These advances in the battle against cancer could lead to new clinical laboratory screening tests and other diagnostics for early detection of the disease
As Dark Daily reported in part one of this story, the World Economic Forum (WEF) has identified 12 new breakthroughs in the fight against cancer that will be of interest to pathologists and clinical laboratory managers.
As we noted in part one, the WEF originally announced these breakthroughs in an article first published in May 2022 and then updated in October 2024. According to the WEF, the World Health Organization (WHO) identified cancer as a “leading cause of death globally” that “kills around 10 million people a year.”
The WEF is a non-profit organization base in Switzerland that, according to its website, “engages political, business, academic, civil society and other leaders of society to shape global, regional and industry agendas.”
Monday’s ebrief focused on four advances identified by WEF that should be of particular interest to clinical laboratory leaders. Here are the others.
Personalized Cancer Vaccines in England
The National Health Service (NHS) in England, in collaboration with the German pharmaceutical company BioNTech, has launched a program to facilitate development of personalized cancer vaccines. The NHS Cancer Vaccine Launch Pad will seek to match cancer patients with clinical trials for the vaccines. The Launch Pad will be based on messenger ribonucleic acid (mRNA) technology, which is the same technology used in many COVID-19 vaccines.
The BBC reported that these cancer vaccines are treatments, not a form of prevention. BioNTech receives a sample of a patient’s tumor and then formulates a vaccine that exposes the cancer cells to the patient’s immune system. Each vaccine is tailored for the specific mutations in the patient’s tumor.
“I think this is a new era. The science behind this makes sense,” medical oncologist Victoria Kunene, MBChB, MRCP, MSc (above), trial principal investigator from Queen Elizabeth Hospital Birmingham (QEHB) involved in an NHS program to develop personalized cancer vaccines, told the BBC. “My hope is this will become the standard of care. It makes sense that we can have something that can help patients reduce their risk of cancer recurrence.” These clinical trials could lead to new clinical laboratory screening tests for cancer vaccines. (Photo copyright: Queen Elizabeth Hospital Birmingham.)
Seven-Minute Cancer Treatment Injection
NHS England has also begun treating eligible cancer patients with under-the-skin injections of atezolizumab, an immunotherapy marketed under the brand name Tecentriq, Reuters reported. The drug is usually delivered intravenously, a procedure that can take 30 to 60 minutes. Injecting the drug takes just seven minutes, Reuters noted, saving time for patients and cancer teams.
The drug is designed to stimulate the patient’s immune system to attack cancer cells, including breast, lung, liver, and bladder cancers.
AI Advances in India
One WEF component—the Center for the Fourth Industrial Revolution (C4IR)—aims to harness emerging technologies such as artificial intelligence (AI) and virtual reality. In India, the organization says the Center is seeking to accelerate use of AI-based risk profiling to “help screen for common cancers like breast cancer, leading to early diagnosis.”
Researchers are also exploring the use of AI to “analyze X-rays to identify cancers in places where imaging experts might not be available.”
Using AI to Assess Lung Cancer Risk
Early-stage lung cancer is “notoriously hard to detect,” WEF observed. To help meet this challenge, researchers at Massachusetts Institute of Technology (MIT) developed an AI model known as Sybil that analyzes low-dose computed tomography scans to predict a patient’s risk of getting the disease within the next six years. It does so without a radiologist’s intervention, according to a press release.
Using Genomics to Identify Cancer-Causing Mutations
In what has been described as the “largest study of whole genome sequencing data,” researchers at the University of Cambridge in the UK announced they have discovered a “treasure trove” of information about possible causes of cancer.
Using data from England’s 100,000 Genomes Project, the researchers analyzed the whole genome sequences of 12,000 NHS cancer patients.
This allowed them “to detect patterns in the DNA of cancer, known as ‘mutational signatures,’ that provide clues about whether a patient has had a past exposure to environmental causes of cancer such as smoking or UV light, or has internal, cellular malfunctions,” according to a press release.
The researchers also identified 58 new mutational signatures, “suggesting that there are additional causes of cancer that we don’t yet fully understand,” the press release states.
The study appeared in April 2022 in the journal Science.
Validation of CAR-T-Cell Therapy
CAR-T-cell therapy “involves removing and genetically altering immune cells, called T cells, from cancer patients,” WEF explained. “The altered cells then produce proteins called chimeric antigen receptors (CARs), which can recognize and destroy cancer cells.”
The therapy appeared to receive validation in 2022 when researchers at the University of Pennsylvania published an article in the journal Nature noting that two early recipients of the treatment were still in remission after 12 years.
However, the US Food and Drug Administration (FDA) announced in 2023 that it was investigating reports of T-cell malignancies, including lymphoma, in patients who had received the treatment.
WEF observed that “the jury is still out as to whether the therapy is to blame but, as a precaution, the drug packaging now carries a warning.”
Breast Cancer Drug Repurposed for Prevention
England’s NHS announced in 2023 that anastrozole, a breast cancer drug, will be available to post-menopausal women to help reduce their risk of developing the disease.
“Around 289,000 women at moderate or high risk of breast cancer could be eligible for the drug, and while not all will choose to take it, it is estimated that if 25% do, around 2,000 cases of breast cancer could potentially be prevented in England, while saving the NHS around £15 million in treatment costs,” the NHS stated.
The tablet, which is off patent, has been used for many years to treat breast cancer, the NHS added. Anastrozole blocks the body’s production of the enzyme aromatase, reducing levels of the hormone estrogen.
Big Advance in Treating Cervical Cancer
In October 2024, researchers announced results from a large clinical trial demonstrating that a new approach to treating cervical cancer—one that uses currently available therapies—can reduce the risk of death by 40% and the risk of relapsing by 36%.
“This is the biggest improvement in outcome in this disease in over 20 years,” said Mary McCormack, PhD, clinical oncologist at the University College London and lead investigator in the trial.
The scientists published their findings in The Lancet.
Pathologists and clinical lab managers will want to keep track of these 12 breakthrough advancements in the diagnosis and treatment of cancer highlighted by the WEF. They will likely lead to new screening tests for the disease and could save many lives.
Findings could lead to new therapies and clinical laboratory biomarkers for detecting and defeating antibiotic-resistant bacteria
Once again, new research shows that human gut bacteria (microbiota) may be useful in fighting antibiotic-resistant bacterial infections. The study findings could provide new therapeutics and clinical laboratory biomarkers for diagnosing and treating severe gastrointestinal disorders.
Antibiotic-resistant bacterial infections often appear in patients with chronic intestinal conditions and in those with long-term antibiotic use. Enterobacteriaceae is a large family of gram-negative bacteria that includes more than 30 genera and over 100 species.
“Despite two decades of microbiome research, we are just beginning to understand how to define health-promoting features of the gut microbiome,” said Marie-Madlen Pust, PhD, a computational postdoctoral researcher at the Broad Institute and co-first author of the paper, in the news release.
“Part of the challenge is that each person’s microbiome is unique. This collaborative effort allowed us to functionally characterize the different mechanisms of action these bacteria use to reduce pathogen load and gut inflammation,” she added.
The researchers identified a way to treat patients infected by antibiotic-resistant strains of bacteria that does not involve antibiotics. Should further research validate these early findings, this could be a viable approach to treating patients with this condition.
“Microbiome studies can often consist of analyzing collections of genetic sequences, without understanding what each gene does or why certain microbes are beneficial,” said Ramnik Xavier, MD (above), director of Broad Institute’s immunology program, co-director of the infectious disease and microbiome program, and co-senior author on the study, in a news release. “Trying to uncover that function is the next frontier, and this is a nice first step towards figuring out how microbial metabolites influence health and inflammation.” Clinical laboratories that test for intestinal conditions caused by antibiotic resistance will want to follow the Broad Institute’s research. (Photo copyright: Broad Institute.)
Suppressing Growth of Antibiotic-resistant Bacteria
To perform their research, the scientists isolated about 40 strains of bacteria from the stools of five healthy fecal donors. They then used those stool samples in fecal microbiota transplants to treat mice that had been infected with either Escherichia coli (E. coli) or Klebsiella, both forms of Enterobacteriaceae. The scientists tested different combinations of the 40 strains and identified 18 that suppressed the growth of Enterobacteriaceae.
“Antibiotic-resistant Enterobacteriaceae such as E. coli and Klebsiella bacteria are common in hospitals, where they can proliferate in the gut of patients and cause dangerous systemic infections that are difficult to treat. Some research suggests that Enterobacteriaceae also perpetuates inflammation in the intestine and infection by other microbes,” the Broad Institute news release notes.
The researchers discovered that Klebsiella changed the gene expression in carbohydrate uptake and metabolism in the Klebsiella-infected mice that were treated with the 18 beneficial strains. The gene expression included the downregulating of gluconate kinase and transporter genes, which revealed there is increased competition among gut bacteria for nutrients.
When combined, these 18 strains alleviated inflammation in the guts of the treated mice by depriving the harmful gut bacteria of carbohydrates. This non-antibiotic approach also prevented harmful bacteria from colonizing in the gut.
“In partnership with the Broad’s Metabolomics Platform, led by senior director and study co-author Clary Clish, PhD, they analyzed samples from pediatric patients with ulcerative colitis, looking for the presence of alternate gluconate pathway genes of gut microbes and fecal gluconate levels. They found higher levels of gluconate linked to more gluconate-consuming Enterobacteriaceae in samples from pediatric patients with ongoing inflammation, indicated by high levels of the protein calprotectin,” the study authors wrote in Nature.
“Together, the findings suggest that Enterobacteriaceae processes gluconate as a key nutrient and contributes to inflammation in patients. But when a gut microbiome includes the 18 helpful strains, they likely compete with Enterobacteriaceae for gluconate and other nutrient sources, limiting the proliferation of the harmful bacteria,” the scientists concluded.
Promising New Bacterial Therapies
This research could ultimately lead to the development of fecal microbiota transplants for individuals to eradicate antibiotic-resistant bacteria in a more objective and specific manner, with fewer side effects than current treatments.
“Harnessing these activities in the form of live bacterial therapies may represent a promising solution to combat the growing threat of proinflammatory, antimicrobial-resistant Enterobacteriaceae infection,” the scientists wrote in Nature.
According to the news release, they plan to continue research to “uncover the identity and function of unknown metabolites that contribute to gut health and inflammation.” The team hopes to discover how different bacteria compete with each other, and to develop microbial therapeutics that improve gut microbiome and curb bacterial infections.
More studies are needed to prove the efficacy of this type of fecal bacterial treatment. However, this research demonstrates how using nano processes enabled by new technologies to identify the actual work of proteins, RNA, and DNA in the body cheaply, faster, and with greater precision, will open doors to both therapeutic and diagnostic clinical laboratory biomarkers.
New gene-editing systems could provide markedly improved accuracy for DNA and RNA editing leading to new precision medicine tools and genetic therapies
In what may turn out to be a significant development in genetic engineering, researchers from three institutions have identified nearly 200 new systems that can be used for editing genes. It is believed that a number of these new systems can provide comparable or better accuracy when compared to CRISPER (Clustered Regularly Interspaced Short Palindromic Repeats), currently the most-used gene editing method.
CRISPR-Cas9 has been the standard tool for CRISPR gene editing and genetic engineering. However, publication of these new research findings are expected to give scientists better, more precise tools to edit genes. In turn, these developments could lead to new clinical laboratory tests and precision medicine therapies for patients with inherited genetic diseases.
“Best known as a powerful gene-editing tool, CRISPR actually comes from an inbuilt defense system found in bacteria and simple microbes called archaea. CRISPR systems include pairs of ‘molecular scissors’ called Cas enzymes, which allow microbes to cut up the DNA of viruses that attack them. CRISPR technology takes advantage of these scissors to cut genes out of DNA and paste new genes in,” according to Live Science.
In its article, New Atlas noted that the researchers looked to bacteria because “In nature, CRISPR is a self-defense tool used by bacteria.” They developed an algorithm—called FLSHclust—to conduct “a deep dive into three databases of bacteria, found in environments as diverse as Antarctic lakes, breweries, and dog saliva.”
In their paper, the researchers wrote, “We developed fast locality-sensitive hashing–based clustering (FLSHclust), a parallelized, deep clustering algorithm with linearithmic scaling based on locality-sensitive hashing. FLSHclust approaches MMseqs2, a gold-standard quadratic-scaling algorithm, in clustering performance. We applied FLSHclust in a sensitive CRISPR discovery pipeline and identified 188 previously unreported CRISPR-associated systems, including many rare systems.”
“In lab tests [the newfound CRISPR systems] demonstrated a range of functions, and fell into both known and brand new categories,” New Atlas reported.
“Some of these microbial systems were exclusively found in water from coal mines,” Soumya Kannan, PhD (above), a Graduate Fellow at MIT’s Zhang Lab and co-first author of the study, told New Atlas. “If someone hadn’t been interested in that, we may never have seen those systems.” These new gene-editing systems could lead to new clinical laboratory genetic tests and therapeutics for chronic diseases. (Photo copyright: MIT McGovern Institute.)
Deeper Look at Advancement
The CRISPR-Cas9 made a terrific impact when it was announced in 2012, earning a Nobel Prize in Chemistry.
Though CRISPR-Cas9 brought huge benefits to genetic research, the team noted in their Science paper that “existing methods for sequence mining lag behind the exponentially growing databases that now contain billions of proteins, which restricts the discovery of rare protein families and associations.
“We sought to comprehensively enumerate CRISPR-linked gene modules in all existing publicly available sequencing data,” the scientist continued. “Recently, several previously unknown biochemical activities have been linked to programmable nucleic acid recognition by CRISPR systems, including transposition and protease activity. We reasoned that many more diverse enzymatic activities may be associated with CRISPR systems, many of which could be of low abundance in existing [gene] sequence databases.”
Among the previously unknown gene-editing systems the researchers found were some belonging to the Type 1 CRISPR systems class. These “have longer guide RNA sequences than Cas9. They can be directed to their targets more precisely, reducing the risk of off-target edits—one of the main problems with CRISPR gene editing,” New Atlas reported.
“The authors also identified a CRISPR-Cas enzyme, Cas14, which cuts RNA precisely. These discoveries may help to further improve DNA- and RNA-editing technologies, with wide-ranging applications in medicine and biotechnology,” the Science paper noted.
Testing also showed these systems were able to edit human cells, meaning “their size should allow them to be delivered in the same packages currently used for CRISPR-Cas9,” New Atlas added.
Another newfound gene-editing system demonstrated “collateral activity, breaking down nucleic acids after binding to the target, New Atlas reported. SHERLOCK, a tool used to diagnose single samples of RNA or DNA to diagnose disease, previously utilized this system.
Additionally, New Atlas noted, “a type VII system was found to target RNA, which could unlock a range of new tools through RNA editing. Others could be adapted to record when certain genes are expressed, or as sensors for activity in cells.”
Looking Ahead
The strides in science from the CRISPR-Cas9 give a hint at what can come from the new discovery. “Not only does this study greatly expand the field of possible gene editing tools, but it shows that exploring microbial ecosystems in obscure environments could pay off with potential human benefits,” New Atlas noted.
“This study introduces FLSHclust as a tool to cluster millions of sequences quickly and efficiently, with broad applications in mining large sequence databases. The CRISPR-linked systems that we discovered represent an untapped trove of diverse biochemical activities linked to RNA-guided mechanisms, with great potential for development as biotechnologies,” the researchers wrote in Science.
How these newfound gene-editing tools and the new FLSHclust algorithm will eventually lead to new clinical laboratory tests and precision medicine diagnostics is not yet clear. But the discoveries will certainly improve DNA/RNA editing, and that may eventually lead to new clinical and biomedical applications.
Dogs’ acute sense of smell can even surpass effectiveness of some clinical laboratory testing in detecting certain diseases in humans
When it comes to COVID-19 testing, a recent Italian study demonstrates that trained dogs can detect SARS-CoV-2 with accuracy comparable to rapid molecular tests used in clinical laboratories. The researchers wanted to determine if dogs could be more effective at screening people for COVID-19 at airports, schools, and other high-traffic environments as a way to detect the coronavirus and reduce the spread of this infectious disease.
Scientists at the State University of Milan in Italy conducted a study that shows dogs can be trained to accurately identify the presence of the COVID-19 infection from both biological samples and by simply smelling an individual.
For their validation study, the Italian team trained three dogs named Nala, Otto, and Helix, “to detect the presence of SARS-CoV-2 in sweat samples from infected people. At the end of the training, the dogs achieved an average sensitivity of 93% and a specificity of 99%, showing a level of accuracy highly consistent with that of the RT-PCR [reverse transcription polymerase chain reaction] used in molecular tests and a moderate to strong reproducibility over time,” Nature reported.
RT-PCR tests are the current gold-standard for SARS-CoV-2 detection. This is yet another example of scientists training dogs to smell a disease with “acceptable” accuracy. This time for COVID-19.
“We only recruited dogs that showed themselves predisposed and positively motivated to carry out this type of activity. One of the fundamental aspects was not to cause stress or anxiety in the subjects used,” Federica Pirrone, PhD (above), Associate Professor, Department of Veterinary Medicine and Animal Sciences, University of Milan, and one of the authors of the study told Lifegate. “Training always takes place using positive reinforcement of a food nature: whether it’s a particularly appetizing morsel, a biscuit, or something that associates the dog’s search with a rewarding prize.” In some instances, dogs have been shown to be as good or more effective at detecting certain diseases than clinical laboratory testing. (Photo copyright: Facebook.)
Dogs More Accurate than Rapid Antigen Testing
Nala and four other dogs (Nim, Hope, Iris and Chaos) were later trained by canine technicians from Medical Detection Dogs Italy (MDDI) to identify the existence of the SARS-CoV-2 virus by directly smelling people waiting in line in pharmacies to get a nasal swab to test for the coronavirus.
Working with their handlers, the five dogs accurately signaled the presence or absence of the virus with 89% sensitivity and 95% specificity. That rate is “well above the minimum required by the WHO [World Health Organization] for rapid swabs for SARS-CoV-2,” according to Nature.
“The results of studies published so far on the accuracy of canine smell in detecting the presence of SARS-CoV-2 in biological samples (e.g., saliva, sweat, urine, trachea-bronchial secretions) from infected people suggest that sniffer dogs might reach percentages of sensitivity and specificity comparable to, or perhaps even higher, than those of RT-PCR,” the scientists wrote in Scientific Reports.
“However, although most of these studies are of good quality, none of them provided scientific validation of canine scent detection, despite this being an important requirement in the chemical analysis practice. Therefore, further applied research in this field is absolutely justified to provide definitive validation of this biodetection method,” the researchers concluded.
Other Studies into Using Dogs for Detecting Disease
Scientists from the Division of Biological and Health Sciences, Department of Agriculture and Livestock at the University of Sonora; and the Canine Training Center Obi-K19, both in Hermosillo, Mexico, conducted the study “as part of a Frontiers of Science Project of the National Council of Science and Technology (CONACYT), in which in addition to analyzing sweat compounds, trained dogs are put to sniff the samples and make detections in people who show symptoms or could be positive for coronavirus,” Mexico Daily Post reported.
The researchers trained four dogs with sweat samples and three dogs with saliva samples of COVID-19 positive patients. The samples were obtained from a health center located in Hermosillo, Sonora, in Mexico. The dogs were restricted to spend five minutes per patient and the researchers calculated the performance of the dogs by measuring sensitivity, specificity, and their 95% confidence intervals (CI).
The researchers concluded that all four of the dogs could detect COVID-19 from either sweat or saliva samples “with sensitivity and specificity rates significantly different from random [sampling] in the field.” According to the Frontiers in Medicine study, the researchers found their results promising because, they said, it is reasonable to expect the detection rate would improve with longer exposure to the samples.
The objective of the Mexican researchers is for the dogs to ultimately reach the sensitivity range requested by WHO for the performance of an antigen test, which is at least 80% sensitivity and 97% specificity. If that goal is achieved, dogs could become important partners in the control of the COVID-19 pandemic, the scientists wrote.
Data obtained so far from these studies indicate that biosensing dogs may represent an effective method of screening for COVID-19 as well as other diseases. More studies and clinical trials are needed before the widespread use of dogs might become feasible. Nevertheless, scientists all over the world are finding that Man’s best friend can be a powerful ally in the fight against the spread of deadly diseases.
In the meantime, the gold standard in COVID-19 testing will continue to be the FDA-cleared assays used by clinical laboratories throughout the United States.
Proof-of-concept study ‘highlights that using AI to integrate different types of clinically informed data to predict disease outcomes is feasible’ researchers say
Artificial intelligence (AI) and machine learning are—in stepwise fashion—making progress in demonstrating value in the world of pathology diagnostics. But human anatomic pathologists are generally required for a prognosis. Now, in a proof-of-concept study, researchers at Brigham and Women’s Hospital in Boston have developed a method that uses AI models to integrate multiple types of data from disparate sources to accurately predict patient outcomes for 14 different types of cancer.
The process also uncovered “the predictive bases of features used to predict patient risk—a property that could be used to uncover new biomarkers,” according to Genetic Engineering and Biotechnology News (GEN).
Should these research findings become clinically viable, anatomic pathologists may gain powerful new AI tools specifically designed to help them predict what type of outcome a cancer patient can expect.
“Experts analyze many pieces of evidence to predict how well a patient may do. These early examinations become the basis of making decisions about enrolling in a clinical trial or specific treatment regimens,” said Faisal Mahmood, PhD (above) in a Brigham press release. “But that means that this multimodal prediction happens at the level of the expert. We’re trying to address the problem computationally,” he added. Should they be proven clinically-viable through additional studies, these findings could lead to useful tools that help anatomic pathologists and clinical laboratory scientists more accurately predict what type of outcomes cancer patient may experience. (Photo copyright: Harvard.)
AI-based Prognostics in Pathology and Clinical Laboratory Medicine
The team at Brigham constructed their AI model using The Cancer Genome Atlas (TCGA), a publicly available resource which contains data on many types of cancer. They then created a deep learning-based algorithm that examines information from different data sources.
Pathologists traditionally depend on several distinct sources of data, such as pathology images, genomic sequencing, and patient history to diagnose various cancers and help develop prognoses.
For their research, Mahmood and his colleagues trained and validated their AI algorithm on 6,592 H/E (hematoxylin and eosin) whole slide images (WSIs) from 5,720 cancer patients. Molecular profile features, which included mutation status, copy-number variation, and RNA sequencing expression, were also inputted into the model to measure and explain relative risk of cancer death.
The scientists “evaluated the model’s efficacy by feeding it data sets from 14 cancer types as well as patient histology and genomic data. Results demonstrated that the models yielded more accurate patient outcome predictions than those incorporating only single sources of information,” states a Brigham press release.
“This work sets the stage for larger healthcare AI studies that combine data from multiple sources,” said Faisal Mahmood, PhD, Associate Professor, Division of Computational Pathology, Brigham and Women’s Hospital; and Associate Member, Cancer Program, Broad Institute of MIT and Harvard, in the press release. “In a broader sense, our findings emphasize a need for building computational pathology prognostic models with much larger datasets and downstream clinical trials to establish utility.”
Future Prognostics Based on Multiple Data Sources
The Brigham researchers also generated a research tool they dubbed the Pathology-omics Research Platform for Integrative Survival Estimation (PORPOISE). This tool serves as an interactive platform that can yield prognostic markers detected by the algorithm for thousands of patients across various cancer types.
The researchers believe their algorithm reveals another role for AI technology in medical care, but that more research is needed before their model can be implemented clinically. Larger data sets will have to be examined and the researchers plan to use more types of patient information, such as radiology scans, family histories, and electronic medical records in future tests of their AI technology.
“Future work will focus on developing more focused prognostic models by curating larger multimodal datasets for individual disease models, adapting models to large independent multimodal test cohorts, and using multimodal deep learning for predicting response and resistance to treatment,” the Cancer Cell paper states.
“As research advances in sequencing technologies, such as single-cell RNA-seq, mass cytometry, and spatial transcriptomics, these technologies continue to mature and gain clinical penetrance, in combination with whole-slide imaging, and our approach to understanding molecular biology will become increasingly spatially resolved and multimodal,” the researchers concluded.
Anatomic pathologists may find the Brigham and Women’s Hospital research team’s findings intriguing. An AI tool that integrates data from disparate sources, analyzes that information, and provides useful insights, could one day help them provide more accurate cancer prognoses and improve the care of their patients.
