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Posts Tagged ‘Digital pathology’

Google’s Artificial Intelligence Algorithm Shows Improved Accuracy in Reading Mammograms

Posted in Artificial Intelligence - General, Artificial Intelligence Applications in Health Care, Artificial Intelligence in CANCER, Artificial Intelligence in Health Care - Tools & Innovations, Artificial Intelligence in Medicine - Application for Diagnosis, Breast Cancer - impalpable breast lesions, Cancer - General, CANCER BIOLOGY & Innovations in Cancer Therapy, Cancer Screening, Deep Learning in Pathology, tagged AI, Artificial intelligence, breast cancer screening, deep learning, Digital pathology, Google, Google health, mammogram, pathologists, Pathology on January 2, 2020| Leave a Comment »

Google AI improves accuracy of reading mammograms, study finds

Reporter: Stephen J. Williams, PhD

Updated on 12/7/2022

AI system beats doctors at scrutinizing breast cancer scans

AI learned to identify a protein targeted in immunotherapy in a process that could make doctors’ work faster, simpler and more precise.

SOURCE

https://www.israel21c.org/ai-system-beats-doctors-at-scrutinizing-breast-cancer-scans/

 

Anne Stych, Staff Writer
Jan 2, 2020, 10:28am EST

Weinberg-Clark Photography

Google CFO Ruth Porat has blogged about twice battling breast cancer.

Artificial intelligence was often more accurate than radiologists in detecting breast cancer from mammograms in a study conducted by researchers using Google AI technology.

The study, published in the journal Nature, used mammograms from approximately 90,000 women in which the outcomes were known to train technology from Alphabet Inc’s DeepMind AI unit, now part of Google Health, Yahoo news reported.

The AI system was then used to analyze images from 28,000 other women and often diagnosed early cancers more accurately than the radiologists who originally interpreted the mammograms.

See Also

• Duke breakthrough could mean improved breast cancer treatments
• How to support a colleague with breast cancer

In another test, AI outperformed six radiologists in reading 500 mammograms. However, while the AI system found cancers the humans missed, it also failed to find cancers flagged by all six radiologists, reports The New York Times.

The researchers said the study “paves the way” for further clinical trials.

Writing in Nature, Etta D. Pisano, chief research officer at the American College of Radiology and professor in residence at Harvard Medical School, noted, “The real world is more complicated and potentially more diverse than the type of controlled research environment reported in this study.”

Ruth Porat, senior vice president and chief financial officer Alphabet, Inc., wrote in a company blog titled “Breast cancer and tech…a reason for optimism” in October about twice battling the disease herself, and the importance of her company’s application of AI to healthcare innovations.

She said that focus had already led to the development of a deep learning algorithm to help pathologists assess tissue associated with metastatic breast cancer.

“By pinpointing the location of the cancer more accurately, quickly and at a lower cost, care providers might be able to deliver better treatment for more patients,” she wrote.

Google also has created algorithms that help medical professionals diagnose lung cancer, and eye disease in people with diabetes, per the Times.

Porat acknowledged that Google’s research showed the best results occur when medical professionals and technology work together.

Any insights provided by AI must be “paired with human intelligence and placed in the hands of skilled researchers, surgeons, oncologists, radiologists and others,” she said.

Anne Stych is a staff writer for Bizwomen.

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Digital PCR

Posted in Clinical & Translational, Clinical Diagnostics, Genetics & Innovations in Treatment, Infectious Disease & New Antibiotic Targets, Innovations, Microbiologial genetics, Molecular Genetics & Pharmaceutical, tagged diagnostics, Digital pathology, Digital polymerase chain reaction, medical devices and digital health, PCR on March 24, 2016| Leave a Comment »

Digital PCR

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

GEN Roundup: Digital PCR Advances Partition by Partition  

By Partitioning Samples Digital PCR Is Lowering Detection Limits and Enabling New Applications

GEN  Mar 1, 2016 (Vol. 36, No. 5)       http://www.genengnews.com/gen-articles/gen-roundup-digital-pcr-advances-partition-by-partition/5697

 

• Digital PCR (dPCR) has generated intense interest because it is showing potential as a clinical diagnostics tool. It has already proven to be a useful technique for any application where extreme sensitivity or precise quantification is essential, such as identifying mutations or copy number variations in tumor cells, or examining gene expression at the single-cell level.

  GEN interviewed several dPCR experts to find out specifically why the technique is increasing in popularity. GEN also asked the experts to envision dPCR’s future capabilities.

• GEN: What makes dPCR technology such a superior tool for discovery and diagnostic applications?

  Dr. Shelton The high levels of sensitivity, precision, and reproducibility in DNA and quantification are the major strengths of dPCR. The technology is robust where differences in primer efficiency or the presence of sample-specific PCR inhibitors are trivial to the final quantification through an end-point amplification reaction.

  This provides value to discovery as a trusted tool for validating potential biomarkers and hypotheses generated by broad profiling techniques such as microarrays or next-generation sequencing (NGS). In diagnostics applications, the reproducibility and rapid results of dPCR are critical for labs around the world to quickly compare and share data, especially for ultra-low detection of DNA where variability is high.

  Dr. Garner Digital PCR provides a precise direct counting approach for single molecule detection, thereby providing a straightforward process for the absolute quantification of nucleic acids in samples. One of the biggest advantages of using a system such as ours is its ability to do real-time reads on digital samples. When samples go through PCR, their results are recorded after each cycle.

  These results build a curve, and customers can analyze the data if something went wrong. If it isn’t a clean read—from either a contamination issue, primer-dimer issue, or off-target issue—the curve isn’t the classic PCR curve.

  Dr. Menezes Digital PCR allows absolute quantification of target concentration in samples without the need for standard curves. Obtaining consistent, precise, and absolute quantification with regular qPCR is dependent on standard curve generation and amplification efficiency calculations, which can introduce errors.

  Ms. Hibbs At MilliporeSigma Cell Design Studio, the implementation of dPCR has improved and accelerated the custom cell engineering workflow. After the application of zinc finger nuclease or CRISPR/Cas to create precise genetic modifications in mammalian cell lines, dPCR is used to characterize the expected frequency of homologous recombination and develop a screening strategy based on this expected frequency.

  In some cell lines, homologous recombination occurs at a low frequency. In such cases, dPCR is used to screen cell pools and subsequently identify rare clones having the desired mutation. Digital PCR is also used to accurately and expeditiously measure target gene copy number. It is used this way, for example, in polyploid cell lines.

  Dr. Price The ability to partition genomic samples to a level that enables robust detection of single target molecules is what sets dPCR apart as an innovative tool. Each partition (droplet in the case of the RainDrop System) operates as an individual PCR reaction, allowing for sensitive, reproducible, and precise quantification of nucleic acid molecules without the need for reference standards or endogenous controls.

  Partitioning also provides greater tolerance to PCR inhibitors compared to quantitative PCR (qPCR). In doing so, dPCR can remedy many shortcomings of qPCR by transforming the analog, exponential nature of PCR into a digital signal.

  Mr. Wakida Digital PCR is an ideal technology for detecting rare targets at concentrations of 0.1% or lower. By partitioning samples prior to PCR, exceptionally rare targets can be isolated into individual partitions and amplified.

  Digital PCR produces absolute quantitative results, so in some respects, it is easier than qPCR because it doesn’t require a standard curve, with the added advantages of being highly tolerant of inhibitors and being able to detect more minute fold changes. Absolute quantification is useful for generating reference standards, detecting viral load, and preparing NGS libraries.

• GEN: In what field do you think dPCR will have the greatest impact in the future?

  Dr. Shelton dPCR will have a great impact on precision medicine, especially in liquid biopsy analysis. Cell-free DNA from bodily fluids such as urine or blood plasma can be analyzed quickly and cost-effectively using dPCR. For example, a rapid dPCR test can be performed to determine mutations present in a patient’s tumor and help drive treatment decisions.

  Iterative monitoring of disease states can also be achieved due to the relatively low cost of dPCR, providing faster response times when medications are failing. Gene editing will also be greatly impacted by dPCR. Digital PCR enables refinement and optimization of gene-editing tools and conditions. Digital PCR also serves as quality control of therapeutically modified cells and viral transfer vectors used in gene-therapy efforts.

  Dr. Garner The BioMark™ HD system combines dPCR with simultaneous real-time data for counting and validation. This capability is important for applications such as rare mutation detection, GMO quantitation, and aneuploidy detection—where false positives are intolerable and precision is paramount.

  Any field that requires precision and the ability to detect false positives is a likely target for Fluidigm’s dPCR. Suitable applications include detecting and quantifying cancer-causing genes in patients’ cells, viral RNA that infects bacteria, or fetal DNA in an expectant mother’s plasma.

  Dr. Menezes This technology is particularly useful for samples with low frequency sequences as, for example, those containing rare alleles, low levels of pathogen, or low levels of target gene expression. Teasing out fine differences in copy number variants is another area where this technology delivers more precise data.

  Ms. Hibbs Digital PCR overcomes limitations associated with low-abundance template material and quantification of rare mutations in a high background of wild-type DNA sequence. For this reason, dPCR is poised to have significant impacts in diverse clinical applications such as detection and quantification of rare mutations in liquid biopsies, detection of viral pathogens, and detection of copy number variation and mosaicism.

  Dr. Price Due to its high sensitivity, precision, and absolute quantification, the RainDrop dPCR has the potential to extend the range of nucleic acid analysis beyond the reach of other methods in a number of applications that could lend themselves to diagnostic, prognostic, and predictive applications. The precision of dPCR can be extremely useful in applications that require finer measures of fold change and rare variant detection.

  Digital PCR is suitable for addressing varied research and clinical challenges. These include the early detection of cancer, pathogen/viral detection and quantitation, copy number variation, rare mutation detection, fetal genetic screening, and predicting transplant rejection. Additional applications include gene expression analysis, microRNA analysis, and NGS library quantification.

  Mr. Wakida Digital PCR will have an impact on applications for detecting rare targets by enabling investigators to complement and extend their capabilities beyond traditionally employed methods. One such application is using dPCR to monitor rare targets in peripheral blood, as in liquid biopsies.

  The monitoring of peripheral blood by means of dPCR has been described in several peer-reviewed articles. In one such article, investigators considered the clinical value of Thermo’s QuantStudio™ 3D Digital PCR system for the detection of circulating DNA in metastatic colorectal cancer (Dig Liver Dis. 2015 Oct; 47(10): 884–90).

• GEN: Is there a new technology on the horizon that will increase the speed and/or efficiency of dPCR?

  Dr. Shelton High-throughput sample analysis can be an issue with some dPCR systems. However, Bio-Rad’s Automated Droplet Generator allows labs to process 96 samples simultaneously, a capability that eliminates user-to-user variability and minimizes hands-on time.

  We also want users to get the most information from one sample. Therefore, we are focused on expanding the multiplexing capabilities of our system. In development at Bio-Rad are new technologies that increase the multiplexing capabilities without loss of specificity or accuracy in the downstream workflow.

  Dr. Garner Much of the industry direction seems to be in offering ever-higher resolution, or the ability to run more samples at the same resolution. Thus far, however, customers haven’t found commercial uses for these tools. Also, with increasing resolution and the search for even rarer mutations, the challenge of detecting false positives becomes an even bigger issue.

  Dr. Menezes Use of ZEN™ Double-Quenched Probes by IDT in digital PCR provides increased sensitivity and a lower limit of detection. Due to the second quencher, ZEN probes provide even lower background than traditional single-quenched probes. And this lower background enables increased sensitivity when analyzing samples with low copy number targets, where every droplet matters.

  Ms. Hibbs Quantification relies upon counting the number of positive partitions at the end point of the reaction. Accordingly, precision and resolution can be increased by increasing the number of partitions. We are now capable of analyzing on the order of millions of partitions per run, further extending the lower limit of detection. Additionally, the workflow is amenable to the integration of automation in order to increase throughput and standardize reaction set up.

  Dr. Price Although dPCR is still an emerging technology, there is tremendous interest in its potential clinical diagnostics applications. Enabling adoption of dPCR in the clinical lab requires addressing current gaps in workflow, cost, throughput, and turnaround time.

  Digital PCR technology has the potential for being improved significantly in two dimensions. First, one can address the problem of serially detecting positive versus negative partitions by leveraging lower-cost imaging detection technologies. Alternatively, one may capitalize on the small partition volumes to dramatically reduce the time to perform PCR. Ideally, the future will bring both capabilities to bear.

  Mr. Wakida Compared to qPCR, dPCR currently requires more hands-on time to set up experiments. We are investigating methods to address this.

 

PCR Shows Off Its Clinical Chops   

Thanks to Advances in Genomics, PCR Is Becoming More Common in Clinical Applications

• MaryAnn Labant

• Last May, Roche Molecular Systems announced that its cobas Liat Strep A assay received a CLIA waiver. This clinic-ready assay can detect Streptococcus pyogenes (group A ß-hemolytic streptococcus) DNA in throat swabs by targeting a segment of the S. pyogenes genome.

  Since its invention by Kary B. Mullis in 1985, the polymerase chain reaction (PCR) has become well established, even routine, in research laboratories. And now PCR is becoming more common in clinical applications, thanks to advances in genomics and the evolution of more sensitive quantitative PCR methodologies.

  Examples of clinical applications of PCR include point-of-care (POC) molecular tests for bacterial and viral detection, as well as mutation detection in liquid or tumor biopsies for patient stratification and treatment monitoring.

  Industry leaders recently participated in a CHI conference that was held in San Francisco. This conference—PCR for Molecular Medicine—encompassed research and clinical perspectives and emphasized advanced techniques and tools for effective disease diagnosis.

  To kick off the event, speakers shared their views on POC molecular tests. These tests, the speakers insisted, can provide significant value to healthcare only if they support timely decision making.

  Clinic-ready PCR platforms need to combine speed, ease of use, and accuracy. One such platform, the cobas Liat (“laboratory in a tube”), is manufactured by Roche Molecular Systems. The system employs nucleic acid purification and state-of-art PCR-based assay chemistry to enable POC sites to rapidly provide lab-quality results.

  The cobas Liat Strep A Assay detects Streptococcus pyogenes (group A β-hemolytic streptococcus) DNA by targeting a segment of the S. pyogenes genome. The operator transfers an aliquot of a throat swab sample in Amies medium into a cobas Liat Strep A Assay tube, scans the relevant tube and sample identification barcodes, and then inserts the tube into the analyzer for automated processing and result interpretation. No other operator intervention or interpretation is required. Results are ready in approximately 15 minutes.

  According to Shuqi Chen, Ph.D., vp of Point-of-Care R&D at Roche Molecular Systems, clinical studies of the cobas Liat Strep A Assay demonstrated 97.7% sensitivity when the test was used at CLIA-waived, intended-use sites, such as physicians’ offices. In comparison, rapid antigen tests and diagnostic culture have sensitivities of 70% and 81%, respectively (according to a 2009 study Tanz et al. in Pediatrics).

  The cobas Liat assay preserved the same ease-of-use and rapid turnaround as the rapid antigen tests. It addition, it provided significantly faster turnaround than the lab-based culture test, which can take 24–48 hours.

  A CLIA waiver was announced for the cobas Liat Strep A assay in May 2015. CLIA wavers have been submitted for cobas Liat flu assays, and Roche intends to extend the assay menu.

  POC tests are also moving into field applications. Coyote Bioscience has developed a novel method for one-step gene testing without nucleic acid extraction that can be as fast as 10 minutes from blood sample to result. Their portable devices for molecular diagnostics can be used as genetic biosensors to bring complex clinical testing directly to the patient.

  “Instead of sequential steps, reactions happen in parallel, significantly reducing analysis time. Buffer, enzyme, and temperature profiles are optimized to maximize sensitivity,” explained Sabrina Li, CEO, Coyote Bioscience. “Both RNA and DNA can be analyzed simultaneously from a drop of blood in the same reaction.”

  The first-generation Mini-8 system was used for Ebola detection in Africa where close to 600 samples were tested with 98.8% sensitivity. Recently in China, the Mini-8 system was applied in hospitals and small community clinics for hepatitis B and C and Bunia virus detection. The second-generation InstantGene system is currently being tested internally with clinical samples.

• Digital PCR

  Conventional real-time PCR technology, while suited to the analysis of high-quality clinical samples, may effectively conceal amplification efficiency changes when sample quality is inconsistent. A more effective alternative, Bio-Rad suggests, is its droplet-digital PCR (ddPCR) technology, which can provide absolute quantification of target DNA or RNA, a critical advantage when samples are limited, degraded, or contain PCR inhibitors. The company says that of the half-dozen clinical trials that are using digital PCR, half rely on the Bio-Rad QX200 ddPCR system.

  Personalized cancer care requires ultra-sensitive detection and monitoring of actionable mutations from patient samples. The high sensitivity and precision of droplet-digital PCR (ddPCR) from Bio-Rad Laboratories offers critical advantages when clinical samples are limited, degraded, or contain PCR inhibitors.

  Typically, formalin-fixed and paraffin-embedded (FFPE) tissue samples are processed. FFPE samples work well for immunohistochemistry and protein analysis; however, the formalin fixation can damage nucleic acids and inhibit the PCR reaction. Samples may yield 100 ng of purified nucleic acid, but the actual amplifiable material is less than 1%, or 1 ng, in most cases.

  “Current qPCR technology depends on real-time fluorescence accumulation as the PCR is occurring, which can be an effective means of detecting and quantifying DNA targets in nondegraded samples,” commented Dawne Shelton, Ph.D., staff scientist, Digital Biology Center, Applications Development Group, Bio-Rad Laboratories. “Amplification efficiency is critical; if that amplification efficiency changes because of sample quality it is hidden in the qPCR methodology.”

  “In ddPCR, that is a big red flag,” Dr. Shelton continued. “It changes the format of how the data look immediately so you know the amount of inhibition and which samples are too inhibited to use.”

  Tissue types vary and contain different degrees of fat or other content that can also act as PCR inhibitors. In blood monitoring, the small circulating fragments of DNA are extremely degraded; in addition, food, supplements, or other compounds ingested by the patient may have an inhibitory effect.

  Clinical labs test for these variabilities and clean the blood, but remnant PCR inhibitors can remain. In ddPCR, a single template is partitioned into a droplet. If the droplet contains a good template, it produces a signal; otherwise, it does not—a simple yes or no answer.

  “Even if there is no PCR inhibition, most clinical samples yield very small amounts of nucleic acid,” Dr. Shelton added. “To make a secure decision using qPCR is difficult because you are in a gray zone at the very end of its linear range. ddPCR operates best with small sample amounts and provides good statistics for confidence in your results.”

  Currently, at least a half dozen clinical trials worldwide are using digital PCR, half of them are using the Bio-Rad QX200 Droplet Digital PCR system. Examples of studies include examining BCR-ABL monitoring in patients with chronic myelogenous leukemia (CML); identifying activating mutations in epidermal growth factor receptor (EGFR) for first-line therapy of new drugs in patients with lung cancer; and the monitoring of resistance mutations such as EFGR T790M in patients with non-small cell lung cancer (NSCLC).

  Clovis Oncology used a technology called BEAMing (Beads, Emulsions, Amplification, and Magnetics), a type of digital PCR for blood-based molecular testing, to perform EGFR testing on almost 250 patients in clinical trials. In BEAMing, individual EGFR gene copies from plasma are separated into individual water droplets in a water-in-oil emulsion. The gene copies are then amplified by PCR on magnetic beads.

  The beads are counted by flow cytometry using fluorescently labeled probes to distinguish mutant beads from wild-type. Because each bead can be traced to an individual EGFR molecule in the patient’s plasma, the method is highly quantitative.

  “BEAMing is particularly well-suited for the detection of known mutations in circulating tumor DNA. In this circumstance, the mutation of interest often occurs at low levels, perhaps only 1–2 copies per milliliter or even less, and in a high background of wild-type DNA that comes from normal tissue. BEAMing can detect one mutant molecule in a background of 5,000 wild-type molecules in clinical samples,” stated Andrew Allen, MRCP, Ph.D., chief medical officer, Clovis Oncology.

  In the studies, the EGFR-resistance mutation T790M could be identified in plasma 81% of the time that it was seen in the matched patient tumor biopsy. Additionally, about 10% of patients in the study had a T790M mutation in plasma that was not identified in tissue, presumably because of tumor heterogeneity. Another 5–10% of the patients did not provide an EGFR result, usually because the tissue biopsy had no tumor cells.

  In aggregate, these results suggest that plasma EGFR testing can be a valuable complement to tumor testing in the clinical management of NSCLC patients, and can provide an alternative when a biopsy is not available. Tumor biopsies may provide only limited tissue, if in fact any tissue is available, for molecular analysis. Also, mutations may be missed due to tumor heterogeneity. These mutations may be captured by sampling the blood, which acts as a reservoir for mutations from all parts of a patient’s tumor burden.

  In the last few years, a panoply of clinically actionable driver mutations have been identified for NSCLC, including mutations in EGFR, BRAF, and HER2, as well as ALK, ROS, and RET rearrangements. These driver mutations will migrate NSCLC molecular diagnostic testing in the next few years toward panel testing of relevant cancer genes using various digital technologies, including next-generation sequencing.

   

PCR Has a History of Amplifying Its Game

A GEN 35th Anniversary Retrospective

• Jeffrey S. Buguliskis, Ph.D.

PCR is a fast and inexpensive technique used to amplify segments of DNA that continues to adapt and evolve for the demanding needs of molecular biology researchers. This diagram shows the basic principles of PCR amplification. [NHGRI]

• The influence that the polymerase chain reaction (PCR) has had on modern molecular biology is nothing short of remarkable. This technique, which is akin to molecular photocopying, has been the centerpiece of everything from the OJ Simpson Trial to the completion of the Human Genome Project. Clinical laboratories use this DNA amplification method for infectious disease testing and tissue typing in organ transplantation. Most recently, with the explosion of the molecular diagnostics field and meteoric rise in the use of next-generation sequencing platforms, PCR has enhanced its standing as an essential pillar of genomic science.

  Let’s open the door to the past and take a look back around 35 years ago when GEN started reporting on the relatively new disciplines of genetic engineering and molecular biology. At that time, GEN was among the first to hear the buzz surrounding a new method to synthesize and amplify DNA in the laboratory. In reviewing the fascinating history of PCR, we will see how the molecular diagnostics field took shape and where it could be headed in the future.

• Some Like It Hot

  The biological sciences rarely advance within a vacuum—rather they rely on previous discoveries to promote directly or indirectly our understanding. The contributions made by scientists in the field of molecular biology that contributed to the functional pieces of PCR were numerous and spread out over more than two decades.

  It began with H. Gobind Khorana’s advances in understanding the genetic code, leading to the use of synthetic DNA oligonucleotides, continued through Kjell Kleepe’s 1971 vision of a two-primer system for replicating DNA segments, to Fredrick Sanger’s method of DNA sequencing—a process that would win him the Nobel prize in 1980—which utilized DNA oligo primers, nucleotide precursors, and a DNA synthesis enzyme.

  All of the previous discoveries were essential to PCR’s birth, yet it would be an egregious mistake to begin a retrospective on PCR and not discuss the enzyme upon which the entire reaction hinges upon—DNA polymerase. In 1956, Nobel laureate Arthur Kornberg and his colleagues discovered DNA polymerase (Pol I), in Escherichia coli. Moreover, the researchers described the fundamental process by which the polymerase enzyme copies the base sequence of a DNA template strand. However, it would take biologists another 20 years to discover a version of DNA polymerase that was stable enough for use for any meaningful laboratory purposes.

  That discovery came in 1976 when a team of researchers from the University of Cincinnati described the activity of a DNA polymerase (Taq) they isolated from the extreme thermophile bacteria, Thermus aquaticus, which lives in hot springs and hydrothermal vents. The fact that this enzyme could withstand typical protein-denaturing temperatures and function optimally around 75–80°C fortuitously set the stage for the development of PCR.

  By 1983, all of the ingredients to bake the molecular cake were sitting in the biological cupboard waiting to be assembled in the proper order. At that time, Nobel laureate Kary Mullis was working as a scientist for the Cetus Corporation trying to perfect oligonucleotide synthesis. Mullis stumbled upon the idea of amplifying segments of DNA using multiple rounds of replication and the two primer system—essentially modifying and expanding upon Sanger’s sequencing reaction. Mullis discovered that the temperatures for each step (melting, annealing, and extension) in the reaction would need to be painstakingly controlled by hand. In addition, he realized that since the reactions were using a non-thermostable DNA polymerase, fresh enzyme would need to be “spiked in” after each successive cycle.

  Mullis’ hard work and persistence paid off as the reaction was successful at amplifying a particular segment of DNA that was flanked by two opposing nucleotide primer molecules. Two years later, the Cetus team presented their work at the annual meeting of the American Society for Human Genetics, and the first mention of the method was published in Science that same year; however, that article did not go into detail about the specifics of the newly developed PCR method—a paper that would be rejected by roughly 15 journals and would not be published until 1987.

  Although scientists were a bit slow on the uptake for the new method, the researchers at Cetus were developing ways to improve upon the original assay. In 1986, the scientists substituted the original heat-liable DNA polymerase for the temperature-resistant Taq polymerase, removing the need to spike in enzyme and dramatically reducing errors while increasing sensitivity. A year later, PerkinElmer launched their creation of a thermal cycler, allowing scientists to regulate the heating and cooling parts of the PCR reaction with greater efficiency.

  Extremely soon after the introduction of Taq and the launch of the thermal cycler, the PCR reaction exploded exponentially among research laboratories and not only vaulted molecular biology to the pinnacle of researcher interests, it also launched a molecular diagnostics revolution that continues today and shows no signs of slowing down.

• Molecular Workhorse

  In the years since PCR first burst onto the scene, there have been a number of significant advancements to the technique that have widely improved the overall method. For example, in 1991, a new DNA polymerase from the hyperthermophilic bacteria Pyrococcus furiosus, or Pfu, was introduced as a high-fidelity alternative enzyme to Taq. Unlike Taq polymerase, Pfu has built in 3′ to 5′ exonuclease proofreading activity, which allows the enzyme to correct nucleotide incorporation errors on the fly—dramatically increasing base specificity, albeit at a reduced rate of amplification versusTaq.

  In 1995, two advancements were introduced to PCR users. The first, called antibody “hot-start” PCR, utilized an immunoglobulin molecule that is directed to the DNA polymerase and inhibits its activity until the first 95°C melt stage, denaturing the antibody and allowing the polymerase to become active. Although this process was effective in increasing the specificity of the PCR reaction, many researchers found that the technique was time consuming and often caused cross-contamination of samples.

  The second innovation introduced that year began another revolution for molecular biology and the PCR method. Real-time PCR, or quantitative PCR (qPCR), allowed researchers to quantitatively create DNA templates for PCR amplification from RNA transcripts through the use of the reverse-transcriptase enzyme and specifically incorporated fluorescent reporter dyes. The technique is still widely used by researchers to monitor gene expression extremely accurately. Over the past 20 years, many companies have spent many R&D dollars to create more accurate, higher throughput, and simple qPCR machines to meet researcher demands.

  With the advent of next-generation sequencing techniques—and the rise of techniques that started commanding the attention of more and more researchers—PCR machines and methods needed to evolve and modernize to keep pace. PCR remained the lynchpin in almost all the next-generation sequencing reactions that came along, but the traditional technique wasn’t nearly as precise as required.

  Digital PCR (dPCR) was introduced as a refinement of the conventional method, with the first real commercial system emerging around 2006. dPCR can be used to quantify directly and clonally amplify DNA or RNA.

  The apparatus carries out a single reaction within a sample. The sample, however, is separated into a large number of partitions. Moreover, the reaction is performed in each partition individually—allowing a more reliable measurement of nucleic acid content. Researchers often use this method for studying gene-sequence variations, such as copy number variants (CNV), point mutations, rare-sequence detection, and microRNA analysis, as well as for routine amplification of next-generation sequencing samples.

• Future of PCR: Better, Faster, Stronger!

  It is almost impossible to envision a future laboratory setting that wouldn’t utilize PCR in some fashion, especially due to the heavy reliance of next-generation sequencing techniques for accurate PCR samples and at the very least using the method as a simple amplification tool for creating DNA fragments of interest.

  Yet there is at least one new next-generation sequencing technique that can identify native DNA sequences without an amplification step—nanopore sequencing. Although this technique has performed well in many preliminary trials, it is in its relative infancy. It will probably undergo additional development lasting several years before it approaches large-scale adoption by researchers. Even then, PCR has become so engrained into daily laboratory life that to try to phase out the technique would be like asking molecular biologists to give up their pipettes or restriction enzymes.

  Most PCR equipment manufacturers continue to seek ways to improve the speed and sensitivity of their thermal cyclers, while biologists continue to look toward ways to genetically engineer better DNA polymerase molecules with even greater fidelity than their naturally occurring cousins. Whatever the new advancements are, and wherever they lead the life sciences field, you can count on us at GEN to continue to provide our readers with detailed information for another 35 years … at least!

   

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Big Data in Genomic Medicine

Posted in Bio Instrumentation in Experimental Life Sciences Research, Chemical Biology and its relations to Metabolic Disease, Chemical Genetics, Computational Biology/Systems and Bioinformatics, Genome Biology, Genomic Testing: Methodology for Diagnosis, Molecular Genetics & Pharmaceutical, Personalized and Precision Medicine & Genomic Research, Population Health Management, Genetics & Pharmaceutical, Statistical Methods for Research Evaluation, Technology Transfer: Biotech and Pharmaceutical, tagged Beth Israel Deaconess Medical Center, Big data, Digital pathology, DNA, DNA Sequencing, Harvard Medical School, Jim Golden, Laboratory News on December 17, 2012| 9 Comments »

Reporter: Larry H Bernstein, MD, FCAP

Image Source: Created by Noam Steiner Tomer 7/31/2020

Pathologists May Be Healthcare’s Rock Stars of Big Data in Genomic Medicine’s ’Third Wave’

Category: Digital Pathology, Instruments & Equipment, Laboratory Management and Operations, Laboratory News, Laboratory Operations, Laboratory Pathology, Management & Operations

Published: December 17 2012

Pathologists are positioned to be the primary interpreters of big data as genomic medicine further evolves

Pathologists and clinical laboratory managers may be surprised to learn that at least one data scientist has proclaimed pathologists the real big data rock stars of healthcare. The reason has to do with the shift in focus of genomic medicine from therapeutics and presymptomatic disease assessment to big data analytics.

In a recent posting published at Forbes.com, data scientist Jim Golden heralded the pronouncement of Harvard pathologist Mark S. Boguski, M.D., Ph.D., FACM. He declared that “The time of the $1,000 genome meme is over!”

DNA Sequencing Systems and the $1,000 Genome

Golden has designed, built, and programmed DNA sequencing devices. He apprenticed under the Human Genome program and spent 15 years working towards the $1,000 genome. “I’m a believer,” he blogged. “[That’s] why I was so intrigued [by Boguski’s remarks].

Boguski is Associate Professor of Pathology at the Center for Biomedical Informatics at Harvard Medical School and the Department of Pathology at Beth Israel Deaconess Medical Center. It was in a presentation at a healthcare conference in Boston that Boguski pronounced that it is time for the $1,000 genome to go.

Both Golden and Boguski acknowledged the benefits generated by the race to the $1,000 genome. Competition to be first to achieve this milestone motivated scientists and engineers to swiftly drive down the cost of decoding DNA. The result was a series of advances in instrumentation, chemistry, and biology.

Pathologists and Big Data Analytics

“Our notions about how genome science and technology would improve health and healthcare have changed,” Boguski wrote in an editorial published at Future Medicine. He then noted that the focus has shifted to big data analytics.

In the editorial, Boguski described the phases of development of genomic medicine as “waves.” The first wave occurred during the mid- to late-1990s. It focused on single- nucleotide polymorphisms (SNP) and therapeutics.

Medical Laboratories Have Opportunity to Perform Presymptomatic Testing

The second wave focused on presymptomatic testing for disease risk assessment and Genome Wide Association Studies (GWAS). Researchers expected this data to help manage common diseases.

The first two waves of medical genomics were conducted largely by the pharmaceutical industry, as well as with  primary care and public health communities, according to Boguski. Considerable optimism accompanied each wave of medical genomics.

“Despite the earlier optimism, progress in improving human health has been modest and incremental, rather than paradigm-shifting,” noted Boguski, who wrote that,to date, only a handful of genome-derived drugs have reached the market. He further observed that products such as direct-to-consumer genomic testing have proved more educational and recreational than medical.

“Third Wave” of Genomic Medicine

It was rapid declines in the cost of next-generation DNA sequencing technologies that now has triggered the third wave of genomic medicine. Its focus is postsymptomatic genotyping for individualized and optimized disease management.

“This is where genomics is likely to bring the most direct and sustained impact on healthcare for several reasons,” stated Boguski. “Genomics technologies enable disease diagnosis of sufficient precision to drive both cost-effective [patient] management and better patient outcomes. Thus, they are an essential part of the prescription for disruptive healthcare reform.”

Boguski reiterated the case for the value of laboratory medicine. He stated the following critical—but often overlooked—points, each of which is familiar to pathologists and clinical laboratory managers:

1. Pathologist-directed, licensed clinical laboratory testing has a major effect on clinical decision-making.

2. Medical laboratory testing services account for only about 2% of healthcare expenditures in the United States.

3. Medical laboratory services strongly influence the remaining 98% of costs through the information they provide on the prevention, diagnosis, treatment, and management of disease.

Molecular Diagnostics Reaching Maturity for Clinical Laboratory Testing

“Genome analytics are just another technology in the evolution of molecular diagnostics,” Boguski declared in his editorial.

Read more: Pathologists May Be Healthcare’s Rock Stars of Big Data in Genomic Medicine’s ’Third Wave’ | Dark Daily http://www.darkdaily.com/pathologists-may-be-healthcare%e2%80%99s-rock-stars-of-big-data-in-genomic-medicines-third-wave-1217#ixzz2FL24IRAA

English: Created by Abizar Lakdawalla. (Photo credit: Wikipedia)

English: Workflow for DNA nanoball sequencing (Photo credit: Wikipedia)

DNA sequence (Photo credit: Wikipedia)

Big Data: water wordscape (Photo credit: Marius B)

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• The Fast Changing Landscape of Sequencing Technologies and Their Impact on Microbial Genome Assemblies and Annotation (plosone.org)
• Stanford to rival Broad Institute with Big Data-focused genomics center (fiercebiotechit.com)
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Comment & Response

Right now the cost of the testing and the turnaround times are not favorable. It is going to take a decade or more for clinical labs to catch up. For some time it will be send out tests to Quest, LabCorp, and State or University lab consortia.

The power of the research technology is pushing this along, but for Personalized Medicine the testing should be coincident with the patient visit, and the best list of probable issues should be accessible on the report screen. The EHR industry is dominated by 2 companies that I see have no interest in meeting the needs of the physicians. The payback has to be on efficient workflow, accurate assessment of the record, and timely information. The focus for 25 years has been on billing structure. But even the revised billing codes (ICD10) can’t be less than 5 years out-of-date because of improvements in the knowledge base and improvements in applied math algorithms.

The medical record still may have information buried min a word heap, and the laboratory work is a go-to-you know where sheet with perhaps 15 variables on a page, with chemistry and hematology, immunology, blood bank, and microbiology on separate pages. The ability of the physician to fully digest the information with “errorless” discrimination is tested, and the stress imposed by the time for each patient compromises performance. There is work going on in moving proteomics along to a high throughput system for improved commercial viability, that was reported by Leigh Anderson a few years ago. The genomics is more difficult, but the genomics is partly moving to rapid micropanel tools.

In summary, there are 3 factors:

1. Automation and interpretation
2. Integration into the EHR in real time and usable by a physician.
3. The sorting out of the highest feature “predictors” and classifying them into clinically meaningful sets and subsets.

When this is done, then the next generation of recoding will be in demand.
The Automated Malnutrition Assessment
Gil David1, Larry Bernstein2, Ronald R. Coifman1

1Department of Mathematics, Program in Applied Mathematics,
Yale University, New Haven, CT 06510, USA,
2Triplex Consulting, Trumbull, CT 06611

Abstract

Introduction: We propose an automated nutritional assessment (ANA) algorithm that provides a method for malnutrition risk prediction with high accuracy and reliability.

Materials and Methods: The database used for this study is a file of 432 patients, where each patient is described by 4 laboratory parameters and 11 clinical parameters. A malnutrition risk assessment of low (1), moderate (2) or high (3) was assigned by a dietitian for each patient. An algorithm for data organization and classification via characteristic metrics is proposed. For each patient, the algorithm characterizes its unique profile and builds a characteristic metric to identify similar patients who are mapped into a classification.

Results: The algorithm assigned a malnutrition risk level for each patient based on different training sizes that were taken out of the data.

Our method resulted in an average error (distance between the automated score and the real score) of 0.386, 0.3507, 0.3454, 0.34 and 0.2907 for 10%, 30%, 50%, 70% and 90% training sizes, respectively.

Our method outperformed the compared method even when our method used a smaller training set then the compared method. In addition, we show that the laboratory parameters themselves are sufficient for the automated risk prediction and organize the patients into clusters that correspond to low, low-moderate, moderate, moderate-high and high risk areas.

Discussion: The problem of rapidly identifying risk and severity of malnutrition is crucial for minimizing medical and surgical complications. These are not easily performed or adequately expedited. We characterize for each patient a unique profile and map similar patients into a classification. We also find that the laboratory parameters themselves are sufficient for the automated risk prediction.

Keywords: Network Algorithm, unsupervised classification, malnutrition screening, protein energy malnutrition (PEM), malnutrition risk, characteristic metric, characteristic profile, data characterization, non-linear differential diagnosis.

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