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Academic literature on the topic 'Predicting molecular response in CML'

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Published: 10 December 2022
Last updated: 29 January 2023

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Journal articles on the topic "Predicting molecular response in CML"

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Wolf, Dominik, and Sieghart Sopper. "Molecular response prediction in CML: novel ideas?" Oncotarget 8, no. 46 (September 19, 2017): 80105–6. http://dx.doi.org/10.18632/oncotarget.21049.

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Wolf, Dominik, and Sieghart Sopper. "Correction: Molecular response prediction in CML: novel ideas?" Oncotarget 9, no. 88 (November 9, 2018): 35871. http://dx.doi.org/10.18632/oncotarget.26360.

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Attili, S. V., P. Bapsy, D. Lokanatha, K. Govindababu, J. George, L. A. Jacob, H. K. Dadhich, and G. Anupama. "Are skin reactions a surrogate marker in predicting response to therapy in patients with chronic myeloid leukemia receiving imatinib?" Journal of Clinical Oncology 25, no. 18_suppl (June 20, 2007): 17539. http://dx.doi.org/10.1200/jco.2007.25.18_suppl.17539.

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17539 Background: One of the common toxicities observed with small molecule tyrosine kinase inhibitors are skin rashes, which were proven to predict the response to therapy in cases of lung cancer (Ann. Onc., 2005; 16(5): 780 - 785). However, very few have evaluated the same in patients with chronic myeloid leukemia (CML) on treatment with imatinib. Therefore we thought of doing a prospective study to evaluate skin rashes, and compare it with the clinical, hematological, cytogenetic and molecular remission rates in CML patients on Imatinib therapy. Methods: It is a non randomized, prospective study conducted at a tertiary care cancer center with an approximate attendance of 15,000 new cases. The patients were stratified into those who had skin reactions and do not. CTC version 3.0 was used to assess the skin toxicity. Differences in the proportions were calculated with the help of Medcalc Version 7.5. Results: A total of 314 patients with CML were evaluated who were on regular treatment with Imatinib. Hematological response was assessed monthly, cytogenetic analysis (available in 212 patients) at the end of 3rd month and molecular response (available in 136 patients) at the end of 6th months respectively. The response rates in two groups are as follows. *Percentages calculated for the subset of patients in whom results of either cytogenetic or molecular response are available Conclusion: Our findings suggest that skin reactions are not a good marker to predict either response rates or progression free interval in cases of CML. This is further substantiated by the findings that the percent of skin reactions in west are far less compared to our results, who had a better molecular as well as cytogenetic responses. [Table: see text] No significant financial relationships to disclose.
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Hu, Shiwei, Dan Chen, Xiaofei Xu, Lan Zhang, Shengjie Wang, Keyi Jin, Yan Zheng, Xiaoqiong Zhu, Jie Jin, and Jian Huang. "Targeted Next-Generation Sequencing Identifies Additional Mutations Other than BCR∷ABL in Chronic Myeloid Leukemia Patients: A Chinese Monocentric Retrospective Study." Cancers 14, no. 23 (November 23, 2022): 5752. http://dx.doi.org/10.3390/cancers14235752.

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A proportion of patients with somatic variants show resistance or intolerance to TKI therapy, indicating additional mutations other than BCR∷ABL1 may lead to TKI treatment failure or disease progression. We retrospectively evaluated 151 CML patients receiving TKI therapy and performed next-generation sequencing (NGS) analysis of 22 CML patients at diagnosis to explore the mutation spectrum other than BCR∷ABL1 affecting the achievement of molecular responses. The most frequently mutated gene was ASXL1 (40.9%). NOTCH3 and RELN mutations were only carried by subjects failing to achieve a major molecular response (MMR) at 12 months. The distribution frequency of ASXL1 mutations was higher in the group that did not achieve MR4.0 at 36 months (p = 0.023). The achievement of MR4.5 at 12 months was adversely impacted by the presence of >2 gene mutations (p = 0.024). In the analysis of clinical characteristics, hemoglobin concentration (HB) and MMR were independent factors for deep molecular response (DMR), and initial 2GTKI therapy was better than 1GTKI in the achievement of molecular response. For the scoring system, we found the ELTS score was the best for predicting the efficacy of TKI therapy and the Socal score was the best for predicting mutations other than BCR∷ABL.
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Glauche, Ingmar, Christoph Baldow, Sabine Fröhlich, Philipp Schulze, Amit Roy, Milayna Subar, Xiaoning Wang, and Ingo Roeder. "Model-Based Characterization of the Molecular Response Dynamics of Tyrosine Kinase Inhibitor (TKI)-Treated CML Patients – a Comparison of Imatinib and Dasatinib First-Line Therapy." Blood 124, no. 21 (December 6, 2014): 4562. http://dx.doi.org/10.1182/blood.v124.21.4562.4562.

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Abstract Background: Chronic myeloid leukemia (CML) is characterized by the expression of the BCR-ABL fusion protein in virtually all malignant cells in the vast majority of patients. This molecular specificity forms the basis of a highly efficient, targeted therapy by TKIs. The success of this therapeutic approach is the reason that CML has developed into a showcase example for an efficient, targeted tumor therapy. Methods: As previously shown, the application of a single-cell–based mathematical model, which describes CML as a clonal competition between normal and leukemic hematopoietic stem cells, can consistently describe the median long-term BCR-ABL transcript levels in response to the first-generation TKI imatinib [1]. Furthermore, it has been demonstrated that a similar modeling approach also allows predicting the molecular long-term response to imatinib in individual patients [2]. Specifically, we showed that these predictions, including the determination of an optimal, patient-specific time point for potential treatment cessation, can be derived directly from time course data of the BCR-ABL transcript levels. Here we present novel results on the application of a similar analysis strategy for CML patients, treated with the second-generation TKI dasatinib. Based on unpublished data describing the 4-year molecular response dynamics (ie, BCR-ABL transcript levels) observed in a randomized, controlled clinical trial (DASISION [3]), we directly compare the effects of dasatinib (n=253) and imatinib (n=255). Results: These data show an accelerated and deeper median molecular response in the dasatinib arm (Figure 1). We confirmed this observation by statistical analysis, describing the BCR-ABL response kinetics by a bi-phasic exponential model. Comparing different characteristic parameters of this model, we could demonstrate a significantly steeper initial decline in the dasatinib arm compared to imatinib (P < 0.001, t-test on mean initial decline). Beyond the statistical analysis, we apply the above-mentioned single-cell–based mathematical model. Adapting its parameters to the specific kinetic characteristics observed under the different treatment conditions, model predictions for both the population and individual patients are derived for both treatment scenarios. In our presentation we will compare the model predictions of long-term BCR-ABL kinetics under first line imatinib and dasatinib treatment. The population and patient-specific model predictions will include BCR-ABL levels in the peripheral blood and bone marrow, as well as the estimated risk of molecular relapses after stopping treatment and, related to this, optimal time points for potential treatment cessation. Conclusion: Our analysis suggests that the application of model-prediction tools, previously used for the first-generation TKI imatinib, can be applied to other TKIs. The steeper initial decline in the dasatinib arm may be relevant in estimating relapse risk, which will be determined from long-term outcome of ongoing discontinuation trials. [1] Roeder I et al. (2006) Nat. Med. [2] Horn M et al. (2013) Blood. [3] Cortes JE et al. ASH 2013, Abstract #653. Figure 1: Observed median molecular response dynamics of TKI-treated CML patients. Error bars represent inter-quartile ranges. Figure 1:. Observed median molecular response dynamics of TKI-treated CML patients. Error bars represent inter-quartile ranges. Disclosures Glauche: Bristol-Myers Squibb: Research Funding. Fröhlich:Bristol-Myers Squibb: Employment. Roy:Bristol-Myers Squibb: Employment, Equity Ownership. Subar:Bristol-Myers Squibb: Employment. Wang:Bristol-Myers Squibb: Employment.
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Dybko, Jarosław, Bożena Jaźwiec, Olga Haus, Donata Urbaniak-Kujda, Katarzyna Kapelko-Słowik, Tomasz Wróbel, Tomasz Lonc, et al. "The Hasford Score May Predict Molecular Response in Chronic Myeloid Leukemia Patients: A Single Institution Experience." Disease Markers 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/7531472.

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The Sokal, Hasford, and EUTOS scores were established in different treatment eras of chronic myeloid leukemia (CML). None of them was reported to predict molecular response. In this single center study we tried to reevaluate the usefulness of three main scores in TKI era. The study group included 88 CML patients in first chronic phase treated initially with standard imatinib dose. All of them achieved major molecular response (MMR) in time points defined by European LeukemiaNet (ELN). 42 patients lost MMR in a median time of 47 months and we found a significant difference in MMR maintenance between intermediate-risk (IR) and low-risk (LR) patients assessed by Hasford score. All 42 patients were switched to second-generation TKI (2G-TKI) treatment. At 18 months of 2G-TKI therapy we have still found a significant difference in BCR-ABL transcript levels and MMR rate between IR and LR groups. We did not find any of the described differences discriminating patients by Sokal or EUTOS score. In this retrospective single center analysis we found Hasford score to be useful in predicting molecular response in first chronic phase of CML patients.
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Banjar, Haneen R., and Enaam Alsobhi. "Consistency Test between Scoring Systems for Predicting Outcomes of Chronic Myeloid Leukemia in a Saudi Population Treated with Imatinib." International Scholarly Research Notices 2017 (February 13, 2017): 1–6. http://dx.doi.org/10.1155/2017/1076493.

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Inconsistency in prognostic scores occurs where two different risk categories are applied to the same chronic myeloid leukemia (CML) patient. This study evaluated common scoring systems for identifying risk groups based on patients’ molecular responses to select the best prognostic score when conflict prognoses are obtained from patient profiles. We analyzed 104 patients diagnosed with CML and treated at King Abdulaziz Medical City, Saudi Arabia, who were monitored for major molecular response (achieving a BCR-ABL1 transcript level equal to or less than 0.1%) by Real-Time Quantitative Polymerase Chain Reaction (RQ-PCR), and their risk profiles were identified using Sokal, Hasford, EUTOS, and ELTS scores based on the patients’ clinical and hematological parameters at diagnosis. Our results found that the Hasford score outperformed other scores in identifying risk categories for conflict groups, with an accuracy of 63%.
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Haznedaroglu, Ibrahim C. "MONITORING THE RESPONSE TO TYROSINE KINASE INHIBITOR (TKI) TREATMENT IN CHRONIC MYELOID LEUKEMIA (CML)." Mediterranean Journal of Hematology and Infectious Diseases 6, no. 1 (December 31, 2013): e2014009. http://dx.doi.org/10.4084/mjhid.2014.009.

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The aim of oral tyrosine kinase inhibitor (TKI) treatment in chronic myeloid leukemia (CML) is to get ideal hematological, cytogenetic, molecular responses at the critical time-points. The depth of the response obtained with TKI and time to achieve this response are important for the prediction of prognosis in the patient with CML. The high efficacy of the TKI treatment of CML has prompted the need for accurate methods to monitor response at levels below the landmark of CCyR. Quantification of BCR-ABL transcripts has proven to be the most sensitive method available and has shown prognostic impact with regard to progression-free survival. European LeukemiaNet (ELN) molecular program harmonized the reporting of results according to the IS (Internatıonal harmonization of Scale) in Europe. The aim of this review is to outline monitoring the response to optimal TKI treatment based on the ELN CML 2013 recommendations from the clinical point of view as a physician. Careful cytogenetic and molecular monitoring could help selecting the most convenient TKI drug and to optimize TKI treatment. Excessive monitoring may have an economical cost but failure to optimize TKI treatment may result in CML disease acceleration and death.
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Sopper, Sieghart, Satu Mustjoki, Deborah White, Timothy Hughes, Peter Valent, Andreas Burchert, Bjørn T. Gjertsen, et al. "Reduced CD62L Expression on T Cells and Increased Soluble CD62L Levels Predict Molecular Response to Tyrosine Kinase Inhibitor Therapy in Early Chronic-Phase Chronic Myelogenous Leukemia." Journal of Clinical Oncology 35, no. 2 (January 10, 2017): 175–84. http://dx.doi.org/10.1200/jco.2016.67.0893.

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Purpose Immunologic surveillance of minimal residual disease in chronic myelogenous leukemia (CML) may be relevant for long-term control or cure of CML. Little is known about immune-modulatory effects of nilotinib in vivo, potentially predicting response to therapy. Patients and Methods A prospective and comprehensive flow cytometry–based immunomonitoring program paralleled the ENEST1st clinical study, investigating 52 nilotinib-naïve patients with chronic-phase CML. Data were verified in independent validation cohorts. Results T cells of patients with CML at diagnosis expressed low l-selectin (CD62L) levels, which was not a result of proportional aberrations of T-cell subsets. Low numbers of CD62L-expressing CD4+ and CD8+ T cells correlated with higher Sokal score, increased spleen size, and high leukocyte and peripheral-blood blast counts. At month 6 during nilotinib therapy, CD62L expression returned to levels of healthy individuals. The level of CD62L loss on T cells directly correlated with the extent of soluble CD62L (sCD62L) elevation. In parallel, the proteolytic activity of tumor necrosis factor α–converting enzyme (TACE; ADAM17, CD156b), the metalloproteinase shedding CD62L, was increased at diagnosis and significantly decreased during nilotinib treatment. High CD62L+ expression on both CD4+ and CD8+ T cells and, vice versa, low sCD62L levels at CML diagnosis were linked to superior molecular responses. These findings were corroborated in independent validation cohorts. Conclusion We demonstrate the prognostic impact of CD62L shedding from T cells and increased sCD62L plasma levels at CML diagnosis on molecular response to tyrosine kinase inhibitor therapy in early chronic-phase CML. Functionally, decreased CD62L may be a consequence of increased TACE-mediated CD62L cleavage and potentially impairs immune-cell function. Larger prospective studies are ongoing to confirm the prognostic relevance of this finding.
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de Lavallade, Hugues, Jane F. Apperley, Jamshid S. Khorashad, Dragana Milojkovic, Alistair G. Reid, Marco Bua, Richard Szydlo, et al. "Imatinib for Newly Diagnosed Patients With Chronic Myeloid Leukemia: Incidence of Sustained Responses in an Intention-to-Treat Analysis." Journal of Clinical Oncology 26, no. 20 (July 10, 2008): 3358–63. http://dx.doi.org/10.1200/jco.2007.15.8154.

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Purpose Imatinib is remarkably effective in treating newly diagnosed patients with chronic myeloid leukemia (CML) in chronic phase (CP). To date, most of the available data come from a single multicenter study in which some of the patients were censored for diverse reasons. Here, we report our experience in treating patients at a single institution in a setting where all events were recorded. Patients and Methods A total of 204 consecutive adult patients with newly diagnosed CML in CP received imatinib from June 2000 until August 2006. Response (hematologic, cytogenetic, and molecular), progression-free survival (PFS) and survival were evaluated. Results At 5 years, cumulative incidences of complete cytogenetic response (CCyR) and major molecular response (MMR) were 82.7% and 50.1%, respectively. Estimated overall survival and PFS were 83.2% and 82.7%, respectively. By 5 years, 25% of patients had discontinued imatinib treatment because of an unsatisfactory response and/or toxicity. The 5-year probability of remaining in major cytogenetic response while still receiving imatinib was 62.7%. Patients achieving a CCyR at 1 year had a better PFS and overall survival than those failing to reach CCyR, but achieving a MMR conferred no further advantage. The identification of a kinase domain mutation was the only factor predicting for loss of CCyR. Conclusion Imatinib is highly effective in most patients with CML-CP; patients who respond are likely to live substantially longer than those treated with earlier therapies. Achieving CCyR correlated with PFS and overall survival, but achieving MMR had no further predictive value. However, approximately one third of patients still need better therapy.
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Dissertations / Theses on the topic "Predicting molecular response in CML"

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Glauche, Ingmar, Matthias Kuhn, Christoph Baldow, Philipp Schulze, Tino Rothe, Hendrik Liebscher, Amit Roy, Xiaoning Wang, and Ingo Roeder. "Quantitative prediction of long-term molecular response in TKI-treated CML – Lessons from an imatinib versus dasatinib comparison." Macmillan Publishers Limited, part of Springer Nature, 2018. https://tud.qucosa.de/id/qucosa%3A32495.

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Longitudinal monitoring of BCR-ABL transcript levels in peripheral blood of CML patients treated with tyrosine kinase inhibitors (TKI) revealed a typical biphasic response. Although second generation TKIs like dasatinib proved more efficient in achieving molecular remission compared to first generation TKI imatinib, it is unclear how individual responses differ between the drugs and whether mechanisms of drug action can be deduced from the dynamic data. We use time courses from the DASISION trial to address statistical differences in the dynamic response between first line imatinib vs. dasatinib treatment cohorts and we analyze differences between the cohorts by fitting an established mathematical model of functional CML treatment to individual time courses. On average, dasatinib-treated patients show a steeper initial response, while the long-term response only marginally differed between the treatments. Supplementing each patient time course with a corresponding confidence region, we illustrate the consequences of the uncertainty estimate for the underlying mechanisms of CML remission. Our model suggests that the observed BCR-ABL dynamics may result from different, underlying stem cell dynamics. These results illustrate that the perception and description of CML treatment response as a dynamic process on the level of individual patients is a prerequisite for reliable patient-specific response predictions and treatment optimizations.
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Höijer, Jonas. "Prognostic Factors for 12 Month Major Molecular Response for Patients with Chronic Myeloid Leukemia." Thesis, Uppsala universitet, Statistiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-201419.

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Chronic Myeloid Leukemia is a kind of blood cancer with around 1 incidence per 100 000 persons/year. After the development of an effective treatment, imatinib, in the late 1990:s, the survival percentage has increased drastically. The high survival has turned the attention to different kinds of treatment responses, which in turn are good prognostic factors to future health status. In this thesis, the focus is on whether or not the patient has achieved a so called major molecular response after 12 month, or not. More precisely, the aim is to find prognostic factors to the 12 month response. In order to find prognostic factors for this binary response variable, a multivariate logistic regression analysis is conducted, with the goal of finding a parsimonious logistic model that describes the data. The analysis is done from a merged dataset from three earlier studies. The prognostic factors in the final model are treatment, 3 month response, and enlarged spleen. However, the residual analysis indicates that the model is incomplete, implying that further research needs to be done.
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Shoeb, Dania. "Factors predicting response to treatment in chronic HCV genotype 3 patients." Thesis, Queen Mary, University of London, 2013. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8450.

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Studies to date have failed to identify the most effective treatment regimes for patients with chronic genotype 3 HCV infection. There is controversy regarding the role of cirrhosis in modifying response and disagreement regarding the impact of ethnicity on treatment outcome. Given the importance of genotype 3 HCV in the global epidemic and the lack of high quality research into this genotype, the purpose of this work has been to address some of the deficiencies in our understanding of the optimal management of this strain of hepatitis C. Specifically we have examined the following hypotheses:- 1) Patients from the Indian sub-continent (South Asians) will respond differently to therapy with pegylated interferon and ribavirin when compared to Caucasians. 2) An analysis of viral and host factors underlying differences between treatment sensitive and treatment refractory cohorts will reveal new insights into the virology of Genotype 3 HCV infection. 3) Increasing the duration of therapy in ‘difficult to manage’ patients with Genotype 3 HCV will improve response rates. 4) Whether non-invasive methods of identifying liver fibrosis are valuable in identifying the stages of fibrosis in Genotype 3 HCV patients. Three different research methodologies were used to address these questions including a metaanalysis of factors associated with treatment failure in patients with genotype 3 HCV, virological and immunological studies on patients with genotype 3 HCV who had failed to respond to therapy and a clinical trial evaluating extended duration therapy in patients with Genotype 3 HCV infection and cirrhosis.
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Hamy, Anne-Sophie. "Identification of Factors Predicting Sensitivity or Resistance to Neoadjuvant Chemotherapy in Breast Cancer Neoadjuvant treatment : the future of patients with breast cancer Neoadjuvant treatment for intermediate/high-risk HER2-positive and triple-negative breast cancers: no longer an “option” but an ethical obligation Long-term outcome of the REMAGUS 02 trial, a multicenter randomised phase II trial in locally advanced breast cancer patients treated with neoadjuvant chemotherapy with or without celecoxib or trastuzumab according to HER2 status BIRC5 (survivin) : a pejorative prognostic marker in stage II/III breast cancer with no response to neoadjuvant chemotherapy Beyond Axillary Lymph Node Metastasis, BMI and Menopausal Status Are Prognostic Determinants for Triple-Negative Breast Cancer Treated by Neoadjuvant Chemotherapy Pathological complete response and prognosis after neoadjuvant chemotherapy for HER2-positive breast cancers before and after trastuzumab era: results from a real-life cohort The presence of an in situ component on pre-treatment biopsy is not associated with response to neoadjuvant chemotherapy for breast cancer Chemosensitivity, tumor infiltrating lymphocytes (TILs), and survival of postpartum PABC patients treated by neoadjuvant chemotherapy Lymphovascular invasion after neoadjuvant chemotherapy is strongly associated with poor prognosis in breast carcinoma New insight for pharmacogenomics studies from the transcriptional analysis of two large-scale cancer cell line panels Biological network-driven gene selection identifies a stromal immune module as a key determinant of triple-negative breast carcinoma prognosis A Stromal Immune Module Correlated with the Response to Neoadjuvant Chemotherapy, Prognosis and Lymphocyte Infiltration in HER2-Positive Breast Carcinoma Is Inversely Correlated with Hormonal Pathways Stromal lymphocyte infiltration after neoadjuvant chemotherapy is associated with aggressive residual disease and lower disease-free survival in HER2-positive breast cancer Interaction between molecular subtypes, stromal immune infiltration before and after treatment in breast cancer patients treated with neoadjuvant chemotherapy COX2/PTGS2 Expression Is Predictive of Response to Neoadjuvant Celecoxib in HER2-negative Breast Cancer Patients Celecoxib With Neoadjuvant Chemotherapy for Breast Cancer Might Worsen Outcomes Differentially by COX-2 Expression and ER Status: Exploratory Analysis of the REMAGUS02 Trial Comedications influence immune infiltration and pathological response to neoadjuvant chemotherapy in breast cancer." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLS129.

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La chimiothérapie néoadjuvante (CNA) est utilisée dans les cancers du sein agressifs ou localement avancés (CS). Au delà des bénéfices cliniques, elle représente une opportunité pour monitorer in vivo la sensibilité d’une tumeur à un traitement.A partir de l’analyse de sets de données de patients traités par CNA, nous souhaitons identifier des mécanismes associes à la résistance ou sensibilité au traitement. Dans la première partie, nous avons évalué des paramètres, cliniques, anatomopathologiques et transcriptomiques. Nous avons démontré que des éléments non explorés comme la présence d’embols après CNA revêtaient une information pronostique importante. Dans une 2ème partie, nous avons analysé l’impact de l’infiltrat immunitaire dans le cancer du sein, et avons décrit les changements observés entre des échantillons avant et après CNA. Nous avons montré que l’impact pronostique des TILs était différent avant et après CNA, et était opposé dans les CS triple négatif ou HER2-positif. Finalement, nous avons analysé l’impact des comédications pendant la CNA. Nous avons trouvé des effets positifs – via l’augmentation de l’infiltrat immunitaire et la réponse au traitement – et des effets négatifs avec des effets délétères dans certains sous groupes de patients. En conclusion, la situation néoadjuvante représente une plateforme pour générer et potentiellement valider des hypothèses de recherche. La mise à disposition de jeux de données de patients traités par chimiothérapie néoadjuvante constituerait une ressource majeure pour accélérer la recherche contre le cancer du sein
Neoadjuvant chemotherapy (NAC i.e. chemotherapy before surgery) is increasingly being used for aggressive or locally advanced breast cancer (BCs). Beyond clinical benefits, it represents an opportunity to monitor in vivo sensitivity to treatment. Based on the analysis of datasets of BCs patients treated with NAC, we aimed at identifying mechanisms associated with resistance or sensitivity to treatment.In the first part, we evaluated biological, clinical, pathological and transcriptomic patterns. We demonstrated that unexplored pathological features such as post-NAC lymphovascular invasion may carried an important prognostic information.In a second part, we analyzed impact of imune infiltration in BC and we described extensively the changes of tumor infiltrating lymphocytes (TILs) between pre and post-NAC samples. We showed that the prognostic impact of TILs was different before and after NAC, and was opposite in TNBC and HER2-positive BCs. Finally, we investigated the impact of comedications use during NAC. We found both positive effects - while enhancing immune infiltration and response to treatment - and negative effects with deleterisous oncologic outcomes in specific patients subgroups. In conclusion, the neoadjuvant setting represents a platform to both generate and potentially validate research hypotheses aiming at increasing the efficacy of treatment. The public release of real-life datasets of BC patients treated with NAC would represent a major resource to accelerate BC research
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Banjar, Haneen Reda. "Personalized Medicine Support System for Chronic Myeloid Leukemia Patients." Thesis, 2018. http://hdl.handle.net/2440/117837.

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Personalized medicine offers the most effective treatment protocols to the individual Chronic Myeloid Leukemia (CML) patients. Understanding the molecular biology that causes CML assists in providing efficient treatment. After the identification of an activated tyrosine kinase BCR-ABL1 as the causative lesion in CML, the first-generation Tyrosine Kinase inhibitors (TKI) imatinib (Glivec®), were developed to inhibit BCR-ABL1 activity and approved as a treatment for CML. Despite the remarkable increase in the survival rate of CML patients treated with imatinib, some patients discontinued imatinib therapy due to intolerance, resistance or progression. These patients may benefit from the use of secondgeneration TKIs, such as nilotinib (Tasigna®) and dasatinib (Sprycel®). All three of these TKIs are currently approved for use as frontline treatments. Prognostic scores and molecularbased predictive assays are used to personalize the care of CML patients by allocating risk groups and predicting responses to therapy. Although prognostic scores remain in use today, they are often inadequate for three main reasons. Firstly, since each prognostic score may generate conflicting prognoses for the risk index and it can be difficult to know how to treat patients with conflicting prognoses. Secondly, since prognostic score systems are developed over time, patients can benefit from newly developed systems and information. Finally, the earlier scores use mostly clinically oriented factors instead of those directly related to genetic or molecular indicators. As the current CML treatment guidelines recommend the use of TKI therapy, a new tool that combines the well-known, molecular-based predictive assays to predict molecular response to TKI has not been considered in previous research. Therefore, the main goal of this research is to improve the ability to manage CML disease in individual CML patients and support CML physicians in TKI therapy treatment selection by correctly allocating patients to risk groups and predicting their molecular response to the selected treatment. To achieve this objective, the research detailed here focuses on developing a prognostic model and a predictive model for use as a personalized medicine support system. The system will be considered a knowledge-based clinical decision support system that includes two models embedded in a decision tree. The main idea is to classify patients into risk groups using the prognostic model, while the patients identified as part of the high-risk group should be considered for more aggressive imatinib therapy or switched to secondgeneration TKI with close monitoring. For patients assigned to the low-risk group to imatinib should be predicted using the predictive model. The outcomes should be evaluated by comparing the results of these models with the actual responses to imatinib in patients from a previous medical trial and from patients admitted to hospitals. Validating such a predictive system could greatly assist clinicians in clinical decision-making geared toward individualized medicine. Our findings suggest that the system provides treatment recommendations that could help improve overall healthcare for CML patients. Study limitations included the impact of diversity on human expertise, changing predictive factors, population and prediction endpoints, the impact of time and patient personal issues. Further intensive research activities based on the development of a new predictive model and the method for selecting predictive factors and validation can be expanded to other health organizations and the development of models to predict responses to other TKIs.
Thesis (Ph.D.) -- University of Adelaide, School of Computer Science, 2018
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McLarty, Kristin. "Molecular Imaging as a Tool for Predicting and Monitoring Response of Breast Cancer to Trastuzumab (Herceptin(R))." Thesis, 2009. http://hdl.handle.net/1807/26471.

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The human epidermal growth factor receptor 2 (HER2) is overexpressed in 20% of breast cancers (BCs) and confers an aggressive tumour phenotype with a poor prognosis. Trastuzumab (Herceptin®) is a humanized IgG1 monoclonal antibody (mAb) approved for treatment of HER2-positive breast cancer (BC), however many eligible patients do not respond. The hypothesis was that molecular imaging strategies that probe: i) the expression of HER2; ii) one of the mechanisms of action of trastuzumab or iii) evaluate the viability of tumour cells by their glucose utilization would be useful in predicting and monitoring the response of BC to treatment with trastuzumab. The relationship between tumour HER2 density, uptake of 111In-DTPA-trastuzumab and response to trastuzumab was evaluated by gamma camera imaging, biodistribution studies and monitoring tumour growth in mice implanted with BC xenografts. There was a non-linear relationship between HER2 expression and uptake of this radiopharmaceutical when tumour uptake was corrected for non-specific IgG accumulation and/or circulating blood radioactivity (r2=0.87-0.99). Tumour response corresponded better with the uncorrected tumour uptake of 111In-DTPA-trastuzumab. HER2 downregulation, a putative mechanism of action of trastuzumab, was noted as decreased tumour uptake on microSPECT/CT of mice bearing MDA-MB-361 xenografts administered 111In-DTPA-pertuzumab. Tumour uptake of 111In-DTPA-pertuzumab was reduced by 53% in mice treated for 3 days with trastuzumab (P<0.05) associated with an early molecular response to the drug. Furthermore, tumour uptake of 111In-DTPA-pertuzumab was reduced by 78% (P<0.001) in mice treated for 3 weeks, which corresponded with a reduction in HER2-positive tumour cells, indicating a therapeutic response. The relationship between changes in tumour uptake of 18F-2-fluoro-2-deoxy-D-glucose (18F-FDG) and response to trastuzumab was examined in mice bearing MDA-MB-361 and MDA-MB-231 BC xenografts, with high or very low HER2 expression, treated with trastuzumab. MicroPET imaging and biodistribution studies detected a 43-60% (P<0.03) reduction in tumour uptake of 18F-FDG in mice with MDA-MB-361 xenografts, treated with trastuzumab compared to PBS-treated controls. In contrast, there was no change in 18F-FDG uptake in MDA-MB-231 xenografts, that did not respond to trastuzumab. I conclude that molecular imaging is a promising tool for monitoring response of BC to treatment with trastuzumab.
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Chen, Bao-Ju, and 陳寶如. "Molecular Status of EGFR and KRAS Predicting Response to Erlotinib in Non-Small Cell Lung Cancer (NSCLC): a Meta-Analysis." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/62746866968159167964.

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碩士
國防醫學院
生物化學研究所
98
Erlotinib is a small-molecule epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKIs) to treat patients with non-small-cell lung cancer (NSCLC). In previous clinical trials, some biomarkers have been examined, such as EGFR mutation, EGFR gene copy number, EGFR protein expression, and KRAS mutation. But the relationships of these biomarkers and erlotinib were still unclear. Here, we provide a systematic review and meta-analysis to clarify the effect of these biomarkers and the tumor response of erlotinib to patients with NSCLC. We searched PubMed (from 1999 to 2010) on clinical studies of erlotinib to treat NSCLC and extracted tumor response and the molecular status of patients. There is a total of 17 clinical studies, including 3 randomized controlled trials, in NSCLC patients treated with erlotinib 150 mg a day. Patients who harbored EGFR mutation (odds ratio=10.71, CI 95% 5.48-20.91) or EGFR gene copy number gained (odds ratio=2.89, CI 95% 1.17-7.14) have better response to erlotinib. There is no significant difference between EGFR protein expression (odds ratio=1.07, CI 95% 0.55-2.08) and tumor response. And patients who harbored KRAS mutations (odds ratio=0.23, CI 95% 0.10-22.14) have worse response to erlotinib. This is the first study to figure out the effect of EGFR and KRAS molecular status on erlotinib. Before choosing a treatment for NSCLC, tumor EGFR and KRAS should be examined. Patients with EGFR mutations or gene copy number gained should consider using erlotinib first, while patients with KARS mutations should not consider using erlotinib.
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Thürigen, Olaf [Verfasser]. "Development of a procedure for genome wide expression profiling from minute Tissue samples and application in mammary carcinoma : gene activity patterns unveiling molecular pathways and predicting clinical response / presented by Olaf Thürigen." 2008. http://d-nb.info/987400517/34.

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Books on the topic "Predicting molecular response in CML"

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Sherman, Mark E., Melissa A. Troester, Katherine A. Hoadley, and William F. Anderson. Morphological and Molecular Classification of Human Cancer. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190238667.003.0003.

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Accurate and reproducible classification of tumors is essential for clinical management, cancer surveillance, and studies of pathogenesis and etiology. Tumor classification has historically been based on the primary anatomic site or organ in which the tumor occurs and on its morphologic and histologic phenotype. While pathologic criteria are useful in predicting the average behavior of a group of tumors, histopathology alone cannot accurately predict the prognosis and treatment response of individual cancers. Traditional measures such as tumor stage and grade do not take into account molecular events that influence tumor aggressiveness or changes in the tumor composition during treatment. This chapter provides a primer on approaches that use pathology and molecular biology to classify and subclassify cancers. It describes the features of carcinomas, sarcomas, and malignant neoplasms of the immune system and blood, as well as various high-throughput genomic platforms that characterize the molecular profile of tumors.
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Walsh, Richard A. “Are My Children at Risk, Doctor?”. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190607555.003.0007.

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Few patients with Parkinson’s disease will be found to have a monogenic cause of their disease, even among those with early onset symptoms. The identification of a genetic etiology will in general have no implications on management but can be helpful in offering a prediction on prognosis, predicting response to treatment, and allowing genetic counseling to take place. Insights into the molecular mechanisms provided by a greater understanding of the genetics of Parkinson’s disease may offer the best hope for identifying future disease-modifying therapies. Next-generation sequencing techniques offer a more cost-effective approach to pursuing genetic testing where indicated.
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Book chapters on the topic "Predicting molecular response in CML"

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Smith, Steven Christopher, and Dan Theodorescu. "Molecular Nomograms for Predicting Prognosis and Treatment Response." In Bladder Tumors:, 165–91. Totowa, NJ: Humana Press, 2010. http://dx.doi.org/10.1007/978-1-60761-928-4_9.

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Sehl, Mary E., and Max S. Wicha. "Modeling of Interactions between Cancer Stem Cells and their Microenvironment: Predicting Clinical Response." In Methods in Molecular Biology, 333–49. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7493-1_16.

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Kaira, Kyoichi. "PET-CT, Bio-imaging for Predicting Prognosis and Response to Chemotherapy in Patients with Lung Cancer." In Molecular Targeted Therapy of Lung Cancer, 45–61. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-2002-5_3.

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Walter, Bernhard, Irmela Schrettenbrunner, Martin Vogelhuber, Jochen Grassinger, Klaus Bross, Jochen Wilke, Thomas Suedhoff, et al. "C-Reactive Protein As a Secretome-Derived Biomarker for Predicting Response to Biomodulatory Therapy in Metastatic Renal Clear Cell Carcinoma." In From Molecular to Modular Tumor Therapy, 353–66. Dordrecht: Springer Netherlands, 2010. http://dx.doi.org/10.1007/978-90-481-9531-2_17.

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Crossa, José, Osval Antonio Montesinos-López, Paulino Pérez-Rodríguez, Germano Costa-Neto, Roberto Fritsche-Neto, Rodomiro Ortiz, Johannes W. R. Martini, et al. "Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction." In Methods in Molecular Biology, 245–83. New York, NY: Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2205-6_9.

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AbstractGenomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G × E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G × E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G × E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G × E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G × E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G × E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G × E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and how the use of mechanistic computational modeling can derive the crop growth and development aspects useful for predicting phenotypes and explaining G × E.
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Singh, Sanjay, Sukanya Tripathy, and Anand Prakash. "Multiple Sclerosis: Molecular Biology, Pathophysiology and Biomarkers." In Neurodegenerative Diseases - Multifactorial Degenerative Processes, Biomarkers and Therapeutic Approaches (First Edition), 115–24. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/9789815040913122010010.

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In the brain, multiple sclerosis is a chronic disease caused by immunemediated neurodegeneration. About 2.5 million people around the world suffer from multiple sclerosis (MS), and women are more prone to it. Neither clinical nor imaging biomarkers are used to diagnose or characterize the disease. Molecular biomarkers have been developed from immunology and neurobiology because they are well matched with causal path mechanisms and other disease characteristics, thus, limiting the number of molecular biomarkers used in clinical practice. Currently, the chapter discusses the attribute of flawless MS biomarkers and the challenges associated with developing newer biomarkers. The study also discusses the discovery of biomarkers from the blood and cerebrospinal fluid (CSF) that are useful for diagnosing MS, predicting its prognosis, and evaluating its therapeutic response and side effects.
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Piccart, Martine, Toral Gathani, Dimitrios Zardavas, Hatem A. Azim, Christos Sotiriou, Giuseppe Viale, Emiel J. T. Rutgers, et al. "Cancer of the breast." In Oxford Textbook of Oncology, 546–75. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199656103.003.0043.

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This chapter covers the epidemiology of breast cancer, reproductive and non-reproductive risk factors, as well as aspects of the molecular biology and classification of breast cancer. It presents an overview of the major oncogenic signaling pathways in breast cancer, along with the major findings from next generation sequencing studies in breast cancer, and the role of gene expression signatures in predicting response to primary systemic therapy. The chapter also covers the pathology of breast cancer, and discusses the surgical management of breast cancer in detail. Furthermore, there is an overview of radiotherapy treatment strategies for breast cancer, which is followed by a detailed overview of the medical management of breast cancer with chemotherapy, endocrine therapy, targeted therapy, and bone-modifying agents. Finally, the multidisciplinary management of breast cancer is discussed using case studies.
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Conference papers on the topic "Predicting molecular response in CML"

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Basak, Jayasri, Soma Mukhopadhyay, Sukanta Konar, and Ashis Mukhopadhyay. "Abstract A68: Molecular response of pediatric chronic myeloid leukemia (CML) with imatinib mesylate therapy." In Abstracts: Frontiers in Cancer Prevention Research 2008. American Association for Cancer Research, 2008. http://dx.doi.org/10.1158/1940-6207.prev-08-a68.

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Arruga, Francesca, Francesca Messa, Monica Pradotto, Roberto Bernardoni, Enrico Bracco, Sonia Carturan, Chiara Maffè, et al. "Abstract 251: Disabled gene is involved in CML progression and its expression level at diagnosis can predict major molecular response (MMR) to imatinib therapy." In Proceedings: AACR 101st Annual Meeting 2010‐‐ Apr 17‐21, 2010; Washington, DC. American Association for Cancer Research, 2010. http://dx.doi.org/10.1158/1538-7445.am10-251.

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Choi, Woonyoung, Debasish Sundi, Michael Metcalfe, i.-ling Lee, Shanna Pretzsch, Jolanta Bondaruk, Elizabeth Plimack, et al. "Abstract 995: Impact of molecular subtypes on predicting chemotherapy response and survival in muscle invasive bladder cancer." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-995.

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Peille, Anne-Lise, Armin Maier, Frederic Foucault, Rebekka Krumbach, Tim Kees, Torsten Giesemann, Thomas Metz, Thomas Metcalfe, Heinz-Herbert Fiebig, and Vincent Vuaroqueaux. "Abstract C30: A KRAS pathway activation index predicting response to MEK inhibitors in patient-derived tumor xenografts." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics--Oct 19-23, 2013; Boston, MA. American Association for Cancer Research, 2013. http://dx.doi.org/10.1158/1535-7163.targ-13-c30.

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Hadac, Jamie N., Terrah J. Paul Olson, Alyssa A. Leystra, Dawn M. Albrecht, Linda Clipson, Ruth Sullivan, Michael A. Newton, Richard B. Halberg, and William R. Schelman. "Abstract 2356: Characterization of molecular signatures predicting response to 5-FU based chemotherapy in mouse models of colorectal cancer." In Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA. American Association for Cancer Research, 2014. http://dx.doi.org/10.1158/1538-7445.am2014-2356.

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Nakashima, Jonathan, and Jantzen Sperry. "Abstract P004: Orthotopic patient-derived xenografts are effective precision oncology models in predicting therapeutic response and acquired drug resistance." In Abstracts: AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; October 7-10, 2021. American Association for Cancer Research, 2021. http://dx.doi.org/10.1158/1535-7163.targ-21-p004.

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Sato, N., M. Wakabayashi, J. Lee, B. Lim, NT Ueno, and H. Ishihara. "Abstract P5-02-06: Predicting the response of molecular targeting agents in triple-negative breast cancer cell lines by kinase activities." In Abstracts: Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium; December 8-12, 2015; San Antonio, TX. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.sabcs15-p5-02-06.

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Vuaroqueaux, Vincent, Hoor Al Hasani, Gerhard Kelter, Hans R. Hendriks, and Heinz-Herbert Fiebig. "Abstract C075: The use of 4HF Cancer Data Miner platform for anin Silicopharmacogenomic study predicting tumor response to the CDK4/6 inhibitor Palbociclib." In Abstracts: AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; October 26-30, 2019; Boston, MA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1535-7163.targ-19-c075.

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Makvandi, Mehran, Brian P. Lieberman, Kuiying Xu, Redmond-Craig Anderson, Chenbo Zeng, David A. Mankoff, Daniel A. Pryma, Roger A. Greenberg, and Robert H. Mach. "Abstract C15: Predicting response to PARP inhibitors through quantitative measurements of PARP activity in live BRCA1 mutated cells with a radio-iodinated PARP inhibitor." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; November 5-9, 2015; Boston, MA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1535-7163.targ-15-c15.

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Linakis, Matthew, James Yates, Eric Masson, and Ganesh Mugundu. "Abstract LB-C14: Using Drug Exposure as a Metric for Predicting Clinical Response to Targeted Cancer Therapeutics from Preclinical Efficacy: A Retrospective Preclinical to Clinical Correlation." In Abstracts: AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; November 5-9, 2015; Boston, MA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1535-7163.targ-15-lb-c14.

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Reports on the topic "Predicting molecular response in CML"

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Shani, Uri, Lynn Dudley, Alon Ben-Gal, Menachem Moshelion, and Yajun Wu. Root Conductance, Root-soil Interface Water Potential, Water and Ion Channel Function, and Tissue Expression Profile as Affected by Environmental Conditions. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7592119.bard.

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Constraints on water resources and the environment necessitate more efficient use of water. The key to efficient management is an understanding of the physical and physiological processes occurring in the soil-root hydraulic continuum.While both soil and plant leaf water potentials are well understood, modeled and measured, the root-soil interface where actual uptake processes occur has not been sufficiently studied. The water potential at the root-soil interface (yᵣₒₒₜ), determined by environmental conditions and by soil and plant hydraulic properties, serves as a boundary value in soil and plant uptake equations. In this work, we propose to 1) refine and implement a method for measuring yᵣₒₒₜ; 2) measure yᵣₒₒₜ, water uptake and root hydraulic conductivity for wild type tomato and Arabidopsis under varied q, K⁺, Na⁺ and Cl⁻ levels in the root zone; 3) verify the role of MIPs and ion channels response to q, K⁺ and Na⁺ levels in Arabidopsis and tomato; 4) study the relationships between yᵣₒₒₜ and root hydraulic conductivity for various crops representing important botanical and agricultural species, under conditions of varying soil types, water contents and salinity; and 5) integrate the above to water uptake term(s) to be implemented in models. We have made significant progress toward establishing the efficacy of the emittensiometer and on the molecular biology studies. We have added an additional method for measuring ψᵣₒₒₜ. High-frequency water application through the water source while the plant emerges and becomes established encourages roots to develop towards and into the water source itself. The yᵣₒₒₜ and yₛₒᵢₗ values reflected wetting and drying processes in the rhizosphere and in the bulk soil. Thus, yᵣₒₒₜ can be manipulated by changing irrigation level and frequency. An important and surprising finding resulting from the current research is the obtained yᵣₒₒₜ value. The yᵣₒₒₜ measured using the three different methods: emittensiometer, micro-tensiometer and MRI imaging in both sunflower, tomato and corn plants fell in the same range and were higher by one to three orders of magnitude from the values of -600 to -15,000 cm suggested in the literature. We have added additional information on the regulation of aquaporins and transporters at the transcript and protein levels, particularly under stress. Our preliminary results show that overexpression of one aquaporin gene in tomato dramatically increases its transpiration level (unpublished results). Based on this information, we started screening mutants for other aquaporin genes. During the feasibility testing year, we identified homozygous mutants for eight aquaporin genes, including six mutants for five of the PIP2 genes. Including the homozygous mutants directly available at the ABRC seed stock center, we now have mutants for 11 of the 19 aquaporin genes of interest. Currently, we are screening mutants for other aquaporin genes and ion transporter genes. Understanding plant water uptake under stress is essential for the further advancement of molecular plant stress tolerance work as well as for efficient use of water in agriculture. Virtually all of Israel’s agriculture and about 40% of US agriculture is made possible by irrigation. Both countries face increasing risk of water shortages as urban requirements grow. Both countries will have to find methods of protecting the soil resource while conserving water resources—goals that appear to be in direct conflict. The climate-plant-soil-water system is nonlinear with many feedback mechanisms. Conceptual plant uptake and growth models and mechanism-based computer-simulation models will be valuable tools in developing irrigation regimes and methods that maximize the efficiency of agricultural water. This proposal will contribute to the development of these models by providing critical information on water extraction by the plant that will result in improved predictions of both water requirements and crop yields. Plant water use and plant response to environmental conditions cannot possibly be understood by using the tools and language of a single scientific discipline. This proposal links the disciplines of soil physics and soil physical chemistry with plant physiology and molecular biology in order to correctly treat and understand the soil-plant interface in terms of integrated comprehension. Results from the project will contribute to a mechanistic understanding of the SPAC and will inspire continued multidisciplinary research.
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