Mechanisms of Drug Sensitivity and Resistance in Small Cell Lung Cancer

Introduction

Small cell lung cancer (SCLC), with up to 8000 new diagnosed cases in Germany each year, is the most aggressive lung cancer subtype showing rapid cell division, treatment resistance and tendency to metastasize early. Recently, the first significant improvement in decades has been seen with the addition of immunotherapy to chemotherapy, but the effects are very modest. Much more exploration is needed to identify predictive biomarkers (i.e., biomolecules that can be used for early detection, diagnostic and prognostic) and to understand the underlying molecular mechanisms that cause this devastating disease. Building on recent discoveries in SCLC genetics and transcriptomics, we launch an orchestrated pursuit of mechanistic analyses, with the specific emphasis on identifying druggable features of SCLC like those underlying drug sensitivity, drug resistance and poor patience survival. We aim at advancing the understanding of the molecular development of the disease with the ultimate goal of transferring our novel discoveries into clinical applications that improve the survival of SCLS patients.

Methods

We are a highly interdisciplinary consortium covering expertise in biochemistry and signaling, structural biology, medical chemistry and structure-guided drug design, cancer immunology and modeling, computational cancer genomics, molecular pathology, as well as clinical trials. Our methods range from very well established techniques to novel transdisciplinary approaches, among them: generation of new SCLC models, comparative sequencing studies of drug-sensitive and drug-resistant SCLC tumors and functional characterization of these mutations, complex computational algorithms applied on whole-exome sequencing of SCLS specimens to establish the temporal order of mutational events, mass cytometry and a novel multiplexed immunohistochemistry platform to probe the tumor microenvironment before and after the occurrence of drug resistance, all of these together with long-term monitoring of patients in the clinic.

Results

There are different molecular subtypes of SCLC that can differ in their responses to various treatments. Heterogeneous tumors, that contain two or more of these subtypes, show the presence of neuroendocrine (NE) cells (NE), and non-neuroendocrine (non-NE) cells together. Recently, members of our Team, in an extended collaboration, discovered that the natural death of SCLC tumor cells can be activated in non-NE-cells using BSO (which induces ferroptosis: iron-dependent cell death caused by oxidative stress), while in the other type, the death of NE cells can be induced by Auranofin (an inhibitor of the TRX anti-oxidant pathway). Interestingly, when applying the treatment individually using only one of these mechanisms, the threatened tumor cells transformed themselves (so called, transdifferentiating cells) to avoid being killed (see Fig.1).  Therefore, dual targeting, i.e., tackling both pathways simultaneously, has higher therapeutic efficiency in this kind of tumors.

Discussion

Unfortunately, many other mechanisms that could potentially be used to induce natural tumor-cell death are already suppressed when the cancer is detected in patients. Therefore, characteristic tumor signatures that are potentially targetable or can serve for prediction or prognostic are very valuable. In general, throughout its life, any cell is exposed to various sources of DNA damage (like UV radiation or tobacco) that result in mutations. These mutational processes leave characteristic fingerprints in the DNA of cancer cells that can be exploited. Members of our Team have developed a new tool, called CaMuS, that allow us to disentangle and discover cancer mutational signatures in the DNA of SCLC cancer cells. The algorithm initially fits known “reference signatures” to the DNA data and then performs non-matrix factorization on the unexplained data to infer potentially novel patterns of mutational processes. After being derived mathematically, these mutation signatures have to be experimentally validated. Such studies in metastatic cancer, like SCLC, can provide important insights into therapeutic resistance mechanisms that can lead the development of novel treatments.

Outlook

Combining different approaches from modelling to flow cytometry and proteomics, from sequencing to mathematical algorithms, from laboratory probes to clinical trials, will continue generating new insights into SCLC biology and providing entry routes for targeted therapeutic intervention that derive in the improvement of life-quality and survival of SCLC patients.

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