Academic literature on the topic 'Modified progressive profiling'

Abstract Tumor-associated autoreactive antibodies could represent a moderately sensitive but highly specific type of biomarker. While autoantibodies in the blood of patients with pancreatic cancer have been reported, the consensus among studies is low and data validation is lacking. We profiled the abundance of circulating autoantibodies in patients with pancreatic ductal adenocarcinoma (PDAC) in a multi-step approach. For this purpose, microarrays with in situ expressed proteins were produced that contained 3060 non-mutated human proteins; one emphasis was on cell surface proteins. The microarrays were utilized for autoantibody screening of sera collected from patients of PDAC stages I, IIA, IIB/III and IV. In addition, samples were studied that represented the different grades of the precursor lesion intraductal pupillary mucinous neoplasm (IPMN) – low-grade, high-grade dysplasia and IPMN with associated carcinoma. Third, sera from patients diseased with the PDAC risk factor chronic pancreatitis (CP) as well as healthy donors served as control groups. The analysis revealed a significant increase in the overall proportion of immunoreactive proteins in late grades of IPMN and stages of PDAC; within each group, some sera displayed higher reactivity than others. The screening phase led to the identification of about 100 proteins, which showed a relatively high immunoreactivity associated with PDAC in comparison to an age- and sex-matched healthy control group. The characteristics of PDAC-associated autoantibodies were confirmed for the 100 proteins by analyzing sera from a total of 1200 PDAC, IPMN and CP patients as well as healthy donors. The patient groups were age- and sex-matched among each other. This confirmation phase validated the PDAC-related immunoreactivity of 17 proteins, showing high specificity of samples from PDAC patients in comparison to the healthy control group but low sensitivity of less than 10%. The clinically defined PDAC stages displayed different autoantibody profiles. However, no stage-related autoantibodies could be identified. Further, these PDAC-related antigens were also immunoreactive in smaller proportions of CP and IPMN patients, demonstrating the biological relation between PDAC and its precursors CP and IPMN. The majority of the other antigens showed a high immunoreactivity without correlation of autoantibody abundance and PDAC diagnosis, highlighting the importance of validation in large cohorts. The presence of autoantibodies specific for the 17 identified PDAC-related proteins is currently technically cross-validated by Luminex multiplex serology. In conclusion, the study has identified novel PDAC-related autoantibodies towards non-modified human proteins. While the specificity of some detected autoantibodies was high, the low sensitivity and the immunoreactivity of related precursor lesions make the definition of a broad applicable biomarker panel unlikely or too complex. However, the antigens that are specific for PDAC indicate target molecules, which could offer new therapeutic options in a personalized approach. Citation Format: Henning Boekhoff, Laura Hendricks, Elena Cairo, Andrea Bauer, Mari Hambardzumyan, Markus W. Büchler, Silvia Calderazzo, Vivienn Weru, Anette Kopp-Schneider, Hermann Brenner, Thilo Hackert, Oliver Strobel, Tim Waterboer, Nathalia Giese, Joerg D. Hoheisel. Profiling of circulating autoreactive antibodies in some 1200 patients with pancreatic ductal adenocarcinoma and progressive precursor lesions [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A035.

In athletes, exercise training induces autonomic nervous system (ANS) adaptations that could be used to monitor training status. However, the relationship between training and ANS in athletes has been investigated without regard for individual training loads. We tested the hypothesis that in long-distance athletes, changes in ANS parameters are dose-response related to individual volume/intensity training load and could predict athletic performance. A spectral analysis of heart rate (HR), systolic arterial pressure variability, and baroreflex sensitivity by the sequences technique was investigated in eight recreational athletes during a 6-mo training period culminating with a marathon. Individualized training load responses were monitored by a modified training impulse (TRIMPi) method, which was determined in each athlete using the individual HR and lactate profiling determined during a treadmill test. Monthly TRIMPi steadily increased during the training period. All the ANS parameters were significantly and very highly correlated to the dose of exercise with a second-order regression model ( r2 ranged from 0.90 to 0.99; P < 0.001). Variance, high-frequency oscillations of HR variability (HRV), and baroreflex sensitivity resembled a bell-shaped curve with a minimum at the highest TRIMPi, whereas low-frequency oscillations of HR and systolic arterial pressure variability and the low frequency (LF)-to-high frequency ratio resembled an U-shaped curve with a maximum at the highest TRIMPi. The LF component of HRV assessed at the last recording session was significantly and inversely correlated to the time needed to complete the nearing marathon. These results suggest that in recreational athletes, ANS adaptations to exercise training are dose related on an individual basis, showing a progressive shift toward a sympathetic predominance, and that LF oscillations in HRV at peak training load could predict athletic achievement in this athlete population.

Abstract Follicular lymphoma (FL) is an indolent, but incurable malignancy as most patients eventually experience progressive disease. We hypothesized that clonal heterogeneity and patient-specific immune responses would contribute to variable clinical outcomes and that understanding the complexity of the entire tumor "ecosystem" would allow us to better match patients with specific types of tumor- and immune-targeted therapies. In this study, we performed 38-dimensional single-cell phenotyping by mass cytometry (CyTOF) to simultaneously characterize both the substructure of malignant B cell populations as well as the T cell microenvironment in a cohort of 77 diagnostic patient FL biopsies and 35 benign reactive LN (rLN) biopsies. We first applied the t-distributed Stochastic Neighbour Embedding (t-SNE) algorithm to explore intra- and inter- tumoral heterogeneity among malignant B cell populations. t-SNE mapping of individual samples showed that more than a third of FL samples contain at least two phenotypically distinct tumor subpopulations, supporting the notion of multi-clonal tumor architectures presumably due to ongoing clonal evolution. Batched analysis combining all 77 FL cases together with 35 rLN samples revealed two distinct tumor subtypes comprising about 25% (type "A") and 10% (type "B") of total FL samples, respectively, with individual tumors within each subtype showing highly similar and partially overlapping phenotypes. Mapping the same data using Uniform Manifold Approximation and Projection (UMAP), a dimensional reduction algorithm similar to t-SNE but preserves global structure more accurately, revealed that type A tumors localized in close proximity to normal germinal center (GC) B cells, thus fulfilling conventional expectations as to the histogenesis of FL. In contrast, type B tumors localized more closely to pre-GC B cells, implying the existence of an alternate histogenic path in FL. Importantly, we also performed single-cell RNA-Seq on a subset of FL cases which independently confirmed the type A vs type B distinction in whole transcriptomic space. We next analyzed matching T cell data using a modified Statistical Scaffold algorithm in order to place distinct subsets in context with conventionally defined normal T cell populations. Clustering analysis using multi-layer phenograph performed on T cells from all FL and rLN samples combined yielded hundreds of small, but phenotypically distinct populations that were then annotated according to the nearest conventionally defined T cell subset. These imputed designations were used as features to perform hierarchical clustering of samples which revealed 3 major clusters. Cluster1 was characterized by mostly naive T cell populations and contained the majority of rLN samples. Cluster2 was characterized by more differentiated effector T cell populations and was dominated by FL samples. Samples within Cluster2 could be further divided into Tfh, Treg and Th1-rich subgroups. Cluster3 was characterized by a diverse T cell environment including naive, memory and differentiated effector subsets and contained a mixture of rLN and FL samples. Integrative analysis correlating B- and T- cell features revealed type B FL tumors were associated with a Tfh-rich immune landscape. Taken together, these data reveal pervasive phenotypic heterogeneity in both malignant and immune cell compartments of patient FL samples and suggest that defining tumoral subtypes as well as the status of the local immune response within individual samples will support more refined diagnostic classification and highlight functional interactions most amenable to therapeutic targeting. Disclosures Gascoyne: NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies. Scott:Celgene: Consultancy, Honoraria; Roche: Research Funding; NanoString: Patents & Royalties: Named Inventor on a patent licensed to NanoString Technologies, Research Funding; Janssen: Research Funding. Steidl:Juno Therapeutics: Consultancy; Seattle Genetics: Consultancy; Nanostring: Patents & Royalties: patent holding; Bristol-Myers Squibb: Research Funding; Tioma: Research Funding; Roche: Consultancy.

e12583 Background: Breast cancer is a heterogeneous disease with distinct biological subtypes as determined by gene expression profiling studies. Breast cancer is most common cancer in Indian females and is believed to be biologically different from west, notably in terms of high prevalence of Triple negative subtype (TNBC). Reliable data on clinical and epidemiological profile of TNBC in Indian population is scarce. Aim of this study was to analyze the epidemiological and clinical profile of TNBCs Methods: Data of 355 patients of breast cancer registered in our department between 2013 and 2015 and followed up until December 2016 was collected and reviewed for epidemiological and clinical features Results: Of total 355 patients analysed, TNBC group was most common (n = 152) (43%) followed by Luminal A (25%). Median age at disease presentation in TNBC was 42.4 years compared to overall age of 45.3 years (24–73 years). In TNBC subgroup, 48% patients presented in locally advanced and 15% in metastatic stage, more commonly in pre-menopausal patients. Overall 268 (76%) patients underwent surgery with Modified radical mastectomy being preferred surgical option (86%), followed by adjuvant chemotherapy. TNBC subgroup demonstrated low response rate to neoadjuvant chemotherapy with only 9% of patients having complete response and 25% patients having progressive disease. Median followup was 34 months (6 50 months). Of the total recurrences (n = 19), nearly 2/3rd (n = 13) were documented in TNBC subgroup. Disease free survival (DFS) of TNBC subgroup was lower than of other luminal subtypes (p = .043) Conclusions: TNBC was the most common breast cancer subtype (43%) in Indian population which is nearly twice the rate reported in Western countries. This finding has significant clinical relevance as it may contribute to poor outcomes in Indian patients. Our study also corraborated this fact with higher prevalence of premenopausal breast cancer, poor response to neoadjuvant chemotherapy, high recurrence rates and decreased disease free survival. Additional research is needed to understand the determinants of TNBC in India as it is a prognostic group with aggressive behaviour that commonly lack the benefit of any specific targeted therapy

Increased export of transglutaminase-2 (TG2) by tubular epithelial cells (TECs) into the surrounding interstitium modifies the extracellular homeostatic balance, leading to fibrotic membrane expansion. Although silencing of extracellular TG2 ameliorates progressive kidney scarring in animal models of CKD, the pathway through which TG2 is secreted from TECs and contributes to disease progression has not been elucidated. In this study, we developed a global proteomic approach to identify binding partners of TG2 responsible for TG2 externalization in kidneys subjected to unilateral ureteric obstruction (UUO) using TG2 knockout kidneys as negative controls. We report a robust and unbiased analysis of the membrane interactome of TG2 in fibrotic kidneys relative to the entire proteome after UUO, detected by SWATH mass spectrometry. The data have been deposited to the ProteomeXchange with identifier PXD008173. Clusters of exosomal proteins in the TG2 interactome supported the hypothesis that TG2 is secreted by extracellular membrane vesicles during fibrosis progression. In established TEC lines, we found TG2 in vesicles of both endosomal (exosomes) and plasma membrane origin (microvesicles/ectosomes), and TGF-β1 stimulated TG2 secretion. Knockout of syndecan-4 (SDC4) greatly impaired TG2 exosomal secretion. TG2 coprecipitated with SDC4 from exosome lysate but not ectosome lysate. Ex vivo, EGFP-tagged TG2 accumulated in globular elements (blebs) protruding/retracting from the plasma membrane of primary cortical TECs, and SDC4 knockout impaired bleb formation, affecting TG2 release. Through this combined in vivo and in vitro approach, we have dissected the pathway through which TG2 is secreted from TECs in CKD.

BackgroundOSE2101 (Tedopi®) is an anticancer vaccine with HLA-A2+ restricted modified epitopes targeting five tumor-associated antigens (TAAs) frequently expressed in lung cancer (CEA, HER2, MAGE2, MAGE3, P53). Step-1 results of the phase III, randomized, open-label ATALANTE-1 study comparing Tedopi® vs standard treatment (SoC) showed a favorable benefit/risk of Tedopi® over SoC (HR 0.71 for overall survival OS) in HLA-A2+ NSCLC patients in 2nd or 3rd line treatment after progression on immune checkpoint blockers (ICB).1 We analyze available tumor biopsies at initial diagnosis from some patients treated with Tedopi® to determine the expression of the 5 TAAs and to identify other tumor factors associated with long-term survival.MethodsTumor biopsies were available for 8 HLA-A2+ (blood test) stage IV NSCLC patients included in the trial. Primary (<12 weeks) and secondary (≥ 12 weeks) resistance to ICB were observed in 3 (38%) and 5 (62%) of patients. Best response to Tedopi® and OS were: 1 partial response (PR) (OS of 33 months), 3 stable disease (SD) (OS of 22, 26 and 41 mo.) and 4 disease progression (PD) (OS of 3, 4, 30 and 31 mo.). HLA-class I, PD-L1, CD8 T-cells, HER2, CEA and P53 tumor expression were evaluated by immunohistochemistry (IHC). NanoString gene expression profiling was performed using the Pan Cancer Immune gene set.ResultsHLA-class I was expressed in all tumor samples. IHC analysis revealed that P53, CEA and HER2 were expressed in 6/7, 5/7 and 0/7 patients, respectively. P53, CEA, HER2, MAGE2, and MAGE3 were detected at RNA level in 5/5 tested patients (table 1). IMMUNOSCORE® IC CD8/PDL1 analysis showed High/High, High/Low and Low/Low scores for 1/7, 1/7 and 5/7 patients, respectively. The High/High IMMUNOSCORE® with a pronounced CD8+ T-cell tumor infiltration was observed in the patient with PR. High percentage of tumor cells expressing P53 (69%–97%) and overexpression of genes associated with activated macrophages (TREM2, MARCO, SLC11A1, CHIT1, SERPINB2) were observed in the PR and SD patients. High IFN-gamma and Expanded Immune Gene Signature scores were observed in long-term survivor patients with secondary resistance to ICB, even after progressive disease.Abstract 366 Table 1Summary of clinical and translational dataCEACarcinoembryonic antigen; HER2: Human Epidermal Growth Factor Receptor-2; ICB: Immune checkpoint blocker; IHC: Immunohistochemistry; ND: Not determined; OS: Overall Survival; Patient ID: Patient identification; PDL1: Programmed death-ligand 1; PFS: Progression-free survival; ssGSEA: Single-sample Gene Set Enrichment Analysis. Blue bars = Length of overall survival; Green bars = Gene Signature upregulation; Red bars = Gene Signature downregulationConclusionsThis study shows that all HLA-A2+ patients (blood test), expressed HLA class I in the tumors at initial diagnosis. Transcriptomic data in the patients that benefited from Tedopi® showed activated macrophage pathway, high IFN-gamma and Expanded Immune Gene Signatures scores. These data will be validated on larger number of patients treated with Tedopi® after the step 2 analysis.AcknowledgementsWe thank Julie Le Boulicaut, François Montestruc and Constant Josse (eXYSTAT, Malakoff, France) for the statistical analysis, and HalioDx for the IHC and NanoString analysis.Trial RegistrationEudraCT number2015-003183-36; NCT number: NCT02654587ReferenceGiaccone, et al. Activity of OSE-2101 in HLA-A2+ non-small cell lung cancer (NSCLC) patients after failure to immune checkpoint inhibitors (ICI): step 1 results of phase III ATALANTE-1 randomised trial. ESMO meeting 2020, abstract #1260MO.Ethics ApprovalThe study protocol and its related documents (including the patient information and informed consent form) received approval from the Institutional Review Board (IRB), and the Competent Authority prior to study initiation.ConsentEach patient gave his/her written informed consent prior to study enrolment.

Background: Inherited cardiomyopathy associates with a range of phenotypes, mediated by genetic and nongenetic factors. Noninherited cardiomyopathy also displays varying progression and outcomes. Expression of cardiomyopathy genes is under the regulatory control of promoters and enhancers, and human genetic variation in promoters and enhancers may contribute to this variability. Methods: We superimposed epigenomic profiling from hearts and cardiomyocytes, including promoter-capture chromatin conformation information, to identify enhancers for 2 cardiomyopathy genes, MYH7 and LMNA . Enhancer function was validated in human cardiomyocytes derived from induced pluripotent stem cells. We also conducted a genome-wide search to ascertain genomic variation in enhancers positioned to alter cardiac expression and correlated one of these variants to cardiomyopathy progression using biobank data. Results: Multiple enhancers were identified and validated for LMNA and MYH7 , including a key enhancer that regulates the switch from MYH6 expression to MYH7 expression. Deletion of this enhancer resulted in a dose-dependent increase in MYH6 and faster contractile rate in engineered heart tissues. We searched for genomic variation in enhancer sequences across the genome, with a focus on nucleotide changes that create or interrupt transcription factor binding sites. The sequence variant, rs875908, disrupts a T-Box Transcription Factor 5 binding motif and maps to an enhancer region 2 kilobases from the transcriptional start site of MYH7. Gene editing to remove the enhancer that harbors this variant markedly reduced MYH7 expression in human cardiomyocytes. Using biobank-derived data, rs875908 associated with longitudinal echocardiographic features of cardiomyopathy. Conclusions: Enhancers regulate cardiomyopathy gene expression, and genomic variation within these enhancer regions associates with cardiomyopathic progression over time. This integrated approach identified noncoding modifiers of cardiomyopathy and is applicable to other cardiac genes.

Cellular metabolic changes reflect the characteristics of patients with acute myeloid leukemia (AML) caused by genetic variations, which are important in establishing AML treatment. However, little is known about the metabolic profile of patients with genetic variation-induced AML. Furthermore, the metabolites differ with disease progression. Here, metabolites in the bone marrow serum of ten patients with AML and healthy individuals were analyzed using gas chromatography–mass spectrometry. Compared with that in healthy individuals, expression of most metabolites decreased in patients with AML; hydroxylamine, 2-hydroxybutyric acid, monomethylphosphate, and ethylphosphate expression was unusually increased in the patients. We further examined serial metabolite changes across the initial diagnosis, postremission, and relapse phases. Patients with relapse showed increased metabolite expression compared with those in the diagnostic phase, confirming that patients with AML had aggressively modified leukemic cells. However, a clear difference in metabolite distribution was not observed between the diagnosis and complete remission phases, suggesting that the metabolic microenvironment did not change significantly despite complete remission. Interestingly, metabolite profiles differed with genetic variations in leukemic cells. Our results, which were obtained using paired samples collected during AML progression, provide valuable insights for identifying vulnerable targets in the AML metabolome and developing new treatment strategies.

Abstract Current therapy for multiple myeloma (MM) remains empiric. Only 30–40% of patients respond to any one agent. Moreover, with each new therapy attempted, patients often experience numerous complications and toxicities requiring specialized intervention. In last 4 years four new agents have been approved for use in MM making selection of effective agents more difficult as well as economically taxing. With the improved understanding of oncogenomics in MM and with an ultimate goal of selecting therapies based on their best chance of success, we have used expression profile of myeloma cells to identify expression signature associated with response or resistance to therapeutic agents. We evaluated 34 newly-diagnosed patients with MM enrolled on IFM protocol 2005-01 and treated with bortezomib and dexamethasone as an induction regimen. 18 patients had achieved CR/nCR while 16 patients had no response or progressive disease on therapy. MM cells were purified from bone marrow samples collected prior to initiation of therapy and expression profile was obtained using Affymetrix Human Exon 1.0 ST arrays and analyzed using the dChip software. We next used the “Sample Classification” module in the dChip software to explore predicting patient response using expression data. When we Use two-sample comparison or ANOVA methods to compare the response and to obtain a gene list, and then use a Linear Discriminant Analysis (LDA) to use these genes as features to train a classifier and predict samples, a prediction accuracy of 97% (33/34) was obtained. For unbiased prediction, we modified dChip to perform a leave-one-out cross-validation. Specifically, for each round, one of the 34 samples is left out and the remaining 33 samples are used to select genes and train the classifier. Then the classifier is used to predict the response of the left-out sample and compare it to the real response of this sample. With this analysis we observed 80% positive predictive value which compares favorably with the present CR ratio in the cohort from which these 34 samples come from. In addition, we also used the same cross-validation method to classify the 8 nCR (immunofixation (IFE) positive CR) versus the 10 CR (IFE negative CR) samples. Although the best achievable overall accuracy is 83%, the accuracy is much more variable than the CR versus NR classification when we vary the gene selection stringency. We also realize and in fact foresee that the expression profile will not be able to predict all patients and due to various factors some samples will not provide clear signature of resistance or sensitivity. A two-group comparison of the response Yes and No samples identified response-related genes. The genes down-regulated in the response group are significantly enriched by genes in Gene Ontology categories “biopolymer glycosylation”, “integral to Golgi membrane”, “transferase activity and gene on chromosome 11q.13. The genes up-regulated in the response group are significantly enriched by genes in Gene Ontology categories “cytoskeleton” and genes on chromosome 12p11 and 4p14. These genes provide a basis for investigating how gene expression and pathways change could affect response to the combination treatment with the two drugs. In conclusion, our preliminary pharmacogenomic studies have confirmed our ability to perform large-scale micro-array profiling from patient bone marrow samples and we have identified gene expression signature associated with responsiveness (CR) versus resistance (NR) to combination of Velcade and dexamethasone. The task ahead is to now prospectively validate our ability to predict whether the combination of bortezomib and dexamethasone will be effective in a given patient.

Astringency is an important mouthfeel factor driving wine quality, complexity and consumer preferences. Wine astringency is mainly perceived due to the interactions between polyphenols in wine and salivary proteins during consumption. The wine industry has invested heavily in the analysis of wine phenolic composition and its effects on flavour/mouthfeel. However, our understanding regarding the relationships between specific phenolic fractions/compounds and their respective astringent mouthfeel and sub-qualities (e.g. grippy, puckering), as well as novel and improved techniques for measuring astringency perception and modification of wine astringency levels, are still limited. This thesis comprises a number of studies to investigate these research gaps. The findings of these studies are contained within the thesis chapters two through to and inclusive of chapter five. These are presented here as two published, peer-reviewed papers, one submitted manuscript and one unsubmitted work written in a short research communication format following the introductory chapter one and are outlined in the following summary. Firstly, in an attempt to improve methods to examine human astringency perception and elucidate the different yet more subtle astringent sub-qualities caused by different chemical parameters (basic wine composition and phenolic profiles), a modified progressive profiling was explored. Dynamic astringency profiles of 13 Australian commercial red wines and 2 roses made from 1 1 grape varieties were generated using a trained, modified progressive profiling sensory panel. Overall astringency intensity and 6 sub-qualities: pucker, mouth coat, dry, grippy, adhesive and graininess defined by the panel were rated at six time periods (lasting 10 seconds each), with 20 second gaps between each period. Wine composition and phenolic profiles were also determined to establish correlations with mouthfeel attributes. This alternative sensory methodology enabled dynamic and quantitative intensity measurement of astringent attributes, providing enhanced understanding of the chemical basis of subtle wine astringent sub-quality differences. Secondly, due to consumer demand for non-animal-derived processing aids, the efficacy of potato proteins to manipulate astringent compounds in red wine and the steps required for its optimisation of fining were investigated. This represented the first study to examine the potato protein dose-response kinetics of tannin and phenolic compound removal for two unfined Cabernet Sauvignon wines. Testing the influence of wine matrix and fining parameters (including pH, ethanol concentration, sugar concentration, temperature, and agitation) were according to a fractional 25- 1 factorial design. Insights into potato proteins' optimal use revealed that fining efficiency could be increased by treating wines at higher than usual cellar temperatures (20 °C), and at both a lower pH and/or alcohol concentration. Thirdly, an investigation of a new grape-must polyphenol extraction technique: Accentuated-Cut-Edges (ACE) revealed its capacity for modifying wine astringency. This study reported the effect of the ACE technique on non-volatile chemical composition of Shiraz wine (basic wine chemistry, colour, phenolic components and polysaccharides) and sensory profiles (using rate-all-that-apply and modified progressive profiling) for the first time. Furthermore, any potential improvement provided by ACE for the pre-fermentation water addition to must to reduce alcohol was investigated. The ACE technique increased the intensities of adhesiveness and graininess, which partly overcame the impact of water addition on the astringent sensation. Fourthly, as the experimental Shiraz wines for the ACE study were produced in smallscale fermentation batches (25kg), an investigation at the industrial scale was warranted. Therefore, two pilot commercial wines (ACE with 5-day skin contact and NOACE with 8 days on skins) were produced in 2018 by the Corio le winery at industry scale (averaged 2.45 tonnes for each treatment) and were chemically analysed and underwent sensory profiling in 2019 alongside the ACE research wines in Chapter four. It was a preliminary experiment investigating the feasibility of ACE grape must extraction technique on Shiraz wines at an industry scale. This study indicated that ACE could potentially be used by the wine industry to combat one of the challenges of climate change, vintage compression, caused by climate change, by pressing wine ferments earlier, freeing up tank space for other wines. In conclusion, the research contained in this thesis provides advanced insights and alternative tools for researchers and the wine industry. Uncovering what components impact wine astringency, knowing how to better evaluate perceived wine astringency along with its sub-qualities and modify this important wine sensory attribute with a more informed approach, will enhance the capability of wine producers to better cope with some of the ramifications of climate change such as higher alcohol levels and vintage compression, target product style and quality plus meet consumer expectations.
Thesis (Ph.D.) -- University of Adelaide, Schools of Agriculture, Food and Wine, 2020