Emergent patterns of cellular phenotypes in health and disease

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Johns Hopkins University
The cellular framework that constitutes the building blocks of every living organism undergoes significant changes and transformations throughout its live time. In humans, many processes that involve these cellular changes can greatly influence the healthspan and survival of individuals, two of such processes include: aging and cancer. The two related, yet independent processes both arise due to the deterioration of ‘naïve’ cellular function, and the deficiency—later inability, of cells to properly regulate its physiology. Published studies have demonstrated a bi-phasic relationship between cancer and aging. With the incidences of cancer increasing with increasing age, followed by a plateau point and subsequent decrease; with cancer-type dependent shifts in this plateau point with age. There are a multitude of factors that affect the initiation and rate of progression of these cellular changes, and they stem from both intrinsic factors—such as the individuals’ underlying molecular and phenotypic profiles (i.e. genetics and protein expressions)—and extrinsic factors, such as lifestyle and environmental influences. To gain better understanding of these two naturally occurring processes, I took a piece-wise approach and asked two overarching questions. In regards to aging I asked how does the biochemical and biophysical features of cells construct the phenotypic portrait of human aging, and cane it be used to determine the biological age of individuals? Likewise, in regards to cancer: how does the cells’ physical properties associate with cancer progression and metastasis, and can it predict metastatic state based on the features of individual cells? In the first part of this study, I focus on human aging. Many studies have shown that there are marked changes in the cells’ molecular profiles and phenotypic behaviors with increasing age. To better understand this I procured a cohort of primary dermal fibroblasts and measured various aspects of the cellular biochemical framework (cell secretions, DNA damage response and DNA organization, cytoskeletal content and organization, and ATP content), as well as cellular biophysical features (morphology, motility, wound closure, traction strength, and cytoplasmic rheological properties). With this comprehensive approach, I was able to quantify age-dependent changes in various cellular features, and use these features to further predict biological age with a high degree of certainty. Knowing the biological age of an individual is important, since it is now apparent from the literature that the biological age is a better predictor of human healthspan and longevity than their corresponding chronological age. Secondly, according to the American Cancer Society, two out of every five persons in the US will develop cancer during his/her lifetime, with ninety percent of cancer-related deaths resulting from metastases, i.e. the migration of cancer cells from the primary tumor to distal sites in other organs. Since the completion of the Human Genome Project, researchers have focused on trying to understand the genetic basis of metastasis in an effort to better predict disease progression and uncover new therapeutic targets. However, possibly due to the inherent heterogeneity of cancer, no genetic signatures that clearly delineate cells from the primary tumors versus cells from metastatic sites have been found. Recent estimates suggest that millions of cells are shed from a primary tumor site each day, yet, progression to metastatic disease often take years, suggesting that metastasis is a highly inefficient process. From a biophysical perspective, I reasoned that in order to successfully overcome the difficult multi-step metastatic cascade—invasion and migration through the dense, tortuous stromal matrix, intravasation, survival of shear forces of blood flow, successful re-attachment to blood vessel walls, colonization at distal sites, and reactivation following dormancy—metastatic cells may share precise sets of physical properties. And these key physical properties (which can be thought of as the ensemble effects of it’s genetic, epigenetic and proteomic profiles, etc.) may contribute to the progression and diminished response to therapeutics exhibited by metastatic cells. Using a cohort of 13 clinically annotated PDAC (Pancreatic ductal adenocarcinoma) patient samples, cells were subjected to a phenotyping platform that I have co-developed—htCP (high-throughput cell phenotyping). This study revealed that using biophysical features described by the variations in the cellular morphological features, I was able to discover a phenotypic signature for metastasis, demonstrated in pancreatic and breast cancers, for both 2D and 3D environments.
Aging, Cancer