Study findings could lead to new clinical laboratory screening tests that determine risk for cancer
New disease biomarkers generally lead to new clinical laboratory tests. Such may be the case in an investigational study conducted at the University of Oxford in the United Kingdom (UK). Researchers in the university’s Cancer Epidemiology Unit (CEU) have discovered certain proteins that appear to indicate the presence of cancer years before the disease is diagnosed.
The Oxford scientists “investigated associations between 1,463 plasma proteins and 19 cancers, using observational and genetic approaches in participants of the UK Biobank. They found 618 protein-cancer associations and 317 cancer biomarkers, which included 107 cases detected over seven years before the diagnosis of cancer,” News Medical reported.
To conduct their study, the scientists turned to “new multiplex proteomics techniques” that “allow for simultaneous assessment of proteins at a high-scale, especially those that remain unexplored in the cancer risk context,” News Medical added.
Many of these proteins were in “blood samples of people who developed cancer more than seven years before they received a diagnosis,” an Oxford Population Health news release notes.
“To be able to prevent cancer, we need to understand the factors driving the earliest stages of its development. These studies are important because they provide many new clues about the causes and biology of multiple cancers, including insights into what’s happening years before a cancer is diagnosed,” said Ruth Travis, BA, MSc, DPhil, senior molecular epidemiologist at Oxford Population Health and senior study author, in the news release.
“We now have technology that can look at thousands of proteins across thousands of cancer cases, identifying which proteins have a role in the development of specific cancers and which may have effects that are common to multiple cancer types,” said Ruth Travis, BA, MSc, DPhil (above), senior molecular epidemiologist, Oxford Population Health, in a news release. The study findings could lead to new clinical laboratory screening tests for cancer. (Photo copyright: University of Oxford.)
Proteomics to Address Multiple Cancers Analysis
In their published paper, the Oxford scientists acknowledged other research that identified links between blood proteins and risk for various cancers, including breast, colorectal, and prostate cancers. They saw an opportunity to use multiplex proteomics methods for the simultaneous measurement of proteins “many of which have not previously been assessed for their associations with risk across multiple cancer sites,” the researchers noted.
The researchers described “an integrated multi-omics approach” and the use of the Olink Proximity Extension Assay (PEA) to quantify 1,463 proteins in blood samples from 44,645 participants in the UK Biobank, a large biomedical database and resource to scientists.
Olink, a part of Thermo Fisher Scientific in Waltham, Mass., explains on its website that PEA technology “uniquely combines specificity and scalability to enable high-throughput, multiplex protein biomarker analysis.”
The researchers also compared proteins of people “who did and did not go on to be diagnosed with cancer” to determine differences and identify proteins that suggest cancer risk, News Medical reported.
Proteins Could Assist in Cancer Prevention
“To save more lives from cancer, we need to better understand what happens at the earliest stages of the disease. Data from thousands of people with cancer has revealed really exciting insights into how the proteins in our blood can affect our risk of cancer. Now we need to study these proteins in depth to see which ones could be reliably used for cancer prevention,” Keren Papier, PhD, senior nutritional epidemiologist at Oxford Population Health and joint lead author of the study, told News Medical.
While further studies and regulatory clearance are needed before the Oxford researchers’ approach to identifying cancer in its early stages can be used in patient care, their study highlights scientists’ growing interest in finding biomarker combinations that can predict or diagnose cancer even when it is presymptomatic. By focusing on proteins rather than DNA and RNA, researchers are turning to a source of information other than human genes.
For anatomic pathologists and clinical laboratory leaders, the Oxford study demonstrates how scientific teams are rapidly developing new knowledge about human biology and proteins that are likely to benefit patient care and diagnostics.
List also includes precision oncology, liquid biopsies, and early diagnosis of pancreatic cancer
Pathologists and clinical laboratory managers will be interested to learn that in a recently updated article the World Economic Forum (WEF) identified a dozen important recent breakthroughs in the ongoing fight to defeat cancer, including some related to pathology and clinical laboratory diagnostics.
The article noted that approximately 10 million people die each year from cancer. “Death rates from cancer were falling before the pandemic,” the authors wrote. “But COVID-19 caused a big backlog in diagnosis and treatment.”
The Swiss-based non-profit is best known for its annual meeting of corporate and government leaders in Davos, Switzerland. Healthcare is one of 10 WEF “centers” focusing on specific global issues.
Here are four advances identified by WEF that should be of particular interest to clinical laboratory leaders. The remaining advances will be covered in part two of this ebrief on Wednesday.
“Our study represents a major leap in cancer screening, combining the precision of protein-based biomarkers with the efficiency of sex-specific analysis,” said Novelna founder and CEO Ashkan Afshin, MD, ScD (above), in a company press release. “We’re not only looking at a more effective way of detecting cancer early but also at a cost-effective solution that can be implemented on a large scale.” The 12 breakthroughs listed in the World Economic Forum’s updated article will likely lead to new clinical laboratory screening tests for multiple types of cancer. (Photo copyright: Novelna.)
Novelna’s Early-Stage Cancer Test
Novelna, a biotech startup in Palo Alto, Calif., says it has developed a clinical laboratory blood test that can detect 18 early-stage cancers, including brain, breast, cervical, colorectal, lung, pancreatic, and uterine cancers, according to a press release.
In a small “proof of concept” study, scientists at the company reported that the test identified 93% of stage 1 cancers among men with 99% specificity and 90% sensitivity. Among women, the test identified 84% of stage 1 cancers with 85% sensitivity and 99% specificity.
The researchers collected plasma samples from 440 individuals diagnosed with cancers and measured more than 3,000 proteins. They identified 10 proteins in men and 10 in women that correlated highly with early-stage cancers.
“By themselves, each individual protein was only moderately accurate at picking up early stage disease, but when combined with the other proteins in a panel they were highly accurate,” states a BMJ Oncology press release.
The company says the test can be manufactured for less than $100.
“While further validation in larger population cohorts is necessary, we anticipate that our test will pave the way for more efficient, accurate, and accessible cancer screening,” said Novelna founder and CEO Ashkan Afshin, MD, ScD, in the company press release.
Precision Oncology
According to the National Institutes of Health’s “Promise of Precision Medicine” web page, “Researchers are now identifying the molecular fingerprints of various cancers and using them to divide cancer’s once-broad categories into far more precise types and subtypes. They are also discovering that cancers that develop in totally different parts of the body can sometimes, on a molecular level, have a lot in common. From this new perspective emerges an exciting era in cancer research called precision oncology, in which doctors are choosing treatments based on the DNA signature of an individual patient’s tumor.”
“These advanced sequencing technologies not only extend lifespans and improve cure rates for cancer patients through application to early screening; in the field of cancer diagnosis and monitoring they can also assist in the formulation of personalized clinical diagnostics and treatment plans, as well as allow doctors to accurately relocate the follow-up development of cancer patients after the primary treatment,” Wang wrote.
Based in China, Genetron Health describes itself as a “leading precision oncology platform company” with products and services related to cancer screening, diagnosis, and monitoring.
Liquid and Synthetic Biopsies
Liquid biopsies, in which blood or urine samples are analyzed for presence of biomarkers, provide an “easier and less invasive” alternative to conventional surgical biopsies for cancer diagnosis, the WEF article notes.
These tests allow clinicians to “pin down the disease subtype, identify the appropriate treatment and closely track patient response, adjusting course, if necessary, as each case requires—precision medicine in action,” wrote Merck Group CEO Belén Garijo, MD, in an earlier WEF commentary.
The WEF article also highlighted “synthetic biopsy” technology developed by Earli, Inc., a company based in Redwood City, Calif.
As explained in a Wired story, “Earli’s approach essentially forces the cancer to reveal itself. Bioengineered DNA is injected into the body. When it enters cancer cells, it forces them to produce a synthetic biomarker not normally found in humans.”
The biomarker can be detected in blood or breath tests, Wired noted. A radioactive tracer is used to determine the cancer’s location in the body.
“Pancreatic cancer is one of the deadliest cancers,” the WEF article notes. “It is rarely diagnosed before it starts to spread and has a survival rate of less than 5% over five years.”
The test is based on a technology known as high-conductance dielectrophoresis (DEP), according to a UC San Diego press release. “It detects extracellular vesicles (EVs), which contain tumor proteins that are released into circulation by cancer cells as part of a poorly understood intercellular communication network,” the press release states. “Artificial intelligence-enabled protein marker analysis is then used to predict the likelihood of malignancy.”
The test detected 95.5% of stage 1 pancreatic cancers, 74.4% of stage 1 ovarian cancers, and 73.1% of pathologic stage 1A lethally aggressive serous ovarian adenocarcinomas, they wrote.
“These results are five times more accurate in detecting early-stage cancer than current liquid biopsy multi-cancer detection tests,” said co-senior author Scott M. Lippman, MD.
Look to Dark Daily’s ebrief on Wednesday for the remainder of breakthroughs the World Economic Forum identifies as top advancements in the fight to defeat cancer.
Use of artificial intelligence in clinical laboratory testing could improve the diagnosis of cancer worldwide
In a proof of concept study, scientists at Shanghai Jiao Tong University in China have developed a clinical laboratory test that utilizes artificial intelligence (AI) to diagnose three types of cancer from a single drop of dried blood. The paper-based test was able to identify patients with colorectal, gastric, and pancreatic cancers and distinguish between patients with and without cancer.
The team’s goal was to develop a way to diagnose cancer while the disease is still in the earlier stages, especially in rural areas.
“Over a billion people across the world experience a high rate of missed disease diagnosis, an issue that highlights the need for diagnostic tools showing increased accuracy and affordability. In addition, such tools could be used in ecologically fragile and energy-limited regions, pointing to the need for developing solutions that can maximize health gains under limited resources for enhanced sustainability,” the researchers wrote in an article published in the journal Nature Sustainability titled, “A Sustainable Approach to Universal Metabolic Cancer Diagnosis.”
The researchers determined that by using less than 0.05 millimeters of dried blood, their test could accurately and quickly identify if a patient had cancer between 82% to 100% of the time.
According to Chaoyuan Kuang, MD, PhD (above), an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine, unlike liquid blood, dried serum can be “collected, stored, and transported at much lower cost and with much simpler equipment,” Live Science reported. “This could help democratize the availability of cancer early detection testing across the world,” he added. A paper-based clinical laboratory test that can detect and distinguish one cancer type from another would be a boon to cancer diagnosis worldwide. (Photo copyright: Albert Einstein College of Medicine.)
Improving Cancer Screening in Rural Areas
An earlier study conducted in China in 2022 examined results from 1,570 cancer survivors from both urban and rural areas of China. That study showed that 84.1% of the patients were diagnosed with cancer only after developing symptoms and that urban patients were more likely to be diagnosed in the early stages of cancer. In addition, rural patients also had less screening and treatment options available to them.
The researchers in this latest Chinese study tested their AI model on blood donors with and without cancer and compared the results to traditional liquid-blood biopsy tests.
“Based on modeling they performed, they reported the new tool could reduce the estimated proportion of undiagnosed cases of pancreatic, gastric, and colorectal cancers by about 20% to 50% if it was used for population-level cancer screening in rural China,” Live Science reported.
The scientists used dried serum spots (DSS) and machine learning to perform the research. According to their Nature Sustainability paper, DSS can be challenging in cancer research because sensitive biomarkers in the samples are often degraded or have inadequate amount of blood for proper analysis. To circumvent these issues, the researchers used nanoparticle-enhanced laser desorption/ionization mass spectrometry (NPELDI MS) to increase reliability and sensitivity. Inorganic nanoparticles were applied to the samples to strengthen selectivity and refine metabolic compounds from the samples.
However, the study authors noted that “the adaptation of NPELDI MS to dried spot analysis has not been validated,” Interesting Engineering reported.
A ‘Great Start’
The machine learning algorithm the Chinese scientists created demonstrates that DSS samples can be used to preserve important biological markers and could be beneficial in the diagnosis of cancer.
Their research indicated an overall reduction rate of undiagnosed cancers in the range of 20.35% to 55.10%. The researchers estimated the implementation of their AI tool could reduce the proportion of specific undiagnosed cancer cases in rural China by:
84.30% to 29.20% for colorectal cancer,
77.57% to 57.22% for gastric cancer, and
34.56% to 9.30% for pancreatic cancer.
It’s a “great start,” Chaoyuan Kuang, MD, PhD, an oncologist at Montefiore Health System and assistant professor at the Albert Einstein College of Medicine told Live Science. “This cancer test won’t enter use for a long time,” he said. Nevertheless, the potential of the tool is “immense,” he added, but that “we are still years away from being able to offer this test to patients.
“With further development, it could theoretically be used for the early detection of other types of cancer or for other diseases, or to monitor the progression of disease in patients who have already been diagnosed,” he noted.
Further research and clinical trials are needed before this AI tool can be used in a clinical diagnostic setting. This study is another example of researchers looking for cancer biomarkers in specimen types that are not tissue and further supports the hope that machine learning may one day detect cancer in earlier stages, increase survival rates, and save healthcare costs.
One factor motivating this type of research in China is the fact that the nation has more than 36,000 hospitals and approximately 20,000 anatomic pathologists. Of this total, only a minority of these pathologists have been trained to the standards of North America and Northern Europe.
Like other nations, China’s demand for subspecialist pathology services outstrips its supply of such pathologists. This is the reason why researchers in that country want to develop diagnostic assays for cancer and other diseases that are faster, cheaper, and comparable to a human pathologist in accuracy.
The new method employs a pH sensitive dye and AI algorithms to ‘distinguish between cells originating from normal and cancerous tissue, as well as among different types of cancer’ the researchers said
Might a pH-sensitive dye in tandem with an image analysis solution soon be used to identify cancerous cells within blood samples as well within tissue? Recent research indicates that could be a possibility. If further studies and clinical trials confirm this capability, then anatomic pathologists could gain another valuable tool to use in diagnosing cancers and other types of disease.
Currently, surgical pathologists use a variety of hematoxylin and eosin stains (H/E) to bring out useful features in cells and cell structures. So, staining tissue on glass slides is a common practice. Now, thanks to machine learning and artificial intelligence, anatomic pathologists may soon have a similar tool for spotting cancer cells within both tissue and blood samples.
Researchers at the National University of Singapore (NUS) have developed a method for identifying cancer that uses a pH sensitive dye called bromothymol blue. The dye reacts to various levels of acidity in cancer cells by turning colors. “The pH inside cancer cells tends to be higher than that of healthy cells. This phenomenon occurs at the very early phases of cancer development and becomes amplified as it progresses,” Labroots reported.
In “Machine Learning Based Approach to pH Imaging and Classification of Single Cancer Cells,” published in the journal APL Bioengineering, the NUS researchers wrote, “Here, we leverage a recently developed pH imaging modality and machine learning-based single-cell segmentation and classification to identify different cancer cell lines based on their characteristic intracellular pH. This simple method opens up the potential to perform rapid noninvasive identification of living cancer cells for early cancer diagnosis and further downstream analyses.”
According to an NUS news release, the bromothymol blue dye is “applied onto patients’ cells” being held ex vivo in cell culture dishes. The dye’s color changes depending on the acidity level of the cancer cells it encounters. Microscopic images of the now-visible cancers cells are taken, and a machine-learning algorithm analyzes the images before generating a report for the anatomic pathologist.
The NUS researchers claim the test can provide answers in about half an hour with 95% accuracy, Labroots reported.
“The ability to analyze single cells is one of the holy grails of health innovation for precision medicine or personalized therapy. Our proof-of-concept study demonstrates the potential of our technique to be used as a fast, inexpensive and accurate tool for cancer diagnosis,” said Lim Chwee Teck, PhD, NUS Society Professor and Director of NUS’ Institute for Health Innovation and Technology, in the NUS news release.
The novel technique for differentiating cancer cells from non-cancerous cells being developed at the National University of Singapore (NUS) could eventually become useful in detecting cancer cells in tissue samples, either obtained from tumor biopsies or blood samples. “As the number of cells in these samples can be in millions or even billions, the ability to detect the very few cancer cells among the others will be useful for clinicians,” NUS Society Professor and Director of NUS’ Institute for Health Innovation and Technology, Lim Chwee Teck, PhD (above) told The Straits Times. (Photo copyright: The Straits Times.)
AI Cell Analysis versus Laborious Medical Laboratory Steps
By developing an AI-driven method, Professor Lim and the NUS team sought to improve upon time-consuming techniques for identifying cells that traditionally involve using florescent probes, nanoparticles, and labeling steps, or for cells to be fixed or terminated.
“Unlike other cell analysis techniques, our approach uses simple, inexpensive equipment, and does not require lengthy preparation and sophisticated devices. Using AI, we are able to screen cells faster and accurately,” Professor Lim told Labroots. “Furthermore, we can monitor and analyze living cells without causing any toxicity to the cells or the need to kill them.”
The new technique may have implications for cancer detection in tumor tissue as well as in liquid biopsies.
“We are also exploring the possibility of performing the real-time analysis on circulating cancer cells suspended in blood,” Professor Lim said in the NUS news release. “One potential application for this would be in liquid biopsy where tumor cells that escaped from a primary tumor can be isolated in a minimally-invasive fashion from bodily fluids such as blood.”
Diagnosing Cancer in Real Time
The NUS’ method requires more research and clinical studies before it could become an actual tool for anatomic pathologists and other cancer diagnosticians. Additionally, the NUS researchers acknowledged that the focus on only four cell lines (normal cells, benign breast tumor cells, breast cancer cells, and pancreatic cancer cells) limited their study, as did lack of comparison with conventional florescent pH indicators.
Still, the NUS scientists are already planning more studies to advance their concept to different stages of cell malignancy. They envision a “real-time” version of the technique to enable recognition of cells and fast separation of those that need to be referred to clinical laboratories for molecular testing and/or genetic sequencing.
Medical laboratory leaders may want to follow the NUS study. An inexpensive AI-driven method that can accurately detect and classify cancer cells based on pH within the cells is provocative and may be eventually become integrated with other cancer diagnostics.
The device automates the process used by pathology labs to process biopsy specimens and could be applied to automate other scientific processes
Hoping to speed up the processing of human biopsies to reduce the time required to diagnose cancers, two undergraduate engineering students at the University of Washington (UW) have developed a cheap, miniaturized device that could one day be used in anatomic pathology laboratories.
The protype is a low-cost, credit-card-sized device that automates the processing of human tissue biopsies using fluid transport. The device could help pathologists diagnose pancreatic cancer earlier and faster, to hopefully treat patients before it progresses to a deadly stage, according to a UW press release.
Unlike cancers that can be diagnosed early with fine needle biopsy, such as breast cancer, pancreatic cancer is one of the deadliest forms of cancers. It kills 94% of victims within five years because diagnosis usually is too late to effectively treat the disease. (more…)