Periodic Reporting for period 1 - BIOSMALL (Identification of subtype-specific biomarkers in small cell lung cancer)
Période du rapport: 2023-10-01 au 2025-09-30
Lung cancer is one of the most frequently diagnosed malignancy worldwide and the leading cause of cancer-related mortality. Historically lung cancer is divided into two major categories: non-small-cell lung cancer (NSCLC, ~85%) and small-cell lung cancer (SCLC, ~15%). SCLC is infamous within the field of oncology for being among the deadliest cancers. This is due to its ability to rapidly develop resistance against current “gold standard” treatment strategies and extensively give rise to organ metastases. With more than 200.000 deaths worldwide each year it represents a major health issue and a great socioeconomic and humanistic burden.
Clinically, SCLC is still regarded as a ‘homogenous’ disease, without significant therapeutic- and survival improvements in the last three decades. However, recently, there has been a worldwide resurgence of studies on SCLC, with the identification of distinct molecular subtypes.
In the proposed study, our multidisciplinary team aims to deepen our understanding of the clinical significance of molecular subtypes in SCLC. Specifically, we aim to identify novel potentially targetable proteins and signaling pathways, to determine the genetic mutation landscape of SCLC, to reveal the efficacy of chemotherapeutic and targeted agents, to gain insights into the specific metastatic patterns of each subtype and to establish diagnostic/predictive/prognostic biomarker panels.
Our project might help to focus and accelerate SCLC research and thus improve the clinical management of this devastating disease.
Clinically, SCLC is still regarded as a ‘homogenous’ disease, without significant therapeutic- and survival improvements in the last three decades. However, recently, there has been a worldwide resurgence of studies on SCLC, with the identification of distinct molecular subtypes.
In the proposed study, our multidisciplinary team aims to deepen our understanding of the clinical significance of molecular subtypes in SCLC. Specifically, we aim to identify novel potentially targetable proteins and signaling pathways, to determine the genetic mutation landscape of SCLC, to reveal the efficacy of chemotherapeutic and targeted agents, to gain insights into the specific metastatic patterns of each subtype and to establish diagnostic/predictive/prognostic biomarker panels.
Our project might help to focus and accelerate SCLC research and thus improve the clinical management of this devastating disease.
During the first reporting period, the project successfully established the collaboration framework among the participating institutions. The initial scientific work focused on harmonizing methodologies and setting up the technical and administrative infrastructure necessary for smooth project implementation.
We selected a panel of small cell lung cancer (SCLC) cell lines representing different subtypes, which provides the basis for future analyses. In parallel, we worked on establishing new cell lines from human samples.
We carried out experiments to study how different types of SCLC cancer cells grow and move, both in the laboratory and in mice. We introduced a special enzyme, luciferase, and fluorescent labels into the cells, allowing us to follow tumor growth in living animals without surgery using a dedicated imaging system (IVIS Spectrum CT).
We developed advanced methods to study proteins in cancer cells, including approaches that allow analysis at very small sample sizes. In addition, we established reliable workflows to combine protein and genetic data and to identify relevant protein variants.
By analyzing existing cancer databases, we identified potential markers that may help predict how patients respond to the disease. The relevance of these markers was also tested in tumor samples from patients.
Tumor tissue samples are continuously collected from primary tumors and available metastatic sites during surgery or rapid autopsy and preserved for further analysis.
When suitable tissue material is available, tumor samples are transplanted into mice with a weakened immune system to create models that closely resemble human cancer. These models are compared to the original patient tumors using detailed tissue analysis and combined molecular profiling.
Blood samples are collected from both patients and mice involved in the project. In parallel, we are developing methods to isolate and analyze extracellular vesicles—tiny particles released by cells—from very small volumes of blood plasma.
Patients who undergo PET scans are prospectively included in our study. We compare imaging results with laboratory analysis of tumor samples from the same patients to assess how well the two approaches match. The stained tissue samples are digitized and are currently being evaluated by expert pathologists.
We selected a panel of small cell lung cancer (SCLC) cell lines representing different subtypes, which provides the basis for future analyses. In parallel, we worked on establishing new cell lines from human samples.
We carried out experiments to study how different types of SCLC cancer cells grow and move, both in the laboratory and in mice. We introduced a special enzyme, luciferase, and fluorescent labels into the cells, allowing us to follow tumor growth in living animals without surgery using a dedicated imaging system (IVIS Spectrum CT).
We developed advanced methods to study proteins in cancer cells, including approaches that allow analysis at very small sample sizes. In addition, we established reliable workflows to combine protein and genetic data and to identify relevant protein variants.
By analyzing existing cancer databases, we identified potential markers that may help predict how patients respond to the disease. The relevance of these markers was also tested in tumor samples from patients.
Tumor tissue samples are continuously collected from primary tumors and available metastatic sites during surgery or rapid autopsy and preserved for further analysis.
When suitable tissue material is available, tumor samples are transplanted into mice with a weakened immune system to create models that closely resemble human cancer. These models are compared to the original patient tumors using detailed tissue analysis and combined molecular profiling.
Blood samples are collected from both patients and mice involved in the project. In parallel, we are developing methods to isolate and analyze extracellular vesicles—tiny particles released by cells—from very small volumes of blood plasma.
Patients who undergo PET scans are prospectively included in our study. We compare imaging results with laboratory analysis of tumor samples from the same patients to assess how well the two approaches match. The stained tissue samples are digitized and are currently being evaluated by expert pathologists.
During the first reporting period, we successfully established unique models representing different SCLC subtypes. In addition to commercially available cell lines, newly generated models are now being used to better reflect the complexity of the disease. A large number of tissue and blood samples were collected, providing a valuable translational resource with the potential to guide precision medicine and deepen our understanding of SCLC.
State-of-the-art analytical workflows were optimized, enabling the study of tumor biology with unprecedented precision. These advances go beyond the current state of the art by creating powerful new tools and resources for the international research community. In the long term, they will support the identification of biomarkers for earlier diagnosis, disease monitoring, and therapy selection, as well as the discovery of novel therapeutic targets.
State-of-the-art analytical workflows were optimized, enabling the study of tumor biology with unprecedented precision. These advances go beyond the current state of the art by creating powerful new tools and resources for the international research community. In the long term, they will support the identification of biomarkers for earlier diagnosis, disease monitoring, and therapy selection, as well as the discovery of novel therapeutic targets.