Publication success!

Understanding the Role of IFN-γ in Preventing Melanoma Spread

Cancer metastasis remains one of the most daunting challenges in oncology. For cancers such as melanoma, the spread of tumour cells to distant parts of the body significantly complicates treatment and worsens patient prognosis. A critical element in this spread is the lymphatic system, which can act as a highway for tumour cells. Recent research from our colleagues in Zhengzhou, China, now sheds light on how the immune signalling molecule IFN-γ has a crucial role in maintaining the integrity of the lymphatic system, thereby preventing the dissemination of melanoma cells.

Key Takeaways

1. Lymphatic System and Cancer Spread:
   • The lymphatic system is essential in preventing the spread of tumour cells, such as melanoma.
   • Tumour-associated lymphatic vessel barrier function is vital in stopping cancer cells from migrating to distant sites.
2. Role of IFN-γ:
   • IFN-γ is known to inhibit lymphangiogenesis, a process linked to cancer metastasis.
   • This study highlights IFN-γ’s role in regulating the barrier function of lymphatic vessels, thereby influencing cancer cell dissemination.
3. Mechanisms of IFN-γ Action:
   • Using lymphatic endothelial cell (LEC)-specific IFN-γ receptor knockout mice, Linyu Zhu et al., found that the absence of IFN-γ receptors increased melanoma cell spread to lymph nodes.
   • IFN-γ inhibits the migration of melanoma cells across LECs, enhancing the lymphatic barrier.
4. Tight Junction Proteins:
   • IFN-γ upregulates Claudin-3, a tight junction protein in LECs.
   • Knocking down Claudin-3 in LECs negated the inhibitory effect of IFN-γ on melanoma cell migration, emphasizing Claudin-3’s role in maintaining barrier integrity.
5. Metabolic Pathways:
   • IFN-γ inhibits AMPK signalling activation, a pathway involved in fatty acid metabolism regulation.
   • Altering fatty acid metabolism and AMPK activation in LECs affected melanoma cell spread, linking metabolic processes to lymphatic barrier function.

Why This Matters

Understanding the mechanisms behind cancer metastasis is crucial for developing effective treatments. The insights from this study highlight the importance of IFN-γ in maintaining lymphatic vessel integrity and preventing cancer spread. By unravelling how IFN-γ influences tight junction proteins and metabolic pathways in LECs, researchers can explore new therapeutic strategies to enhance lymphatic barrier function and inhibit metastasis.

 

To dive deeper into the findings and explore the detailed mechanisms, read the full article and stay informed about the latest advancements in cancer metastasis research:

https://www.sciencedirect.com/science/article/abs/pii/S0925443924003077?via%3Dihub

 

Many congratulations to all those involved in this inspiring study: it was a pleasure working with you!

Revolutionizing Cancer Diagnosis: How Deep Learning and Better Labelling Are Changing the Game

In the ever-evolving landscape of cancer research and treatment, technological advancements continue to push boundaries and offer new hope. A recent study published last month in Frontiers in Immunology delves into a particularly promising area: the use of deep learning (DL) models to predict biomarker expression in images of haematoxylin and eosin (H&E)-stained tissues. This advancement could vastly improve access to critical immunophenotyping, essential for monitoring therapy, discovering new biomarkers, and developing personalized treatments. But there’s a catch—how we derive the data that trains these models significantly impacts their performance.

The Study: Unveiling the Methodology

Our great colleagues in Singapore devised a study to tackle this important aspect of DL models—namely, how the derivation of ground truth cell labels affects their predictive accuracy. The study was spearheaded by Joe Yeong, Mai Chan Lau and Yiyu Cai et al., and focused on CD3+ T-cells in lung cancer tissues. The researchers compared two approaches using Pix2Pix generative adversarial network (P2P-GAN)-based virtual staining models:

1. Same-Section Model: This model was trained with cell labels obtained from the exact same tissue section as the H&E-stained section.
2. Serial-Section Model: This one used cell labels derived from an adjacent tissue section, which is the conventional method.

Key Findings: A Step Forward in Precision

The results were clear and compelling. The same-section model outperformed the serial-section model in several significant ways:

• Improved Prediction Performance: The accuracy of predicting biomarker expression was markedly better in the same-section model.
• Better Patient Stratification: When applied to a public lung cancer cohort, the same-section model more effectively stratified patients based on survival outcomes.

These findings suggest that using ground truth cell labels from the same tissue section enhances the accuracy and clinical utility of DL models in immunophenotyping.

Why Should You Care?

This study isn’t just a technical improvement; it’s a potential game-changer for patients and healthcare providers. Here’s why:

1. Enhanced Diagnostic Accuracy: More accurate predictions of biomarker expressions mean better diagnostic precision, leading to more targeted and effective treatments.
2. Personalized Treatment Plans: Improved stratification of patients can lead to more personalized treatment strategies, which are critical in managing complex diseases like cancer.
3. Accelerated Research and Discovery: Better DL models can expedite the discovery of new biomarkers, opening doors to novel therapeutic avenues.

Bridging the Gap in Cancer Care

In essence, this study underscores the importance of methodological rigor in the development of AI tools in healthcare. As we continue to refine these technologies, the promise of a future where personalized, effective cancer treatment is the norm rather than the exception becomes increasingly tangible.

We are really excited to see how this work progresses, and to explore the incredible advancements at the intersection of technology and healthcare, and how they’re transforming lives every day. It was such a pleasure to work with the study authors in preparing their submission and look forward to learning of their continued success: Congratulations to all those involved!

You can check out the full text here: Frontiers | Training immunophenotyping deep learning models with the same-section ground truth cell label derivation method improves virtual staining accuracy (frontiersin.org), available now at Frontiers in Immunology.

Many congratulations to the study authors – it was a pleasure working with you and learning about this exciting research!

New publication success!

A collaborative team of researchers based at the Shanghai Institute of Immunology, the First affiliated hospital of Zhejiang University, the Singapore Immunology Network, the National University of Singapore (NUS), and the SingHealth Duke-NUS Academic Medical Center, have published the results of a superb study into how mutations in CSF-1R affect #microglia to promote #neurodegenerative disease.

The focus of this study was hereditary diffuse leukoencephalopathy with axonal spheroids (#HDLS) – a rare yet fatal neurodegenerative disease underpinned by mutations in CSF-IR. Wei Jie Wong and colleagues developed a state-of-the-art macrophage and forebrain #organoid co-culture derived from induced pluripotent stem cells isolated from two patients with HDLS.

Compared to control organoids (in which CSF-1R gene mutations were corrected), they found that the patient-derived macrophages exhibited a metabolic shift towards the glycolytic pathway and reduced CSF-1 sensitivity. The result of this shift was an increase in IL-1β production and an activated inflammatory phenotype. RNA sequencing revealed that these macrophages existed in a reactive state, which led to impaired neuronal cell regulation.

This ground breaking study has provided yet more evidence of the diverse roles of microglia, as well as great insight into the pathological mechanisms of HDLS. We have no doubt that immunologists, neuroscientists, and clinicians will all be thrilled to read this exciting study and learn how Wei Jie Wong et al. tackled this complex question.

If you are interested to learn more, the paper is now available to download here, complete with referee reports: https://lnkd.in/dcY2kYxh

Many congratulations to the whole team: Wei Jie Wong, Yi Wen Zhu, Hai Ting Wang, Jia Wen Qian, Ziyi Li, Li Song, Zhao Yuan Liu, Wei Guo, Shuang Yan Zhang, Bing Su, Fang Ping He, Kang Wang and Florent Ginhoux!

Researchers land Horizon Europe funding to tackle the burden of sepsis

Earlier this year, we had the great pleasure of working with Jan Frič and colleagues on their Horizon Europe proposal that aims to raise awareness and tackle the long-term consequences of sepsis.

We are delighted to share the news that this hugely exciting proposal has now been awarded a staggering 6.9 million euros! The consortium involved are already hard at work kick-starting their 5-year project titled “Biomarkers established to stratify sepsis long-term adverse effects to improve patients’ health and quality of life” – aka “BEATsep”.

We can’t wait to see how BEATsep progresses and to work with the team on their research outputs in the near future. For more information, check out their post below and their website: www.beatsepsis.eu

Huge congratulations to everyone involved!

Publication success!

Congratulations to Deola Sara and colleagues at Sidra Medicine (Qatar) and the Università degli Studi del Piemonte Orientale (Italy) on their recent publication in Blood Advances just last month!

Deola and colleagues conducted an impactful study to improve #genetherapy approaches for #hemophilia. For those of you unsure, hemophilia is a bleeding disorder that occurs as a result of a blood-clotting protein deficiency or dysfunction. Treatment options are currently limited, but progress has been made in recent #clinicaltrials that have looked at replacing the blood clotting protein factor VIII in autologous hematopoietic stem cells (HSCs) using viral delivery systems.

Here,  Deola et al. identified exactly which cell types should be targeted for such gene therapy, by looking at which HSCs and their progeny produce factor VIII. They achieved this by leveraging a flow cytometry method to generate a comprehensive map of native and lentivirus-based transgenic factor VIII production right from the HSC stage to the mature blood cell stage. Their map showed that factor VIII is produced during the progenitor-cell stages after cytokine stimulation. In the mature blood-cell stages, monocytes are responsible for most factor VIII production.

Moving to a zebrafish model of transient HA to validate their findings, Deola et al. found that promoting HSC self-renewal by treating these cells with the agonist UM171 resulted in the specific expansion of CD14+/CD31+ monocytes. These monocytes could carry the factor VIII transgene, thus correcting HA in zebrafish!

These findings might signal an advance towards a permanent treatment for patients with HA! Check out the details here: https://lnkd.in/drmBuRgT

Well done to everyone involved in this really exciting project: Insight Editing London’s Ilya Demchenko really enjoyed getting a sneak peek of these results before submission and assisting with the editing.