Addressing the gap in lung cancer screening

A novel biosensor technology with high accuracy for detecting lung cancer presents a solution to the challenges of finding lung cancer when it can be cured.
Addressing the gap in lung cancer screening
Like

Share this post

Choose a social network to share with, or copy the shortened URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

Lung cancer is the most deadly cancer.

More than any other cancer, lung cancer consistently takes more lives than the next top three cancers combined. Worldwide, 2.5 million new cases of lung cancer will be diagnosed in 2024 leading to over 1.8 million deaths. There are many challenges associated with identifying patients when the disease can be successfully treated. Unlike all other cancers, more patients are identified when the disease has already moved to distant sites. Once the disease has spread, treatment is generally palliative though survivorship has increased through precision medications (or biomarker targeted therapies) when indicated, long-term outcomes are still very poor. In contrast, one can survive lung cancer if it is detected early enough.

Effective detection is a particular challenge for lung cancer. Public health advocacy and research have improved detection and survival of patients with breast, colorectal, and cervical cancer significantly over the last 20 years. Thank you Katie Couric! A huge effort was made to demonstrate that chest CT scans result in 20% fewer deaths from lung cancer in the National Lung Screening Trial (NLST) [1]. However, 10 years after implementation, less than 5% of the people who should be screened actually get screened [2]. Outside the United States, there are few examples of programmatic lung cancer screening tests anywhere.

So what’s going on with lung cancer screening? It’s a complex question but the top few answers go a long way to explaining the solution that is needed. Smoking remains the greatest risk factor for lung cancer and has a stigma whereby patients are perceived as having brought the disease onto themselves. Also, the standard of care to find lung cancer is imaging via a chest scan. Any suspicious masses found  with a scan lead to additional diagnostic processes all with their own costs and risks to the patient. These factors contribute to an inertia in implementing screening aggressively [3]. 

While it is true that a history of heavy smoking accounts for ~85% of lung cancers, this is changing quickly. The fastest-growing cancer population is lung cancer in female never smokers, especially Asian females [4]. Additional risk factors such as Radon emissions and environmental pollution are not addressed by current screening standards because of the risks associated with both a chest scan and the necessary, often invasive, diagnostic testing needed to confirm chest scan results. And this is on top of the ever changing definition of current risk. 

The NLST trial recommended a population at risk for lung cancer based on age and smoking history numbering about 7 million individuals [5]. It grew to 14 million when the risk profile was expanded in 2021 [6] and further grew to 19.3 million individuals when the American Cancer Society considered any history of smoking even if you quit [7]. The risk of lung cancer isn’t actually changing this quickly. What is changing is the clear understanding that early detection does lead to improved outcomes balanced against the cost of finding people with lung cancer.

Top panel is a transmission electron micrograph of a graphene based biosensor. It is a nanoscale amorphous shaped particle annotated with the sensor targets. The bottom panel is a cartoon of the sensor mechanism. Peptides tethering a fluorescent dye to the graphene backbone suppress the fluorescent signal unless the peptide target is cleaved by an active protease enzyme in the sera sample. The activity is targeted by the sequence of amino acids in the peptide tether.

Mode of action of the Sensor

This challenge drove the effort behind the paper (link to paper) describing a novel sensor technology for lung cancer detection. To improve the earlier detection and successful treatment of lung cancer, initially in the smoking population, and in the future expanded risk groups, we need three things:

  1. A fast and accurate test that can process samples with a straightforward workflow to test very large populations of individuals.
  2. A test that can find a signal of the disease across all stages including the earliest stages when patients can be cured. 
  3. A technology that is so cost-effective that it can be deployed at population-scale without burdening health care systems.

Mechanism of Action

The biosensor technology described in this paper can be manufactured without the need for biologics such as expensive enzymes or antibodies associated with diagnostic assays. It produces a result in a couple of hours with a fluorescence plate reader which is an inexpensive laboratory tool present in most molecular immunology settings. And it detects 90% of patients who have lung cancer, whether or not symptoms are present, even those with early Stage I disease.

Video explaining how the sensors work to detect lung cancer

The sensor is comprised of a graphene-based particle decorated with fluorescent short proteins. In the  “OFF” state, the graphene backbone turns the fluorescence off. In the presence of protein-digesting enzymes in a blood sample, the sensor is turned ON when the short proteins are snipped releasing the fluorescent signal. The diagnostic target of these sensors are enzymes produced by two sources: 1) the body mounts an immune response against a growing tumor to get rid of it using proteases as modulator proteins and 2)  conversely, the tumor cells try to turn off the immune response while also modifying their environment so they have room to divide and grow using many of the same protease enzymes.

By using a panel of these sensors to target different enzymes, we developed a “fingerprint” of protease enzyme activity that mirrors someone with lung cancer - the Lung Enzyme Activity Profile or LEAP. This “fingerprint” is different from a similar patient, with the same age and smoking history, who does not have lung cancer. In this way, we have built a platform that can identify patients quickly, cost-effectively, and at scale. A distributed tool like this can be used to accelerate the uptake of lung cancer screening globally. It is also well suited to address the disparities in healthcare that are seen in many different underserved communities. 

References

1. Team, N.L.S.T.R. et al. The New England Journal of Medicine 365, 395-409 (2011).

2. Jemal, A. & Fedewa, S.A. JAMA Oncol 3, 1278-1281 (2017).

3. Zarinshenas, R. et al. Cancers (Basel) 15 (2023).

4. Pinheiro, P.S. et al. Lung Cancer 174, 50-56 (2022).

5. Moyer, V.A. & U.S.P.S.T.F. Ann. Intern. Med. 160, 330-338 (2014).

6. U.S. Preventive Services Task Force. JAMA 325, 962-970 (2021).

7. Wolf, A.M.D. et al. CA Cancer J. Clin. (2023).

Please sign in or register for FREE

If you are a registered user on Research Communities by Springer Nature, please sign in

Follow the Topic

Lung Cancer
Life Sciences > Health Sciences > Clinical Medicine > Diseases > Cancers > Lung Cancer
Sensors
Physical Sciences > Chemistry > Analytical Chemistry > Sensors
Biological Sensors and Probes
Life Sciences > Biological Sciences > Biological Techniques > Biological Sensors and Probes
Diagnostic Markers
Life Sciences > Health Sciences > Biomedical Research > Biomarkers > Diagnostic Markers

Related Collections

With collections, you can get published faster and increase your visibility.

Liquid biopsy

Publishing Model: Open Access

Deadline: Aug 13, 2024