-growing hepatocellular carcinomas and worst survival. Results from a prospective study.

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As controls, we included 66 matching non-tumor livers and 5 histologically normal livers from patients undergoing resection of liver metastases of extrahepatic primary cancers. Fresh tissues were frozen at C in N2-cooled isopentane and stored at - 80 C under quality-controlled conditions. Statistical analysis Transcriptomic data preprocessing Raw feature data from Gene Expression Omnibus were normalized and log2 intensity expression summary values for each probe set were calculated using Robust Multiarray Average RMA, packages Affy or Limma.

Each dataset was assessed for the detection of outliers and inter-array, experiment-related batch effects by principal component analysis PCA and density plots. The outliers removed were: Then, probes being detected over the background noise in at least one HCC were retained. To search for predictors of CTNNB1 mutational status, we performed bootstrap over three PLS- DA principal components, whereby rounds of bootstrap subsampling optimized the stability of predictors.

Prediction was then validated on statistical tools based on one-tailed t- tests to objectively choose the number of optimal components and to identify the most robust set of predictors[2] see supplementary figure 2. After further validation of these markers in the external validation in-house HCC collection by real-time PCR figure 2A,B , we built an arithmetic score as shown in figure 2C. For each normalization technique and gene combination, the predictive score was calculated and the common threshold maximizing sensitivity and specificity in both training and validation sets was evaluated.

Then, in each of the nine datasets, samples with a score higher than the threshold were predicted as mutated. The performance of this method and the predicted mutation rate in the nine datasets is presented in supplementary table 5. Dataset quality control and combination for transcriptome meta-analysis To assess the quality of each dataset, Pearson correlation coefficients were calculated for gene sets expected to be correlated: Thus, nine datasets passing the quality control analysis were combined into a transcriptomic metadata set intended for meta-classification figure 1B and supplementary table 2 , that totalized HCCs.

The nine datasets had common genes. Probes were merged to the gene level and all nine datasets were normalized with the COMBAT algorithm to eliminate platformrelated batch effect[11] see supplementary figure 5. Thus, the metadata set consisted of HCCs with common genes. To highlight robust HCC subclasses, we applied the following four steps which are outlined below. Detailed description of the four steps applied to highlight robust HCC subclasses 1 Identifying HCC samples highly associated with a subclass by individual reproducibility analysis.

To isolate HCCs robustly linked to each cluster, we calculated an individual reproducibility score applying the following steps, modified from Boyault et al. Unsupervised gene selection based on the two following criteria: For each gene G we tested whether its variance across samples was different from the median of the variances of the genes. This statistic was compared to a percentile of the Chi-square distribution with n-1 degrees of freedom and yielded a p-value for each gene; and ii.

Six rcv percentile thresholds were used: The rcv for each gene was calculated by dividing the standard deviation by the mean. It was called robust because the highest and the lowest expression values across the samples for each gene were deleted. Hierarchical clustering of the samples using the whole metadata set or data restricted to each of the six gene sets defined by the rcv percentile thresholds see ii above produced seven dendrograms.

For each dendrogram, a sample was noted 1 for a given cluster if it was classified in this cluster and 0 if it was not. The individual reproducibility score of clusters was calculated with the mean of the scores of the seven dendrograms. Then, samples with a reproducibility score over 0. For this test, the dataset GSE was used and genes were selected. Three PLS-DA models were obtained on the metadata set with differentially expressed genes for the prediction of the three subclasses defined by individual reproducibility analysis red, purple and green.

Then, variable importance in the projection VIP was calculated for each gene and each principal component. The ultra-thin sections of nm were prepared with ReicherteYoung ultra-microtome Vienna, Austria layers were contrasted with uranyl acetate and lead nitrate. After removing the thin layer formed at the surface, the supernatant was recovered and analyzed as follows. Assays were performed with five independent samples. Dough rheology The rheological analysis was carried out on seven samples of fresh and thawed dough for each type of freezing process.

Uniaxial strain was used to evaluate freezing treatment effect on dough Havet et al. During the experiment, dough disk of 5 cm in diameter, 2. Results and discussion 3. Analysis of kinetic thermograms Timeetemperature profiles were recorded in dough core for each freezing treatment with a common pace Fig. The profile of curve can be divided in three zones: A high freezing rate formed small size ice crystals, which were less damaging to the cellular structure and preserved the final frozen products quality. The choice of T1 and T2 strongly influences the value the freezing rate Le Bail et al.

The freezing rates obtained for each freezing treatment are presented in Table 1. The respective freezing rates were 8. However, the air-blast freezing rate is relatively slow, ranging between 0. According to the literature, the highest freezing obtained by cryo-genic freezing applied for bakery products was 2. Effects of freezing treatment on yeast cells and ultrastructure investigations The yeast survival results according to the different freezing treatment were presented in Fig. The freezingethawing process presents a double stress for the cell yeast: Physical changes occurred in yeast cells during freezing.

This was due to the supercooling and the presence of intra or extracellular solutes which reduced the freezing point. The mass transfer between intracellular and extracellular medium is limited by the water-membrane permeability value of yeast cell Dumont et al. The freezing rate had a direct influence on maintaining osmotic equilibrium into the cell yeast membrane during freezing. When slow freezing rate was applied, the kinetics of water transfer from intracellular to extracellular medium was favored through yeast membrane by exosmosis.

The external cellular solution increased, so a hyperosmotic environment was created and the extern ice crystals were formed. Release of intracellular water provoked extreme conditions these cells could be dehydrated and plasmolysed. This effect was well illustrated by TEM micrograph in Fig.

Furthermore, high freezing rate, did not allow water efflux into extracellular medium, resulting in the formation of intracellular ice crystals visible in TEM micrographs Fig. Therefore, the more the freezing rate increases, the lower is the transmembrane water flux is low favoring the formation of intracellular ice crystals, until the optimal conditions for vitrification are reached Dumont Table 1 et al.

Nonetheless, the small ice crystals were thermody-namically unstable and might recrystallize into large crystals progressively, during thawing around 20 h. The formation of intracellular ice was almost always lethal to the cells Meryman, In addition, intracellular ice formation and expansion during dough warming could exert sufficient force to rupture the membranes Mazur, Muldrew and McGann suggested that high freezing rate led to the highest osmotic pressure gradients share across the membrane, resulting in rupturing the membrane and allowing ice to propagate into the cell.

Mazur and Schmidt indicated that the small ice crystals formed by rapid freezing in the yeast cells, and if thawing is done slowly this study they would have time to grow according to the recrystallization process. Thereby, an optimal freezing and thawing rates were necessary to taking into consideration dough composition. Freezing rate should be simultaneously high to avoid the exposure of cells at high osmotic pressure and slow to minimize the formation of intracel-lular crystals ice. These results suggest that the slow freezing preserve the yeast viability in frozen sweet doughs.

Effects of freezing treatment on gassing power and dough volume during proofing Fermentative capacities of dough were represented by the gassing power after freezing treatments and are represented in Fig. Three phases were observed during proofing for the non-frozen dough: This choice of time line resulted from the industrial process which consists in a 3 h proofing time before cooking.

As a result of different freezing treatments, the total CO2 volume produced at min was defined as the general parameter expressing the overall power of gassing power. The unfrozen dough produced 2. Freezing rate and dough porosity rupture volume and rupture time evolution according to the freezing treatment. Each measurement was performed in triplicate. B Effect of freezing rate on the compression rate of fresh and thawed sweet doughs. C Dough open porosity curve of fresh sweet dough: The lowest gas volume was obtained for the dough immerged in liquid nitrogen 0.

As shown in Fig. Overall, the trends in CO2 production and yeast viability were closely related and contributed to the fermentative capacity. However, the freezing of yeast caused a decrease in the number of yeast cells then the ability to produce gas from the surviving ones. B Specific CO2 production at min of proofing according to freezing treatment. Data represent averages of three independent repeats.

Data are presented as mean - standard deviation; a, b: The lysed yeasts boost survival yeasts by releasing growth factors Lewis, that explained a better specific CO2 production. Effects of freezing treatment on dough open porosity To study the open porosity of fresh and frozen sweet doughs, the CO2 and dough volumes curves obtained during proofing were studied. The intersection between the CO2 volume and dough volume plateau tangents defined the dough open porosity coordi-nates rupture time and rupture volume as described in Fig. For dough volume a plateau was observed with all freezing treatment indicating freezing damage of gluten network resulted in non-retention of CO2.

No dough porosity was observed in liquid nitrogen after a 5 h proofing, probably because of the loss of yeast viability and capacity to produce gas reduced gassing as shown in Fig. The rupture volume and rupture time related to freezing rate were shown in Table 1. The average fresh dough rupture volume was 2. The rupture volume decreases whereas the rupture time increases significantly by increasing freezing rate.

Similar results were reported by Havet et al. The open porosity depends on two main factors: The open porosity study results suggested that freezing rate had a significant effect on the rheological properties of frozen doughs. The disrup-tions were reflected by reduction in the elasticity of dough. These results were in agreement with the results shown in Fig. ANOVA revealed the effect of freezing treatment on dough rheological properties. However, no significant differences for the maximum strength and the residual force after relaxation were observed between fresh and cryogenic treatment.

A TEM micrographs of dough: Cryogenic immersion better preserved the gluten network probably due to the small size of ice crystals formed by rapid freezing rate. These results were confirmed by Meziani et al. For other freezing process, the alterations of gluten network were probably due to rupture gluten bonds caused by mechanical action of ice crystals. The integrity of the gluten network depends on location and size of ice crystals that are governed by freezing rate Mazur, ; Phimolsiripol et al. The disruption of gluten matrix results in a less continuous and more ruptured protein matrix.

Ice crystal formation led to starch dehydration and the gluten network became separated from granules reducing strongly the mechanical properties Angioloni et al. To elucidate the effect of glutathione GSH released by lysed yeast during freezingethawing, the glutathione was assayed in different frozen and fresh sweet doughs.

The results presented are shown in Fig. In this study, the amount of glutathione released by yeasts during freezing is then insufficient to reduce some disulfide bonds and induce rheological changes in frozen sweet doughs. No significant change in the structure of the dough was observed. It can be concluded that the rheological changes of gluten network of frozen sweet doughs are mainly due to the ice crystals action formed during freezing. Effect of freezing rate on glutathione released in sweet dough.

Each experiment was carried out in duplicate; each measurement was performed in triplicate each time. A Dough volume evolution and B Gas volume evolution according to freezing treatment: The results are average of three independent replicates. Volume rupture decrease with an increasing freezing rate explains the degree of damage to the gluten network of the dough. Conclusion The main objective of this study was to reveal the influence of freezing rate on fermentative activity and rheological properties of frozen sweet dough.

It was confirmed in the study that the rapid freezing preserves the integrity of gluten network, thus it contrib-uted to CO2 retention. On the other hand, the relatively low freezing rates ensured yeast viability for maintaining gassing power. As shown by dough open porosity results, the rheological properties were affected by the freezing rate.

This was expressed by perforation of three-dimensional network during slower freezing rate. More-over, the gassing power depends on the yeast cells number, the cell activity and the fermentable sugars amount. A strong correlation exists between the lysed yeasts and the glutathione released during freezing treatments. These findings could used for dough stabili-zation at industrial scale.

Special thanks to Carole Perroud and Carole Jeandel for their technical support. References Abd El-Hady, E. Small and large deformation tests for the evaluation of frozen dough viscoelastic behaviour. Journal of Food Engineering, 87 4 , Utilization of dairy byproduct proteins, surfactants, and enzymes in Frozen Dough. Critical Reviews in Food Science and Nutrition, 51 4 , Effect of modified whey protein concentrates on empirical and fundamental dynamic mechanical properties of frozen dough.

Food Hydrocolloids, 23 7 , Cereal Chemistry, 69 4 , Influence of thermal and osmotic stresses on the viability of the yeast Saccharomyces cer-evisiae. Cereal Chemistry, 72 1 , Frozen and Refrigerated Doughs and Batters, 19e Thermodynamic analysis of the freezing of bread. Bread technology and sourdough technology. Trends in Food Science and Technology, 16 , Frozen bread dough, effect of dough mixing and thawing methods. American Institute of Baking, 8 4 , Cereal Chemistry, 56 5 , e International Institute of Refrigeration. Recommendations for the processing and handling of frozen foods 3rd ed.

Cereal Chemistry, 78 4 , e Factors affecting the stability of frozen bread doughs. Prepared by the straight dough method. Effect of aging and ice structuring proteins on the morphology of frozen hydrated gluten networks. Bio-macromolecules, 8 4 , e Journal of Food Engineering, 39 3 , e In Hygiene, quality and safety in the cold chain and air conditioning pp. Programmed death in bacteria. Microbiology and Molecular Biology Reviews, 64 3 , e Freezing of doughs for the production of bread and rolls in the US. Frozen and Refrigerated Doughs and Batters, e Quality changes of yeasted dough influenced by different freezing regime.

Interactions of cooling velocity, temperature, and warming velocity on the survival of frozen and thawed yeast. Cryobiology, 5 1 , 1e Freezing injury and its prevention in living cells. Annual Review of Biophysics and Bioengineering, 3 0 , Mechanisms of intracellular ice formation. Biophysical Journal, 57 3 , Effects of freezing treatments on viscoelastic and structural behavior of frozen sweet dough. Journal of Food Engineering, , Effect of freezing rate in textural and rheological characteristics of frozen cooked organic pasta.

Journal of Food Engineering, 90 2 , Aeration of bread dough influenced by different way of processing. Journal of Cereal Science, 51 1 , Effect of cold pre- treatment duration before freezing on frozen bread dough quality. Inter-national Journal of Food Science and Technology, 43 10 , Long-term stability of blood glutathione and cysteine in humans. Clinical Chemistry, 42 7 , Influence of formulation and mixing conditions on breadmaking qualities of French frozen dough. Journal of Food Engineering, 43 4 , Cereal Chemistry, 61 3 , Combined effects of freezing rate, storage temperature and time on breaddough and baking properties.

Please cite this article in press as: The results revealed the effect of low freezing rates on the frozen sweet dough rheologic properties,resulting in elasticity reduction of 8. This can be attributed to dehydration of the dough network, and the starch retrogradation phenomenon. This present study also showed that freezing rate is not the only parameter responsible for rheologic changes that occur during freezing.

External freezing temperature could be explain the changes taking place at slow freezing rates. Introduction The bakery market is in constant evolution and must be able to adapt quickly. The bakery and pastry industry need flexibility and ability to produce many different products Olivera and Salvadori, For example, demands increase for freshly baked, healthy, ethnic and safe products.

To this end, freezing allows manufacturers to develop products to face their requests more likely. The use frozen dough in the bakery industry permits the baker to reduce night work and reduce logistic constraints. In addition, using frozen dough facilitates the centralization of dough production and extends the distribution area. The frozen processes give a longer shelf life and preserve freshness; this parameter is greatly depen-dent on an adequate control of freezing rate and thawing Angioloni et al.

This is some reasons why frozen doughs are now well widespread in the bakery and pastry market. Frozen dough is obtained by adapting mechanized processes usually developed by international companies, which reduce pro- duction costs. Moreover, manufacturers can provide standard prod- ucts at any time Rosell and Gomez, Different freezing treatments are currently used in bakery as freezing by contact, air blast and cryogenic methods. The key technologies of frozen bakery products depend on the time of the freezing step in manufacturing process: The unfermented frozen dough allows baking on sale point hot point and does not require staff competences, provides fresh prod- ucts, with excellent organoleptic and textural properties.

However, frozen dough is often exposed to a decrease of specific volume. This phenomenon is responsible of an increase proofing time compared to fresh dough products during freezing and long frozen storage Anon et al. Different causes have been given to explain this proofing delay. First, the viability and fermentative capacity of yeast could be dete- riorated during freezing process.

Indeed, yeast lysis occurs during freezing treatment and a loss of the gluten network integrity cause a lower capacity to retain carbon dioxide during proofing. The quality of the bakery product made from frozen dough is lar- gely influenced by dough formulation Rouille et al. The freezing rate plays an important role in the final quality of frozen product, two opposite effects are observed.

A high freezing rate allows the formation of ice micro crystals, which do not affect the integrity of the three-dimensional gluten http: This remains the most important parameter which re-duces physical damage disturbance and dehydration of gluten net-work induced by freezing, ultimately to the extent that the starch granules appear to be associated with the network gluten Angiolo- ni et al.

Nonetheless, rapid freezing might fatally compro-mise the yeast activity. A compromise of freezing rate is needed to freeze the dough, slowly enough to maximize yeast activity but fastly enough to limit dough weakening. On other hand, during freezing the death yeast release reducing agents glutathione in dough have been which reduces disulfide cross the gluten network Collins and Haley, Several authors revealed the effect of freezing on dough rheol-ogy. Although the majority of previous works concerned bread dough produced from a basic recipe.

Manufacturing sweet bakery products from frozen dough adds more challenges than those of an unsweetened frozen dough. To better understand the action mechanisms of freezing rate on the sweet dough rheologic proper-ties, various investigation methods were used in this study. Up to now, only Esselink et al. According to the literature, no study focalized on the freezing rate effect on the rheologic properties of sweet dough gluten network with complex recipe using ATR Fourier transform infrared FTIR. Van Velzen et al. The characterization allows us to understand the distribution of protein, starch, water and fat during kneading.

In order to give direct answers to the industry, variable freezing treatments on sweet dough were compared to definite the process the less destructuring. For this purpose, rheologic and structural characteristics of frozen sweet dough were studied by means of different instrumental analysis: The results of different freezing treatments were compared to a fresh dough value. Finally, the best freezing treatment preserving the fresh dough properties was determined. Materials and methods 2.

The dough recipe comprised: All ingredients were mixed in a bread machine Moulinex OW , France with double propellers. Two steps were followed. The ingredients were mixed during 10 min at a low-speed 40 rpm , and then butter was added at a high-speed 80 rpm during 10 min. The dough portion g was put in a plastic tube Sigwald SA, France ; the polypropylene had a thickness of lm, 48 mm in diameter and 15 cm in length. Ten rolls of dough were obtained from each freezing treatment. The reference fresh dough was analyzed, be-fore each treatment.

Freezing treatments Two types of freezing processes were used to treat the dough: The dough cylinder was fitted with thermocouples placed at different radial locations. The K type thermocouples 0. For each freezing process, three replicates were used. Temperature in cryogenic process was moni- tored by a K type thermocouples lm diameter Ahlborn France connected to a data logger model Almemo V5 AMR. The use of cryogenic immersion is an effective way to obtain ra-pid freezing rates.

On contrary, air freezer cabinet lead to slow freezing rates. The latter depending on air speed and temperatures. Firstly, the initial freezing point of frozen sweet doughs in all cases was The beginning criterion T1 equal to the initial freezing temper- ature appears to be preferable before the initiation of ice nucle-ation is not supposed to be influent on the size and the number of ice crystals Le Bail et al.

In present work, the freezing rates in dough cylinder center are estimated at: Thawing and preparation of dough for analysis To cut of the rolls of dough in slices, the thawing is carried out in two steps according to method previously described Havet et al. Scanning rate was 10 kHz and scans were used for reference and samples between cm- 1 and cm- 1. The nominal instrument resolution was 4 cm- 1. References were recorded on air. Then, the dough was put on the ZnSe crystal of the optical cell. The ATR equipment was purged with dry air for the duration of the measurements.

Six replicates were done for each dough. Raw absorbance spectra were smoothed using a nine-points Savitsky-Golay smoothing function. Spectra were cut between cm- 1 and cm- 1 for analyzing the amide III band. Elastic baseline correction using points was then applied to spectra. Then, spectra were centered and normalized using OPUS software. These second derivative spectra were used only for identifying individual peak positions as already described Farrell et al. Finally, the treated spectra were deconvoluted by a non-linear regression curve fitting program of Gaussian peaks to the original spectra Opus Software.

This deconvolution allowed the determination of the fraction of the various secondary elements in the protein under different freezing treatment. Freezing point depression The physicochemical and structural dough changes depending on the freezing rate were investigated, by freezing-point depression. Relations between freezing-point depression and physicochemical variations during a hydrolysis or retrogradation of dough compo-nents starch were investigated.

The cryo-scope was calibrated with distilled water and a calibration standard at Rheologic measurements The small deformation oscillatory shear properties of the dough samples were carried with a Kinexus rheometer Malvern, England. Silicone oil was added around the plate edges to prevent sample dehydration. A frequency sweep test was conducted to identify the linear viscoelas-tic region and a target 1 Hz, which was within this linear region, was chosen for measurements.

A frequency sweep test 0. Each test was carried out on four samples of fresh and frozen doughs for each type of freez-ing. In this region, rheologic properties do not depend on the frequency. Temperature probes were inserted at different positions in the dough Fig. A linear regression was applied be-tween the surface freezing rate and central position for each freez-ing treatment. As shown by the coefficients R 2 between 0. As previously showed in the literature, the freezing rate deter-mines the type, size and distribution of ice crystals formation dur-ing freezing.

A slow freezing rate promotes the large ice crystals formation inducing the dehydration of dough matrix. However, a rapid freezing prevents the water migration and promotes numer-ous small ice crystals. As the freezing rate lightly varies during according to the position in the sweet dough cylinder, ice crystals could slightly vary between the surface and the center of the dough cylinder. These data showed if the effect of cylinder position influ-ence lightly freezing kinetic of air blast freezing, a strong effect exist for liquid nitrogen immersion due to the limiting effect of dough thermal conductivity.

In this work, the linear evolution of freezing rate vs radius was used to compare the different freezing treatments, three groups have been distinguished: This temperature allows having a good representation of dough rheologic properties without yields growing. Tan d indicates the dominant character. This behavior could be due to gluten network weakening produced by freezing treatment Angioloni et al. Local freezing rate according to the radial position in 5 cm-diameter cylindrical sweet dough different freezing temperatures: These results could be explained by the gluten network disrup-tion of frozen sweet dough caused by ice crystallization and the water redistribution provoked by a modification in the water 62 S.

Indeed, dough weakening during freezing has been attributed to the reduc-tion of gluten by reducing substances, glutathione, released from dead yeast cells Collins and Haley, Freezing causes a rise in osmotic pressure of the external medium and rapidly frozen, causing the water efflux from the matrix. The ice formation com-presses the network, thereby altering the dough components dis-tribution starch, yeast.


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Rheologic changes of dough occurred during slow freezing can be explained by the large size crystals for-mation and the mechanical action of ice crystals, while the rapid freezing rate led to small ice crystals growth without consequences on the dough Angioloni et al. High freezing rate has also been shown to result in lower starch retrogradation than slow freezing. The rapid freezing advan-tages can be attributed to the prevention of starch retrogradation nuclei formation due to the fast transition through the rubbery state during which both nucleation and propagation occur Ferrero et al.

How-ever, a decrease in tan d versus control signifies that slow freezing air blast freezing treatments increased the solid behavior more than the elastic one. Lipids also contribute to viscoelastic behavior considering that lipid globules may act as network filling. Indeed, amylose—lipid and lipid—granule interactions can help strengthen the network Navarro et al. On the other hand, the freezing and thawing treatment promote a reduction in the dough resistance.

Effect of freezing treatment on protein denaturation During freezing, temperature, pH, and high ionic strength influ-ence dehydration, protein denaturation and aggregates formation due to competition with existing electrostatic bonds, lipid oxida-tion, enzymatic reaction, surface tension and physical effects of ice Wagner and Anon, Protein integrity is af-fected by freezing rate. In general, high freezing rates do not allow water diffusion in the dough network, local smaller ice crystals are formed and cause less damage.

The ice crystals damage may be direct mechanical and consequent water distribution. The secondary structure of dough gluten network was studied using Fourier transform infrared spectroscopy Fig. The distinc-tive absorption bands of the main components were shown in infrared spectrum of the sweet dough Fig. Different zones were identified: Although most of the literature studies investigated the amide I band for its strong signal, interferences with the water vibration band limit its exploitation Cai and Singh, The amide III band deconvolution was shown in Fig.

The various peaks and their frequencies corre- spond to: The quantitative estimation of each shoulder areas have been grouped in Table 2. Notable differences were observed when the dough proteins were frozen compared with fresh dough. These results suggest that b-sheet and a-helix are sensitive to freezing; the b-sheets were partially unfolding under freezing rate effect.

This can be interpreted as the formation of a range of new b- sheet together with a shift to less strongly hydrogen-bonded structures Georget et al. On the other hand, the results showed that other structures were less sensitive to freezing; it would be probably due to formation of new proteins bonds with other components Cai and Singh, The secondary structures change indicates proteins aggregation.

This observation is consis-tent with the results from thermal denaturation of globular proteins studied by Georget et al. Freezing process caused yeast lyses and the release of reducing substances as glutathione reduced interchain disulfide bonds of the gluten network thus leading to dough weakening Collins and Haley, Changes in the protein structure could be as-signed to the reducing agents like glutathione.

The slow freezing air blast freezing promoted a decrease in the a-helix fraction cor-related with increased content of extended b- sheet amount. This change could be regarded as a sign of protein aggregation. Various studies have shown freezing effect on proteins denatur- ation. During freezing, water diffuses and migrates to form ice crys- tals, resulting in the interruption of the organized hydrogen bonding system that stabilizes the protein structure, therefore hydrophobic and hydrophilic regions of proteins are exposed to a new environment.

New intermolecular cross-links can appear within the protein molecule or between two neighboring molecules Santos-Yap, This study confirmed that rapid freezing liquid nitrogen better preserves the secondary structure of gluten proteins. Effect of freezing treatment on starch retrogradation FTIR spectroscopy is a technique also used to study the conforma- tional changes of starch. The spectral region of — cm-1 was used to investigate the changes in starch structure of frozen dough Fig. The amide III — cm- 1 and starch regions of the spectra — cm-1 have been identified. Indeed, various studies revealed the effect of freezing tempera-ture above the glass transition temperature accelerated the starch retrogradation, therefore increasing the frozen dough hardness Charoenrein and Preechathammawong, The results of freezing point depression Fig.

The phenomenon of starch retrogradation, indicating the water expulsion syneresis , is even faster at low temperature, which complicates their use in the frozen products manufacturing. In order to explain the above-mentioned results, numerous works have shown on the effect of freezing rate on the starch retrogradation syneresis starch-based products Satmalee and Charoenrein, In addition, the large ice crystals formed during slow freezing distort the system structure and contribute to the starch retrogradation process. Slow freezing would allow amylose molecules to align and release the trapped water, favoring retrogradation of starch Navarro et al.

In this present study, freezing point determination was used as an indicator of the starch retrogradation degree. Secondary structures fractions determined Cai and Singh, at: Effect of freezing rate on sweet dough freezing point depression. Conclusion Rheologic and structural methods can be used in order to evalu-ate the influence of freezing rate on frozen sweet dough rheologic properties.

Linear regression showed that a linear correlation exists between local freezing rate and radial position for each freez-ing treatment. On the other hand, slow freezing causes pro-tein aggregation manifested by a decrease in the amount of a-helix correlated with increased content of extended b-sheet fraction. In general, the rheologic changes in frozen sweet dough are might be due to the formation and the mechanical action of ice crystals, leading to dehydration of the dough components, these ef-fects were particularly significant for low freezing rates.

It can be concluded that the immersion cryogenic freezing fast freezing rate gave the overall best results with regard to the rhe-ologic properties of frozen dough. The results of this study to understand the action mechanisms of freezing on the sweet dough rheologic properties, it will be interest-ing to study sensorial and texture attributes after bake of frozen sweet doughs. Carole Perroud and CaroleJeandel are also acknowledged for their technical support. Small and large deformation tests for the evaluation of frozen dough viscoelastic behavior.

Journal of Food Engineering 87 4 , — Effect of freezing on dough ingredients. Marcel Dekker, New York, pp. Identification of b-turn and random coil amide III infrared bands for secondary structure estimation of proteins. Biophysical Chemistry 80 1 , 7— Use of centrifugation-filtration for determination of syneresis in freeze—thaw starch gels. Carbohydrate Polymers 73 1 , — Undercooling associated with slow freezing and its influence on the microstructure and properties of rice starch gels.

Journal of Food Engineering 2 , — Chorleywood Digest , 21— Impact of industrial dough processing on structure: Cereal Chemistry 80 4 , — Secondary structural studies of bovine caseins: Food Hydrocolloids 15 , — Corn starch—xanthan gum interaction and its effect on the stability during storage of frozen gelatinized suspension. Effect of flour heating on dough rheology. Lebensmittel-Wissenschaft und-Technologie 37 1 , — Effects of temperature and water content on the secondary structure of wheat gluten studied by FTIR spectroscopy. Journal of Food Engineering 45 3 , — Rheological and structural characteristics of starch in maize tortillas.

Plant Foods for Human Nutrition formerly Qualitasplantarum 65 2 , — Studies on frozen doughs II. Cereal Chemistry 69 4 , — Application of freezing rate expressions and gassing power to frozen bread dough. Journal of Food Engineering 39 3 , — Molecular rearrangement of starch during in vitro digestion: Biomacromolecules 9 7 , — Frozen and Refrigerated Doughs and Batters, — Viscoelastic properties of frozen starch-triglycerides systems.

Journal of Food Engineering 34 4 , — Effects of ingredients and processing conditions on the frozen dough bread quality of a Canada Western Red Spring wheat flour during prolonged storage. Food Research International 29 7 , — Journal of Food Engineering 90 2 , — Protein denaturation during freezing and thawing in phosphate buffer systems: Archives of Biochemistry and Biophysics 2 , — Frozen dough and partially baked bread: Food Reviews International 23 3 , — Journal of Food Engineering 43 4 , — Fish and seafood, Freezing Effects on Food Quality.

Jeremiah Lester E p. Acceleration of ageing in rice stick noodle sheets using low temperature. International Journal of Food Science and Technology 44 7 , — Factors associated with dough stickiness as sensed by attenuated total reflectance infrared spectroscopy.

Effect of frozen storage on protein denaturation in bovine muscle 1 Myofibrillar ATPase activity and differential scanning calorimetric studies. International Journal of Food Science and Technology 21 1 , 9— Cereal Foods World 40 11 , — Two types of dough were studied to estimate dough shelf life: Fermentative activity yeast viability, gassing power, and dough volume , rheological and textural parameters were assessed for frozen sweet doughs.

These effects were explored by different and complementary methods: This modification led to lower specific volume of frozen sweet dough during proofing. The observed changes of the frozen sweet doughs rheological properties after thawing may be attrib-uted to the damage on the gluten cross-linking, mainly produced by the ice crystallization during frozen storage.

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The storage effect was particularly concentrated in the first 27 days of storage. Introduction Frozen products are not indefinitely stable; they gradually dete- riorate until they reach an unacceptable quality. This quality loss is reflected by reduction in dough volume and an increase in proofing time in comparison with dough prepared by using traditional methods.

The shelf life of frozen dough is estimated for 8—9 weeks if the dough has not been abused during transportation and frozen stor-age temperature, formulation, freezing, transportation Le Bail et al. However, the decrease of frozen dough volume is related to phenomena that occur during freezing and frozen storage: The resistance decrease leads to cracking of dough gluten network, the latter resulting in poor gas retention and loss of volume when baking.

These phenomena are probably due to uneven water redistribu-tion in dough matrix during freezing Giannou and Tzia, On the other hand, Gormley et al. Indeed, the gassing power depends on the yeast cells number, strain, physio-logical state of yeast and fermentable sugars amount Teunissen et al. Freezing and frozen storage affect the viability and activity of yeast cell. The volume of carbon dioxide produced has been used as a measure of yeast activity, since it is primarily produced by yeast. Various studies reported the freezing effect on properties of yeast which is a major concern in the frozen dough manufacturing.

This phenomenon can be explained by a high sensitivity of yeast cells to damage caused by osmotic pressure in dough matrix. The freezing rate must be slow enough to avoid the crystals ice formation in the cell, while quick to minimize the cells exposure to the effects of solu-tion concentration caused by water crystallization. However, the injuries caused by freezing and storage can be minimized by adopting appropriate measures during formulation and use adapted production process. To improve freezing performance, some technological parameters, such as freezing rate and freezing temperature must be taken into consideration as well as yeast strain choice and increasing the yeast amount to compensate the loss of fermenta-tive activity.

However, over addition of yeast increases the process cost and could cause a yeasty taste in the final product Lorenz and Kulp, ; Neyreneuf and Van Der Plaat, Various authors have reported the frozen storage time effect on the dough textural and rheological properties Gelinas and McKin- non, During freezing, there are also structural changes in frozen dough due to the mechanical action of ice crystals during freezing and storage, leading to a deterioration of frozen dough network which is manifested by dough strength decrease and poor gas retention during proofing Berglund et al.

In addition, the gluten network weakening of frozen dough is attributed to the release of yeast substance reducing such as gluta- thione Kline and Sugihara, Several authors investigated the individual effects of storage time or temperature on the bread dough properties. According to the literature, no FTIR spectroscopy studies describing the effect of freezing rate and storage time on the rhe- ological properties of frozen dough were published.

We also investigated the yeast content effects on the fermentative activity gas production, yeast viability and specific volume and rheological behaviors in frozen sweet doughs during frozen storage and these properties were compared to control 0 day ii to define the optimal storage time for sweet doughs. Sample preparation Samples of dough have been prepared as described in a previous work Meziani et al. Dough experiments were done in duplicate. In order to study the effect of yeast and the freezing time, two types of dough were studied: The freezing rate was estimated to be about Temperature in the dough during freezing process was recorded using a K type thermocouple lm diameter Ahlborn France connected to an Almemo data logger model V5 AMR.

Thawing and preparation of dough for analysis After frozen storage, frozen dough samples were thawed into two steps according to the method previously described by Meziani et al. All dough analyses were performed on four frozen doughs samples tested for each dough type during storages period. Yeast survival determination After thawing, the number of viable yeasts was determined in the each dough sample, using the direct plate count method Phi- molsiripol et al.

Logarithmic dilution counts were carried after the dilution of 10 g of dough in 90 g of tryptone salt solution Biokar Diagnostics, France. The developed CFUs were expressed per gram of dough. Triplicates plates were prepared for each of three dough samples per sweet dough SY and DY. Gassing power and dough volume evaluation during proofing The CO2 production was measured. The vessel was connected to inverted test-tube filled with water at pH 2 and hermetically closed. The CO2 volume was measured at regular intervals through the displacements of water in the test-tube Peighambardoust et al.

The dough volume was determined by the method described by Havet et al. Dough pieces were placed in a sterilized grad- uated test-tube 5 cm diameter and 10 cm height. The device was placed in a chamber at 2. The vertical displacement of the cursor due to the dough volume increase in graduated test-tube during proofing gave the dough volume ml. Infrared measurements Similarities and differences in secondary structures of sweet doughs according frozen storage time were investigated using Fou- rier-transform infrared FT-IR spectroscopy. The protocol used in this study has been previously described by Meziani et al.

Six independent experiments were done for each sweet dough. Data analysis was carried out using the OPUS 3. This decomposition allowed the determination of the fraction of the various secondary elements in the protein during frozen storage time. To study the water effect on protein on secondary structure; the amide III band was investigated.

The amide III band deconvolution provide various peaks and their frequencies correspond to: The compression-tension measurement is one of the standard assays used to measure the dough textural 69 properties. The textural parameters were carried out on seven S. The experimental parameters were the following: Hardness is defined as the peak force during the first compression cycle and the springiness is defined as the ratio of length of dough detected height during the second compression to that the first compression.

Hardness and springiness were measured in the ab- sence of dough adhesiveness by using a plastic film on the dough surface to avoid the distortion induced by the negative peak of adhesiveness Collar et al. The experimental samples data were: Dynamic rheological measure-ments were performed with a Kinexus rheometer Malvern, Eng-land using the method described previously by Meziani et al. The reduction kinetics of yeast cells that affect the overall qual-ity of products bread products in our study could be obtained from the following equation: The different reaction orders were studied 0, 1 and 2.

The model equations and their correlation coefficients R 2 were determined for each reaction order and the slope K was deter-mined from these equations. The values of yeast loss rate K obtained for the Fig. The majority of authors recommends to increase or double yeast quantity to compensate this loss in the frozen dough manufacturing Phimolsiripol, During frozen storage, the kinetic of yeast viability decrease seemed to follow the same trend for both doughs. For the same time, the yeast survival number on DY was equivalent to the SY dough be-fore freezing. The desiccation and electrolyte release giving to hyperosmotic stress during freezing Hatano et al.

This recrystallization can occur during prolonged frozen storage and especially during slow thawing at low temperatures Mazur, Yeast cells viability in frozen dough depends on the composi-tion and integrity of the cell membrane. During freezing, the yeast membrane integrity is subjected to high osmotic pressure, to with- stand a high content of phospholipids to prevent rupture Codon et al. Hohmann suggested that exposure to hyperos- motic stress leads to rapid dehydration of the cells thus limiting CO2 production, which results in increases in proofing time.

These effects are enhanced in frozen sweet dough, because yeast is ex-posed to high osmotic pressures and reduced water activity during freezing and frozen storage. On the other hand, the direct consequence of temperature on yeast cell walls and cytoplasmic cell membranes cannot be excluded; temperature determines the amount of ice present in the matrix. A lower temperature can lead to phase transitions and loss fluidity of the lipid bilayer and alter interactions between the bilayer membrane proteins Morris and Clarke, This present study revealed that the yeast population number of SY dough at 0 days was equivalent to that DY frozen dough stored for 27 days.

Effect of frozen storage on yeast activity The effect of frozen storage time of both SY and DY frozen doughs on the CO2 production gassing power and specific volume are shown in Table 1. As a result, gas production decreased signif-icantly with frozen storage time. Table 1 Gassing power and specific volume of SY and DY frozen sweet doughs with increasing frozen storage duration. The corresponding dough volume followed the same trend as the gassing power affected by storage time. It is commonly known that a freezing process followed by stor-age in frozen condition affects the CO2 production El-Hady et al.

The fermentative activity CO2 production and specific volume of DY sweet dough stored for 27 days is equivalent to the SY sweet dough that is not frozen; this can be explained by maintaining a sufficient yeast population. The results showed that yeast activity parameters yeast popu- lation, specific volume and gassing power of both frozen sweet doughs showed a strong negative correlation with frozen storage time. The frozen storage caused a decrease in yeast cells number which induces a decrease in gas production capacity from residual surviving yeast.

The CO2 production depends on the frequency, the number of yeast cells, the cell activity and the amount of ferment-able sugars. In other words yeast cells may suffer nonlethal damage in frozen dough that precludes them from forming colonies on a plate while retaining the ability to ferment sugars and produce CO2 in dough. As shown in Table 1, up to 27 days, the yeast quantity had no significant effect on yeast gassing power. This can be explained by the limitation of substrate fermentable sugars. Beyond 27 days of frozen storage, the ability of fermentative yeasts is strongly influenced by the duration of storage.

The results obtained in this study were consistent with the re-sults of Le Bail et al. Neyreneuf and Delpuech suggested that temperature fluctuations accelerate ice recrystallization that reduces fermentative activity of frozen sweet doughs. No significant differ-ence was found between the DY sweet dough stored during 38 days and the SY control.

The results of this study are in accordance with Angioloni et al. Regarding the springiness of frozen sweet doughs have suffered the same fate as the previous settings. Results of rheological properties grouped in Fig. As shown by the compression-tension measurements, similar trends were observed with tan d for the two types of sweet doughs SY and DY.

However, for the two types of sweet dough, the rheological behavior was divided in two parts. During the first four weeks of frozen storage, the tan d decrease. After four weeks of storage, tan d increased. This phenomenon was due to the recrystallization of water in the dough matrix. These results were in accordance with the FTIR study. The authors explained these rheological changes to the storage temperature that covers the glass transition tempera-ture Tg. During frozen storage the total ice quantity will not vary unless ice formation was kinetically inhibited during freezing, however ice crystals may undergo changes in shape and size.

Indeed, the ice crystals growth induces a water redistribution causing mechanical damage to the gluten network of frozen doughs Selomulyo and Zhou, , which leads to a reduction of gluten cross-linking. On other hand, transmission electron microscope TEM micrographs high-light the intracellular ice crystals on the yeast cells during freezing data not shown. However, the ice recrystallization accelerated by temperature fluctuations during storage leads to changes in dough matrix by reducing its ability to retain gas Neyreneuf and Delpuech, In addition, the physical state of frozen sweet doughs during frozen storage may affect dough quality.

Therefore, it is important to understand phase and state transitions, including glass transi-tion, occurring in sweet doughs at sub-zero temperatures. The difference between the observed val-ues and the one reported by Laaksonen and Roos could have resulted from the use of different recipes in this paper water—flour mixture. Sugar, salt and butter used in our study have a great ef-fect on freezing properties, decreasing the freezing point. At this temperature of storage, the dough is close to glassy state thermodynamically unstable and a low energy intake can destabi-lize and eventually promote the recrystallization water.

In addition, prolonged storage at temperature near the glassy state can expose the sweet dough for a maximum cryoconcentra-tion effect maximum dehydration of the matrix, because most of the water is frozen around Tg , this phenomenon is amplified by the water diffusion into ice crystals.