Best of all, the researchers say the test could provide an inexpensive means of early diagnosis. This assay could also be used to monitor how well patients respond to cancer therapy, according to a news release.
The protein had previously been identified as a promising biomarker and is readily detectable in tumor tissue, they wrote. However, it is found in extremely low concentrations in blood plasma and is “well below detection limits of conventional clinical laboratory methods,” they noted.
To overcome that obstacle, they employed an ultra-sensitive immunoassay known as a Simoa (Single-Molecule Array), an immunoassay platform for measuring fluid biomarkers.
“We were shocked by how well this test worked in detecting the biomarker’s expression across cancer types,” said lead study author gastroenterologist Martin Taylor, MD, PhD, Instructor in Pathology, Massachusetts General Hospital and Harvard Medical School, in the press release. “It’s created more questions for us to explore and sparked interest among collaborators across many institutions.”
“We’ve known since the 1980s that transposable elements were active in some cancers, and nearly 10 years ago we reported that ORF1p was a pervasive cancer biomarker, but, until now, we haven’t had the ability to detect it in blood tests,” said pathologist and study co-author Kathleen Burns, MD, PhD (above), Chair of the Department of Pathology at Dana-Farber Cancer Institute and a Professor of Pathology at Harvard Medical School, in a press release. “Having a technology capable of detecting ORF1p in blood opens so many possibilities for clinical applications.” Clinical laboratories may soon have a new blood test to detect multiple types of cancer. (Photo copyright: Dana-Farber Cancer Institute.)
Simoa’s Advantages
In their press release, the researchers described ORF1p as “a hallmark of many cancers, particularly p53-deficient epithelial cancers,” a category that includes lung, breast, prostate, uterine, pancreatic, and head and neck cancers in addition to the cancers noted above.
“Pervasive expression of ORF1p in carcinomas, and the lack of expression in normal tissues, makes ORF1p unlike other protein biomarkers which have normal expression levels,” Taylor said in the press release. “This unique biology makes it highly specific.”
Simoa was developed at the laboratory of study co-author David R. Walt, PhD, the Hansjörg Wyss Professor of Bioinspired Engineering at Harvard Medical School, and Professor of Pathology at Harvard Medical School and Brigham and Women’s Hospital.
The Simoa technology “enables 100- to 1,000-fold improvements in sensitivity over conventional enzyme-linked immunosorbent assay (ELISA) techniques, thus opening the window to measuring proteins at concentrations that have never been detected before in various biological fluids such as plasma or saliva,” according to the Walt Lab website.
Simoa assays take less than two hours to run and require less than $3 in consumables. They are “simple to perform, scalable, and have clinical-grade coefficients of variation,” the researchers wrote.
Study Results
Using the first generation of the ORF1p Simoa assay, the researchers tested blood samples of patients with a variety of cancers along with 406 individuals, regarded as healthy, who served as controls. The test proved to be most effective among patients with colorectal and ovarian cancer, finding detectable levels of ORF1p in 58% of former and 71% of the latter. Detectable levels were found in patients with advanced-stage as well as early-stage disease, the researchers wrote in Cancer Discovery.
Among the 406 healthy controls, the test found detectable levels of ORF1p in only five. However, the control with the highest detectable levels, regarded as healthy when donating blood, “was six months later found to have prostate cancer and 19 months later found to have lymphoma,” the researchers wrote.
They later reengineered the Simoa assay to increase its sensitivity, resulting in improved detection of the protein in blood samples from patients with colorectal, gastroesophageal, ovarian, uterine, and breast cancers.
The researchers also employed the test on samples from 19 patients with gastroesophageal cancer to gauge its utility for monitoring therapeutic response. Although this was a small sample, they found that among 13 patients who had responded to therapy, “circulating ORF1p dropped to undetectable levels at follow-up sampling.”
“More Work to Be Done”
The Simoa assay has limitations, the researchers acknowledged. It doesn’t identify the location of cancers, and it “isn’t successful in identifying all cancers and their subtypes,” the press release stated, adding that the test will likely be used in conjunction with other early-detection approaches. The researchers also said they want to gauge the test’s accuracy in larger cohorts.
“The test is very specific, but it doesn’t tell us enough information to be used in a vacuum,” Walt said in the news release. “It’s exciting to see the early success of this ultrasensitive assessment tool, but there is more work to be done.”
More studies will be needed to valid these findings. That this promising new multi-cancer immunoassay is based on a clinical laboratory blood sample means its less invasive and less painful for patients. It’s a good example of an assay that takes a proteomic approach looking for protein cancer biomarkers rather than the genetic approach looking for molecular DNA/RNA biomarkers of cancer.
Norwegian researchers reviewed large clinical trials of six common cancer screenings, including clinical laboratory tests, but some experts question the findings
Cancer screenings are a critical tool for diagnosis and treatment. But how much do they actually extend the lives of patients? According to researchers at the University of Oslo in Norway, not by much. They recently conducted a review and meta-analysis of 18 long-term clinical trials, five of the six most commonly used types of cancer screening—including two clinical laboratory tests—and found that with few exceptions, the screenings did not significantly extend lifespans.
The 18 long-term clinical trials included in the study were randomized trials that collectively included a total of 2.1 million participants. Median follow-up periods of 10 to 15 years were used to gauge estimated lifetime gain and mortality.
“The findings of this meta-analysis suggest that current evidence does not substantiate the claim that common cancer screening tests save lives by extending lifetime, except possibly for colorectal cancer screening with sigmoidoscopy,” the researchers wrote in their published paper.
The researchers noted, however, that their analysis does not suggest all screenings should be abandoned. They also acknowledged that some lives are saved by screenings.
“Without screening, these patients may have died of cancer because it would have been detected at a later, incurable stage,” the scientists wrote, MedPage Today reported. “Thus, these patients experience a gain in lifetime.”
Still, some independent experts questioned the validity of the findings.
Gastroenterologist Michael Bretthauer, MD, PhD (above), a professor at the University of Oslo in Norway led the research into cancer screenings. In their JAMA Internal Medicine paper, he and his team wrote, “The findings of this meta-analysis suggest that colorectal cancer screening with sigmoidoscopy may extend life by approximately three months; lifetime gain for other screening tests appears to be unlikely or uncertain.” How their findings might affect clinical laboratory and anatomic pathology screening for cancer remains to be seen. (Photo copyright: University of Oslo.)
Pros and Cons of Cancer Screening
The clinical trials, according to MedPage Today and Oncology Nursing News covered the following tests:
Mammography screening for breast cancer (two trials).
As reported in these trials, “colorectal cancer screening with sigmoidoscopy prolonged lifetime by 110 days, while fecal testing and mammography screening did not prolong life,” the researchers wrote. “An extension of 37 days was noted for prostate cancer screening with prostate-specific antigen testing and 107 days with lung cancer screening using computed tomography, but estimates are uncertain.”
The American Cancer Society (ACS) recommends certain types of screening tests to detect cancers and pre-cancers before they can spread, thus improving the chances for survival.
The ACS advises screenings for breast cancer, colorectal cancer, and cervical cancer regardless of whether the individual is considered high risk. Lung cancer screenings are advised for people with a history of smoking. Men who are 45 to 50 or older should discuss the pros and cons of prostate cancer screening with their healthcare providers, the ACS states.
A CNN report about the University of Oslo study noted that the benefits and drawbacks of cancer screening have long been well known to doctors.
“Some positive screening results are false positives, which can lead to unnecessary anxiety as well as additional screening that can be expensive,” CNN reported. “Tests can also give a false negative and thus a false sense of security. Sometimes too, treatment can be unnecessary, resulting in a net harm rather than a net benefit, studies show.”
In their JAMA paper, the University of Oslo researchers wrote, “The critical question is whether the benefits for the few are sufficiently large to warrant the associated harms for many. It is entirely possible that multicancer detection blood tests do save lives and warrant the attendant costs and harms. But we will never know unless we ask,” CNN reported.
Hidden Impact on Cancer Mortality
ACS Chief Scientific Officer William Dahut, MD, told CNN that screenings may have an impact on cancer mortality in ways that might not be apparent from randomized trials. He noted that there’s been a decline in deaths from cervical cancer and prostate cancer since doctors began advising routine testing.
“Cancer screening was never really designed to increase longevity,” Dahut said. “Screenings are really designed to decrease premature deaths from cancer.” For example, “if a person’s life expectancy at birth was 80, a cancer screening may prevent their premature death at 65, but it wouldn’t necessarily mean they’d live to be 90 instead of the predicted 80,” CNN reported.
Dahut told CNN that fully assessing the impact of cancer screenings on life expectancy would require a clinical trial larger than those in the new study, and one that followed patients “for a very long time.”
“From its title, one would have expected this paper to be based on analysis of individual lifetime data. However, it is not,” he wrote in a compilation of expert commentary from the UK’s Science Media Center. “The paper’s conclusions are based on arithmetic manipulation of relative rates of all-cause mortality in some of the screening trials. It is therefore difficult to give credence to the claim that screening largely does not extend expected lifetime.”
He also questioned the inclusion of one particular trial in the University of Oslo study—the Canadian National Breast Screening Study—“as there is now public domain evidence of subversion of the randomization in this trial,” he added.
Another expert, Leigh Jackson, PhD, of the University of Exeter in the UK, described the University of Oslo study as “methodologically sound with some limitations which the authors clearly state.”
But he observed that “the focus on 2.1 million individuals is slightly misleading. The study considered many different screening tests and 2.1 million was indeed the total number of included patients, however, no calculation included that many people.”
Jackson also characterized the length of follow-up as a limitation. “This may have limited the amount of data included and also not considering longer follow-up may tend to underestimate the effects of screening,” he said.
This published study—along with the range of credible criticisms offered by other scientists—demonstrates how analysis of huge volumes of data is making it possible to tease out useful new insights. Clinical laboratory managers and pathologists can expect to see other examples of researchers assembling large quantities of data across different areas of medicine. This huge pools of data will be analyzed to determine the effectiveness of many medical procedures that have been performed for years with a belief that they are helpful.
FDA says the move will make it easier to gain authorization for other clinical laboratory tests to utilize at-home collection kits In another sign of how diagnostic testing is responding to changing consumer preferences, the US Food and Drug Administration (FDA) granted marketing authorization to LetsGetChecked for the company’s Simple 2 test for chlamydia and gonorrhea, which includes at-home collection of samples sent to the test developer’s clinical laboratories in the US and in Ireland....
Spectroscopic technique was 91% accurate in identifying the notoriously difficult-to-diagnose disease suggesting a clinical diagnostic test for CFS may be possible
Most clinical pathologists know that, despite their best efforts, scientists have failed to come up with a reliable clinical laboratory blood test for diagnosing myalgic encephalomyelitis (ME), the condition commonly known as chronic fatigue syndrome (CFS)—at least not one that’s ready for clinical use.
But now an international team of researchers at the University of Oxford has developed an experimental non-invasive test for CFS using a simple blood draw, artificial intelligence (AI), and a spectroscopic technique known as Raman spectroscopy.
The approach uses a laser to identify unique cellular “fingerprints” associated with the disease, according to an Oxford news release.
“When Raman was added to a panel of potentially diagnostic outputs, we improved the ability of the model to identify the ME/CFS patients and controls,” Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University, told Advanced Science News. Morton led the research team along with Wei Huang, PhD, Professor of Biological Engineering at Oxford.
The researchers claim the test is 91% accurate in differentiating between healthy people, disease controls, and ME/CFS patients, and 84% accurate in differentiating between mild, moderate, and severe cases, the new release states.
“This could be a game changer as we are unsure what causes [ME/CFS] and diagnosis occurs perhaps 10 to 20 years after the condition has started to develop,” said Karl Morten, PhD, Director of Graduate Studies and Principal Investigator at Oxford University. “An early diagnosis might allow us to identify what is going wrong with the potential to fix it before the more long-term degenerative changes are observed.” Though this research may not lead to a simple clinical laboratory blood test for CFS, any non-invasive diagnostic test would enable doctors to help many people. (Photo copyright: Oxford University.)
Need for an ME/CFS Test
The federal Centers for Disease Control and Prevention (CDC) describes ME/CFS as “a serious, long-term illness that affects many body systems,” with symptoms that include severe fatigue and sleep difficulties. Citing an Institute of Medicine (IoM) report, the agency estimates that 836,000 to 2.5 million Americans suffer from the condition but notes that most cases have not been diagnosed.
“One of the difficulties is the complexity of the disease,” said Jonas Bergquist, MD, PhD, Director of the ME/CFS Research Center of Uppsala University in Sweden, told Advanced Science News. “Because it’s a multi-organ disorder, you get symptoms from many different regions of the body with different onsets, though it’s common with post viral syndrome to have different overlapping [symptoms] that disguise the diagnosis.” Bergquist was not involved with the Oxford study.
One key to the Oxford researchers’ technique is the use of multiple artificial intelligence models to analyze the spectral profiles. “These signatures are complex and by eye there are not necessarily clear features that separate ME/CFS patients from other groups,” Morten told Advanced Science News.
“The AI looks at this data and attempts to find features which can separate the groups,” he continued. “Different AI methods find different features in the data. Individually, each method is not that successful at assigning an unknown sample to the correct group. However, when we combine the different methods, we produce a model which can assign the subjects to the different groups very accurately.”
Without a reliable test, “diagnosis of the condition is difficult, with most patients relying on self-report, questionnaires, and subjective measures to receive a diagnosis,” the Oxford press release noted.
But developing such a test has been challenging, Advanced Science News noted.
How Oxford’s Raman Technique Works
Raman spectroscopy uses a laser to determine the “vibrational modes of molecules,” according to the Oxford press release.
“When a laser beam is directed at a cell, some of the scattered photons undergo frequency shifts due to energy exchanges with the cell’s molecular components,” the press release stated. “Raman micro-spectroscopy detects these shifted photons, providing a non-invasive method for single cell analysis. The resulting single cell Raman spectra serve as a unique fingerprint, revealing the intrinsic and biochemical properties and indicating the physiological and metabolic state of the cell.”
The researchers employed the technique on blood samples from 98 subjects, including 61 ME/CFS patients, 16 healthy controls, and 21 controls with multiple sclerosis (MS), Advanced Science reported.
The Oxford scientists focused their attention on peripheral blood mononuclear cells (PBMCs), as previous studies found that these cells showed “reduced energetic function” in ME/CFS patients. “With this evidence, the team proposed that single-cell analysis of PBMCs might reveal differences in the structure and morphology in ME/CFS patients compared to healthy controls and other disease groups such as multiple sclerosis,” the press release states.
Clinical Laboratory Blood Processing and the Oxford Raman Technique
Oxford’s Raman spectroscopic technique “only requires a small blood sample which could be developed as a point-of-care test perhaps from one drop of blood,” the researchers wrote. However, Advanced Science News pointed out that required laser microscopy equipment costs more than $250,000.
In their Advanced Science paper, the researchers note that the test could be made more widely available by transferring blood samples collected by local clinical laboratories to diagnostic centers that have the needed hardware.
“Alternatively, a compact system containing portable Raman instruments could be developed, which would be much cheaper than a standard Raman microscope, and [which] incorporated with microfluidic systems to stream cells through a Raman laser for detection, eliminating the need for lengthy blood sample processing,” the researchers wrote.
They noted that the technique could be adapted to test for other chronic conditions as well, such as MS, fibromyalgia, Lyme disease, and long COVID.
“Our paper is very much a starting point for future research,” Morten told Advanced Science News. “Larger cohorts need to be studied, and if Raman proves useful, we need to think carefully about how a test might be developed.”
Bergquist agreed, stating it’s “not necessarily something you would see in a doctor’s office. It requires a lot of advanced data analysis to use—I still see it as a research methodology. But in the long run, it could be developed into a tool that could be used in a more simplistic way.”
Though a useable diagnostic test may be far off, clinical laboratories should consider how they can aid in ME/CFS research.
Genetic engineers at the lab used the new tool to generate a catalog of 71 million possible missense variants, classifying 89% as either benign or pathogenic
Genetic engineers continue to use artificial intelligence (AI) and deep learning to develop research tools that have implications for clinical laboratories. The latest development involves Google’s DeepMind artificial intelligence lab which has created an AI tool that, they say, can predict whether a single-letter substitution in DNA—known as a missense variant (aka, missense mutation)—is likely to cause disease.
The Google engineers used their new model—dubbed AlphaMissense—to generate a catalog of 71 million possible missense variants. They were able to classify 89% as likely to be either benign or pathogenic mutations. That compares with just 0.1% that have been classified using conventional methods, according to the DeepMind engineers.
This is yet another example of how Google is investing to develop solutions for healthcare and medical care. In this case, DeepMind might find genetic sequences that are associated with disease or health conditions. In turn, these genetic sequences could eventually become biomarkers that clinical laboratories could use to help physicians make earlier, more accurate diagnoses and allow faster interventions that improve patient care.
“AI tools that can accurately predict the effect of variants have the power to accelerate research across fields from molecular biology to clinical and statistical genetics,” wrote Google DeepMind engineers Jun Cheng, PhD (left), and Žiga Avsec, PhD (right), in a blog post describing the new tool. Clinical laboratories benefit from the diagnostic biomarkers generated by this type of research. (Photo copyrights: LinkedIn.)
AI’s Effect on Genetic Research
Genetic experiments to identify which mutations cause disease are both costly and time-consuming, Google DeepMind engineers Jun Cheng, PhD, and Žiga Avsec, PhD, wrote in a blog post. However, artificial intelligence sped up that process considerably.
“By using AI predictions, researchers can get a preview of results for thousands of proteins at a time, which can help to prioritize resources and accelerate more complex studies,” they noted.
Of all possible 71 million variants, approximately 6%, or four million, have already been seen in humans, they wrote, noting that the average person carries more than 9,000. Most are benign, “but others are pathogenic and can severely disrupt protein function,” causing diseases such as cystic fibrosis, sickle-cell anemia, and cancer.
“A missense variant is a single letter substitution in DNA that results in a different amino acid within a protein,” Cheng and Avsec wrote in the blog post. “If you think of DNA as a language, switching one letter can change a word and alter the meaning of a sentence altogether. In this case, a substitution changes which amino acid is translated, which can affect the function of a protein.”
In the Google DeepMind study, AlphaMissense predicted that 57% of the 71 million variants are “likely benign,” 32% are “likely pathogenic,” and 11% are “uncertain.”
The AlphaMissense model is adapted from an earlier model called AlphaFold which uses amino acid genetic sequences to predict the structure of proteins.
“AlphaMissense was fed data on DNA from humans and closely related primates to learn which missense mutations are common, and therefore probably benign, and which are rare and potentially harmful,” The Guardian reported. “At the same time, the program familiarized itself with the ‘language’ of proteins by studying millions of protein sequences and learning what a ‘healthy’ protein looks like.”
The model assigned each variant a score between 0 and 1 to rate the likelihood of pathogenicity [the potential for a pathogen to cause disease]. “The continuous score allows users to choose a threshold for classifying variants as pathogenic or benign that matches their accuracy requirements,” Avsec and Cheng wrote in their blog post.
However, they also acknowledged that it doesn’t indicate exactly how the variation causes disease.
The engineers cautioned that the predictions in the catalog are not intended for clinical use. Instead, they “should be interpreted with other sources of evidence.” However, “this work has the potential to improve the diagnosis of rare genetic disorders, and help discover new disease-causing genes,” they noted.
Genomics England Sees a Helpful Tool
BBC noted that AlphaMissense has been tested by Genomics England, which works with the UK’s National Health Service. “The new tool is really bringing a new perspective to the data,” Ellen Thomas, PhD, Genomics England’s Deputy Chief Medical Officer, told the BBC. “It will help clinical scientists make sense of genetic data so that it is useful for patients and for their clinical teams.”
AlphaMissense is “a big step forward,” Ewan Birney, PhD, Deputy Director General of the European Molecular Biology Laboratory (EMBL) told the BBC. “It will help clinical researchers prioritize where to look to find areas that could cause disease.”
Other experts, however, who spoke with MIT Technology Review were less enthusiastic.
Heidi Rehm, PhD, co-director of the Program in Medical and Population Genetics at the Broad Institute, suggested that the DeepMind engineers overstated the certainty of the model’s predictions. She told the publication that she was “disappointed” that they labeled the variants as benign or pathogenic.
“The models are improving, but none are perfect, and they still don’t get you to pathogenic or not,” she said.
“Typically, experts don’t declare a mutation pathogenic until they have real-world data from patients, evidence of inheritance patterns in families, and lab tests—information that’s shared through public websites of variants such as ClinVar,” the MIT article noted.
Is AlphaMissense a Biosecurity Risk?
Although DeepMind has released its catalog of variations, MIT Technology Review notes that the lab isn’t releasing the entire AI model due to what it describes as a “biosecurity risk.”
The concern is that “bad actors” could try using it on non-human species, DeepMind said. But one anonymous expert described the restrictions “as a transparent effort to stop others from quickly deploying the model for their own uses,” the MIT article noted.
And so, genetics research takes a huge step forward thanks to Google DeepMind, artificial intelligence, and deep learning. Clinical laboratories and pathologists may soon have useful new tools that help healthcare provider diagnose diseases. Time will tell. But the developments are certain worth watching.
