Predicting cancer versus autism risk in PTEN patients

In a new study, a team of researchers led by Charis Eng, M.D., Ph.D., Chair of Cleveland Clinic’s Genomic Medicine Institute, identified a metabolite that may predict whether individuals with PTEN mutations will develop cancer or autism spectrum disorder (ASD).

Germline mutations of the tumour suppressor gene PTEN are associated with a spectrum of rare genetic disorders that increase the risk of certain cancers, cognitive and behavioural deficits, benign growths and tumours (i.e., hamartomas), and macrocephaly. These disorders are referred to collectively as PTEN hamartoma tumour syndrome (PHTS), but clinical manifestations vary greatly among patients and often are difficult to anticipate.

For example, subsets of Cowden syndrome (CS) and Bannayan-Riley-Ruvalcaba syndrome (BRRS), two well-defined disorders on the PHTS spectrum, are characterized by either a high risk of certain cancers or ASD. There are functional and structural differences between PTEN mutations associated with ASD and those associated with cancer. However, a biomarker that could proactively determine if a patient with CS/BRRS will develop cancer or ASD has not yet been identified.
Previous studies have established metabolic dysregulation as one of the hallmarks of cancer. Specifically, germline variants in the SDHx genes cause an accumulation of the metabolite succinate, which has been linked to tumorigenesis. Some patients with PTEN mutations have been found to have succinate accumulation despite the lack of SDHx mutations, suggesting that variations in metabolite levels may indicate susceptibility to cancer versus ASD.
To investigate this further, Dr. Eng’s team analyzed the metabolite levels of 511 patients with CS, BRRS, or Cowden-like syndrome compared to controls. The results suggest that certain metabolites are associated with specific mutations and/or clinical features.
In particular, they discovered that decreased levels of fumarate, a metabolite formed from succinate, was more strongly associated with ASD or other developmental disorders compared to cancer in individuals with PTEN mutations. These findings indicate that certain metabolites, such as fumarate, may serve as predictive biomarkers that could distinguish patients who will develop neurodevelopmental disorders from those who will develop cancer.
“By identifying a way to differentiate those with germline PTEN mutations who develop cancer and those who develop autism, this provides clinicians with a MedicalXpress.
MedicalXpressmedicalxpress.com/news/2019-09-cancer-autism-pten-patients.html

New blood test capable of detecting multiple types of cancer

A new blood test in development has shown ability to screen for numerous types of cancer with a high degree of accuracy, a trial of the test shows.

The test, developed by GRAIL, Inc., uses next-generation sequencing technology to probe DNA for tiny chemical tags (methy-lation) that influence whether genes are active or inactive. When applied to nearly 3,600 blood samples – some from patients with cancer, some from people who had not been diagnosed with cancer at the time of the blood draw – the test successfully picked up a cancer signal from the cancer patient samples, and correctly identified the tissue from where the cancer began (the tissue of origin). The test’s specificity – its ability to return a positive result only when cancer is actually present – was high, as was its ability to pinpoint the organ or tissue of origin, researchers found.

The new test looks for DNA, which cancer cells shed into the bloodstream when they die. In contrast to “liquid biopsies,” which detect genetic mutations or other cancer-related alterations in DNA, the technology focuses on modifications to DNA known as methyl groups. Methyl groups are chemical units that can be attached to DNA, in a process called methylation, to control which genes are “on” and which are “off.” Abnormal patterns of methylation turn out to be, in many cases, more indicative of cancer – and cancer type – than mutations are. The new test zeroes in on portions of the genome where abnormal methylation patterns are found in cancer cells.

“Our previous work indicated that methylation-based assays outperform traditional DNA-sequencing approaches to detecting multiple forms of cancer in blood samples,” said the study’s lead author, Geoffrey Oxnard, MD, of Dana-Farber. “The results of the new study demonstrate that such assays are a feasible way of screening people for cancer.”

In the study, investigators analysed cell-free DNA (DNA that had once been confined to cells but had entered the bloodstream upon the cells’ death) in 3,583 blood samples, including 1,530 from patients diagnosed with cancer and 2,053 from people without cancer. The patient samples comprised more than 20 types of cancer, including hormone receptor-negative breast, colorectal, esophageal, gallbladder, gastric, head and neck, lung, lymphoid leukemia, multiple myeloma, ovarian, and pancreatic cancer.

The overall specificity was 99.4%, meaning only 0.6% of the results incorrectly indicated that cancer was present. The sensitivity of the assay for detecting a pre-specified high mortality cancers (the percent of blood samples from these patients that tested positive for cancer) was 76%. Within this group, the sensitivity was 32% for patients with stage I cancer; 76% for those with stage II; 85% for stage III; and 93% for stage IV. Sensitivity across all cancer types was 55%, with similar increases in detection by stage. For the 97% of samples that returned a tissue of origin result, the test correctly identified the organ or tissue of origin in 89% of cases.

Detecting even a modest percent of common cancers early could translate into many patients who may be able to receive more effective treatment if the test were in wide use, Oxnard remarked.

Dana-Farber Cancer Institutewww.dana-farber.org/newsroom/news-releases/2019/new-blood-test-capable-of-detecting-multiple-types-of-cancer/

Artificial intelligence to diagnose genetic diseases

Researchers at Rady Children’s Institute for Genomic Medicine (RCIGM) have utilized automated machine-learning and clinical natural language processing (CNLP) to diagnose rare genetic diseases in record time. This new method is speeding answers to physicians caring for infants in intensive care and opening the door to increased use of genome sequencing as a first-line diagnostic test for babies with cryptic conditions.

“Some people call this artificial intelligence, we call it augmented intelligence,” said Stephen Kingsmore, MD, DSc, President and CEO of RCIGM. “Patient care will always begin and end with the doctor. By harnessing the power of technology, we can quickly and accurately determine the root cause of genetic diseases. We rapidly provide this critical information to intensive care physicians so they can focus on personalizing care for babies who are struggling to survive.”

The workflow and research were led by the RCIGM team in collaboration with leading technology and data-science developers —Alexion, Clinithink, Diploid, Fabric Genomics and Illumina.

Dr. Kingsmore’s team has pioneered a rapid Whole Genome Sequencing process to deliver genetic test results to neonatal and paediatric intensive care (NICU/PICU) physicians to guide medical intervention. RCIGM is the research arm of Rady Children’s Hospital-San Diego.

By reducing the need for labour-intensive manual analysis of genomic data, the supervised automated pipeline provided significant time-savings. In February 2018, the same team achieved the Guinness World Record for fastest diagnosis through whole genome sequencing. Of the automated runs, the fastest times – averaging 19 hours – were achieved using augmented intelligence.

“This is truly pioneering work by the RCIGM team—saving the lives of very sick newborn babies by using AI to rapidly and accurately analyse their whole genome sequence “ says Eric Topol, MD, Professor of Molecular Medicine at Scripps Research and author of the new book Deep Medicine.

RCIGM has optimized and integrated several time-saving technologies into a rapid Whole Genome Sequencing (rWGS) process to screen a child’s entire genetic makeup for thousands of genetic anomalies from a blood sample.

Key components in the rWGS pipeline come from Illumina, the global leader in DNA sequencing, including Nextera DNA Flex library preparation, whole genome sequencing via the NovaSeq 6000 and the S1 flow cell format. Speed and accuracy are enhanced by Illumina’s DRAGEN (Dynamic Read Analysis for GENomics) Bio-IT Platform.

Other pipeline elements include Clinithink’s clinical natural language processing platform CliX ENRICH that quickly combs through a patient’s electronic medical record to automatically extract comprehensive patient phenotype information.

Another core element of the machine learning system is MOON by Diploid. The platform automates genome interpretation using AI to automatically filter and rank likely pathogenic variants. Deep phenotype integration, based on natural language processing of the medical literature, is one of the key features driving this automated interpretation. MOON takes five minutes to suggest the causal mutation out of the 4.5 million variants in a whole genome.

In addition, Alexion’s rare disease and data science expertise enabled the translation of clinical information into a computable format for guided variant interpretation.

As part of this study, the genetic sequencing data was fed into automated computational platforms under the supervision of researchers. For comparison and verification, clinical medical geneticists on the team used Fabric Genomics’ AI-based clinical decision support software, OPAL (now called Fabric Enterprise)—to confirm the output of the automated pipeline. Fabric software is part of RCIGM’s standard analysis and interpretation workflow.

The study titled “Diagnosis of genetic diseases in seriously ill children by rapid whole-genome sequencing and automated phenotyping and interpretation,” found that automated, retrospective diagnoses concurred with expert manual interpretation (97 percent recall, 99 percent precision in 95 children with 97 genetic diseases).

Researchers concluded that genome sequen-cing with automated phenotyping and interpretation—in a median 20:10 hours—may spur use in intensive care units, thereby enabling timely and precise medical care. “Using machine-learning platforms doesn’t replace human experts. Instead it augments their capabilities,” said Michelle Clark, PhD, statistical scientist at RCIGM and the first author of the study. “By informing timely targeted treatments, rapid genome sequencing can improve the outcomes of seriously ill children with genetic diseases.”
Rady Children’s Institutewww.radygenomics.org/category/news/pr/

Liquid biopsy blood test improves breast cancer diagnostics

A new type of blood test for breast cancer could help avoid thousands of unnecessary surgeries and otherwise precisely monitor disease progression, according to a study led by the Translational Genomics Research Institute (TGen) and Mayo Clinic in Arizona.

The study suggests that the test called TARDIS — TARgeted DIgital Sequencing — is as much as 100 times more sensitive than other blood-based cancer monitoring tests.

TARDIS is a “liquid biopsy” that specifically identifies and quantifies small fragments of cancer DNA circulating in the patient’s bloodstream, known as circulating tumour DNA (ctDNA). According to the study, TARDIS detected ctDNA in as low as 2 parts per 100,000 in patient blood.
“By precisely measuring ctDNA, this test can detect the presence of residual cancer, and inform physicians if cancer has been successfully eradicated by treatment,” said Muhammed Murtaza, M.B.B.S., Ph.D., Assistant Professor and Co-Director of TGen’s Center for Noninvasive Diagnostics. He also holds a joint appointment on the Research Faculty at Mayo Clinic in Arizona, and is one of the study’s senior authors.

For example, Dr. Murtaza explained, TARDIS is precise enough to tell if early stage breast cancer patients have responded well to pre-operative drug therapy. It is more sensitive than the current method of determining response to drug therapy using imaging.

“This has enormous implications for women with breast cancer. This test could help plan the timing and extent of surgical resection and radiation therapy after patients have received pre-operative therapy,” said Dr. Barbara A. Pockaj, M.D., a surgical oncologist who specializes in breast and melanoma cancer patients at Mayo Clinic in Arizona, and is the study’s other senior author. Dr. Pockaj is the Michael M. Eisenberg professor of surgery and the chair of the Breast Cancer Interest Group (BIG), a collaboration between researchers at Mayo, TGen and ASU.

Unlike traditional biopsies, which only produce results from one place at one time, liquid biopsies use a simple blood draw, and so could safely be performed repeatedly, as often as needed, to detect a patient’s disease status.

“TARDIS is a game changer for response monitoring and residual disease detection in early breast cancer treated with curative intent. The sensitivity and specificity of patient-specific TARDIS panels will allow us to tell very early, probably after one cycle, whether neo-adjuvant (before surgery) therapy is working and will also enable detecting micro-metastatic disease and risk-adapted treatment after completing neo-adjuvant therapy,” said Dr. Caldas, who also is Senior Group Leader at the Cancer Research UK Cambridge Institute, and one of the study’s contributing authors.

Following further clinical testing and trials, TARDIS could someday be routinely used for monitoring patients during cancer treatment, and discovering when patients are essentially cured and cancer free.

“The results of these tests could be used to individualize cancer therapy avoiding overtreatment in some cases and under treatment in others,” Dr. Murtaza said. “The central premise of our research is whether we can develop a blood test that can tell patients who have been completely cured apart from patients who have residual disease. We wondered whether we can see clearance of ctDNA from blood in patients who respond well to pre-surgical treatment.”

Current tests and imaging lack the sensitivity needed to make this determination.

“Fragments of ctDNA shed into blood by tumours carry the same cancer-specific mutations as the tumour cells, giving us a way to measure the tumour,” said Bradon McDonald, a computational scientist in Dr. Murtaza’s lab, and the study’s first author.

“The problem is that ctDNA levels can be so low in non-metastatic cancer patients, there are often just not enough fragments of ctDNA in a single blood sample to reliably detect any one mutation. This is especially true in the residual disease setting, when there is no obvious tumour left during or after treatment,” McDonald said. “So, instead of focusing on a single mutation from every patient, we decided to integrate the results of dozens of mutations from each patient.”
Translational Genomics Research Institutewww.tgen.org/news/2019/august/07/new-ctdna-blood-test-for-cancer/

Clinical-grade computational pathology using weakly supervised deep learning on whole slide images

The development of decision support systems for pathology and their deployment in clinical practice have been hindered by the need for large manually annotated datasets.
To overcome this problem, the authors present a multiple instance learning-based deep learning system that uses only the reported diagnoses as labels for training, thereby avoiding expensive and time-consuming pixel-wise manual annotations. We evaluated this framework at scale on a dataset of 44,732 whole slide images from 15,187 patients without any form of data curation. Tests on prostate cancer, basal cell carcinoma and breast cancer metastases to axillary lymph nodes resulted in areas under the curve above 0.98 for all cancer types. Its clinical application would allow pathologists to exclude 65-75% of slides while retaining 100% sensitivity. The results show that this system has the ability to train accurate classification models at unprecedented scale, laying the foundation for the deployment of computational decision support systems in clinical practice.
NCBIwww.ncbi.nlm.nih.gov/pubmed/31308507

Renal disease diagnosis

Elevated hormone flags liver problems in mice with methylmalonic acidemia. Researchers have discovered that a hormone, fibroblast growth factor 21 (FGF21), is extremely elevated in mice with liver disease that mimics the same condition in patients with methylmalonic acidemia (MMA), a serious genomic disorder. Based on this finding, medical teams treating patients with MMA will be able to measure FGF21 levels to predict how severely patients’ livers are affected and when to refer patients for liver transplants.

The findings also might shed light on more common disorders such as fatty liver disease, obesity and diabetes by uncovering similarities in how MMA and these disorders affect energy metabolism and, more specifically, the function of mitochondria, the cells’ energy powerhouses. The study was conducted by researchers at the National Human Genome Research Institute (NHGRI), part of the National Institutes of Health.

“Findings from mouse studies usually take years to translate into health care treatment, but not in this case,” said Charles P. Venditti, M.D., Ph.D., senior author and senior investigator in the NHGRI Medical Genomics and Metabolic Genetics Branch. “We can use this information today to ensure that patients with MMA are treated before they develop severe complications.”

MMA is a genomic disease that impairs a person’s ability to break down food proteins and certain fatty acids. The condition affects roughly 1 in 50,000 children born in the United States and can be detected through newborn screening. Children with MMA suffer from frequent life-threatening metabolic crises when they encounter a minor viral illness or other stressors like trauma, dietary imbalance or surgery. They must adhere to a special low-protein diet and take various supplements their entire lives.

The NHGRI team created a new mouse model and used it to discover key pathways that were affected during a fasting challenge to model a metabolic crisis in a patient with MMA. It enabled them to identify markers that they could then measure in MMA patients to assess the severity of the dysfunction in their mitochondria, specifically in the liver.
The MMA mice also allowed them to study the response to liver-directed gene therapy and to compare the findings in patients after liver transplant surgery. Liver transplants give patients with MMA a missing enzyme and ease some of the symptoms, but do not cure the disease. Kidney transplantation, on the other hand, is necessary when these patients reach terminal stages of renal failure, an expected chronic complication of MMA. Selecting which patients would benefit from a liver or combined liver/kidney transplant as opposed to just a kidney transplant is an important clinical decision for families and their clinicians.

“We found that having MMA, whether in a mouse or person, causes stress pathways to be chronically activated and can impair their ability to respond to acute stress,” said Irini Manoli, M.D., Ph.D., lead author and associate investigator in NHGRI’s Medical Genomics and Metabolic Genetics Branch. “Our new markers can accurately predict how effective a therapy, whether cellular or genomic, might be for the patients.”
National Human Genome Research Institutewww.genome.gov/news/news-release/Elevated-hormone-flags-liver-problems-in-mice-with-methylmalonic-acidemia-MMA

Horiba Yumizen hematology analysers minimize microscopy slide reviews

Horiba has recently announced the publication of scientific studies which demonstrate the excellent performance of its new HELO high throughput fully automated hematology platform on body fluid and pathological samples. Horiba’s Yumizen® H2500 and H1500 automated hematology analysers within the HELO platform deliver enhanced precision for complete blood counts and white blood cell (WBC) differential testing, with body fluid analysis included as standard. This improves diagnosis, minimizes unnecessary manual microscopy slide reviewing and enhances laboratory workflow, as highlighted by two recent scientific evaluation studies.
The first study was undertaken by Nantes University Hospital (CHU de Nantes) focusing on the need for automated analysis of biological fluids for robust and reliable results reporting. Hematological analysis of body fluids (BF) can provide clinicians with valuable diagnostic information as it can indicate a number of serious medical conditions. Manual microscopy has traditionally been used to determine total and differentiated WBC in BFs, however, results can be affected by inter-operator variability and take time to undertake. By using an automated method of analysis of WBC in a body fluid smear, this can improve turnaround times and accuracy.
To ensure the robustness and reliability of automated BF analysis in routine laboratory workflows, the evaluation study was undertaken on the performance of the automated body fluid analysis cycle on the Yumizen H2500. The study included 98 samples from cerebro-spinal, pleural, ascitic, pericardic and bronchoalveolar liquid (BAL) fluids which were used for comparative leukocyte and erythrocyte counts, as well as differential. This confirmed the good analytical performance of Yumizen analyser in comparison with conventional microscopic count, as well as a reference analyser.
The second study explored the flagging efficiency of the new analyser. Pathological samples, coming from patients with altered hematopoiesis, often trigger a WBC-Diff flag; this is due to poor cell separation and requires a manual slide review (MSR) by microscopy to confirm the WBC differential. Laboratory workload would be optimized if MSR could be reduced without compromising patient care. Therefore, the study undertaken by the Institut Bergonié Comprehensive Cancer Centre compared the flagging performance in the WBC differential of the Yumizen H1500/H2500 to a routine analyser. This included patients with pathology or treatment affecting hematopoiesis, such as those undergoing chemotherapy or with onco-hematologic disorders.
The study on 228 pathological samples (100 from patients on chemotherapy for solid tumours and 128 from patients with malignant blood disease) demonstrated an improvement in the WBC-diff analysis and reliability of the Yumizen H1500/2500 analyser compared to a routine analyser. It delivered better precision and specificity, due to improved cell separation, and a significant decrease (-21%) in unnecessary morphology reviewing by microscopy, thus saving significant time in the laboratory.
Commenting on the successful outcome of the studies, Mandy Campbell, Horiba Medical said, “These evaluation studies undertaken by recognized authorities in hematological analysis, demonstrate the excellent performance of our new Yumizen H1500/H2500 automated hematology analysers with both body fluid and pathological samples. Body fluid analysis is available as standard on these analysers which have been shown to enhance diagnoses and lower film review rates to improve laboratory workflow.” www.horiba.com/medical

Zika virus study reveals possible causes of brain pathology

In healthy individuals, the Zika virus causes flu-like symptoms. If a pregnant woman becomes infected, the unborn child can suffer from severe brain abnormalities as a result of mechanisms that have not yet been explained. A study by the Technical University of Munich (TUM) and the Max Planck Institute of Biochemistry (MPI-B) shows that Zika virus proteins bind to cellular proteins that are required for neural development.

A few years ago, Zika virus spread across South America, posing a health issue with global impact. A significant number of South American women who came into contact with the virus for the first time at the start of their pregnancy by a mosquito bite subsequently gave birth to children with severe disabilities. The babies suffered from a condition known as microcephaly; they were born with a brain that was too small. This can lead to intellectual disabilities and other serious neurological disorders.

Scientists succeeded in proving that these deformities are caused by Zika virus infections, but so far they have been unable to explain why. Andreas Pichlmair, Chair for Viral Immunopathology at TUM and his team from the TUM Institute of Virology and MPI-B have examined how Zika virus influences human brain cells. They identified the virus proteins with the potential to affect neuronal development in the developing brain.

 “Zika virus is closely related to the Hepatitis C virus and certain tropical diseases such as Dengue and West Nile virus. It is, however, the only virus that causes brain damage in newborns,” explains Pichlmair, who headed the recent study.

The researchers discovered that the virus uses certain cellular proteins to replicate its own genome. These molecules are also important neurological factors in the process of a stem cell developing into a nerve cell. “Our findings suggest that the virus takes these factors away from brain development and uses them to replicate its genome, which prevents the brain from developing properly,” explains the virologist.

When the team headed by Pichlmair removed the factors in the cells, the virus found it much harder to replicate. The researchers were able to demonstrate which virus proteins come in contact with these development factors and cause the brain defects. “Previous studies revealed the virus proteins necessary for the packaging or replication of the viral genome but it was enigmatic to understand how these proteins influence neuronal development. It appears that viral proteins are responsible for causing the serious defects in the unborn – unintentionally we presume,” says Pichlmair.

In their comprehensive proteomics survey, the research team identified cellular proteins that were altered chemically or numerically by the virus or which bound to virus proteins. In this way, they were not only able to illustrate possible reasons for the caused deformities, but also obtained a very clear picture of how the virus reprograms the cell to use it for its own replication. www.tum.de/nc/en/about-tum/news/press-releases/details/34920/

Astell Scientific at Medica

Astell Scientific is a world renowned manufacturer and supplier of steam sterilizers. Astell Scientific autoclaves, steam generators and effluent decontamination systems (EDS) are designed to meet the exacting demands of modern Laboratory, Research and Medical professionals, and as such incorporate innovations such as colour touchscreen controllers as standard throughout the range.

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Oncimmune at Medica

The battle against cancer hinges on the early detection and then delivery of effective treatment. Oncimmune is working to revolutionise both the detection of cancer and its treatment by harnessing the sophisticated disease-detecting capabilities of the immune system to find cancer in its early stages. Oncimmune’s range of diagnostic tests assist clinicians to identify the presence of cancer on average four years before standard clinical diagnosis, whilst its technology platform and sample biobanks are helping healthcare companies to develop new cancer treatments.

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