Lung Cancer Progression & Metastasis
Cancer metastasis is often depicted as an orderly cascade of events whereby malignant cells first spread from a primary tumor to eventually colonize a distant organ. In fact, the clinical course of metastatic disease is complex, being influenced by unique cellular origins, altered microenvironments, distinct physiologic restrictions, as well as specific molecular alterations. Importantly, current treatment regimens may actually enhance the development of drug resistant metastases. As such, innovative prognostic and therapeutic solutions are needed to abate or prevent metastasis progression.
Our goals are to develop models of cancer metastasis, identify molecular determinants of this process, and assess their clinical relevance. To achieve this, we have generated syngeneic, xenograft, and human patient derived models of metastasis. This permits both in vivo and ex vivo characterization of malignant cells that initiate tumors and colonize different microenvironments (Figure 1). Our mechanistic studies integrate various genomic and epigenomic approaches. We have also generated novel biorepositories of tumor tissue and liquid biopsies obtained directly from cancer patients (Figure 2). This unique resource can be leveraged to discover genetic and proteomic markers for the clinical management of metastatic disease. Our multi-faceted approach is being applied to the following areas of research:
1. Dysregulated lineage programs and lung cancer progression.
Lung cancers account for most cancer related deaths and are particularly diverse, with some subtypes capable of forming metastases in the liver, bones, adrenal glands, or most frequently the brain. Using various epigenomic platforms, we have uncovered transcriptional programs that predict metastasis when detected in models and early stage patient tumors. These programs are functionally linked to the erosion of normal pulmonary epithelial lineages and aberrant activation of neuronal traits. We aim to define the epigenetic mechanisms and biological consequences of these lineage gene expression patterns in metastatic cancer cells.
2. Contextual cues from the microenvironment.
Certain pathways are intrinsic to cancer cells and regulate overall metastatic competence. Alternatively, other signaling molecules may be triggered as disseminated cancer cells encounter specific microenvironments. Our models recapitulate several important tumor-stromal interactions, including the co-option of unique inflammatory cell types (Figure 3). We are using in vivo and ex vivo models, to mechanistically dissect paracrine interactions which affect the balance between tumor latency and metastatic outgrowth.
3. Linking metastasis with resistance to therapy.
Therapeutic resistance of aggressive cancers often correlates with metastatic relapse. Yet it is unclear how these two phenomena are mechanistically linked. A particularly intriguing example is the frequent secondary brain relapses observed in lung, breast, or skin cancer patients that were initially treated with chemotherapy or targeted therapy. Is this acquired resistance due to tumor cell intrinsic alterations, factors from the brain metastatic niche, or inefficient systemic drug delivery to the affected organ? Using biological and pharmacological insights obtained from our models, we are attempting to solve these questions with the goal of overcoming sanctuary site drug resistance of metastatic tumors.