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Snapshots of Life

Working to Improve Immunotherapy for Lung Cancer

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Lung Cancer Immunotherapy
Credit: Xiaodong Zhu, Fred Hutchinson Cancer Research Center, Seattle

For those who track cancer statistics, this year started off on a positive note with word that lung cancer deaths continue to decline in the United States [1]. While there’s plenty of credit to go around for that encouraging news—and continued reduction in smoking is a big factor—some of this progress likely can be ascribed to a type of immunotherapy, called PD-1 inhibitors. This revolutionary approach has dramatically changed the treatment landscape for the most common type of lung cancer, non-small cell lung cancer (NSCLC).

PD-1 inhibitors, which have only been available for about five years, prime one component of a patient’s own immune system, called T cells, to seek and destroy malignant cells in the lungs. Unfortunately, however, only about 20 percent of people with NSCLC respond to PD-1 inhibitors. So, many researchers, including the team of A. McGarry Houghton, Fred Hutchinson Cancer Research Center, Seattle, are working hard to extend the benefits of immunotherapy to more cancer patients.

The team’s latest paper, published in JCI Insight [2], reveals that one culprit behind a poor response to immunotherapy may be the immune system’s own first responders: neutrophils. Billions of neutrophils circulate throughout the body to track down abnormalities, such as harmful bacteria and malignant cells. They also contact other parts of the immune system, including T cells, if help is needed to eliminate the health threat.

In their study, the Houghton team, led by Julia Kargl, combined several lab techniques to take a rigorous, unbiased look at the immune cell profiles of tumor samples from dozens of NSCLC patients who received PD-1 inhibitors as a frontline treatment. The micrographs above show tumor samples from two of these patients.

In the image on the left, large swaths of T cells (light blue) have infiltrated the cancer cells (white specks). Interestingly, other immune cells, including neutrophils (magenta), are sparse.

In contrast, in the image on the right, T cells (light blue) are sparse. Instead, the tumor teems with other types of immune cells, including macrophages (red), two types of monocytes (yellow, green), and, most significantly, lots of neutrophils (magenta). These cells arise from myeloid progenitor cells in the bone marrow, while T cells arise from the marrow’s lymphoid progenitor cell.

Though the immune profiles of some tumor samples were tough to classify, the researchers found that most fit neatly into two subgroups: tumors showing active levels of T cell infiltration (like the image on the left) or those with large numbers of myeloid immune cells, especially neutrophils (like the image on the right). This dichotomy then served as a reliable predictor of treatment outcome. In the tumor samples with majority T cells, the PD-1 inhibitor worked to varying degrees. But in the tumor samples with predominantly neutrophil infiltration, the treatment failed.

Houghton’s team has previously found that many cancers, including NSCLC, actively recruit neutrophils, turning them into zombie-like helpers that falsely signal other immune cells, like T cells, to stay away. Based on this information, Houghton and colleagues used a mouse model of lung cancer to explore a possible way to increase the success rate of PD-1 immunotherapy.

In their mouse experiments, the researchers found that when PD-1 was combined with an existing drug that inhibits neutrophils, lung tumors infiltrated with neutrophils were converted into tumors infiltrated by T cells. The tumors treated with the combination treatment also expressed genes associated with an active immunotherapy response.

This year, January brought encouraging news about decreasing deaths from lung cancer. But with ongoing basic research, like this study, to tease out the mechanisms underlying the success and failure of immunotherapy, future months may bring even better news.

References:

[1] Cancer statistics, 2020. Siegel RL, Miller KD, Jemal A. CA Cancer J Clin. 2020 Jan;70(1):7-30.

[2] Neutrophil content predicts lymphocyte depletion and anti-PD1 treatment failure in NSCLC. Kargl J, Zhu X, Zhang H, Yang GHY, Friesen TJ, Shipley M, Maeda DY, Zebala JA, McKay-Fleisch J, Meredith G, Mashadi-Hossein A, Baik C, Pierce RH, Redman MW, Thompson JC, Albelda SM, Bolouri H, Houghton AM. JCI Insight. 2019 Dec 19;4(24).

[3] Neutrophils dominate the immune cell composition in non-small cell lung cancer. Kargl J, Busch SE, Yang GH, Kim KH, Hanke ML, Metz HE, Hubbard JJ, Lee SM, Madtes DK, McIntosh MW, Houghton AM. Nat Commun. 2017 Feb 1;8:14381.

Links:

Non-Small Cell Lung Cancer Treatment (PDQ®)–Patient Version (National Cancer Institute/NIH)

Spotlight on McGarry Houghton (Fred Hutchinson Cancer Research Center, Seattle)

Houghton Lab (Fred Hutchinson Cancer Research Center)

NIH Support: National Cancer Institute


How Mucus Tames Microbes

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Scanning EM of mucus
Credit: Katharina Ribbeck, Massachusetts Institute of Technology, Cambridge

Most of us think of mucus as little more than slimy and somewhat yucky stuff that’s easily ignored until you come down with a cold like the one I just had. But, when it comes to our health, there’s much more to mucus than you might think.

Mucus covers the moist surfaces of the human body, including the eyes, nostrils, lungs, and gastrointestinal tract. In fact, the average person makes more than a liter of mucus each day! It houses trillions of microbes and serves as a first line of defense against the subset of those microorganisms that cause infections. For these reasons, NIH-funded researchers, led by Katharina Ribbeck, Massachusetts Institute of Technology, Cambridge, are out to gain a greater understanding of the biology of healthy mucus—and then possibly use that knowledge to develop new therapeutics.

Ribbeck’s team used a scanning electron microscope to take the image of mucus you see above. You’ll notice right away that mucus doesn’t look like simple slime at all. In fact, if you could zoom into this complex web, you’d discover it’s made up of mucin proteins and glycans, which are sugar molecules that resemble bottle brushes.

Ribbeck and her colleagues recently discovered that the glycans in healthy mucus play a long-overlooked role in “taming” bacteria that might make us ill [1]. This work builds on their previous findings that mucus interferes with bacterial behavior, preventing these bugs from attaching to surfaces and communicating with each other [2].

In their new study, published in Nature Microbiology, Ribbeck, lead author Kelsey Wheeler, and their colleagues studied mucus and its interactions with Pseudomonas aeruginosa. This bacterium is a common cause of serious lung infections in people with cystic fibrosis or compromised immune systems.

The researchers found that in the presence of glycans, P. aeruginosa was rendered less harmful and infectious. The bacteria also produced fewer toxins. The findings show that it isn’t just that microbes get trapped in a tangled web within mucus, but rather that glycans have a special ability to moderate the bugs’ behavior. The researchers also have evidence of similar interactions between mucus and other microorganisms, such as those responsible for yeast infections.

The new study highlights an intriguing strategy to tame, rather than kill, bacteria to manage infections. In fact, Ribbeck views mucus and its glycans as a therapeutic gold mine. She hopes to apply what she’s learned to develop artificial mucus as an anti-microbial therapeutic for use inside and outside the body. Not bad for a substance that you might have thought was nothing more than slimy stuff.

References:

[1] Mucin glycans attenuate the virulence of Pseudomonas aeruginosa in infection. Wheeler KM, Cárcamo-Oyarce G, Turner BS, Dellos-Nolan S, Co JY, Lehoux S, Cummings RD, Wozniak DJ, Ribbeck K. Nat Microbiol. 2019 Oct 14.

[2] Mucins trigger dispersal of Pseudomonas aeruginosa biofilms. Co JY, Cárcamo-Oyarce, Billings N, Wheeler KM, Grindy SC, Holten-Andersen N, Ribbeck K. NPJ Biofilms Microbiomes. 2018 Oct 10;4:23.

Links:

Cystic Fibrosis (National Heart, Lung, and Blood Institute/NIH)

Video: Chemistry in Action—Katharina Ribbeck (YouTube)

Katharina Ribbeck (Massachusetts Institute of Technology, Cambridge)

NIH Support: National Institute of Biomedical Imaging and Bioengineering; National Institute of Environmental Health Sciences; National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases


Replenishing the Liver’s Immune Protections

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Kupffer cells
Credit: Thomas Deerinck, National Center for Microscopy and Imaging Research, University of California, San Diego.

Most of our immune cells circulate throughout the bloodstream to serve as a roving security force against infection. But some immune cells don’t travel much at all and instead safeguard a specific organ or tissue. That’s what you are seeing in this electron micrograph of a type of scavenging macrophage, called a Kupffer cell (green), which resides exclusively in the liver (brown).

Normally, Kupffer cells appear in the liver during the early stages of mammalian development and stay put throughout life to protect liver cells, clean up old red blood cells, and regulate iron levels. But in their experimental system, Christopher Glass and his colleagues from University of California, San Diego, removed all original Kupffer cells from a young mouse to see if this would allow signals from the liver that encourage the development of new Kupffer cells.

The NIH-funded researchers succeeded in setting up the right conditions to spur a heavy influx of circulating precursor immune cells, called monocytes, into the liver, and then prompted those monocytes to turn into the replacement Kupffer cells. In a recent study in the journal Immunity, the team details the specific genomic changes required for the monocytes to differentiate into Kupffer cells [1]. This information will help advance the study of Kupffer cells and their role in many liver diseases, including nonalcoholic steatohepatitis (NASH), which affects an estimated 3 to 12 percent of U.S. adults [2].

The new work also has broad implications for immunology research because it provides additional evidence that circulating monocytes contain genomic instructions that, when activated in the right way by nearby cells or other factors, can prompt the monocytes to develop into various, specialized types of scavenging macrophages. For example, in the mouse system, Glass’s team found that the endothelial cells lining the liver’s blood vessels, which is where Kupffer cells hang out, emit biochemical distress signals when their immune neighbors disappear.

While more details need to be worked out, this study is another excellent example of how basic research, including the ability to query single cells about their gene expression programs, is generating fundamental knowledge about the nature and behavior of living systems. Such knowledge is opening new possibilities to more precise ways of treating and preventing diseases all throughout the body, including those involving Kupffer cells and the liver.

References:

[1] Liver-Derived Signals Sequentially Reprogram Myeloid Enhancers to Initiate and Maintain Kupffer Cell Identity. Sakai M, Troutman TD, Seidman JS, Ouyang Z, Spann NJ, Abe Y, Ego KM, Bruni CM, Deng Z, Schlachetzki JCM, Nott A, Bennett H, Chang J, Vu BT, Pasillas MP, Link VM, Texari L, Heinz S, Thompson BM, McDonald JG, Geissmann F3, Glass CK. Immunity. 2019 Oct 15;51(4):655-670.

[2] Recommendations for diagnosis, referral for liver biopsy, and treatment of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Spengler EK, Loomba R. Mayo Clinic Proceedings. 2015;90(9):1233–1246.

Links:

Liver Disease (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

Nonalcoholic Fatty Liver Disease & NASH (NIDDK)

Glass Laboratory (University of California, San Diego)

NIH Support: National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences; National Cancer Institute


What a Memory Looks Like

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Engram Image
Credit: Stephanie Grella, Ramirez Group, Boston University

Your brain has the capacity to store a lifetime of memories, covering everything from the name of your first pet to your latest computer password. But what does a memory actually look like? Thanks to some very cool neuroscience, you are looking at one.

The physical manifestation of a memory, or engram, consists of clusters of brain cells active when a specific memory was formed. Your brain’s hippocampus plays an important role in storing and retrieving these memories. In this cross-section of a mouse hippocampus, imaged by the lab of NIH-supported neuroscientist Steve Ramirez, at Boston University, cells belonging to an engram are green, while blue indicates those not involved in forming the memory.

When a memory is recalled, the cells within an engram reactivate and turn on, to varying degrees, other neural circuits (e.g., sight, sound, smell, emotions) that were active when that memory was recorded. It’s not clear how these brain-wide connections are made. But it appears that engrams are the gatekeepers that mediate memory.

The story of this research dates back several years, when Ramirez helped develop a system that made it possible to image engrams by tagging cells in the mouse brain with fluorescent dyes. Using an innovative technology developed by other researchers, called optogenetics, Ramirez’s team then discovered it could shine light onto a collection of hippocampal neurons storing a specific memory and reactivate the sensation associated with the memory [1].

Ramirez has since gone on to show that, at least in mice, optogenetics can be used to trick the brain into creating a false memory [2]. From this work, he has also come to the interesting and somewhat troubling conclusion that the most accurate memories appear to be the ones that are never recalled. The reason: the mammalian brain edits—and slightly changes—memories whenever they are accessed.

All of the above suggested to Ramirez that, given its tremendous plasticity, the brain may possess the power to downplay a traumatic memory or to boost a pleasant recollection. Toward that end, Ramirez’s team is now using its mouse system to explore ways of suppressing one engram while enhancing another [3].

For Ramirez, though, the ultimate goal is to develop brain-wide maps that chart all of the neural networks involved in recording, storing, and retrieving memories. He recently was awarded an NIH Director’s Transformative Research Award to begin the process. Such maps will be invaluable in determining how stress affects memory, as well as what goes wrong in dementia and other devastating memory disorders.

References:

[1] Optogenetic stimulation of a hippocampal engram activates fear memory recall. Liu X, Ramirez S, Pang PT, Puryear CB, Govindarajan A, Deisseroth K, Tonegawa S. Nature. 2012 Mar 22;484(7394):381-385.

[2] Creating a false memory in the hippocampus. Ramirez S, Liu X, Lin PA, Suh J, Pignatelli M, Redondo RL, Ryan TJ, Tonegawa S. Science. 2013 Jul 26;341(6144):387-391.

[3] Artificially Enhancing and Suppressing Hippocampus-Mediated Memories. Chen BK, Murawski NJ, Cincotta C, McKissick O, Finkelstein A, Hamidi AB, Merfeld E, Doucette E, Grella SL, Shpokayte M, Zaki Y, Fortin A, Ramirez S. Curr Biol. 2019 Jun 3;29(11):1885-1894.

Links:

The Ramirez Group (Boston University, MA)

Ramirez Project Information (Common Fund/NIH)

NIH Director’s Early Independence Award (Common Fund)

NIH Director’s Transformative Research Award (Common Fund)

NIH Support: Common Fund


Defining Neurons in Technicolor

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Brain Architecture
Credit: Allen Institute for Brain Science, Seattle

Can you identify a familiar pattern in this image’s square grid? Yes, it’s the outline of the periodic table! But instead of organizing chemical elements, this periodic table sorts 46 different types of neurons present in the visual cortex of a mouse brain.

Scientists, led by Hongkui Zeng at the Allen Institute for Brain Science, Seattle, constructed this periodic table by assigning colors to their neuronal discoveries based upon their main cell functions [1]. Cells in pinks, violets, reds, and oranges have inhibitory electrical activity, while those in greens and blues have excitatory electrical activity.

For any given cell, the darker colors indicate dendrites, which receive signals from other neurons. The lighter colors indicate axons, which transmit signals. Examples of electrical properties—the number and intensity of their “spikes”—appear along the edges of the table near the bottom.

To create this visually arresting image, Zeng’s NIH-supported team injected dye-containing probes into neurons. The probes are engineered to carry genes that make certain types of neurons glow bright colors under the microscope.

This allowed the researchers to examine a tiny slice of brain tissue and view each colored neuron’s shape, as well as measure its electrical response. They followed up with computational tools to combine these two characteristics and classify cell types based on their shape and electrical activity. Zeng’s team could then sort the cells into clusters using a computer algorithm to avoid potential human bias from visually interpreting the data.

Why compile such a detailed atlas of neuronal subtypes? Although scientists have been surveying cells since the invention of the microscope centuries ago, there is still no consensus on what a “cell type” is. Large, rich datasets like this atlas contain massive amounts of information to characterize individual cells well beyond their appearance under a microscope, helping to explain factors that make cells similar or dissimilar. Those differences may not be apparent to the naked eye.

Just last year, Allen Institute researchers conducted similar work by categorizing nearly 24,000 cells from the brain’s visual and motor cortex into different types based upon their gene activity [2]. The latest research lines up well with the cell subclasses and types categorized in the previous gene-activity work. As a result, the scientists have more evidence that each of the 46 cell types is actually distinct from the others and likely drives a particular function within the visual cortex.

Publicly available resources, like this database of cell types, fuel much more discovery. Scientists all over the world can look at this table (and soon, more atlases from other parts of the brain) to see where a cell type fits into a region of interest and how it might behave in a range of brain conditions.

References:

[1] Classification of electrophysiological and morphological neuron types in the mouse visual cortex. N Gouwens NW, et al. Neurosci. 2019 Jul;22(7):1182-1195.

[2] Shared and distinct transcriptomic cell types across neocortical areas. Tasic B, et al. Nature. 2018 Nov;563(7729):72-78.

Links:

Brain Basics: The Life and Death of a Neuron (National Institute of Neurological Disorders and Stroke/NIH)

Cell Types: Overview of the Data (Allen Brain Atlas/Allen Institute for Brain Science, Seattle)

Hongkui Zeng (Allen Institute)

NIH Support: National Institute of Mental Health; Eunice Kennedy Shriver National Institute of Child Health & Human Development


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