Posts Tagged ‘HPV’

Clinical Laboratory Challenges

Larry H. Bernstein, MD, FCAP, Curator




The Lab and CJD: Safe Handling of Infectious Prion Proteins

Body fluids from individuals with possible Creutzfeldt-Jakob disease (CJD) present distinctive safety challenges for clinical laboratories. Sporadic, iatrogenic, and familial CJD (known collectively as classic CJD), along with variant CJD, kuru, Gerstmann-Sträussler-Scheinker, and fatal familial insomnia, are prion diseases, also known as transmissible spongiform encephalopathies. Prion diseases affect the central nervous system, and from the onset of symptoms follow a typically rapid progressive neurological decline. While prion diseases are rare, it is not uncommon for the most prevalent form—sporadic CJD—to be included in the differential diagnosis of individuals presenting with rapid cognitive decline. Thus, laboratories may deal with a significant number of possible CJD cases, and should have protocols in place to process specimens, even if a confirmatory diagnosis of CJD is made in only a fraction of these cases.

The Lab’s Role in Diagnosis

Laboratory protocols for handling specimens from individuals with possible, probable, and definitive cases of CJD are important to ensure timely and appropriate patient management. When the differential includes CJD, an attempt should be made to rule-in or out other causes of rapid neurological decline. Laboratories should be prepared to process blood and cerebrospinal fluid (CSF) specimens in such cases for routine analyses.

Definitive diagnosis requires identification of prion aggregates in brain tissue, which can be achieved by immunohistochemistry, a Western blot for proteinase K-resistant prions, and/or by the presence of prion fibrils. Thus, confirmatory diagnosis is typically achieved at autopsy. A probable diagnosis of CJD is supported by elevated concentration of 14-3-3 protein in CSF (a non-specific marker of neurodegeneration), EEG, and MRI findings. Thus, the laboratory may be required to process and send CSF samples to a prion surveillance center for 14-3-3 testing, as well as blood samples for sequencing of the PRNP gene (in inherited cases).

Processing Biofluids

Laboratories should follow standard protective measures when working with biofluids potentially containing abnormally folded prions, such as donning standard personal protective equipment (PPE); avoiding or minimizing the use of sharps; using single-use disposable items; and processing specimens to minimize formation of aerosols and droplets. An additional safety consideration is the use of single-use disposal PPE; otherwise, re-usable items must be either cleaned using prion-specific decontamination methods, or destroyed.

Blood. In experimental models, infectivity has been detected in the blood; however, there have been no cases of secondary transmission of classical CJD via blood product transfusions in humans. As such, blood has been classified, on epidemiological evidence by the World Health Organization (WHO), as containing “no detectible infectivity,” which means it can be processed by routine methods. Similarly, except for CSF, all other body fluids contain no infectivity and can be processed following standard procedures.

In contrast to classic CJD, there have been four cases of suspected secondary transmission of variant CJD via transfused blood products in the United Kingdom. Variant CJD, the prion disease associated with mad cow disease, is unique in its distribution of prion aggregates outside of the central nervous system, including the lymph nodes, spleen, and tonsils. For regions where variant CJD is a concern, laboratories should consult their regulatory agencies for further guidance.

CSF. Relative to highly infectious tissues of the brain, spinal cord, and eye, infectivity has been identified less often in CSF and is considered to have “low infectivity,” along with kidney, liver, and lung tissue. Since CSF can contain infectious material, WHO has recommended that analyses not be performed on automated equipment due to challenges associated with decontamination. Laboratories should perform a risk assessment of their CSF processes, and, if deemed necessary, consider using manual methods as an alternative to automated systems.


The infectious agent in prion disease is unlike any other infectious pathogen encountered in the laboratory; it is formed of misfolded and aggregated prion proteins. This aggregated proteinacious material forms the infectious unit, which is incredibly resilient to degradation. Moreover, in vitro studies have demonstrated that disrupting large aggregates into smaller aggregates increases cytotoxicity. Thus, if the aim is to abolish infectivity, all aggregates must be destroyed. Disinfectant procedures used for viral, bacterial, and fungal pathogens such as alcohol, boiling, formalin, dry heat (<300°C), autoclaving at 121°C for 15 minutes, and ionizing, ultraviolet, or microwave radiation, are either ineffective or variably effective against aggregated prions.

The only means to ensure no risk of residual infectious prions is to use disposable materials. This is not always practical, as, for instance, a biosafety cabinet cannot be discarded if there is a CSF spill in the hood. Fortunately, there are several protocols considered sufficient for decontamination. For surfaces and heat-sensitive instruments, such as a biosafety cabinet, WHO recommends flooding the surface with 2N NaOH or undiluted NaClO, letting stand for 1 hour, mopping up, and rinsing with water. If the surface cannot tolerate NaOH or NaClO, thorough cleaning will remove most infectivity by dilution. Laboratories may derive some additional benefit by using one of the partially effective methods discussed previously. Non-disposable heat-resistant items preferably should be immersed in 1N NaOH, heated in a gravity displacement autoclave at 121°C for 30 min, cleaned and rinsed in water, then sterilized by routine methods. WHO has outlined several alternate decontamination methods. Using disposable cover sheets is one simple solution to avoid contaminating work surfaces and associated lengthy decontamination procedures.

With standard PPE—augmented by a few additional safety measures and prion-specific decontamination procedures—laboratories can safely manage biofluid testing in cases of prion disease.


The Microscopic World Inside Us  

Emerging Research Points to Microbiome’s Role in Health and Disease

Thousands of species of microbes—bacteria, viruses, fungi, and protozoa—inhabit every internal and external surface of the human body. Collectively, these microbes, known as the microbiome, outnumber the body’s human cells by about 10 to 1 and include more than 1,000 species of microorganisms and several million genes residing in the skin, respiratory system, urogenital, and gastrointestinal tracts. The microbiome’s complicated relationship with its human host is increasingly considered so crucial to health that researchers sometimes call it “the forgotten organ.”

Disturbances to the microbiome can arise from nutritional deficiencies, antibiotic use, and antiseptic modern life. Imbalances in the microbiome’s diverse microbial communities, which interact constantly with cells in the human body, may contribute to chronic health conditions, including diabetes, asthma and allergies, obesity and the metabolic syndrome, digestive disorders including irritable bowel syndrome (IBS), and autoimmune disorders like multiple sclerosis and rheumatoid arthritis, research shows.

While study of the microbiome is a growing research enterprise that has attracted enthusiastic media attention and venture capital, its findings are largely preliminary. But some laboratorians are already developing a greater appreciation for the microbiome’s contributions to human biochemistry and are considering a future in which they expect to measure changes in the microbiome to monitor disease and inform clinical practice.

Pivot Toward the Microbiome

Following the National Institutes of Health (NIH) Human Genome Project, many scientists noted the considerable genetic signal from microbes in the body and the existence of technology to analyze these microorganisms. That realization led NIH to establish the Human Microbiome Project in 2007, said Lita Proctor, PhD, its program director. In the project’s first phase, researchers studied healthy adults to produce a reference set of microbiomes and a resource of metagenomic sequences of bacteria in the airways, skin, oral cavities, and the gastrointestinal and vaginal tracts, plus a catalog of microbial genome sequences of reference strains. Researchers also evaluated specific diseases associated with disturbances in the microbiome, including gastrointestinal diseases such as Crohn’s disease, ulcerative colitis, IBS, and obesity, as well as urogenital conditions, those that involve the reproductive system, and skin diseases like eczema, psoriasis, and acne.

Phase 1 studies determined the composition of many parts of the microbiome, but did not define how that composition affects health or specific disease. The project’s second phase aims to “answer the question of what microbes actually do,” explained Proctor. Researchers are now examining properties of the microbiome including gene expression, protein, and human and microbial metabolite profiles in studies of pregnant women at risk for preterm birth, the gut hormones of patients at risk for IBS, and nasal microbiomes of patients at risk for type 2 diabetes.

Promising Lines of Research

Cystic fibrosis and microbiology investigator Michael Surette, PhD, sees promising microbiome research not just in terms of evidence of its effects on specific diseases, but also in what drives changes in the microbiome. Surette is Canada research chair in interdisciplinary microbiome research in the Farncombe Family Digestive Health Research Institute at McMaster University
in Hamilton, Ontario.

One type of study on factors driving microbiome change examines how alterations in composition and imbalances in individual patients relate to improving or worsening disease. “IBS, cystic fibrosis, and chronic obstructive pulmonary disease all have periods of instability or exacerbation,” he noted. Surette hopes that one day, tests will provide clinicians the ability to monitor changes in microbial composition over time and even predict when a patient’s condition is about to deteriorate. Monitoring perturbations to the gut microbiome might also help minimize collateral damage to the microbiome during aggressive antibiotic therapy for hospitalized patients, he added.

Monitoring changes to the microbiome also might be helpful for “culture negative” patients, who now may receive multiple, unsuccessful courses of different antibiotics that drive antibiotic resistance. Frustration with standard clinical biology diagnosis of lung infections in cystic fibrosis patients first sparked Surette’s investigations into the microbiome. He hopes that future tests involving the microbiome might also help asthma patients with neutrophilia, community-acquired pneumonia patients who harbor complex microbial lung communities lacking obvious pathogens, and hospitalized patients with pneumonia or sepsis. He envisions microbiome testing that would look for short-term changes indicating whether or not a drug is effective.

Companion Diagnostics

Daniel Peterson, MD, PhD, an assistant professor of pathology at Johns Hopkins University School of Medicine in Baltimore, believes the future of clinical testing involving the microbiome lies in companion diagnostics for novel treatments, and points to companies that are already developing and marketing tests that will require such assays.

Examples of microbiome-focused enterprises abound, including Genetic Analysis, based in Oslo, Norway, with its high-throughput test that uses 54 probes targeted to specific bacteria to measure intestinal gut flora imbalances in inflammatory bowel disease and irritable bowel syndrome patients. Paris, France-based Enterome is developing both novel drugs and companion diagnostics for microbiome-related diseases such as IBS and some metabolic diseases. Second Genome, based in South San Francisco, has developed an experimental drug, SGM-1019, that the company says blocks damaging activity of the microbiome in the intestine. Cambridge, Massachusetts-based Seres Therapeutics has received Food and Drug Administration orphan drug designation for SER-109, an oral therapeutic intended to correct microbial imbalances to prevent recurrent Clostridium difficile infection in adults.

One promising clinical use of the microbiome is fecal transplantation, which both prospective and retrospective studies have shown to be effective in patients with C. difficile infections who do not respond to front-line therapies, said James Versalovic, MD, PhD, director of Texas Children’s Hospital Microbiome Center and professor of pathology at Baylor College of Medicine in Houston. “Fecal transplants and other microbiome replacement strategies can radically change the composition of the microbiome in hours to days,” he explained.

But NIH’s Proctor discourages too much enthusiasm about fecal transplant. “Natural products like stool can have [side] effects,” she pointed out. “The [microbiome research] field needs to mature and we need to verify outcomes before anything becomes routine.”

Hurdles for Lab Testing

While he is hopeful that labs someday will use the microbiome to produce clinically useful information, Surette pointed to several problems that must be solved beforehand. First, molecular methods commonly used right now should be more quantitative and accurate. Additionally, research on the microbiome encompasses a wide variety of protocols, some of which are better at extracting particular types of bacteria and therefore can give biased views of communities living in the body. Also, tests may need to distinguish between dead and live microbes. Another hurdle is that labs using varied bioinfomatic methods may produce different results from the same sample, a problem that Surette sees as ripe for a solution from clinical laboratorians, who have expertise in standardizing robust protocols and in automating tests.

One way laboratorians can prepare for future, routine microbiome testing is to expand their notion of clinical chemistry to include both microbial and human biochemistry. “The line between microbiome science and clinical science is blurring,” said Versalovic. “When developing future assays to detect biochemical changes in disease states, we must consider the contributions of microbial metabolites and proteins and how to tailor tests to detect them.” In the future, clinical labs may test for uniquely microbial metabolites in various disease states, he predicted.


Automated Review of Mass Spectrometry Results  

Can We Achieve Autoverification?

Author: Katherine Alexander and Andrea R. Terrell, PhD  // Date: NOV.1.2015  // Source:Clinical Laboratory News


Paralleling the upswing in prescription drug misuse, clinical laboratories are receiving more requests for mass spectrometry (MS) testing as physicians rely on its specificity to monitor patient compliance with prescription regimens. However, as volume has increased, reimbursement has declined, forcing toxicology laboratories both to increase capacity and lower their operational costs—without sacrificing quality or turnaround time. Now, new solutions are available enabling laboratories to bring automation to MS testing and helping them with the growing demand for toxicology and other testing.

What is the typical MS workflow?

A typical workflow includes a long list of manual steps. By the time a sample is loaded onto the mass spectrometer, it has been collected, logged into the lab information management system (LIMS), and prepared for analysis using a variety of wet chemistry techniques.

Most commercial clinical laboratories receive enough samples for MS analysis to batch analyze those samples. A batch consists of a calibrator(s), quality control (QC) samples, and patient/donor samples. Historically, the method would be selected (i.e. “analysis of opiates”), sample identification information would be entered manually into the MS software, and the instrument would begin analyzing each sample. Upon successful completion of the batch, the MS operator would view all of the analytical data, ensure the QC results were acceptable, and review each patient/donor specimen, looking at characteristics such as peak shape, ion ratios, retention time, and calculated concentration.

The operator would then post acceptable results into the LIMS manually or through an interface, and unacceptable results would be rescheduled or dealt with according to lab-specific protocols. In our laboratory we perform a final certification step for quality assurance by reviewing all information about the batch again, prior to releasing results for final reporting through the LIMS.

What problems are associated with this workflow?

The workflow described above results in too many highly trained chemists performing manual data entry and reviewing perfectly acceptable analytical results. Lab managers would prefer that MS operators and certifying scientists focus on troubleshooting problem samples rather than reviewing mounds of good data. Not only is the current process inefficient, it is mundane work prone to user errors. This risks fatigue, disengagement, and complacency by our highly skilled scientists.

Importantly, manual processes also take time. In most clinical lab environments, turnaround time is critical for patient care and industry competitiveness. Lab directors and managers are looking for solutions to automate mundane, error-prone tasks to save time and costs, reduce staff burnout, and maintain high levels of quality.

How can software automate data transfer from MS systems to LIMS?

Automation is not a new concept in the clinical lab. Labs have automated processes in shipping and receiving, sample preparation, liquid handling, and data delivery to the end user. As more labs implement MS, companies have begun to develop special software to automate data analysis and review workflows.

In July 2011, AIT Labs incorporated ASCENT into our workflow, eliminating the initial manual peak review step. ASCENT is an algorithm-based peak picking and data review system designed specifically for chromatographic data. The software employs robust statistical and modeling approaches to the raw instrument data to present the true signal, which often can be obscured by noise or matrix components.

The system also uses an exponentially modified Gaussian (EMG) equation to apply a best-fit model to integrated peaks through what is often a noisy signal. In our experience, applying the EMG results in cleaner data from what might appear to be poor chromatography ultimately allows us to reduce the number of samples we might otherwise rerun.

How do you validate the quality of results?

We’ve developed a robust validation protocol to ensure that results are, at minimum, equivalent to results from our manual review. We begin by building the assay in ASCENT, entering assay-specific information from our internal standard operating procedure (SOP). Once the assay is configured, validation proceeds with parallel batch processing to compare results between software-reviewed data and staff-reviewed data. For new implementations we run eight to nine batches of 30–40 samples each; when we are modifying or upgrading an existing implementation we run a smaller number of batches. The parallel batches should contain multiple positive and negative results for all analytes in the method, preferably spanning the analytical measurement range of the assay.

The next step is to compare the results and calculate the percent difference between the data review methods. We require that two-thirds of the automated results fall within 20% of the manually reviewed result. In addition to validating patient sample correlation, we also test numerous quality assurance rules that should initiate a flag for further review.

What are the biggest challenges during implementation and continual improvement initiatives?

On the technological side, our largest hurdle was loading the sequence files into ASCENT. We had created an in-house mechanism for our chemists to upload the 96-well plate map for their batch into the MS software. We had some difficulty transferring this information to ASCENT, but once we resolved this issue, the technical workflow proceeded fairly smoothly.

The greater challenge was changing our employees’ mindset from one of fear that automation would displace them, to a realization that learning this new technology would actually make them more valuable. Automating a non-mechanical process can be a difficult concept for hands-on scientists, so managers must be patient and help their employees understand that this kind of technology leverages the best attributes of software and people to create a powerful partnership.

We recommend that labs considering automated data analysis engage staff in the validation and implementation to spread the workload and the knowledge. As is true with most technology, it is best not to rely on just one or two super users. We also found it critical to add supervisor level controls on data file manipulation, such as removing a sample that wasn’t run from the sequence table. This can prevent inadvertent deletion of a file, requiring reinjection of the entire batch!


Understanding Fibroblast Growth Factor 23

Author: Damien Gruson, PhD  // Date: OCT.1.2015  // Source: Clinical Laboratory News

What is the relationship of FGF-23 to heart failure?

A Heart failure (HF) is an increasingly common syndrome associated with high morbidity, elevated hospital readmission rates, and high mortality. Improving diagnosis, prognosis, and treatment of HF requires a better understanding of its different sub-phenotypes. As researchers gained a comprehensive understanding of neurohormonal activation—one of the hallmarks of HF—they discovered several biomarkers, including natriuretic peptides, which now are playing an important role in sub-phenotyping HF and in driving more personalized management of this chronic condition.

Like the natriuretic peptides, fibroblast growth factor 23 (FGF-23) could become important in risk-stratifying and managing HF patients. Produced by osteocytes, FGF-23 is a key regulator of phosphorus homeostasis. It binds to renal and parathyroid FGF-Klotho receptor heterodimers, resulting in phosphate excretion, decreased 1-α-hydroxylation of 25-hydroxyvitamin D, and decreased parathyroid hormone (PTH) secretion. The relationship to PTH is important because impaired homeostasis of cations and decreased glomerular filtration rate might contribute to the rise of FGF-23. The amino-terminal portion of FGF-23 (amino acids 1-24) serves as a signal peptide allowing secretion into the blood, and the carboxyl-terminal portion (aa 180-251) participates in its biological action.

How might FGF-23 improve HF risk assessment?

Studies have shown that FGF-23 is related to the risk of cardiovascular diseases and mortality. It was first demonstrated that FGF-23 levels were independently associated with left ventricular mass index and hypertrophy as well as mortality in patients with chronic kidney disease (CKD). FGF-23 also has been associated with left ventricular dysfunction and atrial fibrillation in coronary artery disease subjects, even in the absence of impaired renal function.

FGF-23 and FGF receptors are both expressed in the myocardium. It is possible that FGF-23 has direct effects on the heart and participates in the physiopathology of cardiovascular diseases and HF. Experiments have shown that for in vitro cultured rat cardiomyocytes, FGF-23 stimulates pathological hypertrophy by activating the calcineurin-NFAT pathway—and in wild-type mice—the intra-myocardial or intravenous injection of FGF-23 resulted in left ventricular hypertrophy. As such, FGF-23 appears to be a potential stimulus of myocardial hypertrophy, and increased levels may contribute to the worsening of heart failure and long-term cardiovascular death.

Researchers have documented that HF patients have elevated FGF-23 circulating levels. They have also found a significant correlation between plasma levels of FGF-23 and B-type natriuretic peptide, a biomarker related to ventricular stretch and cardiac hypertrophy, in patients with left ventricular hypertrophy. As such, measuring FGF-23 levels might be a useful tool to predict long-term adverse cardiovascular events in HF patients.

Interestingly, researchers have documented a significant relationship between FGF-23 and PTH in both CKD and HF patients. As PTH stimulates FGF-23 expression, it could be that in HF patients, increased PTH levels increase the bone expression of FGF-23, which enhances its effects on the heart.


The Past, Present, and Future of Western Blotting in the Clinical Laboratory

Author: Curtis Balmer, PhD  // Date: OCT.1.2015  // Source: Clinical Laboratory News

Much of the discussion about Western blotting centers around its performance as a biological research tool. This isn’t surprising. Since its introduction in the late 1970s, the Western blot has been adopted by biology labs of virtually every stripe, and become one of the most widely used techniques in the research armamentarium. However, Western blotting has also been employed in clinical laboratories to aid in the diagnosis of various diseases and disorders—an equally important and valuable application. Yet there has been relatively little discussion of its use in this context, or of how advances in Western blotting might affect its future clinical use.

Highlighting the clinical value of Western blotting, Stanley Naides, MD, medical director of Immunology at Quest Diagnostics observed that, “Western blotting has been a very powerful tool in the laboratory and for clinical diagnosis. It’s one of many various methods that the laboratorian brings to aid the clinician in the diagnosis of disease, and the selection and monitoring of therapy.” Indeed, Western blotting has been used at one time or the other to aid in the diagnosis of infectious diseases including hepatitis C (HCV), HIV, Lyme disease, and syphilis, as well as autoimmune disorders such as paraneoplastic disease and myositis conditions.

However, Naides was quick to point out that the choice of assays to use clinically is based on their demonstrated sensitivity and performance, and that the search for something better is never-ending. “We’re constantly looking for methods that improve detection of our target [protein],” Naides said. “There have been a number of instances where we’ve moved away from Western blotting because another method proves to be more sensitive.” But this search can also lead back to Western blotting. “We’ve gone away from other methods because there’s been a Western blot that’s been developed that’s more sensitive and specific. There’s that constant movement between methods as new tests are developed.”

In recent years, this quest has been leading clinical laboratories away from Western blotting toward more sensitive and specific diagnostic assays, at least for some diseases. Using confirmatory diagnosis of HCV infection as an example, Sai Patibandla, PhD, director of the immunoassay group at Siemens Healthcare Diagnostics, explained that movement away from Western blotting for confirmatory diagnosis of HCV infection began with a technical modification called Recombinant Immunoblotting Assay (RIBA). RIBA streamlines the conventional Western blot protocol by spotting recombinant antigen onto strips which are used to screen patient samples for antibodies against HCV. This approach eliminates the need to separate proteins and transfer them onto a membrane.

The RIBA HCV assay was initially manufactured by Chiron Corporation (acquired by Novartics Vaccines and Diagnostics in 2006). It received Food and Drug Administration (FDA) approval in 1999, and was marketed as Chiron RIBA HCV 3.0 Strip Immunoblot Assay. Patibandla explained that, at the time, the Chiron assay “…was the only FDA-approved confirmatory testing for HCV.” In 2013 the assay was discontinued and withdrawn from the market due to reports that it was producing false-positive results.

Since then, clinical laboratories have continued to move away from Western blot-based assays for confirmation of HCV in favor of the more sensitive technique of nucleic acid testing (NAT). “The migration is toward NAT for confirmation of HCV [diagnosis]. We don’t use immunoblots anymore. We don’t even have a blot now to confirm HCV,” Patibandla said.

Confirming HIV infection has followed a similar path. Indeed, in 2014 the Centers for Disease Control and Prevention issued updated recommendations for HIV testing that, in part, replaced Western blotting with NAT. This change was in response to the recognition that the HIV-1 Western blot assay was producing false-negative or indeterminable results early in the course of HIV infection.

At this juncture it is difficult to predict if this trend away from Western blotting in clinical laboratories will continue. One thing that is certain, however, is that clinicians and laboratorians are infinitely pragmatic, and will eagerly replace current techniques with ones shown to be more sensitive, specific, and effective. This raises the question of whether any of the many efforts currently underway to improve Western blotting will produce an assay that exceeds the sensitivity of currently employed techniques such as NAT.

Some of the most exciting and groundbreaking work in this area is being done by Amy Herr, PhD, a professor of bioengineering at University of California, Berkeley. Herr’s group has taken on some of the most challenging limitations of Western blotting, and is developing techniques that could revolutionize the assay. For example, the Western blot is semi-quantitative at best. This weakness dramatically limits the types of answers it can provide about changes in protein concentrations under various conditions.

To make Western blotting more quantitative, Herr’s group is, among other things, identifying losses of protein sample mass during the assay protocol. About this, Herr explains that the conventional Western blot is an “open system” that involves lots of handling of assay materials, buffers, and reagents that makes it difficult to account for protein losses. Or, as Kevin Lowitz, a senior product manager at Thermo Fisher Scientific, described it, “Western blot is a [simple] technique, but a really laborious one, and there are just so many steps and so many opportunities to mess it up.”

Herr’s approach is to reduce the open aspects of Western blot. “We’ve been developing these more closed systems that allow us at each stage of the assay to account for [protein mass] losses. We can’t do this exactly for every target of interest, but it gives us a really good handle [on protein mass losses],” she said. One of the major mechanisms Herr’s lab is using to accomplish this is to secure proteins to the blot matrix with covalent bonding rather than with the much weaker hydrophobic interactions that typically keep the proteins in place on the membrane.

Herr’s group also has been developing microfluidic platforms that allow Western blotting to be done on single cells, “In our system we’re doing thousands of independent Westerns on single cells in four hours. And, hopefully, we’ll cut that down to one hour over the next couple years.”

Other exciting modifications that stand to dramatically increase the sensitivity, quantitation, and through-put of Western blotting also are being developed and explored. For example, the use of capillary electrophoresis—in which proteins are conveyed through a small electrolyte-filled tube and separated according to size and charge before being dropped onto a blotting membrane—dramatically reduces the amount of protein required for Western blot analysis, and thereby allows Westerns to be run on proteins from rare cells or for which quantities of sample are extremely limited.

Jillian Silva, PhD, an associate specialist at the University of California, San Francisco Helen Diller Family Comprehensive Cancer Center, explained that advances in detection are also extending the capabilities of Western blotting. “With the advent of fluorescence detection we have a way to quantitate Westerns, and it is now more quantitative than it’s ever been,” said Silva.

Whether or not these advances produce an assay that is adopted by clinical laboratories remains to be seen. The emphasis on Western blotting as a research rather than a clinical tool may bias advances in favor of the needs and priorities of researchers rather than clinicians, and as Patibandla pointed out, “In the research world Western blotting has a certain purpose. [Researchers] are always coming up with new things, and are trying to nail down new proteins, so you cannot take Western blotting away.” In contrast, she suggested that for now, clinical uses of Western blotting remain “limited.”


Adapting Next Generation Technologies to Clinical Molecular Oncology Service

Author: Ronald Carter, PhD, DVM  // Date: OCT.1.2015  // Source: Clinical Laboratory News

Next generation technologies (NGT) deliver huge improvements in cost efficiency, accuracy, robustness, and in the amount of information they provide. Microarrays, high-throughput sequencing platforms, digital droplet PCR, and other technologies all offer unique combinations of desirable performance.

As stronger evidence of genetic testing’s clinical utility influences patterns of patient care, demand for NGT testing is increasing. This presents several challenges to clinical laboratories, including increased urgency, clinical importance, and breadth of application in molecular oncology, as well as more integration of genetic tests into synoptic reporting. Laboratories need to add NGT-based protocols while still providing old tests, and the pace of change is increasing.What follows is one viewpoint on the major challenges in adopting NGTs into diagnostic molecular oncology service.

Choosing a Platform

Instrument selection is a critical decision that has to align with intended test applications, sequencing chemistries, and analytical software. Although multiple platforms are available, a mainstream standard has not emerged. Depending on their goals, laboratories might set up NGTs for improved accuracy of mutation detection, massively higher sequencing capacity per test, massively more targets combined in one test (multiplexing), greater range in sequencing read length, much lower cost per base pair assessed, and economy of specimen volume.

When high-throughput instruments first made their appearance, laboratories paid more attention to the accuracy of base-reading: Less accurate sequencing meant more data cleaning and resequencing (1). Now, new instrument designs have narrowed the differences, and test chemistry can have a comparatively large impact on analytical accuracy (Figure 1). The robustness of technical performance can also vary significantly depending upon specimen type. For example, LifeTechnologies’ sequencing platforms appear to be comparatively more tolerant of low DNA quality and concentration, which is an important consideration for fixed and processed tissues.

Figure 1 Comparison of Sequencing Chemistries

Sequence pile-ups of the same target sequence (2 large genes), all performed on the same analytical instrument. Results from 4 different chemistries, as designed and supplied by reagent manufacturers prior to optimization in the laboratory. Red lines represent limits of exons. Height of blue columns proportional to depth of coverage. In this case, the intent of the test design was to provide high depth of coverage so that reflex Sanger sequencing would not be necessary. Courtesy B. Sadikovic, U. of Western Ontario.


In addition, batching, robotics, workload volume patterns, maintenance contracts, software licenses, and platform lifetime affect the cost per analyte and per specimen considerably. Royalties and reagent contracts also factor into the cost of operating NGT: In some applications, fees for intellectual property can represent more than 50% of the bench cost of performing a given test, and increase substantially without warning.

Laboratories must also deal with the problem of obsolescence. Investing in a new platform brings the angst of knowing that better machines and chemistries are just around the corner. Laboratories are buying bigger pieces of equipment with shorter service lives. Before NGTs, major instruments could confidently be expected to remain current for at least 6 to 8 years. Now, a major instrument is obsolete much sooner, often within 2 to 3 years. This means that keeping it in service might cost more than investing in a new platform. Lease-purchase arrangements help mitigate year-to-year fluctuations in capital equipment costs, and maximize the value of old equipment at resale.

One Size Still Does Not Fit All

Laboratories face numerous technical considerations to optimize sequencing protocols, but the test has to be matched to the performance criteria needed for the clinical indication (2). For example, measuring response to treatment depends first upon the diagnostic recognition of mutation(s) in the tumor clone; the marker(s) then have to be quantifiable and indicative of tumor volume throughout the course of disease (Table 1).

As a result, diagnostic tests need to cover many different potential mutations, yet accurately identify any clinically relevant mutations actually present. On the other hand, tests for residual disease need to provide standardized, sensitive, and accurate quantification of a selected marker mutation against the normal background. A diagnostic panel might need 1% to 3% sensitivity across many different mutations. But quantifying early response to induction—and later assessment of minimal residual disease—needs a test that is reliably accurate to the 10-4 or 10-5 range for a specific analyte.

Covering all types of mutations in one diagnostic test is not yet possible. For example, subtyping of acute myeloid leukemia is both old school (karyotype, fluorescent in situ hybridization, and/or PCR-based or array-based testing for fusion rearrangements, deletions, and segmental gains) and new school (NGT-based panel testing for molecular mutations).

Chemistries that cover both structural variants and copy number variants are not yet in general use, but the advantages of NGTs compared to traditional methods are becoming clearer, such as in colorectal cancer (3). Researchers are also using cell-free DNA (cfDNA) to quantify residual disease and detect resistance mutations (4). Once a clinically significant clone is identified, enrichment techniques help enable extremely sensitive quantification of residual disease (5).

Validation and Quality Assurance

Beyond choosing a platform, two distinct challenges arise in bringing NGTs into the lab. The first is assembling the resources for validation and quality assurance. The second is keeping tests up-to-date as new analytes are needed. Even if a given test chemistry has the flexibility to add analytes without revalidating the entire panel, keeping up with clinical advances is a constant priority.

Due to their throughput and multiplexing capacities, NGT platforms typically require considerable upfront investment to adopt, and training staff to perform testing takes even more time. Proper validation is harder to document: Assembling positive controls, documenting test performance criteria, developing quality assurance protocols, and conducting proficiency testing are all demanding. Labs meet these challenges in different ways. Laboratory-developed tests (LDTs) allow self-determined choice in design, innovation, and control of the test protocol, but can be very expensive to set up.

Food and Drug Administration (FDA)-approved methods are attractive but not always an option. More FDA-approved methods will be marketed, but FDA approval itself brings other trade-offs. There is a cost premium compared to LDTs, and the test methodologies are locked down and not modifiable. This is particularly frustrating for NGTs, which have the specific attraction of extensive multiplexing capacity and accommodating new analytes.

IT and the Evolution of Molecular Oncology Reporting Standards

The options for information technology (IT) pipelines for NGTs are improving rapidly. At the same time, recent studies still show significant inconsistencies and lack of reproducibility when it comes to interpreting variants in array comparative genomic hybridization, panel testing, tumor expression profiling, and tumor genome sequencing. It can be difficult to duplicate published performances in clinical studies because of a lack of sufficient information about the protocol (chemistry) and software. Building bioinformatics capacity is a key requirement, yet skilled people are in short supply and the qualifications needed to work as a bioinformatician in a clinical service are not yet clearly defined.

Tumor biology brings another level of complexity. Bioinformatic analysis must distinguish tumor-specific­ variants from genomic variants. Sequencing of paired normal tissue is often performed as a control, but virtual normal controls may have intriguing advantages (6). One of the biggest challenges is to reproducibly interpret the clinical significance of interactions between different mutations, even with commonly known, well-defined mutations (7). For multiple analyte panels, such as predictive testing for breast cancer, only the performance of the whole panel in a population of patients can be compared; individual patients may be scored into different risk categories by different tests, all for the same test indication.

In large scale sequencing of tumor genomes, which types of mutations are most informative in detecting, quantifying, and predicting the behavior of the tumor over time? The amount and complexity of mutation varies considerably across different tumor types, and while some mutations are more common, stable, and clinically informative than others, the utility of a given tumor marker varies in different clinical situations. And, for a given tumor, treatment effect and metastasis leads to retesting for changes in drug sensitivities.

These complexities mean that IT must be designed into the process from the beginning. Like robotics, IT represents a major ancillary decision. One approach many labs choose is licensed technologies with shared databases that are updated in real time. These are attractive, despite their cost and licensing fees. New tests that incorporate proprietary IT with NGT platforms link the genetic signatures of tumors to clinically significant considerations like tumor classification, recommended methodologies for monitoring response, predicted drug sensitivities, eligible clinical trials, and prognostic classifications. In-house development of such solutions will be difficult, so licensing platforms from commercial partners is more likely to be the norm.

The Commercial Value of Health Records and Test Data

The future of cancer management likely rests on large-scale databases that link hereditary and somatic tumor testing with clinical outcomes. Multiple centers have such large studies underway, and data extraction and analysis is providing increasingly refined interpretations of clinical significance.

Extracting health outcomes to correlate with molecular test results is commercially valuable, as the pharmaceutical, insurance, and healthcare sectors focus on companion diagnostics, precision medicine, and evidence-based health technology assessment. Laboratories that can develop tests based on large-scale integration of test results to clinical utility will have an advantage.

NGTs do offer opportunities for net reductions in the cost of healthcare. But the lag between availability of a test and peer-evaluated demon­stration of clinical utility can be considerable. Technical developments arise faster than evidence of clinical utility. For example, immuno­histochemistry, estrogen receptor/progesterone receptor status, HER2/neu, and histology are still the major pathological criteria for prognostic evaluation of breast cancer at diagnosis, even though multiple analyte tumor profiling has been described for more than 15 years. Healthcare systems need a more concerted assessment of clinical utility if they are to take advantage of the promises of NGTs in cancer care.

Disruptive Advances

Without a doubt, “disruptive” is an appropriate buzzword in molecular oncology, and new technical advances are about to change how, where, and for whom testing is performed.

• Predictive Testing

Besides cost per analyte, one of the drivers for taking up new technologies is that they enable multiplexing many more analytes with less biopsy material. Single-analyte sequential testing for epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase, and other targets on small biopsies is not sustainable when many more analytes are needed, and even now, a significant proportion of test requests cannot be completed due to lack of suitable biopsy material. Large panels incorporating all the mutations needed to cover multiple tumor types are replacing individual tests in companion diagnostics.

• Cell-Free Tumor DNA

Challenges of cfDNA include standardizing the collection and processing methodologies, timing sampling to minimize the effect of therapeutic toxicity on analytical accuracy, and identifying the most informative sample (DNA, RNA, or protein). But for more and more tumor types, it will be possible to differentiate benign versus malignant lesions, perform molecular subtyping, predict response, monitor treatment, or screen for early detection—all without a surgical biopsy.

cfDNA technologies can also be integrated into core laboratory instrumentation. For example, blood-based EGFR analysis for lung cancer is being developed on the Roche cobas 4800 platform, which will be a significant change from the current standard of testing based upon single tests of DNA extracted from formalin-fixed, paraffin-embedded sections selected by a pathologist (8).

• Whole Genome and Whole Exome Sequencing

Whole genome and whole exome tumor sequencing approaches provide a wealth of biologically important information, and will replace individual or multiple gene test panels as the technical cost of sequencing declines and interpretive accuracy improves (9). Laboratories can apply informatics selectively or broadly to extract much more information at relatively little increase in cost, and the interpretation of individual analytes will be improved by the context of the whole sequence.

• Minimal Residual Disease Testing

Massive resequencing and enrichment techniques can be used to detect minimal residual disease, and will provide an alternative to flow cytometry as costs decline. The challenge is to develop robust analytical platforms that can reliably produce results in a high proportion of patients with a given tumor type, despite using post-treatment specimens with therapy-induced degradation, and a very low proportion of target (tumor) sequence to benign background sequence.

The tumor markers should remain informative for the burden of disease despite clonal evolution over the course of multiple samples taken during progression of the clinical course and treatment. Quantification needs to be accurate and sensitive down to the 10-5 range, and cost competitive with flow cytometry.

• Point-of-Care Test Methodologies

Small, rapid, cheap, and single use point-of-care (POC) sequencing devices are coming. Some can multiplex with analytical times as short as 20 minutes. Accurate and timely testing will be possible in places like pharmacies, oncology clinics, patient service centers, and outreach programs. Whether physicians will trust and act on POC results alone, or will require confirmation by traditional laboratory-based testing, remains to be seen. However, in the simplest type of application, such as a patient known to have a particular mutation, the advantages of POC-based testing to quantify residual tumor burden are clear.


Molecular oncology is moving rapidly from an esoteric niche of diagnostics to a mainstream, required component of integrated clinical laboratory services. While NGTs are markedly reducing the cost per analyte and per specimen, and will certainly broaden the scope and volume of testing performed, the resources required to choose, install, and validate these new technologies are daunting for smaller labs. More rapid obsolescence and increased regulatory scrutiny for LDTs also present significant challenges. Aligning test capacity with approved clinical indications will require careful and constant attention to ensure competitiveness.


1. Liu L, Li Y, Li S, et al. Comparison of next-generation sequencing systems. J Biomed Biotechnol 2012; doi:10.1155/2012/251364.

2. Brownstein CA, Beggs AH, Homer N, et al. An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge. Genome Biol 2014;15:R53.

3. Haley L, Tseng LH, Zheng G, et al. Performance characteristics of next-generation sequencing in clinical mutation detection of colorectal ­cancers. [Epub ahead of print] Modern Pathol July 31, 2015 as doi:10.1038/modpathol.2015.86.

4. Butler TM, Johnson-Camacho K, Peto M, et al. Exome sequencing of cell-free DNA from metastatic cancer patients identifies clinically actionable mutations distinct from primary ­disease. PLoS One 2015;10:e0136407.

5. Castellanos-Rizaldos E, Milbury CA, Guha M, et al. COLD-PCR enriches low-level variant DNA sequences and increases the sensitivity of genetic testing. Methods Mol Biol 2014;1102:623–39.

6. Hiltemann S, Jenster G, Trapman J, et al. Discriminating somatic and germline mutations in tumor DNA samples without matching normals. Genome Res 2015;25:1382–90.

7. Lammers PE, Lovly CM, Horn L. A patient with metastatic lung adenocarcinoma harboring concurrent EGFR L858R, EGFR germline T790M, and PIK3CA mutations: The challenge of interpreting results of comprehensive mutational testing in lung cancer. J Natl Compr Canc Netw 2015;12:6–11.

8. Weber B, Meldgaard P, Hager H, et al. Detection of EGFR mutations in plasma and biopsies from non-small cell lung cancer patients by allele-specific PCR assays. BMC Cancer 2014;14:294.

9. Vogelstein B, Papadopoulos N, Velculescu VE, et al. Cancer genome landscapes. Science 2013;339:1546–58.

10. Heitzer E, Auer M, Gasch C, et al. Complex tumor genomes inferred from single circulating tumor cells by array-CGH and next-generation sequencing. Cancer Res 2013;73:2965–75.

11. Healy B. BRCA genes — Bookmaking, fortunetelling, and medical care. N Engl J Med 1997;336:1448–9.





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Pathology Insights

Larry H Bernstein, MD, FCAP, Curator



Predicting the Prognosis of Lung Cancer: The Evolution of Tumor, Node and Metastasis in the Molecular Age—Challenges and Opportunities

Ramón Rami-Porta; Hisao Asamura; Peter Goldstraw

Transl Lung Cancer Res. 2015;4(4):415-423.



The tumor, node and metastasis (TNM) classification of malignant tumors was proposed by Pierre Denoit in the mid-20th century to code the anatomic extent of tumors. Soon after, it was accepted by the Union for International Cancer Control and by the American Joint Committee on Cancer, and published in their respective staging manuals. Till 2002, the revisions of the TNM classification were based on the analyses of a database that included over 5,000 patients, and that was managed by Clifton Mountain. These patients originated from North America and almost all of them had undergone surgical treatment. To overcome these limitations, the International Association for the Study of Lung Cancer proposed the creation of an international database of lung cancer patients treated with a wider range of therapeutic modalities. The changes introduced in the 7th edition of the TNM classification of lung cancer, published in 2009, derived from the analysis of an international retrospective database of 81,495 patients. The revisions for the 8th edition, to be published in 2016, will be based on a new retrospective and prospective international database of 77,156 patients, and will mainly concern tumor size, extrathoracic metastatic disease, and stage grouping. These revisions will improve our capacity to indicate prognosis and will make the TNM classification more robust. In the future the TNM classification will be combined with non-anatomic parameters to define prognostic groups to further refine personalized prognosis.


Obvious as it may seem, it is important that the readers of this article keep in mind that the tumor, node and metastasis (TNM) classification of lung cancer is no more and no less than a system to code the anatomic extent of the disease. Therefore, by definition, the TNM classification does not include other elements that, while they can help improve our capacity to prognosticate the disease for a given patient, are unrelated to the anatomy of the tumor, i.e., parameters from blood analysis, tumor markers, genetic signatures, comorbidity index, environmental factors, etc. Prognostic indexes combining the TNM classification and other non-anatomic parameters are called, by consensus between the Union for International Cancer Control (UICC) and the American Joint Committee on Cancer (AJCC), prognostic groups to differentiate them from the anatomic stage groupings.

The TNM classification of lung cancer is applied to all histopathological subtypes of non-small cell carcinoma, to small cell carcinoma and to typical and atypical carcinoids. It is governed by general rules[1–3] (Table 1) that apply to all malignancies classified with this system, and by site-specific rules applicable to lung cancer exclusively.[4] There also are recommendations and requirements issued with the objective to classify tumors in a uniform way when their particular characteristics do not fit in the basic rules.[4]

The three components of the classification have several categories that are defined by different descriptors. For lung cancer, those for the T component are based on tumor size, tumor location and involved structures; those for the N, on the absence, presence and location of lymph node metastasis; and those for the M, on the absence, presence and location of distant metastasis. There are optional descriptors that add information on the local aggressiveness of the tumor (differentiation grade, perineural invasion, vascular invasion and lymphatic permeation) all of which have prognostic relevance;[5–8] assess the intensity of the investigation to determine the stage (certainty factor); and assess the residual tumor after therapy (residual tumor).

The TNM classification was developed by Pierre Denoit in a series of articles published from 1943 to 1952. It was soon adopted by the UICC that published brochures covering several anatomical sites, the lung being included in 1966. Two years later, the UICC published the first edition of the TNM Classification of Malignant Tumors and agreements were reached with the AJCC, created in 1959 as the American Joint Committee for Cancer Staging and End Results Reporting, to consult each other to avoid publication of differing classifications. Since then, the UICC and the AJCC have been responsible for updating and revising the TNM classifications of malignant tumors with the participation of national TNM committees of several countries and taking into account the published reports on the topic. The second to sixth editions of the UICC manual on the TNM Classification of Malignant Tumors and the first to sixth editions of the AJCC Staging Manual included classifications for lung cancer that had been informed by a progressively enlarging database initially collected by Mountain, Carr and Anderson, and subsequently managed by Mountain. Their database originally contained a little over 2,000 patients, but it had grown to more than 5,000 by the time the fifth edition of the TNM classification for lung cancer was published in 1997. The sixth edition was published in 2002 with no modifications.[9]

While the fifth edition of the classification was being printed, the International Workshop on Intrathoracic Staging took place in London, United Kingdom, in October 1996, sponsored by the International Association for the Study of Lung Cancer (IASLC).[10] At that meeting, in the presence of Dr. Mountain, the limitations of the database that had been used to revise the TNM classification for lung cancer were openly discussed. In essence, it was considered that, while the database consisted of a relatively large number of patients, all of them originated from the United States of America, and, therefore, the staging system could not really be called ‘international’, as it was called at that time; and, although all tumors had clinical and pathological classifications, the majority had been treated surgically. So, the database was thought not to be representative of the international community, as there were no patients from other countries; or of the current clinical practice, as there were no patients treated with other therapies. Therefore, an agreement was reached to issue a worldwide call to build a really international database of lung cancer patients treated by all therapeutic modalities. This required the constitution of an International Staging Committee that was approved and given a small amount of funding, to pump-prime, by the IASLC Board in 1998. Subsequently substantial financial support was secured by an unrestricted grant from Eli-Lilly. Cancer Research And Biostatistics (CRAB), a not-for-profit biosciences statistical center in Seattle, was appointed to collect, manage and analyze the new database. The proprietors and managers of known databases were subsequently summoned to attend a series of preparatory meetings to identify potential contributors to the IASLC international database for the purpose of revising the TNM classification of lung cancer.

The Future of the TNM Classification

The TNM classification of lung cancer is the most consistent and solid prognosticator of the disease, but it does not explain the whole prognosis because prognosis is multifactorial. In addition to the anatomic extent of the tumor, patient and environmental factors also count. Prognosis also is dynamic, as it may be different at the time of diagnosis, after treatment or at recurrence.[71] In the TNM classification, tumor resection plays an important role as it defines pathological staging and may modify the prognostic assessment based on clinical staging. Other than that, the TNM classification does not include blood analyses, tumor markers, genetic characteristic of the tumor or environmental factors that may account for the differences in survival among similar tumors in different geographic areas.

In order to make progress to indicate a more personalized prognosis, instead of a prognosis based on cohorts of patients with tumors of similar anatomic extent, the IASLC Staging and Prognosis Factors Committee decided to expand its activities to the study of non-anatomic prognostic factors. Therefore, in the third phase of the IASLC Lung Cancer Staging Project, the activities of the committee will be directed to further refine the TNM classification and to find available factors that can be combined with tumor staging to define prognostic groups. To some extent, this already was done with the analyses of the database used for the 7th edition. Prognostic groups with statistically significant differences were defined by combining anatomic tumor extent and very simple clinical variables, such as performance status, gender, and age. These prognostic groups were defined for clinically and pathologically staged tumors, and for small-cell and non-small cell lung cancers.[22,23]

The database used for the 8th edition includes several non-anatomical elements related to the patient, the tumor and the environment that may help refine prognosis at clinical and pathological staging.[69]Due to the limitations of the previous databases, future revisions of the TNM classification will need to be more balanced in terms of therapeutic modalities, and better populated with patients from underrepresented geographical areas, such as Africa, India, Indonesia, North, Central and South America, and South East Asia. The data contributed in the future will have to be complete regarding the TNM descriptors, and preferably prospective. The more robust the TNM, the more important its contribution to the prognostic groups.

To achieve all of the above, international collaboration is essential. Those interested in participating in this project should send an email expressing their interest to, stating ‘IASLC staging project’ in the subject of the email. The IASLC Staging and Prognostic Factors Committee has been very touched by the overwhelming generosity of colleagues around the world who have contributed cases to inform the 7th and the 8th editions of the TNM classification of lung cancer. We continue to count on their collaboration to further revise future editions and to define prognostic groups that will eventually allow a more personalized indication of prognosis.

MicroRNAs in the Pathobiology of Sarcomas

Anne E Sarver; Subbaya Subramanian

Lab Invest. 2015;95(9):987-984


Sarcomas are a rare and heterogeneous group of tumors. The last decade has witnessed extensive efforts to understand the pathobiology of many aggressive sarcoma types. In parallel, we have also begun to unravel the complex gene regulation processes mediated by microRNAs (miRNAs) in sarcomas and other cancers, discovering that microRNAs have critical roles in the majority of both oncogenic and tumor suppressor signaling networks. Expression profiles and a greater understanding of the biologic roles of microRNAs and other noncoding RNAs have considerably expanded our current knowledge and provided key pathobiological insights into many sarcomas, and helped identify novel therapeutic targets. The limited number of sarcoma patients in each sarcoma type and their heterogeneity pose distinct challenges in translating this knowledge into the clinic. It will be critical to prioritize these novel targets and choose those that have a broad applicability. A small group of microRNAs have conserved roles across many types of sarcomas and other cancers. Therapies that target these key microRNA-gene signaling and regulatory networks, in combination with standard of care treatment, may be the pivotal component in significantly improving treatment outcomes in patients with sarcoma or other cancers.

Sarcomas are a heterogenous group of tumors that account for ~200 000 cancers worldwide each year (~1% of all human malignant tumors); however, they represent a disproportionately high 15% of all pediatric malignant tumors.[1,2] Sarcomas comprise over 50 subtypes that can broadly be classified into bone and soft-tissue sarcomas that are generally based on the cell and/or tissue type.[3] The vast majority of sarcomas fall into the soft-tissue group, primarily affecting connective tissues such as muscle (smooth and skeletal), fat, and blood vessels. Bone sarcomas are relatively rare, representing only ~20% of all diagnosed sarcomas (~0.2% of all cancers). Even within a specific subtype, sarcomas are highly heterogenous making them diagnostically and therapeutically challenging. Several sarcoma types are genetically characterized by chromosomal translocations or DNA copy number alterations, both of which are used as diagnostic markers.[2,4,5]

The four main types of bone sarcomas are defined by their histology, cell of origin (when known), clinical features, and site distribution—osteosarcoma, Ewing’s sarcoma, chondrosarcoma, and chordoma. The most common primary bone malignancy, osteosarcoma, predominantly affects children and young adults and is characterized by undifferentiated bone-forming proliferating cells.[6] Ewing’s sarcoma, another aggressive pediatric malignancy, usually arises in growing bone and is genetically characterized by a fusion of EWS–FLI1 oncoproteins that act as gain-of-function transcriptional regulators.[7] Chondrosarcoma is itself a heterogenous group of malignant bone tumors arising from the malignant transformation of cartilage-producing cells, frequently with mutations in IDH1/2 and COL2A1.[8,9] Chordoma is an aggressive, locally invasive cancer that typically arises from bones in the base of the skull and along the spine. It is characterized, in part, by its abnormal expression of transcription factor T, which is normally only expressed during embryonic development or in the testes.[10]

Soft-tissue sarcomas are also primarily defined by their histology, cell of origin, and, in some cases, by characteristic genetic translocation events. Rhabdomyosarcoma is a malignant skeletal-muscle derived tumor comprised of two main histological subtypes, embryonal and alveolar, is one of the most common childhood soft-tissue sarcomas, accounting for 6–8% of all pediatric tumors.[11] Liposarcoma is the most common soft-tissue cancer overall, accounting for 20% of adult sarcoma cases. It originates in deep-tissue fat cells and is characterized primarily by amplification of the 12q chromosomal region.[12] Other common soft-tissue sarcomas include angiosarcomas, fibrosarcomas, gastrointestinal stromal tumors, and synovial sarcomas, each with their own unique genetic signature.

Ever since the discovery of oncogenes, the primary emphasis in cancer research has been on understanding the role of proteins and protein-coding genes. However, the percent of the genome dedicated to coding genes is small compared with noncoding regions. The last decade has seen a surge of interest in these noncoding regions with small noncoding RNAs such as microRNAs (miRNAs) gaining particular prominence. These small RNAs have critical roles in tumor formation and progression. Understanding their roles in sarcoma will lead to new therapeutic targets and diagnostic biomarkers, opening the door to a greater understanding of the molecular mechanisms of all cancers.

miRNAs are evolutionarily conserved, small, noncoding RNA molecules of 18–24 nucleotides in length at maturity that can control gene function through mRNA degradation, translational inhibition, or chromatin-based silencing mechanisms.[13] Each miRNA can potentially regulate hundreds of targets via a ‘seed’ sequence of ~5–8 nucleotides at the 5′ end of the mature miRNA. miRNAs bind to complementary sequences in the 3′-untranslated regions (3′-UTRs) of target mRNA molecules, leading to either translational repression or transcriptional degradation.[14] The short seed sequence length and relatively low stringency requirement for these miRNA–3′-UTR interactions allow a single miRNA to potentially regulate hundreds of genes.[15] Small changes in the expression level of a few miRNAs can therefore have a dramatic biological impact, particularly when dysregulated. miRNA expression profiles can be used to distinguish between closely related soft-tissue sarcoma subtypes and may provide a more consistent diagnosis than histological inspection.[16–18]

miRNAs have critical roles in the majority of canonical cellular signaling networks and their dysregulation is implicated in many cancers including breast cancer, colon cancer, gastric cancer, lung cancer, and sarcomas.[19,20] Dysregulation of miRNA expression may result from a variety of factors, including abnormal cellular stimuli, genetic mutations, epigenetic alterations, copy number variations, and chromosomal fusions. Because miRNAs act as critical regulator molecules in a variety of signaling pathways and regulatory networks, their dysregulation can be amplified across the entire signaling network.[21–24] Selected miRNAs and targets that have critical regulatory roles in sarcoma and other cancers are summarized in Table 1 .
The p53 signaling pathway is one of the most highly studied cellular signaling networks. It actively induces apoptosis in response to DNA damage and oncogene activation and is therefore a key tumor suppressor pathway.[25] Germline mutations in TP53 are strongly associated with the development of soft-tissue sarcomas, osteosarcoma, and are the underlying cause of Li–Fraumeni Syndrome, a familial clustering of early-onset tumors including sarcomas.[26,27] It is estimated that over 50% of human tumors harbor a TP53 mutation but over 80% of tumors have dysfunctional p53 signaling.[28,29] It is only within the last 10 years that researchers have started uncovering the roles of miRNAs in mediating p53’s activity and resulting pro-apoptotic signals (Figure 1). miRNA dysregulation could be a key factor in the ~30% of tumors with dysfunctional p53 signaling that lack an apparent TP53 mutation.

Figure 1.

p53–miRNA interaction network. p53 interacts with the Drosha complex and promotes the processing of pri-miRNA to pre-miRNA. Although p53 directly or indirectly regulates hundreds of miRNAs, for clarity, only selected cancer-relevant miRNAs are shown. miRNAs and proteins in red are upregulated by p53. miRNAs and proteins in green are downregulated by p53. miRNAs in gray are not known to be directly regulated by p53, they are included because they target p53 regulators MDM2 and/or MDM4. miRNA, microRNA.

Like other transcription factors, p53 exerts its function primarily through transcriptional regulation of target genes that contain p53 response elements in their promoters. p53 also regulates the post-transcriptional maturation of miRNAs by interacting with the Drosha processing complex, promoting the processing of primary miRNAs to precursor miRNAs.[30] In addition to protein-coding genes, many miRNA genes also contain p53 regulatory sites in their promoter regions. Large-scale screens have revealed many different miRNAs directly regulated by p53 including miR-22-3p, miR-34a, miR-125a/b, miR-182, and miR-199a-3p.[31] Some of these miRNAs, such as miR-34a and miR-199a-3p, function themselves as tumor suppressors via the regulation of genes involved in cell cycle, cell proliferation, and even of itself.[32–34] Although some p53-targeted miRNAs form a feedback loop, translationally and transcriptionally inhibiting the TP53 gene (e.g., miR-22-3p, miR-34a, and miR-125b), others target, or are predicted to target, p53 repressors such as MDM2 and/or MDM4 (miR-199a-3p, miR-661).[31,33,35,36] It is impossible to fully understand the regulation of the p53 signaling network without considering the role of these miRNAs.

miR-34a has emerged as a critical and conserved member of the p53 signaling pathway. miR-34a is downregulated in osteosarcoma tumor samples and, in conjunction with other miRNAs, regulates p53-mediated apoptosis in human osteosarcoma cell lines.[32,33,37] The gene encoding miR-34a contains a conserved p53-binding site and is upregulated in response to cellular damage in a p53-dependent manner.[37,38] Protein-coding members of the p53 signaling pathway are well-liked targets for anticancer therapeutic development efforts and miRNAs may prove equally effective. In a preclinical model of lung cancer, therapeutic delivery of a miR-34a mimic specifically downregulated miR-34a-target genes and resulted in slower tumor growth. When combined with a siRNA targeting Kras, this small RNA combination therapy resulted in tumor regression.[39] miRNAs such as miR-34a, miR-125b, and miR-199a-3p also mediate p53’s regulation of other key signaling pathways such as the IGF-1/PI3K/AKT/mTOR signaling network. Activation of the AKT network due to downregulation of PTEN (a negative regulator of AKT) by miR-21 or miR-221 or by alternate activation of AKT is a common mechanism underlying many different types of cancer.[40–43] The induction of cell growth, migration, invasion, and metastasis resulting from the upregulation of either miR-21 or miR-221 is seen across different tumor types.[41,44–50] Dysregulation of these miRNAs is a common factor in sarcomas and other tumors. Understanding their mechanisms of action in sarcoma could lead to broadly useful cancer therapeutics.

In prospective analyses that could be models for other sarcoma studies with sufficient numbers of patient samples, Thayanithy et al[19] and Maire et al[23] each analyzed collections of osteosarcoma tissues and compared them with either normal bone or osteoblasts. They each found a set of consistently downregulated miRNAs localized to the 14q32 region.[19,23] Targeting predictions performed by Thayanithy et al[19] identified a subset of four miRNAs as potential regulators of cMYC. One of the many roles of cMYC is to promote the expression of the miR-17–92 family, a known oncogenic cluster that has been observed to be highly expressed in many cancer types including osteosarcoma, leiomyosarcoma, and alveolar rhabdomyosarcoma.[51–57] Restoring the expression of the four 14q32 miRNAs increased apoptosis of SAOS-2 cells, an effect that was attenuated either by overexpression of a cMYC construct lacking the 3′UTR or by ectopic expression of the miR-17–92 cluster.[19] Although the 14q32 region is dysregulated across many different cancer types, this pattern of dysregulation appears to be a hallmark of osteosarcoma, which is particularly interesting due to the heterogenous nature of osteosarcomas and provides an extremely attractive common therapeutic target.

One particular challenge with these types of expression profiling studies is that the cell-of-origin for a particular sarcoma subtype may not be definitely established. Another challenge is the scarcity of patient samples, particularly for the rare sarcoma subtypes. As a result, there have only been a limited number of studies designed to comprehensively profile miRNA expression in various sarcoma subtypes and to compare those expression profiles with the corresponding normal tissues or cell lines. These studies were reviewed recently in Drury et al[20] and Subramanian and Kartha.[58]

Owing to the scarcity of frozen sarcoma tissue samples, it is tempting to study sarcoma cells in vitro, using either primary or immortalized cell cultures. Studies performed in culture are less expensive and more accessible; however, the cell lines used must be chosen with care and may not truly represent the tumors. Any results derived from cultured cells must be interpreted with caution and validated in vivo when possible. A tumor cell’s microenvironment has a profound effect on gene expression and cell metabolism and culturing for even short periods of time can result in large changes in gene/miRNA expression.[59] Three-dimensional cultures can provide more physiological relevant in vitro models of individual tumors (eg, spheroid cultures) or multi-layered epithelial tissues (eg, organotypic cultures using extracellular matrix proteins, fibroblasts, and/or artificial matrix components) vs the previous standard two dimensional culture model.[60,61]

Complicating the analysis of these miRNA expression changes is the fact that many miRNAs showing differential expression in multiple different studies do not have a consistent direction of change and/or a consistent role (tumor suppressor vs tumor promoter). This likely reflects both random chance observational differences and different tissue biology reflected in different regulatory networks. Elucidation of the regulatory roles played by miRNAs in these networks in their appropriate biological contexts may provide suitable upstream targets for more effective treatment of sarcomas. Recent advances in sequencing and downstream bioinformatics techniques provide the tools to efficiently examine these questions.

For two decades, microarray gene chips containing synthetic oligonucleotides whose sequences are designed to be representative of thousands of genes have allowed researchers to perform simultaneous expression analysis of thousands of RNA transcripts in a single reaction.[62–65] Gene expression profiling has been used to characterize and classify a wide range of sarcomas, in some cases providing a diagnostic resolution more accurate than histological examination.[66–72] With the advent of high-throughput RNA-Seq, sarcoma researchers are now able to prospectively analyze the differential expression of small RNAs, such as miRNAs, without prior knowledge of their sequence.[73,74] RNA-Seq also allows for the prospective identification of novel genomic rearrangements resulting from gene fusions or premature truncations that may be of particular interest to cancer researchers.[75,76] These data are highly quantitative and digital in nature, allowing for a dynamic range that is theoretically only limited by the sequencing depth and approaches the estimated range within the cell itself.[77] Marguerat and Bähler[78] provide a basic overview of the different RNA-Seq technologies and their differences from array-based technologies.[78]

Several groups have taken advantage of these technologies to create miRNA expression profiles for a number of different sarcomas in an effort to find both common sarcoma oncomirs and to discover unique miRNA signatures that could be used in diagnosis, prognosis, and novel therapeutic development. Renner et al[18] used a microarray-based miRNA screen, followed by qRT-PCR verification, to analyze the expression of 1146 known miRNAs across a collection of 76 primary soft-tissue sarcoma samples representing eight different subtypes and across a panel of 15 sarcoma cell lines. In addition to identifying overrepresented miRNAs synovial sarcomas (miR-200 family) and liposarcomas (miR-9) compared with other sarcomas and adipose tissue, respectively, their results revealed a high degree of co-expression of 63 miRNAs clustering in the chromosomal region 14q32.[18] The most comprehensive sarcoma miRNA data set has been published by Sarver et al[79] who profiled miRNA expression in over 300 sarcoma primary tumor tissue samples representing 22 different sarcoma types. These data form the basis for the web-accessible comprehensive Sarcoma microRNA Expression Database (SMED) database, which has tools that allows users to query specific sarcoma types and/or specific miRNAs.[79]

Integrative miRNA–mRNA analysis using a tool such as Ingenuity Pathway Analysis (Qiagen) or GeneSpring (Agilent) allows for more biologically relevant results by highlighting miRNA–mRNA pairs that are linked not only by predicted targeting interactions but whose expression levels are inversely correlated (i.e., as miRNA expression increases one would expect the target mRNA levels to decrease). For example, out of 177 differentially expressed miRNAs in osteosarcoma cell lines vs normal bone, an integrated miRNA–mRNA analysis highlighted two particularly interesting miRNA/mRNA pairs (miR-9/TGFBR2 and miR-29/p85α regulatory subunit of PI3K) that were dysregulated.[44]

It is important to note that the general consensus is that there is often no single ‘correct’ method to analyze miRNA expression data. Different experimental and bioinformatics techniques may reveal different aspects in the data that can be further investigated and experimentally validated. All of these experiments, whether performed at the bench or systems biology, contribute to our greater understanding of sarcoma biology and the central role of dysregulated miRNA–gene networks as drivers of tumor formation and progression.

miRNAs are part of a larger family of noncoding RNAs including long noncoding RNAs (lncRNAs) and competing endogenous RNAs (ceRNAs) that deserve to be evaluated for therapeutic potential in sarcomas with broader applicability to other cancer types. Just like miRNAs, lncRNAs are widely expressed in tissue-specific patterns that are highly disrupted in cancer.[80] As their name implies, ceRNAs compete for their common miRNA targets and influence their expression, which has an indirect effect on the protein-coding genes, such as PTEN, regulated by those miRNAs.[81,82] We have just begun to unravel the role of lncRNAs and ceRNAs in cancer development and progression but recent results hint at yet another layer of complexity and genetic control in tumor biology.

The lessons learned from carcinomas, leukemias, and lymphomas will be helpful in understanding the pathobiology of sarcomas and the insights gained from sarcoma biology may form the foundation for therapeutics to treat a wide range of other cancers. Recent studies have shown miRNAs are very stable in blood serum and plasma, and extensive efforts are underway to develop circulating miRNA-based diagnostic and prognostic markers. Major technical challenges in developing circulating miRNA-based markers still need to be addressed, including standardization of pre-analytical, analytical, and post-analytical methods for effective reproducibility. For example, miR-16, which is used in the normalization of miRNA expression in serum/plasma is also found in red blood cells; thus, any hemolysis during sample collection could significantly affect the downstream expression data analysis.

Cancers do not exist in isolation inside the body and extensive research has been performed on how tumor-derived proteins adapt their microenvironment to provide more favorable conditions for tumor growth and development. Recent studies have shown that miRNAs also have a major role in modulating tumor microenvironment. Although most miRNAs are found inside the cell, a significant number of miRNAs are encapsulated in exosomes that can be used as a delivery system to send miRNAs from one cell to another, allowing tumor cells to modulate gene expression in surrounding tissues.[83,84] Exosome and miRNA-mediated cross talk between sarcoma tumor cells and the surrounding stromal cells is a new and exciting avenue of research and the potential for novel therapeutics is high.

Sarcomas are a diverse collection of rare cancers with proportionally limited resources for research and development of novel treatments. It is therefore crucial that potential therapeutic targets are prioritized and novel therapeutic agents carefully selected for clinical trials to succeed. Extensive studies in preclinical models will be required; however, there are also challenges in the development of appropriate in vitro and in vivo model systems that accurately reflect the different sarcoma types. Sarcomas, such as osteosarcoma, leiomyosarcoma, and angiosarcoma are very heterogeneous in nature, making it unlikely that therapies targeting specific genomic mutations will be successful. Even if specific targets were to be identified it would still be a challenge to develop clinical trials based on the small number of patients harboring those specific mutations. Coordinated efforts such as the Cancer Genome Atlas (TCGA, and its associated preclinical and clinical trial consortiums will help unravel novel miRNA–mRNA interactions and their significance as potential therapeutic targets.

Targeting common miRNA–gene oncogenic or tumor suppressor networks goes after the common denominator underlying many of these cancers. Key regulatory molecules in sarcoma are highly likely to have similar roles in leukemias and lymphomas, for instance, and vice versa. For example, oncogenic activation of STAT3 strongly promotes the expression of miR-135b in lymphoma, resulting in increased angiogenesis and tumor growth.[85] miR-135b is widely overexpressed in sarcomas and STAT3 may be having a similar transcriptional regulatory role, indicating that STAT3 inhibitors could be an effective supplemental therapy in sarcomas.[86] Interestingly, p53 promotes the transcription of miR-125b, which can directly target both STAT3 and p53 transcription. This finely balanced regulatory network is frequently dysregulated in osteosarcoma and Ewing’s sarcoma.[87,88] In retinoblastoma, STAT3 activation is associated with upregulation of the miR-17-92 cluster via a positive feedback loop and inhibition of STAT3-suppressed retinoblastoma proliferation, providing further evidence that STAT3 may be an attractive therapeutic target in many cancers.[89] The dysregulation of key signaling molecules such as the p53 and STAT3 along with their associated signaling networks are a common feature across most cancer types implying that advances in understanding of sarcoma biology may be highly impactful in more frequently occurring solid tumors and lymphomas.

Certain miRNAs appear to be common players across many types of sarcomas and other cancers and their dysregulation contributes to the development of the hallmarks of cancer (Figure 2). miR-210, a key modulator of many downstream pathways involved in the hypoxic response, is upregulated under hypoxic conditions in most solid tumors, including soft-tissue sarcomas, osteosarcoma, renal cancer, and breast cancer.[90] A recent meta-analysis demonstrated that the elevated expression of miR-210 is a prognostic indicator for disease-free, progression-free, and relapse-free survival in a variety of cancer patients.[91] Perhaps the most consistently upregulated miRNA across all tumor types is the anti-apoptotic miR-21, which directly targets the tumor suppressor PDCD4.[92] Levels of miR-21 correlate with cancer progression and patient prognosis.[93]
Figure 2.

Conserved miRNA-tumor suppressor signaling networks in cancer. These miRNAs and tumor suppressors are involved in other network and signaling pathway interactions, such as the p53 signaling network; this figure highlights selected critical conserved pathways.


Human Papillomavirus Oncogenic mRNA Testing for Cervical Cancer Screening

Jennifer L. Reid, PhD; Thomas C. Wright Jr, MD; Mark H. Stoler, MD; Jack Cuzick, PhD; Philip E. Castle, PhD; Janel Dockter; Damon Getman, PhD; Cristina Giachetti, PhD

Am J Clin Pathol. 2015;144(3):473-483.


Objectives: This study determined the longitudinal clinical performance of a high-risk human papillomavirus (HR-HPV) E6/E7 RNA assay (Aptima HPV [AHPV]; Hologic, San Diego, CA) compared with an HR-HPV DNA assay (Hybrid Capture 2 [HC2]; Qiagen, Gaithersburg, MD) as an adjunctive method for cervical cancer screening.

Methods: Women 30 years or older with a negative result for intraepithelial lesions or malignancy cytology (n = 10,860) positive by AHPV and/or HC2 assays and randomly selected women negative by both assays were referred to colposcopy at baseline. Women without baseline cervical intraepithelial neoplasia (CIN) grade 2 or higher (CIN2+) continued into the 3-year follow-up.

Results: The specificity of AHPV for CIN2 or lower was significantly greater at 96.3% compared with HC2 specificity of 94.8% (P < .001). Estimated sensitivities and risks for detection of CIN2+ were similar between the two assays. After 3 years of follow-up, women negative by either human papillomavirus test had a very low risk of CIN2+ (<0.3%) compared with CIN2+ risk in women with positive AHPV results (6.3%) or positive HC2 results (5.1%).

Conclusions: These results support the use of AHPV as a safe and effective adjunctive cervical cancer screening method.


Cervical cancer is one of the most frequent cancers in women worldwide, accounting for approximately 530,000 new cases and 275,000 deaths annually.[1] Countries with well-organized screening programs using conventional Papanicolaou (Pap) stain cytology have experienced substantially reduced mortality from the disease in the past 5 decades.[2–4] Despite this advance, the relatively low sensitivity and reproducibility of both conventional Pap smear and liquid-based cytology screening methods have prompted investigation into identifying adjunctive methods with Pap cytology for improving detection of cervical neoplasia.[5–9]

Infection with 14 high-risk human papillomavirus (HR-HPV) genotypes (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68) is associated with almost all cases of cervical precancer, defined as cervical intraepithelial neoplasia (CIN) grade 2 (CIN2), grade 3 (CIN3), and cancer.[10] Addition of HR-HPV nucleic acid testing to a cervical cytology screening regimen offers higher sensitivity and negative predictive value (NPV) for detection of cervical precancer and cancer compared with cytology alone, especially in older women.[11–15] For this reason, HR-HPV nucleic acid testing is recommended as an adjunctive test to cytology to assess the presence of HR-HPV types in women 30 years of age or older.[16] In this context, HR-HPV testing guides patient management by identifying women at elevated risk for CIN2 or higher (CIN2+) but, importantly, also reassures women who are negative for HR-HPV of their extremely low cancer risk.[17–19]
First-generation HR-HPV molecular tests used for adjunctive cervical cancer screening function by detecting viral genomic DNA in cellular samples from the uterine cervix. However, because the presence of HR-HPV in the female genital tract is common and often transient in nature,[20,21] and most cervical HPV infections resolve without becoming cancerous,[22,23] HR-HPV DNA-based test methods yield only moderate specificity for detection of high-grade cervical disease.[12,24] This leads to unnecessary follow-up and referral of patients to colposcopy, increasing the physical and emotional burdens on patients and elevating health care costs.

A test approved by the US Food and Drug Administration (FDA) for detection of HR-HPV E6/E7 messenger RNA (mRNA) (Aptima HPV [AHPV]; Hologic, San Diego, CA) has shown higher specificity with similar sensitivity for detection of CIN2+ compared with HPV DNA-based tests in patients referred for colposcopy due to an abnormal Pap smear result as well as in a screening setting.[25–30] Expression of mRNA from viral E6 and E7 oncogenes is highly associated with the development of CIN,[31,32] and extensive investigation into the role of E6 and E7 oncoproteins in the human papillomavirus (HPV) life cycle has revealed that the expression of the corresponding oncogenes is necessary and sufficient for cell immortalization, neoplastic transformation, and the development of invasive cancer.[33–35]

To confirm and extend the previous evidence on the clinical utility of HR-HPV oncogenic mRNA testing in a US population-based setting, the clinical performance of AHPV was evaluated as an adjunctive method for cervical cancer screening in women aged 30 years or older with negative for intraepithelial lesions or malignancy (NILM) cytology results from routine Pap testing in a pivotal, prospective, multicenter US clinical study including 3 years of follow-up (the Clinical Evaluation of Aptima mRNA [CLEAR] study). We report herein the results from this study.

1 of 4

Figure 1.

Clinical evaluation of Aptima mRNA study participant disposition. aReasons for withdrawal: did not meet eligibility criteria (70); Pap volume insufficient for AHPV testing (117); specimen expired or unsuitable for testing (190); specimen lost (58); noncompliant site (320); other reasons (26). bReasons for withdrawal: collection site did not participate in follow-up (243); subject terminated participation (37); participant had hysterectomy (22); participant not eligible (17); participant treated prior to CIN2+ diagnosis (8); other reasons (4). AHPV, Aptima HPV (Hologic, San Diego, CA); ASC-US, atypical squamous cells of unknown significance; CIN2+, cervical intraepithelial neoplasia grade 2 or higher; HC2, Hybrid Capture 2 (Qiagen, Gaithersburg, MD); HPV, human papillomavirus; NILM, negative for intraepithelial lesions or malignancy; Pap, Papanicolaou test.

HPV Testing

Baseline PreservCyt specimens (1-mL aliquot) were tested with the AHPV (Hologic) on both the automated Tigris DTS System and Panther System. Results from the two systems were similar; Panther System results are presented here. AHPV is a target amplification assay that uses transcription-mediated amplification to detect the E6/E7 oncogene mRNA of 14 HR-HPV genotypes (16, 18, 31, 33, 35, 39, 45, 51, 52, 56, 58, 59, 66, and 68).


HPV and Disease Prevalence

Cervical disease and HPV status are shown in Table 2 for the baseline evaluation and cumulatively after 3 years of follow-up. Of the 10,860 evaluable participants with NILM cytology at baseline, 512 were positive for AHPV, yielding a prevalence of 4.7% for HR-HPV E6/E7 oncogenic mRNA, whereas prevalence of HR-HPV DNA was 6.5% among 10,229 women with HC2 results. A total of 845 HPV RNA-positive or DNA-positive women and 556 randomly selected HPV-negative women were referred to colposcopy at baseline (Figure 1).

At baseline, the percentage of colposcopy attendance was similar between HPV-positive (62%, n = 526) and randomly selected HPV-negative (61%, n = 339) women with 29 cases of CIN1, nine cases of CIN2, eight cases of CIN3, and three cases of adenocarcinoma in situ (AIS) identified (Table 2). Four of the CIN2 cases and two of the AIS cases were identified based on an ECC biopsy specimen only.

In total, 6,271 women completed the 3-year follow-up with a known disease status (Table 2). Of these, 6,098 (97.2%) women had normal (negative) disease status, and 56 (0.9%) had low-grade lesions (CIN1). In addition to the 20 women with CIN2+ identified at baseline, 15 (0.2%) women had CIN2 and 12 (0.2%) women had CIN3 identified during follow-up, with two cases identified from an ECC biopsy specimen only.

Of the 27 women with CIN2+ identified during follow-up, two had CIN1 at baseline, with CIN3 identified during year 1. Ten women had no disease found at baseline, with five cases of CIN2+ identified during year 1, one case of CIN2+ identified during year 2, and four cases of CIN2+ identified during year 3. The remaining 15 women with CIN2+ identified during follow-up did not have a baseline colposcopy; among them, two cases of CIN2+ were identified during year 1, six cases of CIN2+ during year 2, and seven cases of CIN2+ during year 3.

AHPV Assay Performance

Baseline risk and prevalence estimates adjusted for verification bias are provided in Table 3. The prevalence of CIN2+ was 0.9% in the overall population. CIN2+ occurred in 4.5% (95% CI, 2.7%-7.4%) of women with positive AHPV results and in 0.6% (95% CI, 0.2%–1.9%) of women with negative AHPV results, yielding a relative risk of 7.5 (95% CI, 2.1–26.3). This indicates that women with a positive AHPV result are at significantly greater risk of CIN2+ than women with a negative AHPV result. The CIN2+ relative risk obtained for the HC2 test at baseline was similar (7.3; 95% CI, 1.6–33.5). For CIN3+ diagnosis, the overall prevalence was 0.4%. The AHPV relative risk was 24.9 (95% CI, 2.0–307.0), again with a similar relative risk for HC2 (21.0; 95% CI, 1.0–423.8).

Cumulative absolute and relative risks for AHPV and HC2 over the 3-year follow-up period for HPV-positive and HPV-negative women are shown in Table 4. Women with an HPV-negative result with either test had very low cervical disease risk after 3 years of follow-up (<0.3%). Comparatively, 5% to 6% of women with an HPV-positive result had CIN2+ and 3% to 4% had CIN3+, with overall cumulative absolute and relative risks slightly higher for the AHPV assay than for HC2. Younger women aged 30 to 39 years who were HPV positive had twice the prevalence of disease but a similar increase in relative risk of cervical disease compared with HPV-positive women 40 years and older (Table 4). Risk of cervical disease in HPV-negative women did not vary by age group.

Figure 2 and Figure 3 show the cumulative absolute risk of CIN2+ and CIN3+, respectively, by year according to AHPV or HC2 positivity status at baseline. Both assays show a similar trend, with consistent slightly higher risk for the AHPV assay each year.

Figure 2.

Cumulative absolute risk of cervical intraepithelial neoplasia grade 2 or higher (CIN2+) by year. AHPV, Aptima HPV (Hologic, San Diego, CA); HC2, Hybrid Capture 2 (Qiagen, Gaithersburg, MD).

Figure 3.

Cumulative absolute risk of cervical intraepithelial neoplasia grade 3 or higher (CIN3+) by year. AHPV, Aptima HPV (Hologic, San Diego, CA); HC2, Hybrid Capture 2 (Qiagen, Gaithersburg, MD).

After 3 years of follow-up, the specificity of AHPV for CIN2 or lower was 96.3% (95% CI, 95.8%-96.7%), significantly greater (P < .001) compared with HC2 specificity of 94.8% (95% CI, 94.3%-95.4%) Table 5. AHPV specificity for CIN3 or lower (96.2%; 95% CI, 95.5%–96.5%) was also significantly greater (P < .001) than HC2 specificity (94.7%; 95% CI, 94.1%-95.2%). Estimated sensitivities for detection of CIN2+ and CIN3+ were similar between the two assays (P = .219 and P = 1.0, respectively). For detection of CIN2+, AHPV sensitivity was 55.3% (95% CI, 41.2%-68.6%), and HC2 sensitivity was 63.6% (95% CI, 48.9%-76.2%). For CIN3+ detection, AHPV sensitivity was 78.3% (95% CI, 58.1%-90.3%), and HC2 sensitivity was 81.8% (95% CI, 61.5%-92.7%) (Table 5).


This study presents the results of a 3-year longitudinal evaluation of the AHPV assay as an adjunctive method for screening women 30 years and older who have NILM Pap cytology results. Consistent with previously published data,[28,29] these results demonstrate that HR-HPV oncogenic E6/E7 mRNA testing has a sensitivity similar to an HR-HPV DNA-based test for detection of CIN2+ and CIN3+ and slightly, but significantly, improved specificity compared with HR-HPV DNA testing for both end points. We found that use of AHPV as an adjunctive method for HPV-induced cervical disease screening provided disease detection capability similar to HC2 while reducing the false-positive rate (from 5.2% to 3.7%) relative to the HPV DNA-based test. Reduction of HPV detection in women without cervical disease minimizes the anxiety and burden associated with spurious positive HPV molecular test results in women with NILM cytology, decreases health care costs, and reduces unnecessary follow-up procedures, thereby improving the safety of cervical cancer screening (unnecessary colposcopy is considered a significant “harm” in the recent American Cancer Society guidelines[16]).

Importantly, we show that women with a NILM cytology result who also had a positive AHPV result are approximately 24 times more likely to have CIN2+ disease after 3 years than women with a negative AHPV result. This risk increased to approximately 68-fold for detection of CIN3+ disease. Similar but slightly lower risk estimates were obtained with HC2, demonstrating comparable accuracy of the AHPV and HC2 for identifying participants with CIN2+ and CIN3+ in this respect.

After 3 years of follow-up, women in this study who were HPV negative at baseline using any test method had very low risk for CIN2+ (<0.3%), a result similar to previously published studies with HC2.[42,43] These findings reinforce evidence from previous studies showing that HR-HPV nucleic acid testing should be performed as an adjunctive test to routine Pap for cervical cancer screening of women 30 years or older to increase sensitivity of disease detection.[28] Correspondingly, compared with annual cytology-only screening, this study supports longer screening intervals for women negative for both abnormal cytology and HPV E6/E7 mRNA, due to the high NPV and low risk of disease afforded by this screening algorithm for 3 years following a test-negative baseline visit. Extension of cervical cancer screening intervals following negative HPV and cytology test results in women 30 years or older is a key recommendation of current US screening guidelines from both the American Cancer Society and the US Preventive Services Task Force.[16]

Conversely, since the positive predictive value of any HPV test in women with NILM cytology is low, additional AHPV testing to detect persistent HR-HPV infection during follow-up care in women with an initial AHPV-positive result is likely a better option than direct referral to colposcopy. Alternatively, genotyping with referral for HPV 16– or HPV 18–positive women can optimize referral and minimize loss to follow-up.[44]

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Papilloma viruses for cervical cancer

Larry H. Bernstein, MD, FCAP, Curator


Practice Bulletin No. 131: Screening for Cervical Cancer

Obstetrics & Gynecology:

The incidence of cervical cancer in the United States has decreased more than 50% in the past 30 years because of widespread screening with cervical cytology. In 1975, the rate was 14.8 per 100,000 women. By 2008, it had been reduced to 6.6 per 100,000 women. Mortality from the disease has undergone a similar decrease from 5.55 per 100,000 women in 1975 to 2.38 per 100,000 women in 2008 (1). The American Cancer Society (ACS) estimates that there will be 12,170 new cases of cervical cancer in the United States in 2012, with 4,220 deaths from the disease (2). Cervical cancer is much more common worldwide, particularly in countries without screening programs, with an estimated 530,000 new cases of the disease and 275,000 resultant deaths each year (3, 4). When cervical cancer screening programs have been introduced into communities, marked reductions in cervical cancer incidence have followed (5, 6).

New technologies for cervical cancer screening continue to evolve as do recommendations for managing the results. In addition, there are different risk-benefit considerations for women at different ages, as reflected in age-specific screening recommendations. The ACS, the American Society for Colposcopy and Cervical Pathology (ASCCP), and the American Society for Clinical Pathology (ASCP) have recently updated their joint guidelines for cervical cancer screening (7), and an update to the U.S. Preventive Services Task Force recommendations also has been issued (8). The purpose of this document is to provide a review of the best available evidence regarding screening for cervical cancer.

Study Backs Co-Testing for Cervical Cancer

A positive co-test result was more sensitive than either a positive HPV-only test or a positive Pap-only test.

Charles Bankhead

Cervical cancer screening with a test for human papillomavirus (HPV) resulted in a 50% higher rate of false-negative results versus Pap testing and three times greater versus co-testing, a large retrospective study showed.

Data encompassing more than 250,000 women showed a false-negative rate of 18.6% compared with 12.2% for Pap testing. With a false-negative rate of 5.5%, screening women with the HPV test and Pap test missed the fewest cancers.

The results support clinical guidelines that recommend co-testing, according to authors of a report in Cancer Cytopathology. The results differ dramatically, however, from those of previous studies that have consistently shown greater diagnostic accuracy for the HPV test compared with the Pap test.

“The reason that women are screened is that they want to be protected from cervical cancer,” study author R. Marshall Austin, MD, PhD, of Magee-Women’s Hospital and the University of Pittsburgh, told MedPage Today. “The previous trials have generally focused on cervical intraepithelial neoplasia 2 or 3, so-called precancer. The difference is that most of what we call precancer will actually never develop into cancer.

“The unique thing about this study, and what makes it so important, is that we looked at over 500 invasive cervical cancers, which are what women want to be protected against, and looked at the effectiveness of the methods of testing.”

A year ago, the FDA approved Roche’s cobas assay for HPV DNA as a first-line test for cervical cancer screening, following a unanimous vote for approval by an FDA advisory committee.

The approval was based primarily on a pivotal trial involving 47,200 women at high risk for cervical cancer. The primary endpoint was the proportion of patients who developed grade ≥3 cervical intraepithelial neoplasia (≥CIN3). The results showed a greater than 50% reduction in the incidence of ≥CIN3 with the DNA test versus Pap testing.

Austin and colleagues retrospectively analyzed clinical records for 256,648 average-risk women, ages 30 to 65, all of whom underwent co-testing as a screen for cervical cancer and subsequently had a cervical biopsy within a year of co-testing. The primary objective was to determine the sensitivity of the three screening methods for detection of biopsy-proven ≥CIN3 and invasive cancer.

The results showed that 74.7% of the women had a positive HPV test, 73.8% had an abnormal Pap test (atypical squamous cells of undetermined significance or worse), 89.2% had a positive co-test, and 1.6% had ≥CIN3.

Biopsy results showed that co-testing had the highest sensitivity for ≥CIN3 (98.8% versus 94% for HPV test only and 91.3% for Pap testing alone, P<0.0001). The Pap test had greater specificity versus HPV testing alone or co-testing (26.3% versus 25.6% versus 10.9%, P<0.0001).

Investigators identified 526 patients who developed biopsy-proven invasive cervical cancer. Of those patients, 98 tested negative by HPV assay only, 64 by Pap test only, and 29 by co-testing.

Given the average risk of the patient population included in the study, the results are broadly applicable to women in the age range studied, regardless of baseline risk for cervical cancer, Austin said.

The results are clearly at odds with previously reported comparative data showing superiority for the HPV assay versus Pap testing as a standalone screening test, but the reasons for the inconsistency aren’t clear, said Debbie Saslow, PhD, of the American Cancer Society (ACS) in Atlanta.

The data also show that co-testing is better than either test alone, which supports current ACS recommendations for cervical cancer screening.

“The current approach, according to the American Cancer Society and 25 other organizations that worked with us on our last guideline, co-testing is the preferred strategy,” Saslow told MedPage Today. “This paper completely backs that up. Even though a Pap alone is acceptable, clearly, co-testing is the best way to go.”

Noting that only half of women in the U.S. do not under go co-testing despite clinical guidelines recommending it for more than a decade, Saslow asked, “What’s taking so long?”

Earlier this year, several organizations released joint “interim guidance” regarding cervical cancer screening. Described as an aid to clinical decision-making until existing guidelines are updated, the interim guidance characterized the HPV-DNA test as an acceptable alternative to Pap testing as a primary screening test.

Acknowledging that the guidance focused on use of the HPV assay as a single test, interim guidance lead author Warner Huh, MD, of the University of Alabama at Birmingham, noted that “Every single study worldwide that has looked at this issue shows the same result: HPV testing outperforms Pap testing.”

In their article, Austin and colleagues argued that the HPV assay should be evaluated in comparison with the Pap test but as an alternative to co-testing.

“HPV-only primary screening for cervical cancer presents many challenges for clinicians,” the authors said. “Questions arise regarding its effectiveness, its long-term risk, and when it is the best option for a particular patient.

“Clinicians had similar questions when co-testing was first recommended for women 30 and older in 2006,” they added. “Since then the adoption of co-testing has steadily increased, with approximately 50% of physicians co-testing women 30 and older, but it is still not done at the recommended level.”

The study had some limitations. The authors could not confirm that the cervical biopsy results were from women who did not have an intervening screening test or treatment with a different provider during the study period.

Also, the authors were unable to draw conclusions based on the overall population of women who were screened for cervical cancer because the dataset consisted of screening results of women who underwent biopsies.

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Reporter: Aviva Lev-Ari, PhD, RN

Head and Neck Cancer Studies Suggest Alternative Markers More Prognostically Useful than HPV DNA Testing

September 18, 2012

NEW YORK (GenomeWeb News) – The presence or absence of human papillomavirus DNA on its own in an individual’s head or neck cancer does not provide enough information to help predict a patient’s survival, according to a pair of new papers in the journal Cancer Research.

Two research teams — headed by investigators at Brown University and Heidelberg University, respectively — looked at the reliability of using PCR-based HPV testing to determine which head and neck squamous cell carcinomas were HPV-related and, thus, more apt to respond to treatment.

Previous studies have shown that individuals with HPV-associated head and neck cancers tend to have more favorable outcomes than individuals whose head and neck cancers that are not related to HPV infection.

“Everybody who has studied it has shown that people with virally associated disease do better,” Brown University pathology researcher Karl Kelsey, a senior author on one of the new studies, explained in a statement.

“There are now clinical trials underway to determine if they should be treated differently,” he added. “The problem is that you need to appropriately diagnose virally related disease, and our data suggests that people need to take a close look at that.”

For their part, Kelsey and his co-authors from the US and Germany assessed the utility of testing for the presence of HPV by various means in individuals with head and neck cancer. This included PCR-based tests for HPV DNA in the tumor itself, tests aimed at detecting infection-associated antibodies in an individual’s blood, and tests for elevated levels of an HPV-related tumor suppressor protein.

For 488 individuals with HNSCC, researchers did blood-based testing for antibodies targeting HPV16 in general, as well as testing for antibodies that target the viral proteins E6 and E7.

For a subset of patients, the team assessed the tumors themselves for the presence of HPV DNA and/or for elevated levels of the host tumor suppressor protein p16.

Based on patterns in the samples, the group determined that the presence of viral E6 and E7 proteins in the blood was linked to increased survival for individuals with an oropharyngeal form of HNSCC, which affects part of the throat known as the oropharynx.

A positive test for HPV DNA alone was not significantly linked to head and neck cancer outcomes. On the other hand, when found in combination with E6 and E7 expression, a positive HPV16 test did coincide with improved oropharyngeal cancer outcomes.

Likewise, elevated levels of p16 in a tumor were not especially informative on their own, though they did correspond to better oropharyngeal cancer survival when found together with positive blood tests for E6 and E7.

Based on these findings, Kelsey and his team concluded that “[a] stronger association of HPV presence with prognosis (assessed by all-cause survival) is observed when ‘HPV-associated’ HNSCC is defined using tumor status (HPV DNA or P16) and HPV E6/E7 serology in combination rather [than] using tumor HPV status alone.”

In a second study, meanwhile, a German group that focused on the oropharyngeal form of the disease found its own evidence arguing against the use of HPV DNA as a solo marker for HPV-associated head and neck cancer.

For that analysis, researchers assessed 199 fresh-frozen oropharyngeal squamous cell carcinoma samples, testing the tumors for HPV DNA and p16. They also considered the viral load in the tumors and looked for gene expression profiles resembling those described in cervical carcinoma — another cancer associated with HPV infection.

Again, the presence of HPV DNA appeared to be a poor indicator of HPV-associated cancers or predictor of cancer outcomes. Whereas nearly half of the tumors tested positive for HPV16 DNA, just 16 percent and 20 percent had high viral loads and cervical cancer-like expression profiles, respectively.

The researchers found that a subset of HPV DNA-positive tumors with high viral load or HPV-associated expression patterns belonged to individuals with better outcomes. In particular, they found that cervical cancer-like expression profiles in oropharyngeal tumors coincided with the most favorable outcomes, while high viral load in the tumors came a close second.

“We showed that high viral load and a cancer-specific pattern of viral gene expression are most suited to identify patients with HPV-driven tumors among patients with oropharyngeal cancer,” Dana Holzinger, that study’s corresponding author, said in a statement.

“Once standardized assays for these markers, applicable in routine clinical laboratories, are established, they will allow precise identification of patients with oropharyngeal cancer with or without HPV-driven cancers and, thus, will influence prognosis and potentially treatment decisions,” added Holzinger, who is affiliated with the German Cancer Research Center and Heidelberg University.

In a commentary article online today in Cancer Research, Eduardo Méndez, a head and neck surgery specialist with the University of Washington and Fred Hutchinson Cancer Research Centerdiscussed the significance of the two studies and their potential impact on oropharyngeal squamous cell carcinoma prognoses and treatment.

But he also cautioned that more research is needed to understand whether the patterns described in the new studies hold in other populations and to tease apart the prognostic importance of HPV infection in relation to additional prognostic markers.


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