Cancer Drug Discovery

Single-cell RNA-seq, cell hashing and spatial transcriptomics

Mon, 12 May 2025 14:26:40 GMT

In this training, you will learn how to analyze and interpret your own single cell RNA-seq data using QIAGEN CLC Genomics Workbench starting with either FASTQ or matrix files.

You will learn how to perform secondary analysis on your single cell RNA-seq data with the Workbench. Specifically, you will learn how to:

• Import your raw FASTQ or processed cell-matrix files.

• Use pre-configured but customizable pipelines/workflows for single cell RNA-seq data.

• Generate high resolution visuals and other files from your analysis for publications and biopharmaceutical discoveries. o Dimension reduction (UMAP, t-SNE) plots o Differential expression table for clusters, cell types, or combination of both o Heat map o Dot plots o Violin plots

• Learn how to use “Create Cell Annotations from Hashtags” for cell hashing (i.e., CITE-seq).

• Dive into spatial transcriptomic analysis, the latest feature in the single cell RNA-seq module.

Targeting MUC16 Neoantigens in Pancreatic Cancer: Precision Oncology and...

Tue, 18 Mar 2025 10:09:40 GMT

This webinar shows how we enable identification and prioritization of a novel drug target—MUC16—using data from The Cancer Genome Atlas (TCGA), all without requiring deep bioinformatics expertise. The analyst shows how to mine frequently mutated genes across solid tumors, filter for druggable targets based on subcellular localization and extracellular domain structure and evaluate mutation prevalence and protein context. MUC16 emerged as a compelling candidate, particularly in pancreatic adenocarcinoma, where mutations and high expression levels correlated with poorer patient survival. Despite its relevance, few clinical trials currently target MUC16 in this disease, revealing a potentially untapped therapeutic niche. Network analysis and in silico perturbation simulations further suggested that modulating MUC16 expression could meaningfully influence oncogenic pathways. The session concluded by encouraging attendees to explore digital services and underscoring the speed and accessibility of tools for hypothesis generation and target validation.

Data curation as a key element in successful data science strategy

Tue, 07 Feb 2023 17:12:02 GMT

Learn the 7 habits of effective manual curation that QIAGEN Digital Insights uses to drive and build its data content to advance data science applications in biopharma companies.

Uses include:

biomarker and target identification
Disease networks
Pathway construction
upstream and downstream relationships

Exploring drug response in low-grade glioma

Wed, 31 Aug 2022 02:58:16 GMT

This webinar introduces the Tumor Microenvironment (TME) Pathway in QIAGEN’s Ingenuity Pathway Analysis (IPA), demonstrating how users can explore immune and tumor interactions by constructing networks around targets like IL1B and predicting downstream effects on functions such as tumor proliferation. Using tools like Molecule Activity Predictor and Path Explorer, we show how curated literature-derived relationships can model cytokine activity and TME behavior. Additional features like BioProfiler, Land Explorer, and Activity Plot allow users to analyze public datasets (e.g., TCGA) for expression trends and regulatory roles, with use cases including PD-1–positive and –negative CD8+ T cells in lung cancer. IPA’s upstream regulator analysis further enabled prediction of key drivers influencing immune and tumor cell dynamics.