Research Services Blog

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Nature Research Cancer Community: Identification of actionable targets and potential immunotherapy strategies to treat gallbladder cancers

The advent of immunotherapy has revolutionized cancer treatment with significant survival benefits observed in various cancers including melanoma and lung cancer.
In order to determine potential opportunities for immunotherapy in GBC, we evaluated neoantigens arising from somatic mutations. We predicted high-affinity MHC class I binding neoantigen peptides for each tumor. This resulted in the identification of roughly 15 neoantigens per tumor.

Navigating Spatial Data Analysis for Publishable Research

Spatial analysis has become an indispensable tool in unraveling the complexities of biological systems. From understanding gene function to dissecting tissue microenvironments, spatial data holds the key to unlocking valuable insights into biological processes. However, harnessing the full potential of spatial data requires not only sophisticated analytical techniques but also considerable computational resources and expertise.

Melanoma & Skin Cancer Awareness Month: Genomics for developing effective therapies

Skin cancer is the most common type of cancer in the US. One in five Americans have the likelihood of developing skin cancer by the age of 70. Some common manifestations of skin cancer include basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and melanoma. Research suggests over 5 million cases of skin cancer occur annually in the US alone. Non-melanoma skin cancers (basal cell carcinoma and squamous cell carcinoma) are the most common, followed by melanoma, the more aggressive form. Other types of skin cancer include Merkel cell cancer, cutaneous T-cell lymphoma, Kaposi sarcoma, skin adnexal tumors and sarcomas.

Unveiling the Complexity of Head and Neck Squamous Cell Carcinoma: From Genes to Microenvironment

Head and neck squamous cell carcinoma (HNSCC) ranks among the most prevalent cancers worldwide. In the United States, it is estimated that 58,450 new cases will be diagnosed in 2024, primarily affecting the oral cavity and pharynx1. Incidence rates among males are highest in non-Hispanic White and American Indian/Alaska Native individuals, with lower rates observed in Hispanic and Asian/Pacific Islander populations. Among females, incidence rates are elevated in non-Hispanic White and Asian/Pacific Islander individuals, while being lowest in Hispanic and Black populations.

From Sequences to Solutions: Exploring Colorectal Cancer Research & Treatment

Colorectal cancer (CRC) stands as the third most prevalent cancer and the second leading cause of cancer-related deaths in the US. It is projected that in 2024, there will be around 106,590 new cases of colon cancer and 46,220 new cases of rectal cancer. CRC incidence is notably higher among African Americans and lowest in Asian Americans/Pacific Islanders.

Empowering Prevention: Genomic Insights for National Cancer Prevention Month

National Cancer Prevention Month is observed in the month of February every year, with an objective to raise awareness and promote initiatives to prevent cancer. Cancer ranks as the second leading cause of death in the United States (US). Despite government-led cancer education initiatives, the battle against this disease remains complex, with variations in cancer risk persisting among different ethnic groups due to genetic predispositions and disparities in healthcare access.

From Single Cells to Spatial Landscapes: Unraveling Gene Expression with 10x Flex and Visium

Single-cell RNA sequencing (scRNA-seq) is a powerful method that is widely used in biomedical research. It is extensively used to determine cell composition of complex tissues, identify rare cell types, map heterogeneity at single cell level and identify paired, full-length immunoglobulin sequence and T-cell receptor α/β. Advancements in high-throughput single-cell RNA sequencing technologies, in combination with powerful computational tools, has made scRNA-seq a widely used technology

Transcriptome sequencing to uncover gene expression signatures and disease biomarkers

Transcriptome sequencing/RNA sequencing allows unbiased characterization of global gene expression profiles associated with different cells/tissues. As genes govern cellular function, transcriptome profile can provide valuable insights into molecular mechanisms operating in a biospecimen. RNA sequencing has transformed biological research by discovering almost all transcripts encoded by a genome including mRNAs, long non-coding RNAs and miRNAs. It has also revealed many alternatively spliced variants which is a common feature among complex multicellular organisms.

Immune Repertoire Profiling: New Trends

The field of immune repertoire profiling has witnessed remarkable advancements in recent years, revolutionizing our understanding of the immune system and its role in various diseases. One of the key techniques to understand this complex mechanism is TCR sequencing. TCR, or T-cell receptor, plays a crucial role in the adaptive immune response by recognizing and binding to specific antigens.

Next generation cytogenomics: Optical genome mapping (OGM) for detection of chromosome structure variations

Genetic variation can range from changes at the level of single bases to whole-chromosomal aneuploidies. Structural variations (SVs) refer to a large alterations in chromosomal structure, typically encompassing larger than 1 Kbp of DNA. SVs include both balanced changes, such as inversions and some forms of translocations, as well as those that alter DNA copy number through duplications and deletions of chromosomal segments.

Advanced Bioinformatics Solutions for Single Cell Research

Bioinformatics plays a vital role in analyzing complex high-throughput sequencing data, particularly in the realm of single cell research. The ability to analyze and interpret massive amounts of single cell data has revolutionized our understanding of cellular heterogeneity and its implications in various biological processes. The blog explores the capabilities of bioinformatics team at MedGenome in analyzing single cell sequencing data. Here, we explore different types of bioinformatics reports, the importance of data visualization and generation of interactive reports such as differential gene expression analysis, heatmap visualization, interactive tSNE plots with cell type and cluster information.

Single Cell Sequencing New Insights

The advent of single cell sequencing technologies has enabled us to understand and study the complexities of biological systems at a finer resolution. Traditional bulk sequencing methods provide an average representation of gene expression across a population of cells, masking the inherent heterogeneity that exists within a tissue or organism. However, single cell sequencing allows us to capture the maximal transcript diversity in a given cell and allows for a multi-model analysis strategy to generate meaningful insights.

Introduction to Single Cell Sequencing – Cite-Seq – Series 3

Cite-Seq, short for Cellular Indexing of Transcriptomes and Epitopes by sequencing, is a powerful technology that has revolutionized single-cell sequencing. With its ability to analyze transcriptomes and protein expression at a single-cell level, Cite-Seq has the potential to greatly advance our understanding of cellular heterogeneity and function in biological systems. In this article, we will discuss the workings of Cite-Seq, its current and potential applications in various fields of research, and its limitations.

Introduction to Single Cell Sequencing – Series 2

Single cell sequencing is a cutting-edge technique used in molecular biology that enables the sequencing of the transcriptome of individual cells. In traditional bulk sequencing techniques, RNA is extracted from a large group of cells, and then sequenced as a whole. However, single cell sequencing allows researchers to analyze the genetic material of individual cells, providing a much more detailed and precise understanding of the diversity and heterogeneity of cell populations.

An Introduction to spatial transcriptomics for biological research

Spatial transcriptomics is a technology that allows the analysis of gene expression patterns within a tissue sample in their spatial context. It enables researchers to obtain a comprehensive and high-resolution view of the transcriptome, the set of all expressed genes, across different regions of the tissue. In traditional transcriptomics, gene expression is measured from homogenized cell populations, which can mask important differences in gene expression between different cell types and regions. Spatial transcriptomics, on the other hand, allows researchers to analyze gene expression patterns in intact tissue sections while retaining their spatial information.

Reference Standards in NGS

Next-generation sequencing (NGS) data is being increasingly used in clinical diagnosis to identify genetic variation that can be a cause for the disease. A major challenge in using NGS data in a clinical setting is to make the right interpretation because of its huge size and complexity. Also, there are possibilities of technical errors during the sample processing and/or sequencing stage that may be inherent to the kind of sequencing technology used. Therefore, the use of reference standards is of paramount importance to mitigate and minimize these errors.

MedGenome’s Quality Control Standards and Metrics for NGS Data

NGS technologies is at the forefront of Biological Research. They produce enormous data running into gigabases in a single round of sequencing. However, several sequencing artifacts such as read errors (base calling errors and small insertions/deletions), poor quality reads and primer/adaptor contamination are quite common with the NGS data obtained after sequencing.

MedGenome is a preferred partner for NGS and informatics expertise

Our journey in 2022 was focused on providing the utmost customer experience for the services and solutions that we delivered to you. Along with expanding our portfolio of services and solutions – the tissue dissociation and nuclei isolation services to support our single cell customers, streamlined antibody discovery using high-throughput single B cell receptor sequencing, TSO500 targeted panels for oncology research, single cell and bulk epigenetics assays.

NGS tumor profiling for Oncology from MedGenome

The discovery of genetic and epigenetic mechanisms underlying the onset and progression of numerous diseases, including cancer, has helped redefine clinical research, diagnostic and treatment paradigms. Oncology research and diagnostics have undergone radical changes because of the development of next-generation sequencing (NGS). NGS has improved rationally designed personalized cancer medicine by identifying novel cancer mutations, detecting circulating tumor DNA (ctDNA), and discovering causative mutations for hereditary cancer syndrome. With NGS, it is now possible to sequence the whole genome, whole exome, whole transcriptome, or just targeted genes to provide detailed genomic landscape descriptions for many cancers.

Single cell and Spatial Multiomics to understand Alzheimer’s Disease pathogenesis

Alzheimer’s disease (AD) has long been one of the great challenges in medicine and imposes a constant burden on our aging population. Recent statistics show that approximately 50 million people worldwide suffer from AD or some other form of dementia. The World Health Organization has estimated that the total number of people with dementia worldwide will reach 82 million by 2030 and 152 million by 2050. Of the top 10 leading causes of death based on United States cancer statistics, cardiovascular disease ranks first, tumors rank second and AD ranks sixth.

Single-Cell Sequencing Technologies: Applications in Biomedical and Clinical Investigations

Modern medicine now derives its insights through the deeper understanding of the cellular and molecular mechanisms, which involves modification of the cellular behavior through targeted molecular approaches. Experimental biologists and clinicians now employ various molecular techniques to assess the intrinsic behavior of cells in a variety of ways, such as through analyses of genomic DNA sequences, chromatin structure, messenger RNA (mRNA) sequences, non-protein-coding RNA, protein expression, protein modifications and metabolites.

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