Personalized and Precision Medicine Journal

Abstract The human gut microbiome constitutes a highly diverse and unique ecosystem that plays a critical role in shaping host metabolism, immune function, and vulnerability to numerous diseases. Thanks to recent breakthroughs in high-throughput sequencing, shotgun metagenomics, and integrative multi-omics strategies, researchers can now achieve comprehensive profiling of microbial communities with strain-level precision and detailed functional insights. Specific microbial patterns have emerged as reliable predictive biomarkers for assessing disease risk, tracking progression, and determining treatment outcomes in various conditions, including metabolic syndrome, inflammatory bowel disease, autoimmune disorders, and cancer. By combining microbiome data with host genomics, metabolomics, and clinical metrics, precision medicine is enhanced, facilitating tailored interventions such as dietary changes, probiotics, prebiotics, and fecal microbiota transplantation. Sophisticated bioinformatics tools, alongside machine learning and artificial intelligence, streamline the analysis of complex, high-dimensional multi-omics data, helping to pinpoint crucial microbial taxa, functional pathways, and predictive markers. Nevertheless, significant hurdles persist regarding the standardization of sample collection, sequencing protocols, bioinformatic workflows, and reproducibility across different study cohorts. Additionally, ethical issues such as data privacy, informed consent, and fair access require careful attention. Future studies that integrate longitudinal multi-omics profiling, mechanistic investigations of host microbe interactions, and robust clinical validation of microbial biomarkers are expected to propel microbiome-driven personalized medicine forward. Ultimately, a thorough characterization of the gut microbiome offers a revolutionary approach to proactive, patient-centric healthcare, shifting focus from general population-based models to precise, individualized strategies for prevention, diagnosis, and therapy.

Abstract The human microbiome, consisting of trillions of microorganisms living in and on the body, plays a critical role in maintaining physiological balance and health. Recent advancements in microbiome research have demonstrated its profound influence on immune function, metabolic regulation, and disease pathogenesis. Personalized therapies that integrate the microbiome into treatment strategies have emerged as a promising approach to optimize patient outcomes. This review explores the current understanding of the microbiome’s role in immune and metabolic regulation and highlights emerging approaches for incorporating microbiome-based interventions into personalized therapy regimens. We discuss the potential of microbiome modulation to enhance immune responses, improve metabolic health, and provide novel therapeutic options for diseases such as cancer, diabetes, autoimmune disorders, and inflammatory bowel diseases (IBD).
 

Abstract Background: Matrix metalloproteinases (MMPs) play a critical role in tumor invasion and metastasis in papillary thyroid carcinoma (PTC). This study investigates the association of MMP2 (rs7201) and MMP9 (rs17576) polymorphisms with PTC risk and clinical characteristics, aiming to inform personalized medicine approaches.
Methods: A case-control study was conducted with 210 PTC patients and 210 controls. Genotype frequencies were analyzed using Chi-Square tests, and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Associations with clinical characteristics (T Status, N Status, Stage) were assessed in PTC patients.
Results: The MMP2 rs7201 CC genotype was significantly associated with increased PTC risk (OR = 3.524, 95% CI = 1.809–6.867, p = 0.001) and advanced T Status (T3: 48.6%, p = 0.029), but not with N Status (p = 0.509) or Stage (p = 0.461). The C allele was more frequent in cases (44%) than controls (32%) (OR = 1.590, p = 0.001). Conversely, MMP9 rs17576 showed no association with PTC risk (GG: OR = 0.727, p = 0.277) or clinical characteristics (p > 0.05). Both polymorphisms were in Hardy-Weinberg equilibrium in controls.
Conclusion: The MMP2 rs7201 CC genotype and C allele are associated with increased PTC risk and tumor progression, highlighting their potential as biomarkers for personalized risk stratification. These findings support genotype-based screening to identify high-risk PTC patients, enabling tailored surveillance and therapeutic strategies. Further studies are needed to validate these associations and explore their utility in precision medicine.

Abstract Pharmacogenomics is a relatively new subject that utilizes genomics and pharmacology to investigate the ways in which genetic variants influence individual responses to treatment with pharmaceuticals. A departure from the conventional "one-size-fits-all" treatment strategy is marked by the advent of pharmacogenomics, which makes it possible to tailor pharmacological regimens to the specific genetic profile of an individual. Significant improvements in pharmacological efficacy, reductions in adverse drug reactions (ADRs), and assistance in the development of drugs that are both safe and effective for a wide range of conditions are all possible outcomes of this domain. The purpose of this study is to investigate the prospective results of pharmacogenomics, with a particular emphasis on the function it plays in the process of drug development and its incorporation into personalized medicine. The purpose of this study is to investigate the genetic characteristics that influence the metabolism, efficacy, and toxicity of drugs, as well as to investigate the regulatory framework that is associated with pharmacogenomics testing. This paper provides a synopsis of the most important genes that are involved in pharmacogenomic responses, as well as a discussion of the potential difficulties that may arise in their practical use and the anticipated breakthroughs in this area of study.

Abstract Drug resistance is a major obstacle in the effective treatment of cancer, severely impacting patient outcomes and complicating therapeutic strategies. The development of resistance is multifactorial, involving a combination of genetic and epigenetic changes within cancer cells, alterations in drug metabolism, increased DNA repair mechanisms, overexpression of drug efflux pumps, and complex interactions with the tumor microenvironment. These factors work synergistically to render traditional chemotherapy and targeted therapies less effective over time.
Recent advances in molecular biology, particularly next-generation sequencing and the CRISPR-Cas9 gene-editing tool, have significantly enhanced our understanding of the underlying mechanisms driving resistance. These technologies have enabled researchers to identify novel genetic mutations and signaling pathways that cancer cells exploit to evade treatment, offering new potential targets for therapeutic intervention. Additionally, the dynamic role of the tumor microenvironment, including immune cells, stromal cells, and extracellular matrix components, has emerged as a key factor influencing drug resistance, further complicating treatment strategies.
To address these challenges, several innovative therapeutic approaches are being explored. Combination therapies, which involve the use of multiple drugs targeting different pathways simultaneously, hold promise in overcoming resistance by attacking cancer cells from multiple fronts. Immunotherapy, which harnesses the body's immune system to target cancer cells, is also showing significant potential in resistant cancers. Furthermore, nanomedicine, which uses nanoparticles to deliver drugs directly to tumors, may improve drug efficacy and minimize resistance.
Despite these advancements, much remains to be done. Ongoing research focused on identifying reliable biomarkers, developing personalized medicine approaches, and understanding the intricate relationship between cancer cells and their microenvironment is essential. This review aims to provide a comprehensive overview of the current state of knowledge regarding drug resistance in cancer, emerging therapeutic strategies, and future research directions in this critical field.

Abstract In cancer treatment, anesthesia is commonly used during surgery to remove tumors, as well as for other procedures like biopsies, radiation therapy, and chemotherapy administration. Some research suggests that the choice of specific anesthetic drugs and nerve-sparing techniques can have a significant impact on cancer recurrence rates and overall patient survival. It is well-established that a patient's immune system plays a direct role in postoperative complications and long-term outcomes, highlighting the importance of optimizing anesthesia to minimize potential immune system suppression and improve immune function during cancer surgery. Recent studies have revealed a strong connection between the type of anesthesia used during surgery and the likelihood of cancer relapse and related mortality. Therefore, it is crucial to select the appropriate anesthesia technique for cancer resection, focusing on reversible effects, rapid recovery, and resistance to feedback. The specific anesthetic agents used during surgery have a significant impact on survival rates and the risk of cancer-related mortality. Genetic influences on anesthesia response are significant for improving patient care and achieving better results. Additionally, personalized medicine, which combines diagnostic testing and treatment, is now a clinical reality. Anesthesia's effects on depth, pain signals, vital signs, and the motor system are complex and not fully understood, and many researchers believe that anesthesia is regulated by multiple genes, although further research is needed to identify them and understand how they are regulated. The relationship between anesthesia and cancer is complex and evolving with implications for medical treatment. Limited evidence suggests that anesthesia and surgery-related factors can affect cancer biology and outcomes. Further research is needed to understand these interactions and develop strategies for improving cancer care during surgery. Better understanding can lead to safer and more effective cancer treatment, benefitting patients.

Abstract IntroductionLung cancer is the prevailing form of cancer globally, with a significant fatality rate among both males and females. Lung cancer is the third most frequent type of cancer in Iran, and it is becoming more common all the time. Patients are frequently diagnosed in the advanced stages of the disease, which contributes to the high death rate. Therefore, the ability to identify molecular markers is essential for both early diagnosis and the choice of conventional treatment for lung cancer. Numerous genetic variations have been found to be strongly linked to the development of lung cancer, according to studies. The aim of this work is to look into the genes that contribute to the development of lung cancer.
Materials and methods: The present review was authored using search terms related to lung cancer, key genes, clinical biomarkers, and early diagnosis that were found on PubMed, NCBI, Scopus, Science Direct, and Google Scholar.
Findings: Since the EGFR, KRAS, BRAF, and TP53 genes are the most significant and involved in the development of lung cancer, finding mutations in these genes can be a valuable clinical diagnostic for lung cancer diagnosis and therapy.
Discussion and conclusion: With an emphasis on personalized medicine, the identification of genes linked to lung cancer may be utilized as clinical biomarkers for the disease's early diagnosis and effective treatment. The state of targeted lung cancer therapy and early detection techniques may be enhanced by molecular biomarkers. In the field of personalized medicine, identifying the genes linked to lung cancer as clinical biomarkers for early diagnosis and assessing treatment response to select a targeted treatment can be crucial in streamlining the therapeutic process, improving treatment response, lowering mortality, and lessening the material and spiritual harm this illness causes.

Abstract Variability in medication reactions and illness susceptibility among individuals is often seen in clinical settings. Personalized medicine is now highly esteemed for its focus on prescribing the appropriate medication to each patient. Metabolomics is a developing field that thoroughly assesses all metabolite and low-molecular-weight compounds in a biological sample. Metabolic profiling offers a quick overview of a cell's physiology, making the technique a direct indicator of an organism's physiological condition. Quantifiable correlations exist between the metabolome and other cellular components such as the genome, transcriptome, proteome, and lipidome. These correlations can be utilized to forecast metabolite levels in biological samples based on mRNA levels. One of the key problems in systems biology is to incorporate metabolomics with other -omics data to enhance comprehension of cellular biology. Metabolomics is used to assess the effectiveness of clinical substances by analyzing the metabolic characteristics of patients before treatment to predict their responses (pharmacometabolomic) and to identify individuals at risk of developing diseases (patient stratification). The rapid progress in metabolomics technique highlights its significant potential for use in customized treatment. We reviewed the unique benefits of metabolomics, including instances in assessing medication treatment and individual stratification, and emphasized metabolomics' promise in personalized medicine.

Abstract Precision medicine is a medical approach that involves customizing therapy for an individual by using extensive biological and external data. The rapid progress in the disciplines of molecular biology, gene sequencing, machine learning, and related technologies has facilitated the use of precision medicine. This approach utilizes the wealth of comprehensive information obtained from these advancements to improve the decision-making process in clinical treatment for individuals, particularly in real-time scenarios during the progression of a disease. Diabetes mellitus is a significant worldwide health issue, requiring the implementation of novel strategies to enhance patient outcomes. The efficacy of conventional treatment options that use a uniform approach has been shown to be limited in effectively addressing the heterogeneous character of the illness. In recent times, personalized medicine has surfaced as a revolutionary resolution, customizing treatment strategies in accordance with an individual's health attributes, lifestyle choices, and genetic composition. This review underscores the significance of genetic screening in forecasting susceptibility to diabetes and treatment response, while also emphasizing the potential of pharmacogenomics to optimize medication selection.

Abstract There were more than thirty-eight million HIV infections worldwide. Combination antiretroviral therapy (cART) has progressed to the point where invisible viral loads are now feasible, and HIV carriers frequently lead almost everyday lives with considerably greater average life expectancies than in the past. However, there is still no cure for the disease. Even though the ailment usually advances to a chronic state, an individual's unique course of progression may differ significantly from the average and manifest distinctively for each patient. This diversity begs whether a typical treatment strategy is appropriate for a patient.
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Abstract It has been known for quite some time that gut microbiota plays an important role in human health and illness. Recent years have seen a surge in interest in the human gut microbiota, and the advent of metagenomic investigations has greatly aided our understanding of the resident species and their potential uses. The human digestive tract is home to billions of bacteria, making up the varied gut microbiota. At birth, the gut microbiome begins to take shape and proliferate, and throughout life, numerous genetic, dietary, and environmental variables will shape and multiply this community. Alterations to the gut microbiota's structure and function may affect digestion, metabolism, and the immune system. Meanwhile, personalized medicine, a new therapeutic approach, has opened a new door in the medical sciences, and the link between the microbiome and personalized medicine is one of the most intriguing areas of study going forward. Since the link between this two axis is new, there are few research on it. Therefore, in this review study, the relationship between the gut microbiome, drug interactions, disease progression, and personalized medicine has been discussed.

Abstract A number of animal disease models have been created in the past to investigate the molecular basis of neurological diseases and identify novel treatments, but their effectiveness has been limited by the absence of comparable animal models. There are still several important problems that need to be overcome, including the high expenses associated with creating animal models, ethical issues, and a lack of similarity to human disease. More than 90% of medications fail in the last stage of the human clinical trial as a result of inadequate early screening and assessment of the molecules. A novel strategy based on induced pluripotent stem cells has been developed to get around these restrictions (iPSCs). A new road map for clinical translational research and regeneration treatment has been made possible by the discovery of iPSCs. In this paper, we investigate the potential use of patient-derived iPSCs to neurological disorders as well as their significance in scientific and clinical studies for the creation of disease models and a road map for the next of medicine. The role of human iPSCs in the most prevalent neurodegenerative illnesses (such as Parkinson’s and Alzheimer’s disease, diabetic neuropathy) was evaluated. The patient-on-a-chip idea, where iPSCs may be cultivated on 3D matrices within microfluidic devices to produce an in vitro disease model for tailored medication, is another new development in the field of personalized medicine that we looked into.

Abstract In the twenty-first century, there still needs more clarity on rheumatoid arthritis (RA). Rheumatoid arthritis is a widespread but heterogeneous illness with a broad range in its history, clinical symptoms, and response to therapy. It is now known that prevention of joint destruction, functional impairment, and a poor disease prognosis depends on early, correct diagnosis and starting therapy with disease-modifying drugs (DMARDs), among which methotrexate (MTX) remains the gold standard in the treatment of RA. Early rheumatoid arthritis diagnosis is crucial since it enables a speedier start to primary therapy. Pharmacogenetic and pharmacogenomic research, which aid in identifying a patient’s genetic profile, may bring personalized treatment closer to reality. Identifying disease-specific genes while the organism’s resistance to them is still intact should be made feasible by further study into RA.

Abstract Despite the well-known high prevalence of failure in drug development, recent advancements in tissue engineering and microfabrication have helped to create microphysiological systems (MPS), or "organs-on-chips," which mimic the function of human organs. These "tissue chips" might be used for toxicity and drug screening tests, which could revolutionize the early phases of the drug development process. Additionally, they may be utilized to simulate disease conditions, supplying new instruments for deciphering disease pathologies and causes and evaluating the efficacy of novel treatments. Future clinical trials on chips might be utilized to assess novel medicines in both populations and individuals, opening the door for precision medicine. Here, we'll discuss tissue chips' diverse potential and the difficulties in developing them.

Abstract The ability of immunotherapy to treat ovarian cancer is currently limited, however evaluating sensitive/resistant target treatment subpopulations based on stratification by tumor biomarkers may enhance this ability. These indicators include the number of tumor mutations, PD-L1, tumor-infiltrating lymphocytes, a lack of homologous recombination, and intratumoral heterogeneity of neoantigens. The use of these indicators to choose the best candidates for ovarian cancer treatment is one of the future directions. In addition to reviewing innovative treatments and study designs including tumor biomarkers that improve the chances of immunotherapy success in ovarian cancer, this paper also analyzes the function of immunotherapy in ovarian cancer.

Abstract A model system for precision medicine has been suggested using tumor organoids. Tumor organoids are unique for cancer research on a patient-by-patient basis because they are able to preserve properties of the original tumor. As a result, it is alluring to consider using tumor organoids to improve patient outcomes during clinical decision-making. Patient outcomes have a good correlation with tumor organoid responses to a variety of medicines in vitro. Before application in clinical cancer care can be considered, however, there are still significant obstacles to be overcome and large cohort prospective trials are desperately needed. Tumor organoids offer a lot of potential in preclinical research due to their unique traits and direct connection to patient data. Here, we have evaluated the most recent developments in the development and use of cancer organoids grown from patients for cancer biology research and customized treatment. We have concentrated on the potential of organoids as a platform for the discovery and creation of innovative targeted therapies for the most intractable malignancy, pancreatobiliary cancer.

Abstract Gene therapy, as an experimental therapy, is applied for the treatment of diseases through modification of genes. Gene therapy corrects the mutated genes. Somatic and germline gene therapy are two main types of gene therapy. In germline editing, normal genes are inserted into the human’s eggs or sperm, zygote, or early embryo. Therefore, the gene is transmitted to the next generation, but in somatic gene therapy, a normal gene is inserted into somatic cells and corrects the defective gene without transmission to children. Personalized medicine is a novel therapeutic protocol for the prevention and treatment of diseases that considers individuals’ responding differences to medications.  So, it raises ethical issues. Ethical concerns regarding gene therapy and personalized medicine are as follows: safety, accessibility, cost-efficiency, genetic enhancement, dignity, autonomy, identity, and social discrimination.

Abstract The current study identified pathogenic variables associated with increased mortality risk in infectious diseases using predictive analysis and a combination of genotypic, phenotypic, and medical data. The quick nucleic acid-based clinical assessment might affect the spread of hospital-acquired illnesses, and we think that such life-saving operations should be carried out closer to the individual, preferably in 24/7 medical facilities' specialized labs. Personalized medicine notions are relevant in infections for the (rapid) characterization of a disease-causing microbial community and perseverance of its antibiotic susceptibility characteristic to guide a suitable antibiotic therapy for the proper care of the individual. Personalized medicine aims to interrogate a patient's genetic data, and pharmacodynamics polymorphisms, and guide drug options and dosage. This work demonstrates the potential use of fundamental genetic analysis in treating infectious diseases and theoretically justifies the value of customized therapy

Abstract Alzheimer's disease (AD) is a neurodegenerative disease that leads to progressive and incurable cognitive and behavioral disorders. Personalized medicine, which is also called precision medicine, represents an approach to the treatment of the disease with the aim of improving the effectiveness of the treatment, which stops or slows the disease in an optimal and targeted manner based on a certain time. It enables physician to accurately and efficiently identify the most effective treatment. Personalized medicine is based on molecular knowledge. Genome sequencing by the Human Genome Project (HGP) represents one of the most powerful tools for personalized medicine, as well as transcriptomics, proteomics and metabolomics development which can be used for both disease prediction and better treatment. In this paper, we will review the strategies that personalized medicine offers for the treatment of AD for the future.

Abstract Vitamin D (Vit D) ,as an antioxidant contributes to a wide range of diseases including obesity, type 2 diabetes, multiple sclerosis, and certain cancers that oxidative stress plays a vital role in their development. Excessive oxidative stress can damage to DNA and nucleotide pool. Base excision repair and house-cleaning enzymes can protect genome so that any disruption in expression of these genes indicates enhanced susceptibility risk for diseases like cancer. The present study was conducted aimed at evaluating the effect of Vit D on the expression of MYH and MTH1 as DNA repair genes, as well as effect of ViD treatment in Human Umbilical Vein Endothelial Cells (HUVEC) cell line. To do this, bioinformatics tools were used to predict the interaction of MTH1 and MYH with VDR as a specific transcription factor (TF) for  Vit D. The cell line was treated with VitD. Next, viability was evaluated using MTT assay. The mRNA expression of MTH1 and MYH was assessed using real-time PCR at 48h post-treatment with Vit D.  
Results of the study revealed that Vit D could regulate MTH1 and MYH  transcript expression directly through its specific TF; VDR. In response to VitD treatment a different alteration was observed in DNA repair, and non-canonical nucleotide repair genes. Findings of this study showed a new regulation of DNA repair genes in Vit D signaling pathway, and it may be a new perspective for the therapeutic effect of Vit D on related diseases. Variation in interested genes may affect the vitD signaling and personalized medicine should be considered.  

Abstract The pathophysiology and molecular pathways of breast cancer (BC) are still unclear, but it appears that BC is caused by the interaction between genetic susceptibility and environmental factors. Epidemiology studies have shown the increase risk of BC through polycyclic aromatic hydrocarbons (PAH) exposure. Environmental carcinogens induce disease pathways by altering the expression of specific genes that may be a consequence of epigenetic modifications. In order to understand the effects of PAHs in the BC risk, the epigenetic pathway may consider as an important key and likely play a role in BC initiation. Novel epigenetic  biomarkers and treatments hold promise  in the approch of personalized medicine. Here, we focus to review the epigenetic factors in relation to polycyclic aromatic hydrocarbons exposure that may influence BC risk.

Abstract Due to the lack of reliable biomarkers and a thorough understanding of the etiology of multiple sclerosis (MS), the treatment strategy in MS requires a personalized medicine framework that goes beyond the precision medicine idea. A patient-centered approach is necessary for personalized treatment, and the identification of pathophysiological processes should be employed to help classify diseases. Intracellular aspartic proteinase-A enzyme is expressed by the APR1 gene and is one of the important factors in the development of systemic candidiasis caused by Candida albicans. The aim of this study was molecular detection of fungal DNA in serum of MS patients and to evaluate the expression of the APR1 gene in C. Albicans isolates obtained from patients with multiple sclerosis (MS) and controls. The samples were obtained from 100 MS patients with candidiasis and 100 matched controls of healthy individuals during 2018 - 2019. The evaluation of APR1 gene expression was performed using the reverse transcriptase-polymerase chain reaction (RT-PCR) method. There was a statistically significant difference in APR1 gene expression of C. Albicans strains between MS patients (mean± SD: 0.5008 ± 0.09518) and the control group (mean± SD: 0.7513±0.10505) (P = 0.000). The mean values of EDSS were 1.4074 ± 0.0082 after antifungal treatment and 2.0519 ± 0.1123 before antifungal treatment (P = 0.000). Differences in active fungal infection between patients and controls indicate the importance and possible role of fungi in MS patients. The results suggested that APR1 gene expression in C. Albicans strains isolated from MS patients may be an important factor for invasive C. Albicans strains in the progression of MS disease. Because fungal infections in the serum causes more activity of the body’s immune and defense system and directly affect the activity of the immune system, it further destroys the central nervous system.

Abstract Personalized medicine is the clinical treatment of diseases that is tailored to the physiologic, molecular genetics and lifestyle characteristics of the patient.
Personalized medicine can be considered as a new approach to face diseases and develop traditional methods for their diagnosis and treatment. This novel field of medicine has the potential of changing identification and management of health problems strategies. Corona virus disease 2019 (COVID-19) is an infectious disease that affects the lungs of patients. This novel outbreak was first reported on 31 December 2019 in Wuhan, the capital of Hubei province of China, and it had many effects on people's lives all over the world in various economic, social and health fields until now. Since the start of the pandemic Covid-19, the World Health Organization (WHO) has expressed concern about the public health emergency. Although the disease has mild symptoms and similar to a common cold in most people, in some cases it can lead to pneumonia, acute respiratory distress syndrome, multi-organ dysfunction, and even death. Therefore, due to the different effects of this disease in individuals and even families, the role of personalized medicine becomes more significant and sensitive. Considering the rapid spread and global crisis of Covid-19, recent research has focused more on the control and treatment of the virus. The main goal of this paper is the investigation of different effects of the virus on patients and study of the personalized medicine roles in the control and treatment of the disease.

Abstract Background: Lung cancer is the first cause of cancer deaths in the world. Pemetrexed is an antifolate drug used as a first or second-line in the treatment of advanced non-small cell lung cancer (NSCLC) patients. Methylenetetrahydrofolate reductase (MTHFR) is an important enzyme in a folic acid metabolic pathway and a central role in clinical response to pemetrexed. The aim of this study was to investigate the association between rs1801133 polymorphism and the overall survival of metastatic NSCLC patients.  
Methods: Thirty-four patients with metastatic lung cancer were treated with pemetrexed-based regimen at Rasoul Akram Hospital, Tehran, Iran. Genomic DNA was extracted from the peripheral blood of patients before initiation of treatment. Genotyping of rs1801133 polymorphism was performed at the National Institute of Genetic Engineering by PCR-RFLP methods. Statistical analysis performed with SPSS software, version 21.0.
 Results: Thirty-four patients were enrolled in this study. 21 patients (62%) were male and 13 (38%) were female. The mean age of the patients was 58.90 years. rs1801133 polymorphism were not significantly associated with survival in patients treated with pemetrexed-based chemotherapy.
 Conclusion: Previous studies have demonstrated that MTHFR polymorphism may predict survival among pemetrexed-based regimen treated advanced non-squamous NSCLC patients. However, in this study, the examined polymorphisms were not associated with patients' survival.

Abstract Personalized medicine as a revolutionary in medicine provides medical services tailored to a person's molecular characteristics. In personalized medicine, the physician with the knowledge of information in the person’s molecular profile (omics) can prescribe an effective drug with minimal side effects and appropriate dose for changing lifestyle and diet to prevent and treat diseases.
Theoretically, the molecular profile of each individual could give some information about risk of diseases, the person responses to medications and the relationship between person molecular profile and certain traits, such as lactose intolerance and diet-specific adaptation.
In the past, it was impossible to confirm the presence or absence of mutations in an individual's genome, as the use of molecular techniques such as PCR was very time consuming and was associated with many limitations. On the other hand, many traits and diseases are multigenic and the consequence of interaction with environment. Furthermore mathematical models for measuring genetic risk were not developed.
In recent years, creation of individual genetic profile with determination of a person's genotype and all known mutations in a short time and at low cost became possible, due to advances in microarray technology, computer science and statistics.
In parallel with genomics, advances in other multidisciplinary sciences such as nanotechnology and systematic biology have facilitated the disease interactions at the cellular and molecular scale. Nanomedicine has provided the control of drug release profiles using design and fabrication of nanostructured devices, so it is hoped that by combining these information and examining their interactions, better contribution to human health will be achieved. In this review, we focused on nanotechnology applications and solutions that impact on personalized medicine and accelerate its progress and development.