Members of the Human Tumor Atlas Network (HTAN) have analyzed hundreds of thousands of cells from human and animal tissues to produce a body of work that gives precise insight into cancer in general, but also several diseases including breast, colon, and pancreatic cancer. The HTAN researchers’ work included detailed maps pinpointing cells’ exact position in tumors—3D cell maps also known as cell atlases. One paper even describes a molecular clock. The insights they provide could point to leads for potential treatments.
The research is published in a collection of papers published in Nature journals.
The HTAN describes this work as “A collection of research articles, methods and datasets from a collaborative initiative tracking human tumor evolution in space and time.” HTAN, they say, “offers a multidimensional view of cancer biology.”
Michael P. Snyder, of the department of Genetics, Stanford School of Medicine, is the senior author of one of the papers, which looks at “Global loss of promoter–enhancer connectivity and rebalancing of gene expression during early colorectal cancer carcinogenesis.”
Snyder says that taking this approach, “Let us understand in much better detail how cancer genes are regulated. We find that gene expression is more ‘relaxed’ i.e. less controlled in early stages of cancer.”
Their work, he hopes, will help us better decipher which genes will be turned on in cancer so we can target those. It will give us a better handle on which genes to target with anti-cancer agents. Next Snyder and his team, “Will map it down to the single-cell level and better understand how specific genes are regulated.”
Ken Lau’s group from the Epithelial Biology Center at the Vanderbilt University Medical Center in Nashville also contributed.
Their studies, he said, are unusual, “While most single-cell studies of tissues are performed as a snap-shot in time, our approach adds a critical temporal axis, enabling us to pinpoint timing of key events across development and disease progression. Our approach records multiple layers of information simultaneously at the single-cell level—lineage history, cell division patterns, and cell state—to enable multimodal measurement of time and behavior.”
They describe it as a molecular clock approach, like a microscopic time machine that records biological events as genetic changes in DNA. The concept is similar to building an evolutionary timeline, where DNA changes provide clues about historical events of speciation. Here, our clock approach is engineered in a living system where each “phylum/species” is represented by a cell, and events are recorded when a cell divides.
They aimed to uncover previously unknown or overlooked elements in embryonic development and tumorigenesis—specifically the origins and dynamics of key events. Most of these currently known phenomena were deciphered previously by “watching in real time,” which limits the scale of observation.
“Several findings took us by surprise,” Lau said. Tumorigenesis, for instance, has been viewed as a monoclonal process—originating from a single cell—for over 50 years. Unexpectedly, our recordings revealed that tumor initiation is actually a polyclonal process, requiring cooperation among multiple abnormal cells to form a tumor. People had the incorrect picture because they studied tumor initiation by looking at malignant cancers, where the genetic history of initiation has been erased.”
He points out that, “We were able to connect high resolution temporal recording in a model system of colorectal precancer to lower resolution clonal analysis in a large cohort of human colorectal precancers through the Human Tumor Atlas Network, which extends and validates our findings towards human translation.”
