Introduction
Lung cancer remains the leading cause of cancer-related deaths worldwide, accounting for more mortalities than breast, prostate, and colorectal cancers combined. Lung cancer is often diagnosed at an advanced stage, where treatment options are limited and less effective. Among the various types of lung cancer, non-small cell lung cancer (NSCLC) is the predominant form, constituting approximately 85% of all lung cancer cases. NSCLC itself is not a single disease but a category encompassing several subtypes, the most common of which are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. Each subtype has distinct histological and molecular characteristics, which influence its behavior, prognosis, and response to treatment. Adenocarcinoma, for instance, is the most prevalent subtype, often occurring in the outer regions of the lungs and frequently associated with non-smokers and women. Squamous cell carcinoma, on the other hand, typically arises in the central part of the lungs and is strongly linked to smoking. The global burden of NSCLC is immense, with millions of new cases diagnosed annually. Despite advancements in medical research and treatment, the five-year survival rate for NSCLC remains relatively low, underscoring the urgent need for more effective diagnostic tools, targeted therapies, and comprehensive understanding of the disease at a molecular level. Recent innovations, such as single-cell RNA sequencing and spatial transcriptomics, are paving the way for more personalized and precise treatments, offering hope for better outcomes in the future.
In a recent study published in Nature Communications, Zuani et. al. (2024) leveraged single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics to create a molecular map of immune cells within NSCLC. In addition, Zuani et. al. (2024) characterized a unique population of cells that are hybrid within the tumor microenvironment called cancer-associated macrophage-like cells (CAMLs) that are associated with poorer progression free survival and overall survival in a variety of cancers.
A Deep Dive into the Tumor Microenvironment
In this study, Zuani et. al. (2024) analyzed approximately 900,000 cells from 25 treatment-naive individuals. Importantly, the research included non-tumor samples as controls, providing a robust framework for comparative analysis. Myeloid cells, which play a pivotal role in initiating inflammation, are abundant within tumors. Recent findings suggest that macrophages, a subset of myeloid cells, can either suppress or promote tumor growth. This duality makes them an ideal target for NSCLC therapies. However, the complexity and variety of macrophages necessitate a comprehensive understanding of their behaviors and interactions within the tumor microenvironment.
To capture cell-cell interactions, Zuani et al. (2024) also performed spatial transcriptomics on a subset of the samples. This approach allowed them to construct a comprehensive atlas of both immune and non-immune compartments in lung cancer. One key finding was the diversity of macrophages. The study confirmed an inverse relationship between anti-inflammatory macrophages and natural killer/T cells in tumors. There were significantly more types of myeloid cells in the tumor than in adjacent tissue, with a shift towards cholesterol export in tumor-associated myeloid cells, potentially supporting tumor growth. This finding highlights the dynamic nature of macrophages in the tumor microenvironment and their potential role in promoting tumor progression. In addition, another significant finding was the presence of a fetal-like phenotype in some myeloid cells. These cells exhibited characteristics suggesting they can be reprogrammed within the tumor environment. This aligns with recent findings in the field and opens up new avenues for research into the plasticity of immune cells in cancer. The ability of myeloid cells to adopt a fetal-like state may have implications for their function and interaction with other cells in the tumor microenvironment.
Within the tumor microenvironment, Zuani et. al. (2024) identified a population of cells called CAML, that were characterized by the co-expression of both myeloid and epithelial genes. These cells, with characteristics of both myeloid and epithelial cells, have been observed in blood samples of patients with various malignancies, including NSCLC. CAMLs represent a novel cell type that bridges the gap between immune cells and epithelial cells. Their presence in tumors suggests a potential role in cancer progression and metastasis. CAMLs expressed markers in alignment other published work on tumor hybrid cells, such as KRT19, EPCAM, and CD14, suggesting that these cells possess characteristics of both immune cells (macrophages) and epithelial cells, which are typically found lining the surfaces of organs and structures within the body. CAMLs were found to represent a small minority, comprising less than 0.25 % of the total cell population and were assigned a low doublet score by Scrublet. The authors further attempted to sub-cluster CAMLs, however, these cells still maintained dual gene signatures. Zuani et al. (2024) further conducted an analysis of copy number variation (CNV) on CAMLs, which provided evidence that these cells share genomic alterations to tumor cells. Collectively, the authors argued that this finding provides evidence that the cluster corresponding to CAMLs corresponds to hybrid cells, and is unlikely to be explained by the incidental sequencing of both tumor cells and macrophages.
The discovery of CAMLs in NSCLC opens new avenues for understanding the complexity of the tumor microenvironment and the role of hybrid cells in cancer biology. The identification and characterization of CAMLs could lead to the development of novel diagnostic and therapeutic strategies. For instance, targeting CAMLs might disrupt their potential role in tumor progression and metastasis, thereby improving patient outcomes. Further research is needed to explore the functional implications of CAMLs in cancer and to determine how these cells can be effectively targeted in clinical settings.
Collaborative Efforts and Future Directions
This study was a collaborative effort involving academic and pharmaceutical partners, including Sanofi and GSK. Future research could benefit from even larger datasets, encompassing more individuals to capture genuine differences between disease and control tissues. Additionally, integrating other modalities, such as chromatin accessibility studies, could provide deeper insights into the epigenetic landscape of NSCLC.
Although there were no significant differences in cell composition between adenocarcinomas and squamous cell carcinomas, the study found differences in tumor-immune cell interactions between these subtypes. This led to the identification of various immune checkpoint inhibitors, including novel ones targeting tumor hybrid cells, as potential therapeutic targets. By pinpointing these differences, researchers can develop therapies that specifically target the unique interactions and pathways in each subtype, enhancing the effectiveness of treatment. In summary, this landmark study not only advances our understanding of the immune landscape in NSCLC but also opens new avenues for personalized therapies and collaborative research efforts in the fight against lung cancer.
Outsourcing Bioinformatics Analysis: How Bridge Informatics (BI) Can Help
At Bridge Informatics, we are passionate about empowering life science companies with the latest and most advanced technologies, including large language models (LLM) inspired tools, such as GPTs, to ensure they stay at the forefront of their fields. BI’s data scientists prioritize studying, understanding, and reporting on the latest developments so we can advise our clients confidently. Our bioinformaticians are trained bench biologists, so they understand the biological questions driving your computational analysis.
From pipeline development and software engineering to deploying your existing bioinformatic tools, BI can help you on every step of your research journey. As experts across data types from leading sequencing platforms, we can help you tackle the challenging computational tasks of storing, analyzing and interpreting genomic and transcriptomic data. Click here to schedule a free introductory call with a member of our team.
Haider M. Hassan, Data Scientist, Bridge Informatics
Haider is one of our premier data scientists. He provides bioinformatic services to clients, including high throughput sequencing, data pre-processing, analysis, and custom pipeline development. Drawing on his rich experience with a variety of high-throughput sequencing technologies, Haider analyzes transcriptional (spatial and single-cell), epigenetic, and genetic landscapes.
Before joining Bridge Informatics, Haider was a Postdoctoral Associate at the London Regional Cancer Centre in Ontario, Canada. During his postdoc, he investigated the epigenetics of late-onset liver cancer using murine and human models. Haider holds a Ph.D. in biochemistry from Western University, where he studied the molecular mechanisms behind oncogenesis. Haider still lives in Ontario and enjoys spending his spare time visiting local parks. If you’re interested in reaching out, please email [email protected] or [email protected]
