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US team designs novel mapping of colorectal cancer

From around the age of 45, regular colonoscopies are recommended. However, despite the availability of this highly visual screening process, treatment decisions for individual patients are still largely guided by traditional histology – pathologists assess colorectal cancer by examining slides of tumour samples under a microscope.

Now, in an unusual collaboration between pathologists, engineers and computational scientists, a Harvard Medical School (HMS)-led team has combined histology with cutting-edge single-cell imaging technologies to create large-scale 2D and 3D spatial maps of colorectal cancer. The maps, described in Cell, layer extensive molecular information on top of histological features to provide new information about the structure of the cancer, as well as how it forms, progresses, and interacts with the immune system.

“Our approach provides a molecular window into 150 years of diagnostic pathology, showing that many of the elements and structures traditionally thought to be isolated are actually interconnected in unexpected ways,” said co-senior author Peter Sorger, the Otto Krayer Professor of Systems Pharmacology in the Blavatnik Institute at HMS.

“An analogy is that before, we were just looking at the tail or the foot of the elephant, but now, for the first time, we can start to see the whole elephant at once.”

The maps are part of the team’s broader efforts to create atlases for different cancer types that will be freely available to the scientific community as part of the National Cancer Institute’s Human Tumour Atlas Network.

Previously, the researchers used a similar approach to create in-depth maps of early-stage melanoma, and maps for other cancers are already in development. Ultimately, the team hopes these cancer atlases will propel research and improve diagnosis and treatment.

Combining old and new

Histology has long been the cornerstone of cancer diagnosis and treatment. Pathologists examine a tumour sample stained with haematoxylin and eosin (H&E) under a microscope and pick out key features to determine the grade and stage of the cancer. This information is used by oncologists to develop a treatment plan, which usually involves some combination of surgery, drugs and radiation.

H&E-based histology is relatively simple, cheap, fast and can reveal a lot about a tumour.

“Our existing maps of colorectal cancer originate in pathology – over the course of 150 years, we’ve figured out the most important H&E features for diagnosing a patient,” said co-senior author Sandro Santagata, HMS associate professor of systems biology and associate professor of pathology at Brigham and Women’s Hospital.

However, traditional histology has its limits: it doesn’t capture a cancer’s molecular makeup or physical structure, making it difficult to fully take advantage of the information cancer researchers have gained over the past 50 years.

In the latest paper, the researchers combined histology with single-cell molecular imaging data acquired through a multiplexed imaging technique called cyclic immunofluorescence, or CyCIF. They used this information to create detailed 2D maps of large regions of colorectal cancer.

First author Jia-Ren Lin, platform director in the Laboratory of Systems Pharmacology at HMS, led an effort to stitch these maps together to form a large-scale 3D reconstruction of a tumour.

“Our maps include information on almost 100m cells from large pieces of tumours, and provide an unprecedented look at colorectal cancer,” Santagata said. They allow researchers to start asking key questions about differences between normal and tumour tissues and variation within a tumour, he added, and reveal “exciting architectural features that had never been observed before, as well as molecular changes associated with these features”.

The maps showed that a single tumour can have more and less invasive sections, and more or less malignant-looking regions – resulting in histological and molecular gradients where one part of a tumour transitions into the next.

“Within each tumour, there is a wide range of properties of colorectal cancer. We see many different regions and neighbourhoods that have distinct characteristics, as well as the transitions between them,” Santagata said. From here, he added, scientists can now explore what drives these differences within individual tumours.

For example, the maps showed that immune environments varied dramatically within a single tumour.

“They were as different across a single tumour as among tumours, which is important because tumour-immune interactions are what you are trying to target with immunotherapy,” Sorger said. Similar to their finding in melanoma, the researchers observed that the T cells tasked with fighting off the cancer were not directly suppressed by tumour cells, but rather by other immune cells in the environment around the tumour.

“This gives us a whole new appreciation for how diverse and plastic the tumour environments are: they are rich communities, and we are now better equipped to figure out how they develop,” Santagata said.

The maps also provided new insights into the architecture of the tumours. For example, scientists had previously identified what they thought were 2D pools of a mucus-like substance called mucin with clusters of cancer cells floating inside.

However, in the new study, the 3D reconstruction revealed that these mucin pools are, in fact, a series of caverns interconnected by channels, with finger-like projections of cancer cells.

Translating results

Ultimately, the goal of these colorectal cancer maps is the same as it is for all of the cancer atlases the team is developing: to advance research and improve diagnosis and treatment. Precision medicine, which involves tailoring therapy to an individual patient’s cancer, is becoming an increasingly important part of treatment, Sorger noted, yet it can go only so far with pathology and genetics alone.

“The big translational story here is building the knowledge to make precision medicine practical for most patients,” he said. “We are working with Brigham and Women’s and the Dana-Farber Cancer Institute to determine how our methods can be used in a clinical setting.”

Now, the researchers want to further refine their ability to create 3D reconstructions of tumours and continue integrating new imaging technologies into their maps. They also want to build a bigger cohort of colorectal cancer samples for mapping and explore the basic biology of the disease that their maps have highlighted.

For Sorger, the project represents an unusual collaboration between pathologists, engineers, and computational scientists: As the imaging data rolled in, the computational scientists used machine learning to identify interesting findings they presented to the pathologists, and the pathologists flagged key features to be parsed with machine learning.

The team chose melanoma and colorectal cancer as a starting point because they are common cancers with unmet medical needs that consist of large, solid tumours and require important treatment decisions.

Next, they plan to tackle breast cancer and brain cancer. They also want to train other scientists to use the imaging technologies to build their own cancer maps, which would pave the way for the creation of even more atlases.

Study details

Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer.

Jia-Ren Lin, Shu Wang, Shannon Coy, Yu-An Chen, Clarence Yapp, Madison Tyler, Maulik Nariya, Cody Heiser, Ken Lau, Sandro Santagata, Peter Sorger.

Published in Cell on 19 January 2022

• Multiplexed analysis shows intermixed tumor morphologies and molecular gradients
• Various cancer characteristic cellular features are large, interconnected structures
• 3D TLS networks show intra-TLS patterning variation
• PD1-PDL1 interactions are primarily between T and myeloid cells in this CRC cohort


Advanced solid cancers are complex assemblies of tumour, immune, and stromal cells characterised by high intratumoral variation. We use highly multiplexed tissue imaging, 3D reconstruction, spatial statistics, and machine learning to identify cell types and states underlying morphological features of known diagnostic and prognostic significance in colorectal cancer. Quantitation of these features in high-plex marker space reveals recurrent transitions from one tumour morphology to the next, some of which are coincident with long-range gradients in the expression of oncogenes and epigenetic regulators. At the tumour invasive margin, where tumour, normal, and immune cells compete, T cell suppression involves multiple cell types and 3D imaging shows that seemingly localised 2D features such as tertiary lymphoid structures are commonly interconnected and have graded molecular properties. Thus, while cancer genetics emphasises the importance of discrete changes in tumour state, whole-specimen imaging reveals large-scale morphological and molecular gradients analogous to those in developing tissues.


Cell article – Multiplexed 3D atlas of state transitions and immune interaction in colorectal cancer (Open access)


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Colorectal cancer prevention: BMJ evidence review of 80 meta-analyses


Microbiome patterns predict colorectal cancer occurrence


ACS recommends earlier colorectal cancer screening


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