Two studies are dedicated to amplifying cancer signals

This year, about 240,000 people in the United States will find themselves with lung cancer
.
About 200,000 of them will be diagnosed with non-small cell lung cancer, the second leading cause
of death after cardiovascular disease.
Ahmet Coskun, a researcher at the Georgia Institute of Technology, recently published two studies dedicated to improving the odds of disease in these patients
.
Both studies focused on understanding how patients respond differently to diseases and treatments and how they differ
.

"What we've learned is that the connections and communication between molecules and cells are the factors that really control everything, and it's about whether patients will become healthy or how
they respond to drugs," Coskun said.

The studies, published in the journal npj Precision Oncology and iScience, detail the development of tools and techniques to deeply explore the tumor microenvironment at the subcellular level, leveraging Coskun Labs' expertise
in complex cell imaging methods and artificial intelligence.

"We are better grasping cell signaling and decision-making, and how they are coordinated in the tumor microenvironment, which can lead to better personalized, precise treatment
for these patients," Coskun said.
Coskun is very interested in
why some patients respond to breakthrough immunotherapy drugs and others don't.

With this in mind, his team developed SpatialVizScore, a new method they described in the journal npj Precision Oncology to delve into tumor immunology in cancer tissue and help determine which patients are more likely to respond
to immunotherapy.
This is a major upgrade to the standard method of immune scoring currently used by cancer doctors and researchers
.

Immunity score

Immune scoring is a tool used for prediction to measure how well the body's immune cells surround and enter a
tumor.
It shows hope in predicting the risk of disease recurrence in patients, a key step
in developing a personalized treatment plan.
A higher score indicates better immune cell infiltration, and a lower score indicates a greater
risk of recurrence.

But immune cells are moving targets, exhibiting a high degree of molecular complexity, and traditional immunoscoring methods cannot always be adequately captured
.
Through SpatialVizScore, Coskun's team expanded the coverage of immune scores
.

While the standard approach looks at how T cells interact with tumors, Coskun's system looks at the interactions of other immune cells, such as macrophages, which have two subtypes — M1 and M2 — that often find their own conflicts
.
M1 helps destroy pathogens, while M2 promotes tumor growth
.

Coskun's multiplex imaging system can observe all of this, visualizing how these cells communicate and interact with each other and how these cells interact with cancer cells, not just inside and around the tumor, but throughout the tumor environment
.

"Because cancer cells and immune cells are not always close to each other, we imagine spatial connections, we imagine cell communities or neighbors
," Coskun said.
"But we're not just looking at how cancer cells interact
with immune cells.
We are also studying interactions
between the immune systems.
By looking at the effects of these different interactions, we can interpret tumors and we can develop a more comprehensive immune score
.
”

magnify

In the iScience study, the team moved out of the cell's communities and neighborhoods
.
Instead, they focused on subcellular protein-protein interaction networks, which could affect cancer's signaling pathways — which could be cell division or cell death
when molecules in cells work together to control cell function.

Each molecule activates the other, and this process repeats along the "pathway" until the last molecule is activated and cellular functions (good or bad) are performed
.
Abnormal activation of pathways can lead to cancer, but some drugs target specific molecules that are related and can stop cancer cells from growing
.

Coskun and his team are using their multiplex imaging tools and machine learning to probe protein-protein interactions to decipher the pathogenesis
of the signaling pathways that lead to drug resistance in non-small cell lung cancer.

"We can observe and map protein activity," said Coskun, whose team developed a subcell-resolution imaging technique called rapid multiplexing immunofluorescence (RapMIF
).

"Proteins are making decisions that affect our cells," Coskun added
.
"Now we can see how they communicate and how they affect the final function of
our cells.
" It's a signal-finding approach that can be used to design precision therapies and ultimately help more patients who
are battling cancer.
”

Spatially variant immune infiltration scoring in human cancer tissues.
npj Precision Oncology, 2022; 6 (1)

Multiplexed protein profiling reveals spatial subcellular signaling networks.
iScience, 2022; 25 (9): 104980