Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Current Therapy of the Patients with MDS: Walking towards Personalized Therapy.

ABSTRACT: Myelodysplastic syndromes (MDS) are characterized by ineffective hematopoiesis, dysplasia and peripheral cytopenias. Nowadays, MDS therapy is selected based on risk. The goals of therapy are different in low-risk and high-risk patients. In low-risk MDS, the goal is to decrease transfusion needs and to increase the quality of life. Currently, available drugs for newly diagnosed low-risk MDS include growth factor support, lenalidomide and immunosuppressive therapy. Additionally, luspatercept has recently been added to treat patients with MDS with ring sideroblasts, who are not candidates or have lost the response to erythropoiesis-stimulating agents. Treatment of high-risk patients is aimed to improve survival. To date, the only currently approved treatments are hypomethylating agents and allogeneic stem cell transplantation. However, the future for MDS patients is promising. In recent years, we are witnessing the emergence of multiple treatment combinations based on hypomethylating agents (pevonedistat, magrolimab, eprenetapopt, venetoclax) that have proven to be effective in MDS, even those with high-risk factors. Furthermore, the approval in the US of an oral hypomethylating agent opens the door to exclusively oral combinations for these patients and their consequent impact on the quality of life of these patients. Relapsed and refractory patients remain an unmet clinical need. We need more drugs and clinical trials for this profile of patients who have a dismal prognosis.

SUBMITTER: Palacios-Berraquero ML

PROVIDER: S-EPMC8153316 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Towards personalized therapy for patients with glioblastoma.

Project description:Combined therapy with temozolomide and radiotherapy is a standard treatment and improves the survival for patients with newly diagnosed glioblastoma. However, the prognosis remains poor, with a median survival time of 12-15 months. Currently, several clinical trials of dose-dense temozolomide regimen or molecular-targeting therapies have been performed to overcome the resistance of glioblastoma. In these therapies, rational prognostic biomarkers have also been investigated to predict their outcome and response to treatment. This advanced understanding of the biological markers can help to develop personalized therapies for glioblastoma patients. Generally, due to a reduced tolerance, elderly patients do not seem to benefit from intensive treatment. This population needs individual treatments depended on their age or performance status. In this article, we review the recent studies that can provide personalized therapy for glioblastoma, based on molecular tumor profiling or patients' physical status.

| S-EPMC4297206 | biostudies-literature

Walking on a user similarity network towards personalized recommendations.

Project description:Personalized recommender systems have been receiving more and more attention in addressing the serious problem of information overload accompanying the rapid evolution of the world-wide-web. Although traditional collaborative filtering approaches based on similarities between users have achieved remarkable success, it has been shown that the existence of popular objects may adversely influence the correct scoring of candidate objects, which lead to unreasonable recommendation results. Meanwhile, recent advances have demonstrated that approaches based on diffusion and random walk processes exhibit superior performance over collaborative filtering methods in both the recommendation accuracy and diversity. Building on these results, we adopt three strategies (power-law adjustment, nearest neighbor, and threshold filtration) to adjust a user similarity network from user similarity scores calculated on historical data, and then propose a random walk with restart model on the constructed network to achieve personalized recommendations. We perform cross-validation experiments on two real data sets (MovieLens and Netflix) and compare the performance of our method against the existing state-of-the-art methods. Results show that our method outperforms existing methods in not only recommendation accuracy and diversity, but also retrieval performance.

| S-EPMC4260921 | biostudies-literature

Towards Personalized Medicine in Psoriasis: Current Progress.

Project description:Although innovative targeted therapies have positively revolutionized psoriasis treatment shifting treatment goals to complete or almost complete skin clearance, primary or secondary lack of efficacy is still possible. Hence, identifying robust biomarkers that reflect the various clinical psoriasis phenotypes would allow stratify patients in subgroups or endotypes, and tailor treatments according to the characteristics of each individual (precision medicine). To sum up the current progress in personalized medicine for psoriasis, we performed a review on the available evidence on biomarkers predictive of response to psoriasis treatments, with focus on phototherapy and systemic agents. Relevant literature published in English was searched for using the following databases from the last five years up to March 20, 2022: PubMed, Embase, Google Scholar, EBSCO, MEDLINE, and the Cochrane library. Currently, more evidence exists towards biologicals, as justified by the huge health care costs as compared to phototherapy or conventional systemic drugs. Among them, most of the studies focused on anti-TNF and IL12/23, with still few on IL17 (mainly secukinumab). The most discussed biomarker gene is the HLA-C*02:06 status that has been shown to be associated with psoriasis, and also differential response to biologicals. Although its positivity is associated with great response to MTX, debatable results were retrieved concerning both anti-TNF and IL12/23 while it seems not to affect secukinumab response. Personalized treatment in psoriasis would provide excellent outcome minimizing the risk of side effects. To date, although several candidates were proposed and assessed, the scarcity and heterogeneity of the results do not allow the identification of the gold-standard biomarker per each treatment. Anyway, the creation of a more comprehensive panel would be more reliable for the treatment decision process.

| S-EPMC9444142 | biostudies-literature

Towards Personalized Therapy of Aortic Stenosis.

Project description:Calcific aortic stenosis (CAS) is the most common cause of acquired valvular heart disease in adults with no available pharmacological treatment to inhibit the disease progression to date. This review provides an up-to-date overview of current knowledge of molecular mechanisms underlying CAS pathobiology and the related treatment pathways. Particular attention is paid to current randomized trials investigating medical treatment of CAS, including strategies based on lipid-lowering and antihypertensive therapies, phosphate and calcium metabolism, and novel therapeutic targets such as valvular oxidative stress, coagulation proteins, matrix metalloproteinases, and accumulation of advanced glycation end products.

| S-EPMC8708539 | biostudies-literature

Pharmacogenomics in Pediatric Patients: Towards Personalized Medicine.

Project description:It is well known that drug responses differ among patients with regard to dose requirements, efficacy, and adverse drug reactions (ADRs). The differences in drug responses are partially explained by genetic variation. This paper highlights some examples of areas in which the different responses (dose, efficacy, and ADRs) are studied in children, including cancer (cisplatin), thrombosis (vitamin K antagonists), and asthma (long-acting ?2 agonists). For childhood cancer, the replication of data is challenging due to a high heterogeneity in study populations, which is mostly due to all the different treatment protocols. For example, the replication cohorts of the association of variants in TPMT and COMT with cisplatin-induced ototoxicity gave conflicting results, possibly as a result of this heterogeneity. For the vitamin K antagonists, the evidence of the association between variants in VKORC1 and CYP2C9 and the dose is clear. Genetic dosing models have been developed, but the implementation is held back by the impossibility of conducting a randomized controlled trial with such a small and diverse population. For the long-acting ?2 agonists, there is enough evidence for the association between variant ADRB2 Arg16 and treatment response to start clinical trials to assess clinical value and cost effectiveness of genotyping. However, further research is still needed to define the different asthma phenotypes to study associations in comparable cohorts. These examples show the challenges which are encountered in pediatric pharmacogenomic studies. They also display the importance of collaborations to obtain good quality evidence for the implementation of genetic testing in clinical practice to optimize and personalize treatment.

| S-EPMC4920853 | biostudies-other

Current Approaches for Personalized Therapy of Soft Tissue Sarcomas.

Project description:Soft tissue sarcomas (STS) are a highly heterogeneous group of cancers of mesenchymal origin with diverse morphologies and clinical behaviors. While surgical resection is the standard treatment for primary STS, advanced and metastatic STS patients are not eligible for surgery. Systemic treatments, including standard chemotherapy and newer chemical agents, still play the most relevant role in the management of the disease. Discovery of specific genetic alterations in distinct STS subtypes allowed better understanding of mechanisms driving their pathogenesis and treatment optimization. This review focuses on the available targeted drugs or drug combinations based on genetic aberration involved in STS development including chromosomal translocations, oncogenic mutations, gene amplifications, and their perspectives in STS treatment. Furthermore, in this review, we discuss the possible use of chemotherapy sensitivity and resistance assays (CSRA) for the adjustment of treatment for individual patients. In summary, current trends in personalized management of advanced and metastatic STS are based on combination of both genetic testing and CSRA.

| S-EPMC7152984 | biostudies-literature

FOLFIRINOX and translational studies: Towards personalized therapy in pancreatic cancer.

Project description:Pancreatic cancer is an extremely aggressive disease; although progress has been made in the last few years, the prognosis of these patients remains dismal. FOLFIRINOX is now considered a standard treatment in first-line setting, since it demonstrated an improved overall and progression-free survival vs gemcitabine alone. However, the enthusiasm over the benefit of this three-drug regimen is tempered by the associated increased toxicity profile, and many efforts have been made to improve the feasibility of this schedule. After a more recent phase III trial showing an improved outcome over gemcitabine, the combination of gemcitabine/nab-paclitaxel emerged as another standard first-line treatment. However, this treatment is also associated with more side effects. In addition, despite initial promising data on the predictive role of SPARC levels, recent studies showed that these levels are not associated with nab-paclitaxel efficacy. The choice to use this treatment over FOLFIRINOX is therefore a topic of debate, also because no validated biomarkers to guide FOLFIRINOX treatment are available. In the era of actionable mutations and target agents it would be desirable to identify molecular factors or biomarkers to predict response to therapy in order to maximize the efficacy of treatment and avoid useless toxic effects for non-responding patients. However, until today the milestone of treatment for pancreatic cancer remains chemotherapy combinations, without predictive or monitoring tools existing to optimize therapy. This review analyzes the state-of-the-art treatments, promises and limitations of targeted therapies, ongoing trials and future perspectives, including potential role of microRNAs as predictive biomarkers.

| S-EPMC4988311 | biostudies-literature

A personalized approach to acute myeloid leukemia therapy: current options.

Project description:Therapeutic options for acute myeloid leukemia (AML) have remained unchanged for nearly the past 5 decades, with cytarabine and anthracyclines and use of hypomethylating agents for less intensive therapy. Implementation of large-scale genomic studies in the past decade has unraveled the genetic landscape and molecular etiology of AML. The approval of several novel drugs for targeted therapy, including midostaurin, enasidenib, ivosidenib, gemtuzumab-ozogamicin, and CPX351 by the US Food and Drug Administration has widened the treatment options for clinicians treating AML. This review focuses on some of these novel therapies and other promising agents under development, along with key clinical trial findings in AML.

| S-EPMC6684879 | biostudies-literature

Molecular targeted agents for gastric cancer: a step forward towards personalized therapy.

Project description:Gastric cancer (GC) represents a major cancer burden worldwide, and remains the second leading cause of cancer-related death. Due to its insidious nature, presentation is usually late and often carries a poor prognosis. Despite having improved treatment modalities over the last decade, for most patients only modest improvements have been seen in overall survival. Recent progress in understanding the molecular biology of GC and its signaling pathways, offers the hope of clinically significant promising advances for selected groups of patients. Patients with Her-2 overexpression or amplification have experienced benefit from the integration of monoclonal antibodies such as trastuzumab to the standard chemotherapy. Additionally, drugs targeting angiogenesis (bevacizumab, sorafenib, sunitinib) are under investigation and other targeted agents such as mTOR inhibitors, anti c-MET, polo-like kinase 1 inhibitors are in preclinical or early clinical development. Patient selection and the development of reliable biomarkers to accurately select patients most likely to benefit from these tailored therapies is now key. Future trials should focus on these advances to optimize the treatment for GC patients. This article will review recent progress and current status of targeted agents in GC.

| S-EPMC3730303 | biostudies-other

Towards personalized tumor markers.

Project description:The cancer biomarker discovery pipeline is progressing slowly. The difficulties of finding novel and effective biomarkers for diagnosis and management of cancer patients are well-known. We speculate that it is unlikely to discover new serological biomarkers characterized by high sensitivity and specificity. This projection is supported by recent findings that cancers are genetically highly heterogeneous. Here, we propose a new way of improving the landscape of cancer biomarker research. There are currently hundreds, if not thousands, of described biomarkers which perform at high specificity (>?90%), but at relatively low sensitivity (<?30%). We call these "rare tumor markers." Borrowing from the principles of precision medicine, we advocate that among these low sensitivity markers, some may be useful to specific patients. We suggest screening new patients for hundreds to thousands of cancer biomarkers to identify a few that are informative, and then use them clinically. This is similar to what we currently do with genomics to identify personalized therapies. We further suggest that this approach may explain as to why some biomarkers are elevated in only a small group of patients. It is likely that these differences in expression are linked to specific genomic alterations, which could then be found with genomic sequencing.

| S-EPMC5871887 | biostudies-other

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data