Multimodal stratification of predictive biomarker in lung cancer: A focus on immune checkpoint inhibitor
Dive into the complex landscape of immune checkpoint inhibitors (ICIs) in lung cancer in our poster presentation.
As the use of immunotherapy in early-stage non-small cell lung cancer (NSCLC) remains a challenge, we offer a spatially-informed approach to identify useful biomarkers. By using spatial biomarker assays, and analysis involving spatial transcriptomics and proteomics, we reveal the cell-to-cell interactions in the tumor microenvironment.
Download our poster to explore our findings and gain insights into the suitability of ICIs for personalized therapy
Spatial distribution of B cells and lymphocyte clusters for the treatment of non-small cell lung cancer
Explore the spatial organization of tertiary lymphoid structures (TLS) in non-small cell lung cancer (NSCLC) and its impact on ant-PD-1 treatment response in our poster presentation.
Using high-plex imaging mass cytometry staining, we investigated the relationship between TLS spatial organization, the tumor microenvironment, and patient response to therapy. We leveraged deep learning for cell segmentation and characterization to identify that the presence of tumor-associated TLS correlates with a positive response to ant-PD-1 therapy.
Download our poster to dive into this spatial distribution insight and its potential impact on immunotherapies.
Highly sensitive analysis using EVOSEP-LC-MS/MS assay for targeted PD-L1 and PD-1 expression level for predicting response to immune checkpoint inhibitors
Explore our recent poster presentation, which dives into a highly sensitive analysis using an EVOSEP-LC-MS/MS assay, with a focus on targeted PD-L1 and PD-1 expression levels to predict responses to immune checkpoint inhibitors (ICIs).
We address the limitations of traditional PD-L1 and PD-1 immunoassays and their uncertain clinical value across tumor types. Through analysis of our robust method against routine immunoassays, and use of Overall Response Rate (ORR), we offer a new perspective on the predictive power of biomarkers for non-small cell lung cancer (NSCLC) therapy.
Download our poster to discover the potential of this innovative approach.
LC/MS/MS VS. LC/HRMS: Identifying and quantifying oligonucleotides
LC/MS/MS and LC/HRMS are formidable instruments employed in mass spectrometry for the identification and quantification of Oligonucleotides (OGNTs). Utilizing these approaches, drug developers can obtain detailed insights into the composition and structure of molecules for biotechnology and pharmaceuticals.
Considerations for choosing the right approach for your drug development project will depend on:
- What instrument you have
- Where you want to go
- How much information you want to collect in a single injection
Discover which technique is best for you.
Optimizing small molecule drug development strategies: A step by step approach to a rugged method
Creating a rugged method for the development of small molecule drugs is crucial in the quest for successful therapies. A systematic approach not only guarantees data consistency and reliability but also empowers you to make well-informed decisions, ultimately boosting project efficiency and success.
To help you navigate the complexities and uncertainties that come with advancing small molecules for drug development, we’ve outlined a robust strategy that includes 7 crucial steps.
Download our fact sheet to learn more.
Investigation of immune-checkpoints for personalized therapy selection
Monoclonal antibody-based therapy targeting PD1 blockage has brought a transformative shift in the immunotherapeutic strategy against solid tumors. However, the limited effectiveness of this treatment stems from the absence of precise methodologies, such as immunohistochemistry, for identifying patients who could potentially respond well to immune checkpoint inhibitor therapy.
Because a single biomarker is not accurate enough to predict the interaction of the drug at the site of action, we developed a strategy to investigate the complexity of the tumor microenvironment, while also guiding patients towards combination therapy. Using multiplexed high throughput analysis, we have been able to investigate pathways of immune modulation at the molecular level to drug response and resistance.
Download our application note to learn more:
Sequential pathogenic events in Type I Diabetes
Type 1 diabetes (T1D) arises due to the autoimmune degradation of insulin producing β cells. In order to cure or halt this disease, understanding how cell types, cell states, and cell-cell interactions evolve during T1D development is essential.
Utilizing our proprietary imaging analysis tools, we were able to segment cells to identify cell populations for spatial analysis and further classification in diabetes with precision. Our deep data analysis workflows and advanced imagine techniques introduce new opportunities to investigate the pathology of T1D within the pancreas.
Download our application note to learn more:
Spatially-resolved tumor gene expression analysis
As cancer advances, tumor cells come into contact with new cell types within the microenvironment, but it is still unclear how the tumor cells adapt to new environments. Spatial transcriptomics is a powerful approach to uncover mechanisms that allow tumors to invade the microenvironment and help discover biomarkers for potential therapeutic targets.
In this application note, we outline how we fine-tuned and merged spatial transcriptomics with laser microdissection (LMD) to identify distinct patterns in genes in tumor cells throughout the stages of cancer progression.
Download our application note to learn more:
Intra-tumoral metabolic plasticity
Just as genetic diversity varies, the metabolic characteristics of cancer exhibit significant heterogeneity due to varied signals within the tumor microenvironment. Hence, addressing metabolic adaptability is crucial when developing cancer immunotherapy strategies.
Utilizing our proprietary Mass Spectrometry Imaging and GeoMx platforms, we were able to evaluate the interactions between metabolic pathways and functions of immune cells to assist in the development of new cancer metabolism drugs. A combined workflow of Quantitative Mass Spectrometry Imaging (QMSI) and GeoMx allows for a better understanding of both direct and indirect modulation of anti-tumor immunity through a better understanding of the tumor immune cell interface.
Download our application note to learn more:
Immuno-oncology, T cell metabolic adaptation
The tumor micro-environment is marked by a consistent decline in oxygen levels and nutrients carried by the bloodstream, which significantly impacts the metabolism of specific groups of cells. To overcome tumor-prolonged nutrient deprivation, immune cells populating malignant lesions need to activate alternative pathways.
Tailoring immune responses by manipulating cellular metabolic pathways provide new options for cancer immunotherapy. Our team conducted a Quantitative Mass Spectrometry Imaging (QMSI) data exploration study on stage II colorectal cancer tissues to reveal the role of metabolic signatures in anti-tumor immunity. Based on metabolic clusters found within the TME, predictive metabolic signatures can be identified that infiltrate levels of immune cells, which can be a powerful tool for predicting immunotherapy responses.
Download our application note to learn more: