Researchers uncover novel immune cell populations that respond to immunotherapy treatment as well as key molecular factor required for therapy to succeed
There have been many success stories for checkpoint blockade therapies both in preclinical models and in patients with cancer. But many questions remain about exactly how such immunotherapies elicit their response and what determines when and where checkpoint blockade therapy succeeds or fails at reinvigorating the immune system to eradicate cancer. A new study led by investigators from Brigham and Women’s Hospital in collaboration with colleagues at the Broad Institute examines the effects of checkpoint blockade therapies on different populations of T cells, a key class of immune cells in tumors. The team’s surprising results point to a population of T cells that have been overlooked in the past and led to the identification of a molecular factor that may be predictive of response to treatment. The investigators’ findings are published in Immunity.
“Our study takes advantage of the observation that there is great diversity in the T cells within tumors. When we looked at the effect of therapies on different cell populations, we were surprised and puzzled to find that even T cells that don’t express checkpoint inhibitors showed significant changes at the genetic level,” said co-corresponding author Ana Anderson, PhD, a scientist at the Brigham. “These are cells that have largely been ignored before. Our study broadens the focus of what checkpoint blockade therapy may be doing and how it mediates its effects.”
Anderson and colleagues leveraged modern technology to explore the effect of therapy on T cells across different cancers, capitalizing on computational methodologies and single-cell RNA-seq, a technique for measuring the output of thousands of genes from individual cells in a given population. The researchers took an iterative approach, allowing the data to point them toward interesting leads and then performing further testing in preclinical models of cancer.

This approach led them to Tcf7, a transcription factor that is required for the maintenance and function of an immune cell population that is capable of memory. Through their experimental models, the team found that this factor was required for immune-based therapies to succeed.
Anderson notes that, to date, the field has been largely focused on fully matured, end-stage T cells that are equipped with checkpoint receptors such as PD1 or CTL4. In the early stages of activation, T cells don’t yet express these receptors, and yet, these nascent cells still show a response to the therapy. “We need to understand these early-stage T cells to shed light on how checkpoint blockade therapy works,” said Anderson. “Our study helps define an important immune cell population that responds to checkpoint blockade immunotherapy across different cancers and points to a critical factor in this therapy’s success. With further study, we may be able to define biomarkers to predict a patient’s response to therapy and identify which cells are most important to target with immunotherapy approaches.”
Source – Eurekalert
Kurtulus S, Madi A, Escobar G, Kuchroo VK, Regev A, Anderson Ac. (2019) Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1−CD8+ Tumor-Infiltrating T Cells. Immunity [Epub ahead of print]. [abstract]
Researchers uncover novel immune cell populations that respond to immunotherapy treatment as well as key molecular factor required for therapy to succeed
There have been many success stories for checkpoint blockade therapies both in preclinical models and in patients with cancer. But many questions remain about exactly how such immunotherapies elicit their response and what determines when and where checkpoint blockade therapy succeeds or fails at reinvigorating the immune system to eradicate cancer. A new study led by investigators from Brigham and Women’s Hospital in collaboration with colleagues at the Broad Institute examines the effects of checkpoint blockade therapies on different populations of T cells, a key class of immune cells in tumors. The team’s surprising results point to a population of T cells that have been overlooked in the past and led to the identification of a molecular factor that may be predictive of response to treatment. The investigators’ findings are published in Immunity.
Anderson and colleagues leveraged modern technology to explore the effect of therapy on T cells across different cancers, capitalizing on computational methodologies and single-cell RNA-seq, a technique for measuring the output of thousands of genes from individual cells in a given population. The researchers took an iterative approach, allowing the data to point them toward interesting leads and then performing further testing in preclinical models of cancer.
This approach led them to Tcf7, a transcription factor that is required for the maintenance and function of an immune cell population that is capable of memory. Through their experimental models, the team found that this factor was required for immune-based therapies to succeed.
Source – Eurekalert
Kurtulus S, Madi A, Escobar G, Kuchroo VK, Regev A, Anderson Ac. (2019) Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1−CD8+ Tumor-Infiltrating T Cells. Immunity [Epub ahead of print]. [abstract]
Related Posts
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Eclipsebio expands its RNA characterization capabilities with multi-attribute nanopore-based sequencing assay eSTRAND RNA QC™
Creative Biolabs expands advanced single-cell multi-omics and RNA sequencing solutions to support biomedical discovery
Worm’s radical transformation shows metamorphosis can change the functions of cells
HeartBeat.bio and Cubase Bio Partner to Advance 3D Spatial Transcriptomics for Cardiovascular Drug Discovery
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
New Johns Hopkins Study Identifies Pervasive RT-qPCR Artifact in CRISPR Knockdown Studies and How UltraMarathonRT® Solves It
Atlas of the brain’s striatum could guide researchers to new drug treatments
Lexogen Expands NGS Services with GCLP-Compliant Workflows
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Researchers uncover novel immune cell populations that respond to immunotherapy treatment as well as key molecular factor required for therapy to succeed
There have been many success stories for checkpoint blockade therapies both in preclinical models and in patients with cancer. But many questions remain about exactly how such immunotherapies elicit their response and what determines when and where checkpoint blockade therapy succeeds or fails at reinvigorating the immune system to eradicate cancer. A new study led by investigators from Brigham and Women’s Hospital in collaboration with colleagues at the Broad Institute examines the effects of checkpoint blockade therapies on different populations of T cells, a key class of immune cells in tumors. The team’s surprising results point to a population of T cells that have been overlooked in the past and led to the identification of a molecular factor that may be predictive of response to treatment. The investigators’ findings are published in Immunity.
Anderson and colleagues leveraged modern technology to explore the effect of therapy on T cells across different cancers, capitalizing on computational methodologies and single-cell RNA-seq, a technique for measuring the output of thousands of genes from individual cells in a given population. The researchers took an iterative approach, allowing the data to point them toward interesting leads and then performing further testing in preclinical models of cancer.
This approach led them to Tcf7, a transcription factor that is required for the maintenance and function of an immune cell population that is capable of memory. Through their experimental models, the team found that this factor was required for immune-based therapies to succeed.
Source – Eurekalert
Kurtulus S, Madi A, Escobar G, Kuchroo VK, Regev A, Anderson Ac. (2019) Checkpoint Blockade Immunotherapy Induces Dynamic Changes in PD-1−CD8+ Tumor-Infiltrating T Cells. Immunity [Epub ahead of print]. [abstract]
Related Posts
RNA Sequencing identifies new tick-borne virus that causes flu-like illness
Eclipsebio expands its RNA characterization capabilities with multi-attribute nanopore-based sequencing assay eSTRAND RNA QC™
Creative Biolabs expands advanced single-cell multi-omics and RNA sequencing solutions to support biomedical discovery
Worm’s radical transformation shows metamorphosis can change the functions of cells
HeartBeat.bio and Cubase Bio Partner to Advance 3D Spatial Transcriptomics for Cardiovascular Drug Discovery
RNA sequencing reveals functional chimeric mRNAs in mammalian immunity
New Johns Hopkins Study Identifies Pervasive RT-qPCR Artifact in CRISPR Knockdown Studies and How UltraMarathonRT® Solves It
Atlas of the brain’s striatum could guide researchers to new drug treatments
Lexogen Expands NGS Services with GCLP-Compliant Workflows
Immune cells offer insights on billion-dollar virus
A functionally integrated cross-tissue alternative splicing program during short-term calorie restriction
Dietary oxidized plant sterol shifts macrophage state to fuel aortic inflammation
Unlocking the past – new method helps gain insights into old tissue
Novel AI model trained on RNA-Seq data accurately detects key gene mutations and predicts biomarkers across 32 cancer types
Transcriptomic aging clock reveals age-related molecular patterns in opioid dependence
RNA sequencing helps predict stem cell transplant benefit in pediatric AML
Protein ‘switch’ determines whether liposarcoma cells will become aggressive
Precursor tRNAs sense temperature changes: heat stress-induced capped pre-tRNAs suppress protein synthesis
Ketamine increases neuroplasticity in female mice but not in males
Somatic mutations linked to vascular damage in progeria
Stay Connected
Submit a Post to the Blog
Recent Posts
Subscribe to the RNA-Seq Blog
RNA-Seq Products & Services