Clinical laboratories and pathologists should expect to receive increase referrals from oncologists with younger patients
More people are getting serious cases of cancer at younger and younger ages. So much so that some anatomic pathologists and epidemiologists are using the term “Turbo Cancers” to describe “the recent emergence of aggressive cancers that grow very quickly,” Vigilant News reported.
Cancer continues to be the second leading cause of death in the United States and current trends of the disease appearing in younger populations are causing alarm among medical professionals and scientists.
It’s anatomic pathologists who receive the biopsies and analyze them to diagnose the cancer. Thus, they are on the front lines of seeing an increased number of biopsies for younger patients showing up with the types of cancers that normally take many years to grow large enough to be discovered by imaging and lumps leading to biopsy and diagnosis. It’s a medical mystery that may have long term effects on younger populations.
“What clinicians have been seeing is very strange things,” said Harvey Risch, MD, PhD (above), Professor Emeritus of Epidemiology at the Yale School of Public Health and Yale School of Medicine, in an Epoch TV interview. “For example, 25-year-olds with colon cancer, who don’t have family histories of the disease—that’s basically impossible along the known paradigm for how colon cancer works—and other long-latency cancers that they’re seeing in very young people.” Epidemiologists and anatomic pathologists are describing these conditions as “turbo cancers.” (Photo copyright: Yale University.)
Early-Onset Cancer Rates Jump Sharply
According to the federal Centers for Disease Control and Prevention (CDC), about 3.3 million Americans died in 2022, and 607,800 of those deaths were attributed to cancer. This statistic translates to approximately 18.4% of US deaths being due to cancer last year.
The largest increase in cancer diagnoses occurred in people in the 30 to 39-year-old age group. This number represents a jump of almost 20% for the years analyzed for individuals in that demographic. The researchers also found that cancer rates decreased in individuals over the age of 50.
Breast cancer, which increased by about 8% in younger people, accounted for the most diagnoses in this age group. However, the biggest increase was 15% for gastrointestinal cancers, including colon, appendix, bile duct, and pancreatic cancer.
Because cancer can recur or progress, researchers have concerns about what happens to young cancer patients as they grow older and what effect cancer may have on their lives.
“They are at a transitional stage in life,” Chun Chao, PhD, Research Scientist, Division of Epidemiologic Research at Kaiser Permanente, told The Hill. “If you think about it, this is the age when people are trying to establish their independence. Some people are finishing up their education. People are trying to get their first job, just start to establish their career. And people are starting new families and starting to have kids. So, at this particular age, having a cancer diagnosis can be a huge disruption to these goals.”
“The increase in early-onset cancers is likely associated with the increasing incidence of obesity as well as changes in environmental exposures, such as smoke and gasoline, sleep patterns, physical activity, microbiota, and transient exposure to carcinogenic compounds,” according to the JAMA study.
“Suspected risk factors may involve increasing obesity among children and young adults; also the drastic change in our diet, like increasing consumption of sugar, sweetened beverages, and high fat,” Hyuna Sung, PhD, Cancer Surveillance Researcher at the American Cancer Society, told US News and World Report. “The increase in cancers among young adults has significant implications. It is something we need to consider as a bellwether for future trends.”
“Increased efforts are required to combat the risk factors for early-onset cancer, such as obesity, heavy alcohol consumption, and smoking,” said Daniel Huang, MD, Assistant Professor of Medicine at the National University of Singapore, one of the authors of the study, in the US News and World Report interview.
Other studies also have shown a rise in so-called turbo cancers.
“Cancer as a disease takes a long time to manifest itself from when it starts. From the first cells that go haywire until they grow to be large enough to be diagnosed, or to be symptomatic, can take anywhere from two or three years for the blood cancers—like leukemias and lymphomas—to five years for lung cancer, to 20 years for bladder cancer, or 30 to 35 years for colon cancer, and so on,” Risch told the Epoch Times.
Not the Occurrence Oncologists Expect
“Some of these cancers are so aggressive that between the time that they’re first seen and when they come back for treatment after a few weeks, they’ve grown dramatically compared to what oncologists would have expected,” Risch continued. “This is just not the normal occurrence of how cancer works.”
Risch believes that damage to the immune system is the most likely cause of the rise in turbo cancers. He said the immune system usually recognizes, manages, and disables cancer cells so they cannot progress. However, when the immune system is impaired, cancer cells can multiply to the point where the immune system cannot cope with the number of bad cells.
It is a statistical fact that more people are being diagnosed with serious cases of cancer at younger and younger ages. If this trend continues, clinical laboratories and pathologists can expect to see more oncology case referrals and perform more cancer diagnostic tests for younger patients.
Though still in trials, early results show tests may be more accurate than traditional clinical laboratory tests for detecting prostate cancer
Within weeks of each other, different research teams in the US and UK published findings of their respective efforts to develop a better, more accurate clinical laboratory prostate cancer test. With cancer being a leading cause of death among men—second only to heart disease according to the Centers for Disease Control and Prevention (CDC)—new diagnostics to identify prostate cancer would be a boon to precision medicine treatments for the deadly disease and could save many lives.
Thus, these are two different pathways toward the goal of achieving earlier, more accurate diagnosis of prostate cancer, the holy grail of prostate cancer diagnosis.
“There is currently no single test for prostate cancer, but PSA blood tests are among the most used, alongside physical examinations, MRI scans, and biopsies,” said Dmitry Pshezhetskiy, PhD (above), Professorial Research Fellow at University of East Anglia and one of the authors of the UEA study. “However, PSA blood tests are not routinely used to screen for prostate cancer, as results can be unreliable. Only about a quarter of people who have a prostate biopsy due to an elevated PSA level are found to have prostate cancer. There has therefore been a drive to create a new blood test with greater accuracy.” With the completion of the US and UK studies, clinical laboratories may soon have a new diagnostic test for prostate cancer. (Photo copyright: University of East Anglia.)
East Anglia’s Research into a More Accurate Blood Test
The researchers evaluated their test in a pilot study involving 147 patients. They found their testing method had a 94% accuracy rate, which is higher than that of PSA testing alone. They discovered their test significantly improved the overall detection of prostate cancer in men who are at risk for the disease.
“When tested in the context of screening a population at risk, the PSE test yields a rapid and minimally invasive prostate cancer diagnosis with impressive performance,” Dmitry Pshezhetskiy, PhD, Professorial Research Fellow at UEA and one of the authors of the study told Science Daily. “This suggests a real benefit for both diagnostic and screening purposes.”
The UK scientists hope their test can eventually be used in everyday clinical practice as there is a need for a highly accurate method for prostate cancer screening that does not subject patients to unnecessary, costly, invasive procedures.
Cedars-Sinai’s Research into Nanotechnology Cancer Testing
Researchers from Cedars-Sinai Cancer took a different approach to diagnosing prostate cancer by developing a nanotechnology-based liquid biopsy test that detects the disease even in microscopic amounts.
Their test isolates and identifies extracellular vesicles (EVs) from blood samples. EVs are microscopic non-reproducing protein and genetic material shed by all cells. Cedars-Sinai’s EV Digital Scoring Assay accurately extracts EVs from blood and analyzes them faster than similar currently available tests.
“This research will revolutionize the liquid biopsy in prostate cancer,” said oncologist Edwin Posadas, MD, Medical Director of the Urologic Oncology Program and co-director of the Experimental Therapeutics Program in Cedars-Sinai Cancer in a press release. “The test is fast, minimally invasive and cost-effective, and opens up a new suite of tools that will help us optimize treatment and quality of life for prostate cancer patients.”
The researchers tested blood samples from 40 patients with prostate cancer. They found that their EV test could distinguish between cancer localized to the prostate and cancer that has spread to other parts of the body.
Microscopic cancer deposits, called micrometastases, are not always detectable, even with advanced imaging methods. When these deposits spread outside the prostate area, focused radiation cannot prevent further progression of the disease. Thus, the ability to identify cancer by locale within the body could lead to new precision medicine treatments for the illness.
“[The EV Digital Scoring Assay] would allow many patients to avoid the potential harms of radiation that isn’t targeting their disease, and instead receive systemic therapy that could slow disease progression,” Posadas explained.
Other Clinical Laboratory Tests for Prostate Cancer Under Development
According to the American Cancer Society, the number of prostate cancer cases is increasing. One out of eight men will be diagnosed with the illness during his lifetime. Thus, developers have been working on clinical laboratory tests to accurately detect the disease and save lives for some time.
And in “UPMC Researchers Develop Artificial Intelligence Algorithm That Detects Prostate Cancer with ‘Near Perfect Accuracy’ in Effort to Improve How Pathologists Diagnose Cancer ,” we outlined how researchers at the University of Pittsburgh Medical Center (UPMC) working with Ibex Medical Analytics in Israel had developed an artificial intelligence (AI) algorithm for digital pathology that can accurately diagnose prostate cancer. In the initial study, the algorithm—dubbed the Galen Prostate AI platform—accurately detected prostate cancer with 98% sensitivity and 97% specificity.
More research and clinical trials are needed before the new US and UK prostate cancer testing methods will be ready to be used in clinical settings. But it’s clear that ongoing research may soon produce new clinical laboratory tests and diagnostics for prostate cancer that will steer treatment options and allow for better patient outcomes.
Two studies show the accuracy of perception-based systems in detecting disease biomarkers without needing molecular recognition elements, such as antibodies
Researchers from multiple academic and research institutions have collaborated to develop a non-conventional machine learning-based technology for identifying and measuring biomarkers to detect ovarian cancer without the need for molecular identification elements, such as antibodies.
Traditional clinical laboratory methods for detecting biomarkers of specific diseases require a “molecular recognition molecule,” such as an antibody, to match with each disease’s biomarker. However, according to a Lehigh University news release, for ovarian cancer “there’s not a single biomarker—or analyte—that indicates the presence of cancer.
“When multiple analytes need to be measured in a given sample, which can increase the accuracy of a test, more antibodies are required, which increases the cost of the test and the turnaround time,” the news release noted.
Unveiled in two sequential studies, the new method for detecting ovarian cancer uses machine learning to examine spectral signatures of carbon nanotubes to detect and recognize the disease biomarkers in a very non-conventional fashion.
Perception-based Nanosensor Array for Detecting Disease
In the Science Advances paper, the researchers described their development of “a perception-based platform based on an optical nanosensor array that leverages machine learning algorithms to detect multiple protein biomarkers in biofluids.
“Perception-based machine learning (ML) platforms, modeled after the complex olfactory system, can isolate individual signals through an array of relatively nonspecific receptors. Each receptor captures certain features, and the overall ensemble response is analyzed by the neural network in our brain, resulting in perception,” the researchers wrote.
“This work demonstrates the potential of perception-based systems for the development of multiplexed sensors of disease biomarkers without the need for specific molecular recognition elements,” the researchers concluded.
In the Nature Biomedical Engineering paper, the researchers described a fined-tuned toolset that could accurately differentiate ovarian cancer biomarkers from biomarkers in individuals who are cancer-free.
“Here we show that a ‘disease fingerprint’—acquired via machine learning from the spectra of near-infrared fluorescence emissions of an array of carbon nanotubes functionalized with quantum defects—detects high-grade serous ovarian carcinoma in serum samples from symptomatic individuals with 87% sensitivity at 98% specificity (compared with 84% sensitivity at 98% specificity for the current best [clinical laboratory] screening test, which uses measurements of cancer antigen 125 and transvaginal ultrasonography,” the researchers wrote.
“We demonstrated that a perception-based nanosensor platform could detect ovarian cancer biomarkers using machine learning,” said Yoona Yang, PhD, a postdoctoral research associate in Lehigh’s Department of Chemical and Biomolecular Engineering and co-first author of the Science Advances article, in the news release.
How Perception-based Machine Learning Platforms Work
According to Yang, perception-based sensing functions like the human brain.
“The system consists of a sensing array that captures a certain feature of the analytes in a specific way, and then the ensemble response from the array is analyzed by the computational perceptive model. It can detect various analytes at once, which makes it much more efficient,” Yang said.
“SWCNTs have unique optical properties and sensitivity that make them valuable as sensor materials. SWCNTS emit near-infrared photoluminescence with distinct narrow emission bands that are exquisitely sensitive to the local environment,” the researchers wrote in Science Advances.
“Carbon nanotubes have interesting electronic properties,” said Daniel Heller, PhD, Head of the Cancer Nanotechnology Laboratory at Memorial Sloan Kettering Cancer Center and Associate Professor in the Department of Pharmacology at Weill Cornell Medicine of Cornell University, in the Lehigh University news release.
“If you shoot light at them, they emit a different color of light, and that light’s color and intensity can change based on what’s sticking to the nanotube. We were able to harness the complexity of so many potential binding interactions by using a range of nanotubes with various wrappings. And that gave us a range of different sensors that could all detect slightly different things, and it turned out they responded differently to different proteins,” he added.
The researchers put their technology to practical test in the second study. The wanted to learn if it could differentiate symptomatic patients with high-grade ovarian cancer from cancer-free individuals.
The research team used 269 serum samples. This time, nanotubes were bound with a specific molecule providing “an extra signal in terms of data and richer data from every nanotube-DNA combination,” said Anand Jagota PhD, Professor, Bioengineering and Chemical and Biomolecular Engineering, Lehigh University, in the news release.
This year, 19,880 women will be diagnosed with ovarian cancer and 12,810 will die from the disease, according to American Cancer Society data. While more research and clinical trials are needed, the above studies are compelling and suggest the possibility that one day clinical laboratories may detect ovarian cancer faster and more accurately than with current methods.
The technology is similar to the concept of a liquid biopsy, which uses blood specimens to identify cancer by capturing tumor cells circulating in the blood.
According to the American Cancer Society, lung cancer is responsible for approximately 25% of cancer deaths in the US and is the leading cause of cancer deaths in both men and women. The ACS estimates there will be about 236,740 new cases of lung cancer diagnosed in the US this year, and about 130,180 deaths due to the disease.
Early-stage lung cancer is typically asymptomatic which leads to later stage diagnoses and lowers survival rates, largely due to a lack of early disease detection tools. The current method used to detect early lung cancer lesions is low-dose spiral CT imaging, which is costly and can be risky due to the radiation hazards of repeated screenings, the news release noted.
MGH’s newly developed diagnostic tool detects lung cancer from alterations in blood metabolites and may lead to clinical laboratory tests that could dramatically improve survival rates of the deadly disease, the MGH scientist noted in a news release.
Detecting Lung Cancer in Blood Metabolomic Profiles
The MGH scientists created their lung-cancer predictive model based on magnetic resonance spectroscopy which can detect the presence of lung cancer from alterations in blood metabolites.
The researchers screened tens of thousands of stored blood specimens and found 25 patients who had been diagnosed with non-small-cell lung carcinoma (NSCLC), and who had blood specimens collected both at the time of their diagnosis and at least six months prior to the diagnosis. They then matched these individuals with 25 healthy controls.
The scientists first trained their statistical model to recognize lung cancer by measuring metabolomic profiles in the blood samples obtained from the patients when they were first diagnosed with lung cancer. They then compared those samples to those of the healthy controls and validated their model by comparing the samples that had been obtained from the same patients prior to the lung cancer diagnosis.
The predictive model yielded values between the healthy controls and the patients at the time of their diagnoses.
“This was very encouraging, because screening for early disease should detect changes in blood metabolomic profiles that are intermediate between healthy and disease states,” Cheng noted.
The MGH scientists then tested their model with a different group of 54 patients who had been diagnosed with NSCLC using blood samples collected before their diagnosis. The second test confirmed the accuracy of their model.
Predicting Five-Year Survival Rates for Lung Cancer Patients
Values derived from the MGH predictive model measured from blood samples obtained prior to a lung cancer diagnosis also could enable oncologists to predict five-year survival rates for patients. This discovery could prove to be useful in determining clinical strategies and personalized treatment decisions.
The researchers plan to analyze the metabolomic profiles of the clinical characteristics of lung cancer to understand the entire metabolic spectrum of the disease. They hope to create similar models for other illnesses and have already created a model that can distinguish aggressive prostate cancer by measuring the metabolomics profiles of more than 400 patients with that disease.
In addition, they are working on a similar model to screen for Alzheimer’s disease using blood samples and cerebrospinal fluid.
More research and clinical studies are needed to validate the utilization of blood metabolomics models as early screening tools in clinical practice. However, this technology might provide pathologists and clinical laboratories with diagnostic tests for the screening of early-stage lung cancer that could save thousands of lives each year.
Combining robotic-assisted bronchoscopy with rapid on-site evaluation by cytopathologists enables cancer evaluation and diagnosis in one procedure
New technologies are making it possible to both collect a tissue biopsy and diagnose lung cancer during the same procedure. Cytopathologist are essential in this unique approach, which has the potential to greatly shorten the time required to diagnose lung cancer.
The RAB platform was created by Auris Health in Redwood City, Calif. According to a USA Health new release, the Auris Health Monarch “enables physicians to see inside the lung and biopsy hard-to-reach nodules using a flexible endoscope. When combined with rapid on-site evaluation (ROSE) it allows for diagnosis at the time of bronchoscopy.”
USA Health says it is the only academic health system in Alabama to combine the Auris Health Monarch (Monarch) with ROSE to diagnose lung cancer in a single procedure.
“Nine-nine percent of the time we make a diagnosis—negative or positive (at time of bronchoscopy). We don’t have to do repeat procedures,” said Elba Turbat-Herrera, MD, Director of Pathological Services at USA Health’s Mitchell Cancer Institute (MCI) and Professor, MCI Interdisciplinary Clinical Oncology, in an exclusive interview with Dark Daily.
As a cytopathologist, Turbat-Herrera performs ROSE during procedures at USA Health. “I think we have improved diagnostics very much. With the Monarch equipment, one can see where the needle is traveling in the bronchial tube. It is more precise,” Turbat-Herrera explained.
Patients Benefit from Robotic-assisted Bronchoscopy
Traditionally, anatomic pathologists receive core (tissue sampling) biopsies and fine-needle aspiration biopsies from doctors looking to determine if a lung nodule may be cancerous. But the procedures to secure the biopsies are invasive and stressful for patients waiting for results from clinical laboratories. And some nodules are difficult for surgeons to reach, which can delay care to patients.
Currently, more than 112 US healthcare providers use the Monarch robotic-assisted bronchoscopy (RAB) platform, which garnered US Food and Drug Administration (FDA) clearance in 2018, the USA Health news release noted.
The Monarch platform, according to USA Health, “integrates robotics, micro-instrumentation, endoscope design, and data science into one platform to empower physicians.”
Eric Swanson, a pulmonologist at Essentia Health-St. Mary’s Medical Center in Duluth, MD, calls Monarch a game changer. “It’s a big, big upgrade from what we had before,” Swanson told the Duluth News Tribune. “(Before), you’d just pass a small catheter through a regular bronchoscope, and you turn it and hope you land in the right spot.”
The Monarch platform has enabled USA Health to step-up diagnosis of lung cancer, as compared to FNA (fine needle aspiration) biopsy on its own, according to Turbat-Herrera.
“With FNA alone, you try to get (sample tissue), and you are not sure. Now, if it is there, you should get it because the (Monarch) equipment helps you get there. Our role in pathology is to help guide the hand of the pulmonologist: ‘you don’t have what we need,’ or ‘keep going in that area of the lung,’” she said, adding that physicians have been able to reach tiny lesions.
High Incidence of Lung Cancer
The American Cancer Society, says lung cancer is the second most common cancer, with an estimated 235,760 new lung cancer cases and 131,880 deaths from the disease in 2021.
It’s hoped that healthcare providers’ investment in new robotic technology—such as Monarch and others—may shorten the time required to diagnose lung cancer and eventually save lives.
Providers such as USA Health go a step further by integrating ROSE with RAB. The robotic technology—coupled with on-site rapid evaluation by a cytopathologist that averts repeat biopsy procedures—immediately secures an assessment of sample adequacy and a cancer diagnosis that may benefit patients as well.
This is yet another example of how a new technology in one field can have a benefit for anatomic pathologists.