Functional odor classification through a medicinal chemistry approach.

Crucial for any hypothesis about odor coding is the classification and prediction of sensory qualities in chemical compounds. The relationship between perceptual quality and molecular structure has occupied olfactory scientists throughout the 20th century, but details of the mechanism remain elusive. Odor molecules are typically organic compounds of low molecular weight that may be aliphatic or aromatic, may be saturated or unsaturated, and may have diverse functional polar groups. However, many molecules conforming to these characteristics are odorless. One approach recently used to solve this problem was to apply machine learning strategies to a large set of odors and human classifiers in an attempt to find common and unique chemical features that would predict a chemical's odor. We use an alternative method that relies more on the biological responses of olfactory sensory neurons and then applies the principles of medicinal chemistry, a technique widely used in drug discovery. We demonstrate the effectiveness of this strategy through a classification for esters, an important odorant for the creation of flavor in wine. Our findings indicate that computational approaches that do not account for biological responses will be plagued by both false positives and false negatives and fail to provide meaningful mechanistic data. However, the two approaches used in tandem could resolve many of the paradoxes in odor perception.

Applying medicinal chemistry strategies to understand odorant discrimination.

Associating an odorant's chemical structure with its percept is a long-standing challenge. One hindrance may come from the adoption of the organic chemistry scheme of molecular description and classification. Chemists classify molecules according to characteristics that are useful in synthesis or isolation, but which may be of little importance to a biological sensory system. Accordingly, we look to medicinal chemistry, which emphasizes biological function over chemical form, in an attempt to discern which among the many molecular features are most important for odour discrimination. Here we use medicinal chemistry concepts to assemble a panel of molecules to test how heteroaromatic ring substitution of the benzene ring will change the odour percept of acetophenone. This work allows us to describe an extensive rule in odorant detection by mammalian olfactory receptors. Whereas organic chemistry would have predicted the ring size and composition to be key features, our work reveals that the topological polar surface area is the key feature for the discrimination of these odorants.

Whole-exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer.

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two patients with prostate cancer, including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were present in matched tissue. Moreover, we identified 10 early trunk and 56 metastatic trunk mutations in the non-CTC tumor samples and found 90% and 73% of these mutations, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic.

Single cells from human primary colorectal tumors exhibit polyfunctional heterogeneity in secretions of ELR+ CXC chemokines.

Cancer is an inflammatory disease of tissue that is largely influenced by the interactions between multiple cell types, secreted factors, and signal transduction pathways. While single-cell sequencing continues to refine our understanding of the clonotypic heterogeneity within tumors, the complex interplay between genetic variations and non-genetic factors ultimately affects therapeutic outcome. Much has been learned through bulk studies of secreted factors in the tumor microenvironment, but the secretory behavior of single cells has been largely uncharacterized. Here we directly profiled the secretions of ELR+ CXC chemokines from thousands of single colorectal tumor and stromal cells, using an array of subnanoliter wells and a technique called microengraving to characterize both the rates of secretion of several factors at once and the numbers of cells secreting each chemokine. The ELR+ CXC chemokines are highly redundant, pro-angiogenic cytokines that signal via the CXCR1 and CXCR2 receptors, influencing tumor growth and progression. We find that human primary colorectal tumor and stromal cells exhibit polyfunctional heterogeneity in the combinations and magnitudes of secretions for these chemokines. In cell lines, we observe similar variance: phenotypes observed in bulk can be largely absent among the majority of single cells, and discordances exist between secretory states measured and gene expression for these chemokines among single cells. Together, these measures suggest secretory states among tumor cells are complex and can evolve dynamically. Most importantly, this study reveals new insight into the intratumoral phenotypic heterogeneity of human primary tumors.