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Live Conference Coverage @Medcitynews Converge 2018 Philadelphia:Liquid Biopsy and Gene Testing vs Reimbursement Hurdles

9:25- 10:15 Liquid Biopsy and Gene Testing vs. Reimbursement Hurdles

Genetic testing, whether broad-scale or single gene-testing, is being ordered by an increasing number of oncologists, but in many cases, patients are left to pay for these expensive tests themselves. How can this dynamic be shifted? What can be learned from the success stories?

Moderator: Shoshannah Roth, Assistant Director of Health Technology Assessment and Information Services , ECRI Institute @Ecri_Institute
Speakers:
Rob Dumanois, Manager – reimbursement strategy, Thermo Fisher Scientific
Eugean Jiwanmall, Senior Research Analyst for Medical Policy & Technology Evaluation , Independence Blue Cross @IBX
Michael Nall, President and Chief Executive Officer, Biocept

 

Michael: Wide range of liquid biopsy services out there.  There are screening companies however they are young and need lots of data to develop pan diagnostic test.  Most of liquid biopsy is more for predictive analysis… especially therapeutic monitoring.  Sometimes solid biopsies are impossible , limited, or not always reliable due to metastasis or tough to biopsy tissues like lung.

Eugean:  Circulating tumor cells and ctDNA is the only FDA approved liquid biopsies.  However you choose then to evaluate the liquid biopsy, PCR NGS, FISH etc, helps determines what the reimbursement options are available.

Rob:  Adoption of reimbursement for liquid biopsy is moving faster in Europe than the US.  It is possible in US that there may be changes to the payment in one to two years though.

Michael:  China is adopting liquid biopsy rapidly.  Patients are demanding this in China.

Reimbursement

Eugean:  For IBX to make better decisions we need more clinical trials to correlate with treatment outcome.  Most of the major cancer networks, like NCCN, ASCO, CAP, just have recommendations and not approved guidelines at this point.  From his perspective with lung cancer NCCN just makes a suggestion with EGFR mutations however only the companion diagnostic is approved by FDA.

Michael:  Fine needle biopsies are usually needed by the pathologist anyway before they go to liquid biopsy as need to know the underlying mutations in the original tumor, it just is how it is done in most cancer centers.

Eugean:  Whatever the established way of doing things, you have to outperform the clinical results of the old method for adoption of a newer method.

Reimbursement issues have driven a need for more research into clinical validity and utility of predictive and therapeutic markers with regard to liquid biopsies.  However although many academic centers try to partner with Biocept Biocept has a limit of funds and must concentrate only on a few trials.  The different payers use different evidence based methods to evaluate liquid biopsy markers.  ECRI also has a database for LB markers using an evidence based criteria.  IBX does sees consistency among payers as far as decision and policy.

NGS in liquid biopsy

Rob: There is a path to coverage, especially through the FDA.  If you have a FDA cleared NGS test, it will be covered.  These are long and difficult paths to reimbursement for NGS but it is feasible. Medicare line of IBX covers this testing, however on the commercial side they can’t cover this.  @IBX: for colon only kras or nras has clinical utility and only a handful of other cancer related genes for other cancers.  For a companion diagnostic built into that Dx do the other markers in the panel cost too much?

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Reporter and Curator: Irina Robu, PhD

Monitoring cancer patients and evaluating their response to treatment can sometimes involve invasive procedures, including surgery.

The liquid biopsies have become something of a Holy Grail in cancer treatment among physicians, researchers and companies gambling big on the technology. Liquid biopsies, unlike traditional biopsies involving invasive surgery — rely on an ordinary blood draw. Developments in sequencing the human genome, permitting researchers to detect genetic mutations of cancers, have made the tests conceivable. Some 38 companies in the US alone are working on liquid biopsies by trying to analyze blood for fragments of DNA shed by dying tumor cells.

Premature research on the liquid biopsy has concentrated profoundly on patients with later-stage cancers who have suffered treatments, including chemotherapy, radiation, surgery, immunotherapy or drugs that target molecules involved in the growth, progression and spread of cancer. For cancer patients undergoing treatment, liquid biopsies could spare them some of the painful, expensive and risky tissue tumor biopsies and reduce reliance on CT scans. The tests can rapidly evaluate the efficacy of surgery or other treatment, while old-style biopsies and CT scans can still remain inconclusive as a result of scar tissue near the tumor site.

As recently as a few years ago, the liquid biopsies were hardly used except in research. At the moment, thousands of the tests are being used in clinical practices in the United States and abroad, including at the M.D. Anderson Cancer Center in Houston; the University of California, San Diego; the University of California, San Francisco; the Duke Cancer Institute and several other cancer centers.

With patients for whom physicians cannot get a tissue biopsy, the liquid biopsy could prove a safe and effective alternative that could help determine whether treatment is helping eradicate the cancer. A startup, Miroculus developed a cheap, open source device that can test blood for several types of cancer at once. The platform, called Miriam finds cancer by extracting RNA from blood and spreading it across plates that look at specific type of mRNA. The technology is then hooked up at a smartphone which sends the information to an online database and compares the microRNA found in the patient’s blood to known patterns indicating different type of cancers in the early stage and can reduce unnecessary cancer screenings.

Nevertheless, experts warn that more studies are essential to regulate the accuracy of the test, exactly which cancers it can detect, at what stages and whether it improves care or survival rates.

SOURCE

https://www.fastcompany.com/3037117/a-new-device-can-detect-multiple-types-of-cancer-with-a-single-blood-test

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4356857/

Other related articles published in this Open Access Online Scientific Publishing Journal include the following:

Liquid Biopsy Chip detects an array of metastatic cancer cell markers in blood – R&D @Worcester Polytechnic Institute, Micro and Nanotechnology Lab

Reporters: Tilda Barliya, PhD and Aviva Lev-Ari, PhD, RN

https://pharmaceuticalintelligence.com/2016/12/28/liquid-biopsy-chip-detects-an-array-of-metastatic-cancer-cell-markers-in-blood-rd-worcester-polytechnic-institute-micro-and-nanotechnology-lab/

Liquid Biopsy Assay May Predict Drug Resistance

Curator: Larry H. Bernstein, MD, FCAP

https://pharmaceuticalintelligence.com/2015/11/06/liquid-biopsy-assay-may-predict-drug-resistance/

One blood sample can be tested for a comprehensive array of cancer cell biomarkers: R&D at WPI

Curator: Marzan Khan, B.Sc

https://pharmaceuticalintelligence.com/2017/01/05/one-blood-sample-can-be-tested-for-a-comprehensive-array-of-cancer-cell-biomarkers-rd-wpi

 

 

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Programmed Cell Death and Cancer Therapy

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Programmed Death: A Cat and Mouse Game

 http://www.cancernetwork.com/blog/programmed-death-cat-and-mouse-game

Prologue: The world of cancer care has been shaken up by the news that patients with hard-to-treat tumors benefit from a new type of immunotherapy, called checkpoint inhibition. A key receptor, called programmed death 1 (PD-1), is charged with suppressing the ability of activated T cells and other immune cells to destroy cancer cells, all in the name of preventing damage to normal tissue via autoimmunity. When PD-1 receptors on T cells bind with PD-L1 and PD-L2, complimentary receptors expressed on tumor cells, the immune response (call it the assassination of the cell) is checked and the tumor lives on. The anti PD-1 monoclonal antibodies nivolumab and pembrolizumab keep PD-L1 from turning off T cells, which has produced durable responses in several tumor types including melanoma, lung cancer, and renal cell carcinoma and represents a new hope for many.

Oncologists are excited to relay this news to patients, but is there a way to explain this without putting everyone in the room to sleep? Well, I like to use analogies to make seemingly complicated mechanisms easier to understand and the PD-1/PD-L1 relationship has inspired several colorful examples, to wit:

“Think of T cells as killers that use photographs to identify individual bad guys. Their weakness is that they will not act if the intended victim shakes their hand first. The bad guys used to be born without arms, but over time they evolved to grow arms and hands, thus avoiding elimination. The antibodies are boxing gloves that cover the hands of the T cells. Goodbye, bad guys.”

“Think of T cells as cats specially trained to eliminate mice wherever they hide. Their only weakness is if they smell catnip they will roll over and purr like idiots instead of doing their job. The mice then develop special glands that secrete catnip, thus pacifying the kitties. Solution: plug up the cats’ noses with nivolumab or pembrolizumab. Sayonara, Mr. Mouse.”

“Think of T cells as a fire sprinkler system designed to activate when a metal plug is heated to its melting point, releasing water from a pipe. The fire then emits a toxin that coats the fusible metal, keeping it below its melting point. By fitting a protective shield around the plug we block the toxic molecules and allow the plug to melt in a fire. The shield is the monoclonal antibody against PD-1 and thus the fire is successfully extinguished.”

This is getting exhausting, so I think I will stop, but don’t you agree that the concept of checkpoint inhibition lends itself to a plethora of metaphors? Now for the next lesson: how to explain chimeric antigen receptor T-cell therapy to patients. Hold on—I think I need to explain it to myself first.

 

As an clinical immunologist, i agree with the concept, looks pretty straightforward but definitely much more complex as our immune system work like a network. I would appreciate clinical trial data with statistical significance.

 

Much more confusing. Most people understand simplified concepts.

“Some cancer cells turn off your immune systems ability to recognise them. These drugs ramp up the immune system and prevent the cancer cells from hiding. This allows your cells to attack and kill cancer cells”

If i think patient seem to have better ability to understand I say “the drugs block the “off switch” that cancer cells use to escape their detection. This turns your immune systems ability to attack and kill cancer cells back on”

I haven’t had one patient that has looked confused since.

 

HDAC Inhibitors Enhance Immunotherapy Efficacy in Lung Cancer

http://www.oncotherapynetwork.com/lung-cancer-targets/hdac-inhibitors-enhance-immunotherapy-efficacy-lung-cancer

Histone deacetylase (HDAC) inhibitors like romidepsin might improve the efficacy of programmed cell death-1 (PD-1) blockade in lung cancer, suggest preclinical findings reported in the journal Clinical Cancer Research.

Most lung cancer patients’ tumors do not respond to immune checkpoint blockade agents like those that target PD-1. One possible mechanism underlying tumor resistance to PD-1 blockade is the failure of sufficient numbers of T cells to infiltrate tumor tissue.

Hypothesizing that upregulating T-cell chemokine expression and thereby T-cell infiltration of tumors would improve PD-1 blockade’s efficacy against lung tumors, the research team went hunting for FDA-approved oncology agents that induce chemokine expression. Screening 97 approved agents, they found one class that did: HDAC inhibitors.

The HDAC-inhibiting agent romidepsin significantly increased T-cell tumor infiltration and impacted lung tumor growth in mouse models, the team reported—and when romidepsin was subsequently combined with PD-1 blockade in several lung tumor models, the combination showed greater antitumor activity than either agent on its own.

“These results suggest that combination of HDAC inhibitors with PD-1 blockade represent a promising strategy for lung cancer treatment,” said senior study author Amer A. Beg, PhD, of the Moffitt Cancer Center’s Immunology Program, in a news release.

Romidepsin and other HDAC inhibitors have already been approved by the FDA for use against lymphoma and other hematologic cancers, Dr. Beg noted.

The combination will next be tested in several clinical trials, including a study of patients diagnosed with non-small cell lung cancer (NSCLC) at Moffitt Cancer Center.

 

HDAC inhibitors enhance T cell chemokine expression and augment response to PD-1 immunotherapy in lung adenocarcinoma

Hong Zheng1,  weipeng zhao2Cihui Yan3Crystina C Watson4,…., Brian Ruffell13, and Amer A Beg4,*

Clin Cancer Res March 10, 2016; http://dx.doi.org:/10.1158/1078-0432.CCR-15-2584

Purpose: A significant limitation of checkpoint blockade immunotherapy is the relatively low response rate (e.g. ~20% with PD-1 blockade in lung cancer). In this study, we tested whether strategies which increase T cell infiltration to tumors can be efficacious in enhancing immunotherapy response. Experimental Design: We performed an unbiased screen to identify FDA-approved oncology agents with ability to enhance T cell chemokine expression with the goal of identifying agents capable of augmenting immunotherapy response. Identified agents were tested in multiple lung tumor models as single agents and in combination with PD-1 blockade. Additional molecular and cellular analysis of tumors was used to define underlying mechanisms. Results: We found that histone deacetylase (HDAC) inhibitors (HDACi) increased expression of multiple T cell chemokines in cancer cells, macrophages and T cells. Using the HDACi romidepsin in vivo, we observed increased chemokine expression, enhanced T cell infiltration, and T cell-dependent tumor regression. Importantly, romidepsin significantly enhanced the response to PD-1 blockade immunotherapy in multiple lung tumor models, including nearly complete rejection in two models. Combined romidepsin and PD-1 blockade also significantly enhanced activation of tumor-infiltrating T cells. Conclusions: These results provide evidence for a novel role of HDACs in modulating T cell chemokine expression in multiple cell types. In addition, our findings indicate that pharmacological induction of T cell chemokine expression represents a conceptually novel approach for enhancing immunotherapy response. Finally, these results suggest that combination of HDAC inhibitors with PD-1 blockade represents a promising strategy for lung cancer treatment.

 

Cancer Cell Survival Driven by Novel Metabolic Pathway

http://www.genengnews.com/gen-news-highlights/cancer-cell-survival-driven-by-novel-metabolic-pathway/81252584/

Researchers have identified a novel metabolic pathway that helps cancer cells thrive in conditions that are lethal to normal cells. [National Cancer Institute, NIH] http://www.genengnews.com/Media/images/GENHighlight/thumb_28216_large1422477191.jpg

Being attached to the extracellular matrix (ECM) provides cells with numerous advantages for survival, for instance, receiving much needed growth stimuli. However, for malignant cells to function, they must overcome their anchorage-dependent growth—a scenario that is associated with increased production of reactive oxygen species (ROS) and altered glucose metabolism.

Now, researchers at the Children’s Medical Center Research Institute at UT Southwestern (CRI) believe they have uncovered a novel metabolic pathway that helps cancer cells thrive in conditions that would otherwise be lethal to healthy cells.

“It’s long been thought that if we could target tumor-specific metabolic pathways, it could lead to effective ways to treat cancer,” explained senior study author Ralph DeBerardinis, M.D., Ph.D.,  associate professor, and director of CRI’s Genetic and Metabolic Disease Program. “This study finds that two very different metabolic processes are linked in a way that is specifically required for cells to adapt to the stress associated with cancer progression.”

This new study describes an alternate version of two well-known metabolic pathways, the pentose phosphate pathway (PPP) and the Krebs cycle, to defend against ROS that destroy cells via oxidative stress.

The findings from this study were published recently in Nature in an article entitled “Reductive Carboxylation Supports Redox Homeostasis During Anchorage-Independent Growth.”

Previous work from Dr. DeBerardinis’ laboratory found that the Krebs cycle, a series of chemical reactions that cells use to generate energy, could reverse itself under certain conditions to nourish cancer cells.

Dr. DeBerardinis also noted that cells “are dependent on matrix attachment to receive growth-promoting signals and to regulate their metabolism in a way that supports cell growth, proliferation, and survival.” Detachment from the matrix results in a sudden increase in ROS that is lethal to normal cells. Yet, cancer cells seem to have evolved workaround.

A landmark study from 2009 elucidated that healthy cells were destroyed when detached from the ECM. Moreover, in the same study, investigators found that inserting an oncogene into a normal cell caused it to behave like a cancer cell and survive detachment.

“Another Nature study, this one from CRI Director Dr. Sean Morrison’s laboratory in November 2015, found that the rare skin cancer cells that were able to detach from the primary tumor and successfully metastasize to other parts of the body had the ability to keep ROS levels from getting dangerously high,” Dr. DeBerardinis remarked.

Dr. DeBerardinis and his team worked from the premise that the two findings were pieces of the same puzzle and that a crucial part of the picture seemed to be missing.

It had been well known that the PPP was an important source of nicotine adenine dinucleotide phosphate (NADPH), which provides a source of reducing electrons to scavenge ROS; however, the PPP produces NADPH in the cytosol, whereas the ROS are generated primarily in another subcellular structure called the mitochondria.

“If you think of ROS as fire, then NADPH is like the water used by cancer cells to douse the flames,” Dr. DeBerardinis noted.  But how could NADPH from the PPP help deal with the stress of ROS produced in an entirely different part of the cell? “What we did was to discover how this happens.”

The CRI team was able to demonstrate that cancer cells use a “piggybacking” system to carry the reducing electron from the PPP into the mitochondria. This movement involves an unusual reaction in the cytosol that transfers reducing equivalents from NADPH to a molecule called citrate, similar to a reversed reaction of the Krebs cycle.The citrate then enters the mitochondria and stimulates another pathway that results in the release of reducing electrons to produce NADPH right at the location of ROS creation, allowing the cancer cells to survive and grow without the benefit of matrix attachment.

“We knew that both the PPP and Krebs cycle provide metabolic benefits to cancer cells. But we had no idea that they were linked in this unusual fashion,” Dr. DeBerardinis stated. “Strikingly, normal cells were unable to transport NADPH by this mechanism, and died as a result of the high ROS levels.”

The researchers stressed that their findings were based on cultured cell models and more research will be necessary to test the role of the pathway in living organisms.

“We are particularly excited to test whether this pathway is required for metastasis because cancer cells need to survive in a matrix-detached state in the circulation in order to metastasize,” Dr. DeBerardinis concluded.

 

Reductive carboxylation supports redox homeostasis during anchorage-independent growth

Lei JiangAlexander A. ShestovPamela SwainChendong Yang, …., Brian P. DrankaBenjamin Schwartz & Ralph J. DeBerardinis

Nature(2016)      http://dx.doi.org:/10.1038/nature17393

Cells receive growth and survival stimuli through their attachment to an extracellular matrix (ECM)1. Overcoming the addiction to ECM-induced signals is required for anchorage-independent growth, a property of most malignant cells2. Detachment from ECM is associated with enhanced production of reactive oxygen species (ROS) owing to altered glucose metabolism2. Here we identify an unconventional pathway that supports redox homeostasis and growth during adaptation to anchorage independence. We observed that detachment from monolayer culture and growth as anchorage-independent tumour spheroids was accompanied by changes in both glucose and glutamine metabolism. Specifically, oxidation of both nutrients was suppressed in spheroids, whereas reductive formation of citrate from glutamine was enhanced. Reductive glutamine metabolism was highly dependent on cytosolic isocitrate dehydrogenase-1 (IDH1), because the activity was suppressed in cells homozygous null for IDH1 or treated with an IDH1 inhibitor. This activity occurred in absence of hypoxia, a well-known inducer of reductive metabolism. Rather, IDH1 mitigated mitochondrial ROS in spheroids, and suppressing IDH1 reduced spheroid growth through a mechanism requiring mitochondrial ROS. Isotope tracing revealed that in spheroids, isocitrate/citrate produced reductively in the cytosol could enter the mitochondria and participate in oxidative metabolism, including oxidation by IDH2. This generates NADPH in the mitochondria, enabling cells to mitigate mitochondrial ROS and maximize growth. Neither IDH1 nor IDH2 was necessary for monolayer growth, but deleting either one enhanced mitochondrial ROS and reduced spheroid size, as did deletion of the mitochondrial citrate transporter protein. Together, the data indicate that adaptation to anchorage independence requires a fundamental change in citrate metabolism, initiated by IDH1-dependent reductive carboxylation and culminating in suppression of mitochondrial ROS.

 

Liquid Biopsy Accurately Detects Mutations in Advanced NSCLC

http://www.oncotherapynetwork.com/lung-cancer/liquid-biopsy-accurately-detects-mutations-advanced-nsclc#sthash.bEPxRkAq.dpuf

Droplet digital polymerase chain reaction (ddPCR)-based plasma genotyping—referred to as liquid biopsy—exhibited perfect specificity in identifying EGFR and KRAS mutations in patients with advanced non–small-cell lung cancer (NSCLC), according to the results of a study published in JAMA Oncology.

“We see plasma genotyping as having enormous potential as a clinical test, or assay—a rapid, noninvasive way of screening a cancer for common genetic fingerprints, while avoiding the challenges of traditional invasive biopsies,” said senior author, Geoffrey Oxnard, MD, thoracic oncologist and lung cancer researcher at Dana-Farber and Brigham and Women’s Hospital, in a press release. “Our study was the first to demonstrate prospectively that a liquid biopsy technique can be a practical tool for making treatment decisions in cancer patients.”

According to the press release, the test proved so reliable in the study that the Dana-Farber/Brigham and Women’s Cancer Center this week became the first medical facility in the country to offer it to all patients with NSCLC, either at the time of first diagnosis or of relapse following previous treatment.

Oxnard and colleagues enrolled 180 patients with advanced NSCLC. Patients were either newly diagnosed with the disease (n = 120) or had acquired resistance to prior EGFR kinase inhibitors (n = 60) and were planned for rebiopsy. Patients underwent initial blood sampling and immediate plasma ddPCR screening for EGFR exon 19 deletion, L858R, the EGFR T790M acquired resistance mutation, or KRAS G12X. In addition, patients underwent biopsy for tissue genotyping used to compare the accuracy of ddPCR.

Among the enrolled patients, 80 had EGFR exon19/L858R mutations, 35 had T790M mutations and 25 had KRAS G12X mutations. The median test turnaround time for liquid biopsy was 3 days. In comparison, the median turnaround time for tissue genotyping was 12 days for newly diagnosed patients and 27 days for patients with acquired EGFR inhibitor resistance.

“This long turnaround time is due largely to the practical reality that many patients with newly diagnosed NSCLC require a repeat biopsy to obtain tissue for genotyping, as do all patients with acquired resistance,” the researchers noted.

The liquid biopsy showed 100% positive predictive value for detecting EGFR 19 deletion, L858R, and KRAS mutations. However, it had only a positive predictive value of 79% for T790M mutations. The sensitivity of the test was lower. ddPCR had a sensitivity of 82% for EGFR 19 deletion, 74% for L858R, 77% for T790M, and 64% for KRAS.

The researchers pointed out that “a key limitation of plasma ddPCR is that although this method is adept at rapidly detecting specific targetable mutations, it cannot easily detect copy number alterations and rearrangements. The ddPCR panel assessed in this study thus cannot currently detect targetable alterations in either ALK or ROS1,” two other common mutations in NSCLC.

In an editorial that accompanied the article, P. Mickey Williams, PhD, of Frederick National Laboratory for Cancer Research, and Barbara A. Conley, MD, from the National Cancer Institute, questioned whether or not these results, and the rapid turnaround time for liquid biopsy, could be replicated widely by other institutions.

“However, if this performance were generally applicable, this would indeed be an advance in clinical care, reducing the proportion of patients requiring biopsy, at least in the resistance setting,” Williams and Conley wrote.

“This study is a step in the right direction of preparing needed clinical validation for the use of ctDNA for detection and serial monitoring of clinically relevant tumor mutations. Owing to low sensitivity and high positive predictive value and specificity, this approach is probably best suited for detection of resistance mutations and for serial plasma testing to assess treatment response, and should not replace tumor biopsy assessment for initial treatment decision-making,” they concluded.

 

Prospective Validation of Rapid Plasma Genotyping for the Detection of EGFR and KRAS Mutations in Advanced Lung Cancer

Adrian G. Sacher, MD1,2; Cloud Paweletz, PhD3; Suzanne E. Dahlberg, PhD4,5; Ryan S. Alden, BSc1; Allison O’Connell, BSc3; Nora Feeney, BSc3; Stacy L. Mach, BA1; Pasi A. Jänne, MD, PhD1,2,3; Geoffrey R. Oxnard, MD1,2

JAMA Oncol. Published online April 07, 2016.    http://dx.doi.org:/10.1001/jamaoncol.2016.0173

Importance  Plasma genotyping of cell-free DNA has the potential to allow for rapid noninvasive genotyping while avoiding the inherent shortcomings of tissue genotyping and repeat biopsies.

Objective  To prospectively validate plasma droplet digital PCR (ddPCR) for the rapid detection of common epidermal growth factor receptor (EGFR) and KRAS mutations, as well as the EGFR T790M acquired resistance mutation.

Design, Setting, and Participants  Patients with advanced nonsquamous non–small-cell lung cancer (NSCLC) who either (1) had a new diagnosis and were planned for initial therapy or (2) had developed acquired resistance to an EGFR kinase inhibitor and were planned for rebiopsy underwent initial blood sampling and immediate plasma ddPCR for EGFR exon 19 del, L858R, T790M, and/or KRAS G12X between July 3, 2014, and June 30, 2015, at a National Cancer Institute–designated comprehensive cancer center. All patients underwent biopsy for tissue genotyping, which was used as the reference standard for comparison; rebiopsy was required for patients with acquired resistance to EGFR kinase inhibitors. Test turnaround time (TAT) was measured in business days from blood sampling until test reporting.

Main Outcomes and Measures  Plasma ddPCR assay sensitivity, specificity, and TAT.

Results  Of 180 patients with advanced NSCLC (62% female; median [range] age, 62 [37-93] years), 120 cases were newly diagnosed; 60 had acquired resistance. Tumor genotype included 80 EGFR exon 19/L858R mutants, 35 EGFR T790M, and 25 KRASG12X mutants. Median (range) TAT for plasma ddPCR was 3 (1-7) days. Tissue genotyping median (range) TAT was 12 (1-54) days for patients with newly diagnosed NSCLC and 27 (1-146) days for patients with acquired resistance. Plasma ddPCR exhibited a positive predictive value of 100% (95% CI, 91%-100%) for EGFR 19 del, 100% (95% CI, 85%-100%) for L858R, and 100% (95% CI, 79%-100%) for KRAS, but lower for T790M at 79% (95% CI, 62%-91%). The sensitivity of plasma ddPCR was 82% (95% CI, 69%-91%) for EGFR 19 del, 74% (95% CI, 55%-88%) for L858R, and 77% (95% CI, 60%-90%) for T790M, but lower for KRAS at 64% (95% CI, 43%-82%). Sensitivity for EGFR or KRAS was higher in patients with multiple metastatic sites and those with hepatic or bone metastases, specifically.

Conclusions and Relevance  Plasma ddPCR detected EGFR and KRAS mutations rapidly with the high specificity needed to select therapy and avoid repeat biopsies. This assay may also detect EGFR T790M missed by tissue genotyping due to tumor heterogeneity in resistant disease.

Plasma genotyping uses tumor-derived cell-free DNA (cfDNA) to allow for rapid noninvasive genotyping of tumors. This technology is currently poised to transition into a treatment decision-making tool in multiple cancer types. It is particularly relevant to the treatment of advanced non–small-cell lung cancer (NSCLC), in which therapy hinges on rapid and accurate detection of targetable epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), and ROS1 alterations.1– 6Plasma genotyping is capable of circumventing many limitations of standard tissue genotyping including slow turnaround time (TAT), limited tissue for testing, and the potential for failed biopsies. It may be particularly useful in directing the rapid use of new targeted therapies for acquired resistance in advanced EGFR-mutant NSCLC, where the need for a repeat biopsy to test for resistance mechanisms has amplified the inherent limitations of traditional genotyping.7,8

The need to carefully validate the test characteristics of each of the myriad individual plasma genotyping assays before use in clinical decision making is paramount. We have previously reported the development of a quantitative droplet digital polymerase chain reaction (ddPCR)-based assay for the detection of EGFR kinase mutations andKRAS codon 12 mutations in plasma.9 The detection of these mutations has the potential to guide treatment by either facilitating targeted therapy with an EGFR tyrosine kinase inhibitor (TKI) or ruling out the presence of other potentially targetable alterations in the case of KRAS.5 Alternative platforms including Cobas, peptide nucleic acid–mediated PCR, multiplexed next-generation sequencing (NGS), high-performance liquid chromatography, and Scorpion–amplified refractory mutation system have also been examined in retrospective analyses of patient samples.10– 22 The test characteristics of these assays have been variable and may be attributable to differences in testing platforms, as well as the retrospective nature of these studies, their smaller size, and the timing of blood collection with respect to disease progression and therapy initiation. The absence of reliable prospective data on the use of specific plasma genotyping assays in advanced NSCLC has left key aspects of its utility largely undefined and slowed its uptake as a tool for clinical care in patients with both newly diagnosed NSCLC and EGFR acquired resistance.

To our knowledge, we have conducted the first prospective study of the use of ddPCR-based plasma genotyping for the detection of EGFR and KRAS mutations. This study was performed in the 2 settings where we anticipate clinical adoption of this assay: (1) patients with newly diagnosed advanced NSCLC and (2) those with acquired resistance to EGFR kinase inhibitors. The primary aim of this study was to prospectively evaluate the feasibility and accuracy of this assay for the detection ofEGFR/KRAS mutations in patients with newly diagnosed NSCLC and EGFR T790M in patients with acquired resistance in a clinical setting. Additional end points included test TAT and the effect of sample treatment conditions on test accuracy.

Key Points
  • Question What is the sensitivity, specificity, turnaround time, and robustness of droplet digital polymerase chain reaction (ddPCR)-based plasma genotyping for the rapid detection of targetable genomic alterations in patients with advanced non–small-cell lung cancer (NSCLC)?

  • Findings In this study of 180 patients with advanced NSCLC (120 newly diagnosed, 60 with acquired resistance to epidermal growth factor receptor [EGFR] kinase inhibitors), plasma genotyping exhibited perfect specificity (100%) and acceptable sensitivity (69%-80%) for the detection of EGFR-sensitizing mutations with rapid turnaround time (3 business days). Specificity was lower for EGFR T790M (63%), presumably secondary to tumor heterogeneity and false-negative tissue genotyping.

  • Meaning The use of ddPCR-based plasma genotyping can detect EGFR mutations with the rigor necessary to direct clinical care. This assay may obviate repeated biopsies in patients with positive plasma genotyping results.

CYP3A7*1C Allele Associated With Poor Outcomes in CLL, Breast, and Lung Cancer

 http://www.oncotherapynetwork.com/breast-cancer-targets/cyp3a71c-allele-associated-poor-outcomes-cll-breast-and-lung-cancer#sthash.7uiD8XFD.dpuf

Patients with the CYP3A7*1C allele suffer higher rates of cancer progression and mortality, possibly because of worse outcomes among patients treated with chemotherapy drugs that are broken down by the enzyme encoded by CYP3A7, according to authors of a retrospective study published in the journal Cancer Research.

“We found that individuals with breast cancer, lung cancer, or CLL [chronic lymphocytic leukemia] who carry one or more copy of the CYP3A7*1C allele tend to have worse outcomes,” said Olivia Fletcher, PhD, a senior investigator at the Breast Cancer Now Toby Robins Research Centre at the Institute of Cancer Research in London, England, in an American Association for Cancer Research (AACR) news release.

Approximately 8% of cancer patients harbor the CYP3A7*1C allele, the coauthors noted. For these patients, it is possible that standard chemotherapy with CYP3A substrates “may not be optimal,” they cautioned.

The team analyzed DNA samples from 1,008 patients with breast cancer, 1,128 patients with lung cancer, and 347 patients with CLL. They found that the CYP3A7*1C-associated single nucleotide polymorphism (SNP) rs45446698 is associated with increased breast cancer mortality (hazard ratio [HR] 1.74; P = .03), all-cause mortality among patients with lung cancer (HR 1.43; P = .009), and progression of CLL (HR 1.62; P = .03). The rs45446698 SNP is one of seven SNPs that form the CYP3A7*1C allele.

The CYP3A7*1C allele is expressed in adults, whereas other variants of CYP3A7 are expressed during fetal development. CYP3A7 encodes an enzyme that degrades estrogen and testosterone, and some anticancer drugs.

“We also found borderline evidence of a statistical interaction between the CYP3A7*1C allele, treatment of patients with a cytotoxic agent that is a CYP3A substrate, and clinical outcome (P = .06),” they noted.

“Even though we did not see a statistically-significant difference when stratifying patients by treatment with a CYP3A7 substrate, the fact that we see the same effect in three very different cancer types suggests to me that it is more likely to be something to do with treatment than the disease itself,” commented Dr. Fletcher. “However, we are looking at ways of replicating these results in additional cohorts of patients and types of cancer, as well as overcoming the limitations of this study.”

Limitations included the retrospective nature of the study and the absence of data on how quickly individual patients metabolized chemotherapeutic agents, she said.

 

Cytochrome P450 AlleleCYP3A7*1C Associates with Adverse Outcomes in Chronic Lymphocytic Leukemia, Breast, and Lung Cancer

Nichola Johnson1,2Paolo De Ieso3Gabriele Migliorini4,….., Gillian Ross12Richard S. Houlston, and Olivia Fletcher1,2,*

Cancer Res March 10, 2016; http://dx.doi.org:/10.1158/0008-5472.CAN-15-1410

CYP3A enzymes metabolize endogenous hormones and chemotherapeutic agents used to treat cancer, thereby potentially affecting drug effectiveness. Here, we refined the genetic basis underlying the functional effects of a CYP3A haplotype on urinary estrone glucuronide (E1G) levels and tested for an association betweenCYP3A genotype and outcome in patients with chronic lymphocytic leukemia (CLL), breast, or lung cancers. The most significantly associated SNP was rs45446698, an SNP that tags the CYP3A7*1Callele; this SNP was associated with a 54% decrease in urinary E1G levels. Genotyping this SNP in 1,008 breast cancer, 1,128 lung cancer, and 347 CLL patients, we found that rs45446698 was associated with breast cancer mortality (HR, 1.74; P = 0.03), all-cause mortality in lung cancer patients (HR, 1.43; P = 0.009), and CLL progression (HR, 1.62; P= 0.03). We also found borderline evidence of a statistical interaction between the CYP3A7*1C allele, treatment of patients with a cytotoxic agent that is a CYP3A substrate, and clinical outcome (Pinteraction = 0.06). The CYP3A7*1C allele, which results in adult expression of the fetal CYP3A7 gene, is likely to be the functional allele influencing levels of circulating endogenous sex hormones and outcome in these various malignancies. Further studies confirming these associations and determining the mechanism by which CYP3A7*1C influences outcome are required. One possibility is that standard chemotherapy regimens that include CYP3A substrates may not be optimal for the approximately 8% of cancer patients who are CYP3A7*1C carriers. Cancer Res; 76(6); 1–9. ©2016 AACR.

 

​Specific Form of CYP3A7 Gene Associated With Poor Outcomes for Patients With Several Cancer Types

3/10/2016

PHILADELPHIA — Among patients with breast cancer, lung cancer, or chronic lymphocytic leukemia (CLL), those who had a specific form of the CYP3A7 gene (CYP3A7*1C) had worse outcomes compared with those who did not have CYP3A7*1C, and this may be related to how the patients metabolize, or break down, the therapeutics used to treat them, according to a study published in Cancer Research, a journal of the American Association for Cancer Research.

“The CYP3A7 gene encodes an enzyme that breaks down all sorts of naturally occurring substances—such as sex steroids like estrogen and testosterone—as well as a wide range of drugs that are used in the treatment of cancer,” saidOlivia Fletcher, PhD, a senior investigator at the Breast Cancer Now Toby Robins Research Centre at The Institute of Cancer Research in London. “The CYP3A7 gene is normally turned on in an embryo and then turned off shortly after a baby is born, but individuals who have one or more copy of the CYP3A7*1C form of the gene [the CYP3A7*1C allele] turn on their CYP3A7 gene in adult life.

“We found that individuals with breast cancer, lung cancer, or CLL who carry one or more copy of the CYP3A7*1C allele tend to have worse outcomes,” continued Fletcher. “One possibility is that these patients break down the drugs that they are given to treat their cancer too fast. However, further independent studies that replicate our findings in larger numbers of patients and rule out biases are needed before we could recommend any changes to the treatment that cancer patients with the CYP3A7*1C allele receive.”

To find out whether the CYP3A7*1C allele was associated with outcome for patients with breast cancer, lung cancer, or CLL, Fletcher and colleagues analyzed DNA samples from 1,008 breast cancer patients, 1,142 patients with lung cancer, and 356 patients with CLL for the presence of a single nucleotide polymorphism (SNP), rs45446698. Fletcher explained that a SNP is a type of genetic variant and that because of the way that we inherit our genetic material from our parents, we tend to inherit clusters of genetic variants. She went on to say that rs45446698 is one of seven SNPs that cluster together, forming the CYP3A7*1C allele.

The researchers found that among the breast cancer patients, rs45446698 (and, therefore, the CYP3A7*1C allele) was associated with a 74 percent increased risk of breast cancer mortality. Among the lung cancer patients, it was associated with a 43 percent increased risk of death from any cause, and among the CLL patients, it was associated with a 62 percent increased risk of disease progression.

Patients who were treated with a chemotherapeutic broken down by CYP3A7 tended to have worse outcomes compared with those treated with other chemotherapeutics, but the difference was not statistically significant.

“Even though we did not see a statistically significant difference when stratifying patients by treatment with a CYP3A7 substrate, the fact that we see the same effect in three very different cancer types suggests to me that it is more likely to be something to do with treatment than the disease itself,” said Fletcher. “However, we are looking at ways of replicating these results in additional cohorts of patients and types of cancer, as well as overcoming the limitations of this study.”

Fletcher explained that the main limitation of the study is that the researchers used samples and clinical information collected for other studies. Therefore, they did not have the same clinical information for each patient, and the samples were collected at different time points and for patients treated with various chemotherapeutics. She also noted that the team were not able to determine how quickly the patients broke down the therapeutics they received as treatment.

The study was supported by Breast Cancer Now, Leukaemia and Lymphoma Research (now known as Bloodwise), Cancer Research UK, the Medical Research Council, the Cridlan Trust, the Helen Rollason Cancer Charity, and Sanofi-Aventis. Funding for the authors’ institutions was received from the National Health Service of the United Kingdom. Fletcher declares no conflicts of interest.

 

Liquid Biopsy for NSCLC

‘Liquid biopsy’ blood test accurately detects key genetic mutations in most common form of lung cancer, study finds.

http://www.technologynetworks.com/Diagnostics/news.aspx?ID=190276

A simple blood test can rapidly and accurately detect mutations in two key genes in non-small cell lung tumors, researchers at Dana-Farber Cancer Institute and other institutions report in a new study – demonstrating the test’s potential as a clinical tool for identifying patients who can benefit from drugs targeting those mutations.

The test, known as a liquid biopsy, proved so reliable in the study that Dana-Farber/Brigham and Women’s Cancer Center (DF/BWCC) expects to offer it soon to all patients with non-small cell lung cancer (NSCLC), either at the time of first diagnosis or of relapse following previous treatment.

…….

“Our study was the first to demonstrate prospectively that a liquid biopsy technique can be a practical tool for making treatment decisions in cancer patients. The trial was such a success that we are transitioning the assay into a clinical test for lung cancer patients at DF/BWCC.”

The study involved 180 patients with NSCLC, 120 of whom were newly diagnosed, and 60 of whom had become resistant to a previous treatment, allowing the disease to recur. Participants’ cell-free DNA was tested for mutations in the EGFR and KRAS genes, and for a separate mutation in EGFR that allows tumor cells to become resistant to front-line targeted drugs. The test was performed with a technique known as droplet digital polymerase chain reaction (ddPCR), which counts the individual letters of the genetic code in cell-free DNA to determine if specific mutations are present. Each participant also underwent a conventional tissue biopsy to test for the same mutations. The results of the liquid biopsies were then compared to those of the tissue biopsies.

The data showed that liquid biopsies returned results much more quickly. The median turnaround time for liquid biopsies was three days, compared to 12 days for tissue biopsies in newly diagnosed patients and 27 days in drug-resistant patients.

Liquid biopsy was also found to be highly accurate. In newly diagnosed patients, the “predictive value” of plasma ddPCR was 100 percent for the primary EGFR mutation and the KRAS mutation – meaning that a patient who tested positive for either mutation was certain to have that mutation in his or her tumor. For patients with the EGFR resistance mutation, the predictive value of the ddPCR test was 79 percent, suggesting the blood test was able to find additional cases with the mutation that were missed using standard biopsies.

Prospective Validation of Rapid Plasma Genotyping for the Detection of EGFRand KRAS Mutations in Advanced Lung Cancer

Adrian G. Sacher, MD1,2; Cloud Paweletz, PhD3; Suzanne E. Dahlberg, PhD, et al.       JAMA Oncol. Published online April 07, 2016.  http://dx.doi.org::/10.1001/jamaoncol.2016.0173

Importance  Plasma genotyping of cell-free DNA has the potential to allow for rapid noninvasive genotyping while avoiding the inherent shortcomings of tissue genotyping and repeat biopsies.

Objective  To prospectively validate plasma droplet digital PCR (ddPCR) for the rapid detection of common epidermal growth factor receptor (EGFR) and KRAS mutations, as well as the EGFR T790M acquired resistance mutation.

Design, Setting, and Participants  Patients with advanced nonsquamous non–small-cell lung cancer (NSCLC) who either (1) had a new diagnosis and were planned for initial therapy or (2) had developed acquired resistance to an EGFR kinase inhibitor and were planned for rebiopsy underwent initial blood sampling and immediate plasma ddPCR for EGFR exon 19 del, L858R, T790M, and/or KRAS G12X between July 3, 2014, and June 30, 2015, at a National Cancer Institute–designated comprehensive cancer center. All patients underwent biopsy for tissue genotyping, which was used as the reference standard for comparison; rebiopsy was required for patients with acquired resistance to EGFR kinase inhibitors. Test turnaround time (TAT) was measured in business days from blood sampling until test reporting.

Main Outcomes and Measures  Plasma ddPCR assay sensitivity, specificity, and TAT.

Results  Of 180 patients with advanced NSCLC (62% female; median [range] age, 62 [37-93] years), 120 cases were newly diagnosed; 60 had acquired resistance. Tumor genotype included 80 EGFR exon 19/L858R mutants, 35 EGFR T790M, and 25 KRASG12X mutants. Median (range) TAT for plasma ddPCR was 3 (1-7) days. Tissue genotyping median (range) TAT was 12 (1-54) days for patients with newly diagnosed NSCLC and 27 (1-146) days for patients with acquired resistance. Plasma ddPCR exhibited a positive predictive value of 100% (95% CI, 91%-100%) for EGFR 19 del, 100% (95% CI, 85%-100%) for L858R, and 100% (95% CI, 79%-100%) for KRAS, but lower for T790M at 79% (95% CI, 62%-91%). The sensitivity of plasma ddPCR was 82% (95% CI, 69%-91%) for EGFR 19 del, 74% (95% CI, 55%-88%) for L858R, and 77% (95% CI, 60%-90%) for T790M, but lower for KRAS at 64% (95% CI, 43%-82%). Sensitivity for EGFR or KRAS was higher in patients with multiple metastatic sites and those with hepatic or bone metastases, specifically.

Conclusions and Relevance  Plasma ddPCR detected EGFR and KRAS mutations rapidly with the high specificity needed to select therapy and avoid repeat biopsies. This assay may also detect EGFR T790M missed by tissue genotyping due to tumor heterogeneity in resistant disease.

 

In this prospective study, we demonstrate the highly specific and rapid nature of plasma genotyping. No false-positive test results were seen for driver mutations inEGFR or KRAS, and TAT from when the specimen was obtained to result was a matter of days. This assay exhibited 100% positive predictive value for the detection of these mutations. Sensitivity was more modest and was directly correlated with both number of metastatic sites and the presence of liver or bone metastases. This newly demonstrated relationship is likely related to increased cfDNA shed in the setting of more extensive disease where tumor cfDNA shed is the chief driver of assay sensitivity and determines its upper limit. The characteristics of plasma ddPCR prospectively demonstrated in this study were similar or improved compared with previous retrospective reports of other cfDNA genotyping assays.10– 13,15,16,24,25 These retrospective studies are smaller, frequently examined a mix of tumor types and/or stages, and lack the careful prospective design needed to demonstrate the readiness of this technology to transition to a tool for selecting therapy. Studies that use retrospective samples from clinical trials that enrolled only EGFR-mutant patients are further limited by an inability to both blind laboratory investigators to tissue genotype and to generalize their assay test characteristics to a genetically heterogeneous real-world patient population.11 These differences and the multiple platforms examined previously have led to variable test characteristics and uncertainty regarding the clinical application of these technologies. This study is the first to prospectively demonstrate the ability of a ddPCR-based plasma genotyping assay to rapidly and accurately detect EGFR and KRAS mutations in a real-world clinical setting with the rigor necessary to support the assertion that use of this assay is capable of directing clinical care.

Even with a diagnostic sensitivity of less than 100%, such a rapid assay with 100% positive predictive value carries the potential for immense clinical utility. The 2- to 3-day TAT contrasts starkly with the 27-day TAT for tumor genotyping seen in patients needing a new tumor biopsy. This long TAT is due largely to the practical reality that many patients with newly diagnosed NSCLC require a repeat biopsy to obtain tissue for genotyping, as do all patients with acquired resistance. Consider the case of 1 study participant, an octogenarian with metastatic NSCLC who had developed acquired resistance to erlotinib with painful bone metastases (Figure 3). Due to the patient’s age and comorbidities, significant concerns existed about the risks of a biopsy and further systemic therapy. A plasma sample was obtained, and within 24 hours ddPCR demonstrated 806 copies/mL of EGFR T790M. A confirmatory lung biopsy was performed, which confirmed EGFR T790M. Treatment with a third-generation EGFR kinase inhibitor, osimertinib mesylate, was subsequently initiated and the patient had a partial response to therapy that was maintained for more than 1 year. The potential of this technology to obviate repeated biopsy in both patients with newly diagnosed NSCLC with insufficient tissue, as well as patients with acquired resistance, is considerable.

A key limitation of plasma ddPCR is that although this method is adept at rapidly detecting specific targetable mutations, it cannot easily detect copy number alterations and rearrangements. The ddPCR panel assessed in this study thus cannot currently detect targetable alterations in either ALK or ROS1. This limitation may potentially be addressed by using targeted NGS of cfDNA for broad, multiplexed detection of complex genomic alterations including ALK and ROS1 rearrangements, although this method is potentially slower than ddPCR-based methods and has been less thoroughly evaluated.23 The potential exists to use these technologies in tandem in advanced NSCLC to facilitate rapid initiation of therapy. Tissue genotyping and repeated biopsy would be specifically used to direct therapy in cases in which plasma genotyping was uninformative due to limitations of assay sensitivity. This approach would be particularly useful in cases of EGFR acquired resistance in which a repeated biopsy for T790M testing could be avoided entirely in many patients. Beyond detecting targetable alterations in order to drive therapy, the identification of nontargetable oncogenic drivers such as KRAS mutations that preclude the presence of other targetable alterations may guide a clinician to rapidly initiate alternative therapies such as chemotherapy or immunotherapy.5 The finding that assay sensitivity is highest in patients with more extensive metastatic disease suggests that those patients most in need of rapid treatment initiation would also be least likely to have false-negative results.

One surprising result of our study was evidence of recurrent false-positive results forEGFR T790M in patients with acquired resistance, despite no false-positive test results for other mutations studied. The sensitivity of the EGFR T790M assay was comparable to that of the EGFR sensitizing mutation assays and similarly related to both disease burden and the presence of liver or bone metastases, which are likely predictive of increased tumor cfDNA shed. We hypothesize that the lower assay specificity is due to the genomic heterogeneity whereby the T790M status of the biopsied site is not representative of all metastatic sites in a patient, a phenomenon supported by mounting evidence in the acquired resistance setting.26,27 This is consistent with the finding that a minority of patients with apparently EGFR T790M tissue-negative disease respond to therapy with third-generation EGFR kinase inhibitors.7,8,28 These observations raise questions regarding the fallibility of tissue-based genotyping as the reference standard for T790M status. The use of plasma genotyping to detect EGFR T790M thus has great potential to identify patients who would benefit from newly approved third-generation EGFR kinase inhibitors but would be unable to access them based on falsely negative tissue genotyping results. Indeed, plasma genotyping may allow more reliable assessment of both T790M status as well as the mechanisms of resistance across all sites of a heterogeneous cancer as opposed to a tissue biopsy and is likely to be an essential tool for future trials targeting drug resistance. The potential to avoid a repeat biopsy entirely in patients in whom plasma ddPCR detects T790M further strengthens the utility of this technology, although a repeat biopsy would still be needed in patients with uninformative plasma ddPCR due to limitations with respect to assay sensitivity.

This study also examined the potential of the quantitative nature of ddPCR-based plasma genotyping to allow for the early prediction of treatment response. Distinct patterns of change in mutant allele copy number were observed as early as 2 weeks after treatment and were similar to those reported in other tumor types.19,20 We hypothesize that these distinct patterns of change in this study will correlate with specific patterns of radiographic response and emergence of acquired resistance and plan to report these data once mature. The observed differences in treatment discontinuation rates observed in this study comparing patients with complete resolution of detectable mutant cfDNA with those with incomplete resolution support this hypothesis. The use of this technology to monitor disease status in real time has potential utility for both routine clinical care, as well as use as an integrated biomarker in early-phase clinical trials.10

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Prognostic biomarker for NSCLC and Cancer Metastasis

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Membranous CD24 expression as detected by the monoclonal antibody SWA11 is a prognostic marker in non-small cell lung cancer patients

Michael MajoresAnne SchindlerAngela FuchsJohannes SteinLukas HeukampPeter Altevogt and Glen Kristiansen

BMC Clinical Pathology201515:19   http://dx.doi.org:/10.1186/s12907-015-0019-z

Background    Lung cancer is one of the most common malignant neoplasms worldwide and has a high mortality rate. To enable individualized therapy regimens, a better understanding of the molecular tumor biology has still to be elucidated. The expression of the cell surface protein CD24 has already been claimed to be associated with shorter patient survival in non-small cell lung cancer (NSCLC), however, the prognostic value and applicability of CD24 immunostaining in paraffin embedded tissue specimens has been questioned due to the recent acknowledgement of restricted epitope specificity of the commonly used antibody SN3b.   Methods    A cohort of 137 primary NSCLC cases was immunostained with a novel CD24 antibody (clone SWA11), which specifically recognizes the CD24 protein core and the resulting expression data were compared with expression profiles based on the monoclonal antibody SN3b. Furthermore, expression data were correlated to clinico-pathological parameters. Univariate and multivariate survival analyses were conducted with Kaplan Meier estimates and Cox regression, respectively. Results    CD24 positivity was found in 34 % resp. 21 % (SN3b) of NSCLC with a membranous and/or cytoplasmic staining pattern. Kaplan-Meier analyses revealed that membranous, but not cytoplasmic CD24 expression (clone SWA11) was associated with lympho-nodular spread and shorter overall survival times (both p < 0.05). CD24 expression established by SN3b antibodies did not reveal significant clinicopathological correlations with overall survival, neither for cytoplasmic nor membranous CD24 staining.  Conclusions    Membranous CD24 immunoreactivity, as detected with antibody clone SWA11 may serve as a prognostic factor for lymphonodular spread and poorer overall survival. Furthermore, these results corroborate the importance of a careful distinction between membranous and cytoplasmic localisation, if CD24 is to be considered as a potential prognostic biomarker.

 

Lung cancer is a major cause of carcinoma related death, being responsible for 17.8 % of all cancer deaths and accounting for more than a million deaths worldwide per year [1]. Despite intense studies to improve therapy options, its prognosis has remained poor with a 5-year overall survival rate of less than 15 % [2].

In the past decade, the largest subgroup of lung cancer, i.e. non-small cell lung cancer (NSCLC), has been subjected to exerted research for a better understanding of the underlying molecular biology of lung cancer. More than ten years ago, CD24 has already been suggested as a novel and promising biomarker for carcinoma progression in NSCLC [3] and several groups have confirmed this finding on protein and transcript level [2, 4]. CD24 is a highly glycosylated protein, that binds to the cell surface through a GPI (glycosyl-phosphatidylinositol)-anchor and functions as a cell adhesion molecule and is involved in cell-cell-interaction via its P-selectin binding site [5]. CD24 has been found to be expressed by pre-B-lymphocytes [5]. It is assumed that CD24-positive cells can attach more easily to platelets and activated endothelial cells [6, 7]. Notably, CD24 has also been observed in many human carcinomas, such as ovarian cancer, renal cell cancer, breast cancer and NSCLC [3, 812]. In epithelial ovarian cancer high scores of cytoplasmic CD24 were highly predictive of shorter patient survival times (mean 97.8 vs. 36.5 months), whereas membranous CD24 expression seemed to have no influence on survival times. Interestingly, CD24 positivity (membranous or cytoplasmic) of prostate cancer samples was significantly associated to younger patient age and higher pT stages and a higher 3-year prostate-specific antigen (PSA) relapse rate compared with CD24-negative tumours.

In patients with gallbladder carcinoma, tumors with up-regulation of CD24 revealed lymph node metastasis and lymphovascular invasion more frequently. Moreover, up-regulation of CD24 tended to show deeper invasion depth and higher TNM stage [13]. Together, these findings support CD24 as a prognostic marker for carcinoma progression and poorer survival.

Despite these intriguing findings, major concerns regarding a lack of epitope specificity of the commonly used monoclonal antibody SN3b have been raised [14]. Recent findings indicate that the mAb (monoclonal antibody) SN3b does not bind to the protein core itself, but binds to a glycan structure that decorates the CD24 molecule. On the one hand, this motif is not present on all forms of CD24 and—on the other hand—it can be present in other epitopes irrespective of CD24 [14]. These limitations underline the need for more specific CD24 antibodies, such as the mAb SWA11 antibody that has been suggested to be more specific as it binds to the protein core [14].

As CD24 is a promising biomarker for the risk assessment of disease progression, the goal of the present study was to investigate CD24 expression in NSCLC using the novel, more specific monoclonal antibody (mAb) SWA11. Special emphasis was put on the comparison of SN3b- and SWA11-mediated CD24 detection regarding a) the subcellular distribution of CD24 expression (i.e. membranous versus cytoplasmic expression) and b) its correlation with various clinicopathological features including patient survival times.

Table 1

Clinicopathological characteristics of the NSCLC cohort

  AC SCC
N (%) N (%)
Tumour stage (pT)
1 29 (21.2 %) 5 (3.6)
2 51 (37.2 %) 23 (16.8 %)
3 6 (4.4 %) 6 (4.4 %)
4 1 (0.7 %) 0 (0 %)
Nodal Status (pN) 0 37 (27.0 %) 15 (10.9 %)
1 15 (10.9 %) 9 (6.6 %)
2 14 (10.2 %) 3 (2.2 %)
3 1 (0.7 %) 0 (0.0 %)
Grading (G) 1 5 (3.6 %) 0 (0.0 %)
2 41 (29.9 %) 16 (11.6 %)
3 44 (32.1 %) 17 (12.4 %)
Mean age at surgery 64,2 64,56
(median age) (65) (67)
Sex (m:w) 68:34 30:5
Median OS (months) 52 24
(SD; 95 % CI [months]) (±23.7; 5.5– 98.5) (± 12.8;0.0– 49.0)

 

Immunohistochemical detection of CD24 expression using clone SWA11 and SN3b

Using the mAb SWA11, 47 of 137 (34.3 %) NSCLC revealed CD24 expression (either cytoplasmic or membranous) (Table 2). CD24 expression was observed more frequently in adenocarcinomas (AC) than in squamous cell carcinomas (SCC). In AC cytoplasmic expression was observed more frequently than membranous expression. In SCC, both cyptoplasmic and membranous expression was rare. Normal lung parenchyma (i.e. alveolar surface cells) showed no expression of CD24. Bronchial epithelium showed a strong membranous and cytoplasmic staining of the brush border (Fig. 1).

Table 2

Cytoplasmic and membranous expression of CD24

SWA11 (mAb clone) SN3b (mAB clone)
  AC SCC   AC SCC
Cytoplasmic N (%) N (%) Cytoplasmic N (%) N (%)
0 45 (32.6 %) 19 (13.8 %) 0 76 (55.1 %) 31 (22.5 %)
1 22 (15.9 %) 8 (5.8 %) 1 12 (8.7 %) 1 (0.7 %)
2 17 (12.3 %) 4 (2.9 %) 2 7 (5.1 %) 2 (1.4 %)
3 18 (13.0 %) 4 (2.9 %) 3 1 (0.7 %) 0 (0 %)
AC SCC AC SCC
Membranous N (%) N (%) Membranous N (%) N (%)
0 68 (49.3 %) 21 (15.2 %) 0 64 (46.4 %) 30 (21.7 %)
1 21 (15.2 %) 5 (3.6 %) 1 10 (7.2 %) 2 (1.4 %)
2 8 (5.8 %) 4 (2.9 %) 2 12 (8.7 %) 2 1.4 %)
3 5 (3.6 %) 5 (3.6 %) 3 10 (7.2 %) 0 (0 %)

Staining intensities are determined as follows:

0: negative or equivocal, 1: weak, 2: moderate and 3: strong CD24 staining

 

https://static-content.springer.com/image/art%3A10.1186%2Fs12907-015-0019-z/MediaObjects/12907_2015_19_Fig1_HTML.gif

Fig 1

The immunohistochemical characterization reveals membranous and/or cytoplasmic CD24 (mAb SWA11) expression. Strong cytoplasmic CD24 expression is found in a proportion of both AC (a) and SCC (b, d) specimens. Membranous CD24 expression can be pronounced with only scant or even absent cytoplasmic staining as shown in the AC (c). Also, both membranous and cytoplasmic CD24 detection can be found in some instances (d), the insert is showing the corresponding squamous carcinoma in-situ with membranous staining. Simultaneous membranous and cytoplasmic CD24 expression is also found in AC specimens (e, f). In normal tissue, alveolar epithelial cells do not express CD24 (g), whereas CD24 staining is found at the apical cell membrane of bronchial respiratory epithelia (h)

Using the mAb SN3b, 29 of 137 (21.2 %) NSCLC revealed CD24 expression (either cytoplasmic or membranous) (Table 2). As above, CD24 expression was observed more frequently in adenocarcinomas (AC) than in squamous cell carcinomas (SCC). However, in contrast to mAb SWA11 cytoplasmic expression was observed less frequently than membranous expression in AC. In SCC, both cytoplasmic and membranous expression was rare. Normal lung parenchyma (i.e. alveolar surface cells) showed a distinct membranous immunoreactivity. Bronchial epithelium revealed both membranous and cytoplasmic staining of CD24.

Correlation between SWA11 and SN3b: As SWA11 and SN3b detect different epitopes, we evaluated the correlation of the immunohistochemical staining patterns. Of 132 NSCLC specimens with matched expression data, only 9 specimens (6.8 %) revealed a concordant CD24 expression. Of these cases, 4 cases revealed a concordant cytoplasmic staining and another 5 cases revealed a concordant membranous CD24 expression. Statistically, no significant correlation between the two mAb could be observed (cc = −0.63, p = 0.470; Fisher’s exact test p = 0.665). The correlation of cytoplasmic and membranous expression (for each antibody) was as follows: cc = 0.475 (p < 0.05) for SWA11 (n = 108) and cc = 0.140 (p = 0.11) for SN3b (n = 103).

Survival analyses

Recent studies indicate that CD24 expression is associated with tumor progression and poorer survival rates. Therefore, we performed follow up analyses with a special emphasis on 1) the prognostic value of mAb SWA11 in dependence on subcellular staining characteristics and 2) the prognostic values of different clinicopathological parameters:

Prognostic value of CD24 in Kaplan Meier Analyses

Only membranous CD24 (SWA11) staining revealed significantly poorer survival rates (median overall survival 21 vs. 52 months; p = 0.005) as illustrated in Fig. 2. In contrast, cytoplasmic CD24 (SWA11) staining did not affect the survival rates (median OS 34 vs. 35 months; p = 0.884) (Table 3). When stratifying the cohort into SCC (n = 35) and AC (n = 102) in Kaplan Meier analyses, membranous CD24 (SWA11) expression did not affect patients’ survival, neither in SCC (p = 0.243) nor AC (p = 0.135) (Table 3), probably due to the small number of observations (Fisher exact test: p > 0.05). After stratification for AC subtypes, membranous CD24 expression (SWA11) showed a tendency towards an association with poorer survival in acinar subtype AC, but failed significance (p = 0.328).
https://static-content.springer.com/image/art%3A10.1186%2Fs12907-015-0019-z/MediaObjects/12907_2015_19_Fig2_HTML.gif

Fig 2

Survival analysis. Kaplan-Meier curves according to SWA11 expression. Cases with moderate to strong expression were bundled in a ‘high expression’ and cases with negative or weak expression in a ‘low expression’ group. Membranous expression of CD24 detected by SWA11 proved to be an independent marker for shorter survival times in NSCLC (p = 0.005)

Table 3

Univariate survival analysis

SWA11 No. of cases Mean survival time Median survival time p-value
(months +/− s.e.) (months +/− s.e.)
Mem CD24
Negative 76 84.833 +/− 10.395 52.000 +/− 27.030 0.005
Positive 16 27.925 +/− 6.379 21.000 +/− 4.000
Cyto CD24
Negative 66 75.209 +/− 10.577 35.000 +/− 12.422 0.884
Positive 26 60.540 +/− 11.551 34.000 +/− 12.196
Total CD24
Negative 64 76.972 +/− 10.841 35.000 +/− 13.726 0.633
Positive 28 57.535 +/− 10.895 34.000 +/− 9.303
SCC
Mem CD24 negative 16 52.063 +/− 14.668 16.000 +/− 16.000 0.243
Mem CD24 positive 7 21.571 +/− 7.201 24.000 +/− 23.568
AC
Mem CD24 negative 59 88.953 +/− 11.631 56.000 +/− 22.885 0.135
Mem CD24 positive 8 39.167 +/− 11.674 21.000 +/− 8.485
pN0 31 103.641 +/− 14.940 93.000 +/− 28.224 0.012
pN1+ 30 54.911 +/− 10.646 26.000 +/− 0.983

 

…..

Univariate survival analysis according to the Cox regression model (mAb SWA11)

  Beta HR (hazard ratio) 95 % CI of HR P-value
SWA11 mem all 0.856 2.353 1.268–4.364 0.007
pN 0.963 2.620 1.389–4.943 0.003
pT 0.844 2.325 1.279–4.224 0.006
Tumour type 0.975 2.651 1.999–3.517 0.000

Table 5

Multivariate survival analysis according to the Cox regression model (mAb SWA11)

  Beta HR (hazard ratio) 95 % CI of HR P-value
SWA11 mem all 0.944 2.571 1.211–5.458 0.014
pN 0.737 2.091 1.087–4.021 0.027
pT 0.587 1.799 0.755–4.283 0.185

 

…..

In the present study, we have analyzed immunohistochemical staining characteristics and the prognostic value of CD24 expression in NSCLC with a special emphasis on the comparison of the CD24 antibodies SWA11 and SN3b. The most important result of our study is that the prognostic relevance of CD24 is critically dependent on the careful consideration of sub-cellular compartments and the epitope specificity of the antibody used.

Overall, about one third of the NSCLC cohort revealed a significant CD24 expression (either cytoplasmic or membranous). These results are in line with the findings of other studies. In another NSCLC cohort, CD24 (SN3b) expression was found in 33 % of the samples (87 of 267 cases) [2]. Consistent with those results, we have found similar rates of high CD24 expression levels (35 % of the cases) for SWA11. Originally, we would have expected lower rates than those found by Lee et al, as they used the antibody SN3b, that also recognizes yet unidentified other glycoproteins next to CD24. Furthermore, they used whole mount sections instead of tissue microarrays. A possible explanation for rather equal detection rates would be the fact that it has been demonstrated that the epitope recognized by SN3b is indeed present in CD24, but is not found in all glycoforms of CD24 [14]. In contrast to the commonly used mAb SN3b, mAb SWA11 binds to the protein core of CD24 and does not depict other glycan moieties next to CD24. The protein core of CD24 is linear, consisting of the amino acid sequence leucine-proline-alanine (LAP) next to a glycosyl-phosphatidylinositol anchor [15].

CD24 expression has been associated with disease progression and cancer-related death in the majority of malignant tumors [2, 3, 16, 17], although a caveat to these data is that most of these studies are based on the supposedly less specific CD24 clone SN3b. Lee et al demonstrated a significant association between CD24-high expression (SN3b) and shorter patient survival times. Furthermore, Lee and colleagues and ourselves in former studies referred the results to cytoplasmic CD24 expression [2, 3].

Switching Off Cancers’ Ability to Spread

http://www.technologynetworks.com/rnai/news.aspx?ID=189704

A key molecule in breast and lung cancer cells can help switch off the cancers’ ability to spread around the body.

The findings by researchers at Imperial College London, published in the journal EMBO Reports, may help scientists develop treatments that prevent cancer travelling around the body – or produce some kind of test that allows doctors to gauge how likely a cancer is to spread. During tumour growth, cancer cells can break off and travel in the bloodstream or lymph system to other parts of the body, in a process called metastasis.

Patients whose cancers spread tend to have a worse prognosis, explains Professor Justin Stebbing, senior author of the study from the Department of Surgery and Cancer at Imperial: “The ability of a cancer to spread around the body has a large impact on a patient’s survival. However, at the moment we are still in the dark about why some cancers spread around the body – while others stay in one place. This study has given important insights into this process.”

The researchers were looking at breast and lung cancer cells and they found that a protein called MARK4 enables the cells to break free and move around to other parts of the body, such as the brain and liver. Although scientist are still unsure how it does this, one theory is it affects the cell’s internal scaffolding, enabling it to move more easily around the body. The team found that a molecule called miR-515-5p helps to silence, or switch off, the gene that produces MARK4.

In the study, the team used human breast cancer and lung cancer cells to show that the miR-515-5p molecule silences the gene MARK4. They then confirmed this in mouse models, which showed that increasing the amount of miR-515-5p prevents the spread of cancer cells. The findings also revealed that the silencer molecule was found in lower levels in human tumours that had spread around the body. The team then also established that patients with breast and lung cancers whose tumours had low amounts of these silencer molecules – or high amounts of MARK4 – had lower survival rates.

Researchers are now investigating whether either the MARK4 gene or the silencer molecule could be targeted with drugs. They are also investigating whether these molecules could be used to develop a test to indicate whether a patient’s cancer is likely to spread. Professor Stebbing said: “In our work we have shown that this silencer molecule is important in the spread of cancer. This is very early stage research, so we now need more studies to find out more about this molecule, and if it is present in other types of cancer.”

Dr Olivier Pardo, lead author of the paper, also from the Department of Surgery and Cancer at Imperial, added: “Our work also identified that MARK4 enables breast and lung cancer cells to both divide and invade other parts of the body. These findings could have profound implications for treating breast and lung cancers, two of the biggest cancer killers worldwide.” The study was supported by the NIHR Imperial Biomedical Research Centre, the Medical Research Council, Action Against Cancer and the Cancer Treatment and Research Trust.

 

‘Silencer molecules’ switch off cancer’s ability to spread around body

by Kate Wighton

main image

Scientists have revealed that a key molecule in breast and lung cancer cells can help switch off the cancers’ ability to spread around the body

The findings by researchers at Imperial College London, published in the journal EMBO Reports, may help scientists develop treatments that prevent cancer travelling around the body – or produce some kind of test that allows doctors to gauge how likely a cancer is to spread.

During tumour growth, cancer cells can break off and travel in the bloodstream or lymph system to other parts of the body, in a process called metastasis.

Patients whose cancers spread tend to have a worse prognosis, explains Professor Justin Stebbing, senior author of the study from the Department of Surgery and Cancer at Imperial: “The ability of a cancer to spread around the body has a large impact on a patient’s survival. However, at the moment we are still in the dark about why some cancers spread around the body – while others stay in one place. This study has given important insights into this process.”

The researchers were looking at breast and lung cancer cells and they found that a protein called MARK4 enables the cells to break free and move around to other parts of the body, such as the brain and liver. Although scientist are still unsure how it does this, one theory is it affects the cell’s internal scaffolding, enabling it to move more easily around the body.

 

miR‐515‐5p controls cancer cell migration through MARK4 regulation

Olivier E Pardo, Leandro Castellano, Catriona E Munro, Yili Hu, Francesco Mauri,Jonathan Krell, Romain Lara, Filipa G Pinho, Thameenah Choudhury, Adam EFrampton, Loredana Pellegrino, Dmitry Pshezhetskiy, Yulan Wang, JonathanWaxman, Michael J Seckl, Justin Stebbing    

EMBO reports http://embor.embopress.org/content/early/2016/02/10/embr.201540970     http://dx.doi.org:/
Here, we show that miR‐515‐5p inhibits cancer cell migration and metastasis. RNA‐seq analyses of both oestrogen receptor receptor‐positive and receptor‐negative breast cancer cells overexpressing miR‐515‐5p reveal down‐regulation of NRAS, FZD4, CDC42BPA, PIK3C2B and MARK4 mRNAs. We demonstrate that miR‐515‐5p inhibits MARK4 directly 3′ UTR interaction and that MARK4 knock‐down mimics the effect of miR‐515‐5p on breast and lung cancer cell migration. MARK4 overexpression rescues the inhibitory effects of miR‐515‐5p, suggesting miR‐515‐5p mediates this process through MARK4 down‐regulation. Furthermore, miR‐515‐5p expression is reduced in metastases compared to primary tumours derived from both in vivo xenografts and samples from patients with breast cancer. Conversely, miR‐515‐5p overexpression prevents tumour cell dissemination in a mouse metastatic model. Moreover, high miR‐515‐5p and low MARK4 expression correlate with increased breast and lung cancer patients’ survival, respectively. Taken together, these data demonstrate the importance of miR‐515‐5p/MARK4 regulation in cell migration and metastasis across two common cancers.
Embedded Image

miR‐515‐5p inhibits cancer progression, cell migration and metastasis through its direct target MARK4, a regulator of the cytoskeleton and cell motility. Moreover, reduced miR‐515‐5p and increased MARK4 levels in metastatic lung and breast cancer correlate with poor patient prognosis.

  • MARK4 down‐regulation promotes microtubule polymerisation.

  • Increased cell spreading downstream of miR‐515‐5p overexpression or MARK4 silencing hinders cell motility and invasiveness.

  • miR‐515‐5p overexpression or MARK4 silencing prevent organ colonisation by circulating tumour cells.

  • MARK4 inhibitors may represent novel therapeutic agents to control cancer dissemination.breasat cancer

 

Liquid Biopsy for NSCLC

http://www.technologynetworks.com/Diagnostics/news.aspx?ID=190276

‘Liquid biopsy’ blood test accurately detects key genetic mutations in most common form of lung cancer, study finds.

A simple blood test can rapidly and accurately detect mutations in two key genes in non-small cell lung tumors, researchers at Dana-Farber Cancer Institute and other institutions report in a new study – demonstrating the test’s potential as a clinical tool for identifying patients who can benefit from drugs targeting those mutations.

The test, known as a liquid biopsy, proved so reliable in the study that Dana-Farber/Brigham and Women’s Cancer Center (DF/BWCC) expects to offer it soon to all patients with non-small cell lung cancer (NSCLC), either at the time of first diagnosis or of relapse following previous treatment.

NSCLC is the most common form of lung cancer, diagnosed in more than 200,000 people in the United States each year, according to the American Cancer Society. An estimated 30 percent of NSCLC patients have mutations in either of the genes included in the study, and can often be treated with targeted therapies. The study is being published online today by the journal JAMA Oncology.

The liquid biopsy tested in the study – technically known as rapid plasma genotyping – involves taking a test tube-full of blood, which contains free-floating DNA from cancer cells, and analyzing that DNA for mutations or other abnormalities. (When tumor cells die, their DNA spills into the bloodstream, where it’s known as cell-free DNA.) The technique, which provides a “snapshot” of key genetic irregularities in a tumor, is a common tool in research for probing the molecular make-up of different kinds of cancers.

“We see plasma genotyping as having enormous potential as a clinical test, or assay – a rapid, noninvasive way of screening a cancer for common genetic fingerprints, while avoiding the challenges of traditional invasive biopsies,” said the senior author of the study, Geoffrey Oxnard, MD, thoracic oncologist and lung cancer researcher at Dana-Farber and Brigham and Women’s Hospital. “Our study was the first to demonstrate prospectively that a liquid biopsy technique can be a practical tool for making treatment decisions in cancer patients. The trial was such a success that we are transitioning the assay into a clinical test for lung cancer patients at DF/BWCC.”

The study involved 180 patients with NSCLC, 120 of whom were newly diagnosed, and 60 of whom had become resistant to a previous treatment, allowing the disease to recur. Participants’ cell-free DNA was tested for mutations in the EGFR and KRAS genes, and for a separate mutation in EGFR that allows tumor cells to become resistant to front-line targeted drugs. The test was performed with a technique known as droplet digital polymerase chain reaction (ddPCR), which counts the individual letters of the genetic code in cell-free DNA to determine if specific mutations are present. Each participant also underwent a conventional tissue biopsy to test for the same mutations. The results of the liquid biopsies were then compared to those of the tissue biopsies.

The data showed that liquid biopsies returned results much more quickly. The median turnaround time for liquid biopsies was three days, compared to 12 days for tissue biopsies in newly diagnosed patients and 27 days in drug-resistant patients.

Liquid biopsy was also found to be highly accurate. In newly diagnosed patients, the “predictive value” of plasma ddPCR was 100 percent for the primary EGFR mutation and the KRAS mutation – meaning that a patient who tested positive for either mutation was certain to have that mutation in his or her tumor. For patients with the EGFR resistance mutation, the predictive value of the ddPCR test was 79 percent, suggesting the blood test was able to find additional cases with the mutation that were missed using standard biopsies.

“In some patients with the EGFR resistance mutation, ddPCR detected mutations missed by standard tissue biopsy,” Oxnard remarked. “A resistant tumor is inherently made up of multiple subsets of cells, some of which carry different patterns of genetic mutations. A single biopsy is only analyzing a single part of the tumor, and may miss a mutation present elsewhere in the body. A liquid biopsy, in contrast, may better reflect the distribution of mutations in the tumor as a whole.”

When ddPCR failed to detect these mutations, the cause was less clear-cut, Oxnard says. It could indicate that the tumor cells don’t carry the mutations or, alternatively, that the tumor isn’t shedding its DNA into the bloodstream. This discrepancy between the test results and the presence of mutations was less common in patients whose cancer had metastasized to multiple sites in the body, researchers found.

The ddPCR-based test, or assay, was piloted and optimized for patients at the Translational Resarch lab of the Belfer Center for Applied Cancer Science at Dana-Farber. It was then validated for clinical use at Dana-Farber’s Lowe Center for Thoracic Oncology.

An advantage of this form of liquid biopsy is that it can help doctors quickly determine whether a patient is responding to therapy. Fifty participants in the study had repeat testing done after starting treatment for their cancer. “Those whose blood tests showed a disappearance of the mutations within two weeks were more likely to stay on the treatment than patients who didn’t see such a reduction,” said the study’s lead author, Adrian Sacher, MD, of Dana-Farber and Brigham and Women’s Hospital.

And because tumors are constantly evolving and acquiring additional mutations, repeated liquid biopsies can provide early detection of a new mutation – such as the EGFR resistance mutation – that can potentially be treated with targeted agents.

“The study data are compelling,” said DF/BWCC pathologist Lynette Sholl, MD, explaining the center’s decision to begin offering ddPCR-based liquid biopsy to all lung cancer patients. “We validated the authors’ findings by cross-comparing results from liquid and tissue biopsies in 34 NSCLC patients. To work as a real-world clinical test, liquid biopsy needs to provide reliable, accurate data and be logistically practical. That’s what we’ve seen with the ddPCR-based blood test.

“The test has great utility both for patients newly diagnosed with NSCLC and for those with a recurrence of the disease,” she continued. “It’s fast, it’s quantitative (it indicates the amount of mutant DNA in a sample), and it can be readily employed at a cancer treatment center.”

The co-authors of the study are Cloud Paweletz, PhD, Allison O’Connell, BSc, and Nora Feeney, BSc, of the Belfer Center for Applied Cancer Science at Dana-Farber; Ryan S. Alden BSc, and Stacy L. Mach BA, of Dana-Farber; Suzanne E. Dahlberg, PhD, of Dana-Farber and Harvard T.H. Chan School of Public Health; and Pasi A. Jänne, MD, PhD, of Dana-Farber, the Belfer Center, and Brigham and Women’s Hospital.

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Monitoring AML with “cell specific” blood test

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

‘Liquid Biopsy’ Blood Test Replaces Painful Bone Marrow Biopsy for Leukemia

Mon, 01/11/2016  by BioFluidica, Inc.  http://www.mdtmag.com/news/2016/01/liquid-biopsy-blood-test-replaces-painful-bone-marrow-biopsy-leukemia

 

BioFluidica, Inc. has released the clinical data for minimal residual disease detection in Acute Myeloid Leukemia (AML) patients using circulating leukemic cells selected from blood. The data was published in the peer reviewed journal the Analyst (141 (2016) 640). AML is a rapidly developing leukemic disease with ~20,000 cases reported in 2015 with a 5-year survival rate of only 25%.

The goal of this study was to detect early stages of disease relapse following stem cell transplantation. Currently AML relapse is detected using bone marrow biopsy samples that are painful for the patient and using existing commercial tests, limits the frequency of testing and thus resulting in poor outcomes for AML patients. The paper describes that using BioFluidica’s analytical technology relapse could be detected nearly 2 months earlier than conventional tests. In addition, test frequency could be significantly increased using BioFluidica’s technology compared to tests requiring bone marrow biopsies.

Professor Steven A. Soper, the scientific founder of BioFluidica and co-author of the paper with Dr. Paul Armistead, a hematologist, both at the University of North Carolina states that “the use of a blood test compared to a bone marrow biopsy would be a tremendous advancement in diagnostic capability that can dramatically improve the survival rate of patients with AML.”

BioFluidica is developing innovative technologies for the isolation and analysis of rare, circulating biomarkers in the blood. The company’s first platform has the capacity to isolate circulating tumor cells, exosomes and cfDNA from the blood with unprecedented recovery and purity. The technology is based on patented microfluidics designs which has been clinically validated for 6 different cancer types including Colorectal, Pancreatic Ductal Adenocarcinoma, Ovarian, Breast, Multiple Myeloma and AML. Additionally, stroke detection and infectious disease identification have also obtained clinical validation using the BioFluidica test. The company was cofounded by Dr. Soper who is currently a Professor in Biomedical Engineering and Chemistry at the University of North Carolina at Chapel Hill (UNC-CH). He is also Director of a new center on the UNC-CH campus, Center for BioModular Multi-scale Systems for Precision Medicine, focused on developing new tools for the molecular analysis of circulating biomarkers.

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Point of Care Diagnostics

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Point-of-Care Diagnostics—An Expanding Field Driven by Technology Development 

Impact of Various Disease Classes on the Development of POC Diagnostics

Gary Oosta, Ph.D.Enal Razvi, Ph.D.

Point-of-Care Diagnostics—An Expanding Field Driven by Technology Development

Figure 1. POC diagnostics word cloud

  • There is growing interest in the point-of-care (POC) diagnostics field as the space is expanding and evolving from pure technology development to applications development in various settings. We sought to understand the dynamics of the point-of-care diagnostics field by examining the entire ensemble of publications in this space and analyzing trends from the bottom-up.

  • Click Image To Enlarge +
    Figure 2. POC diagnostics is a global field.

    We harvested and analyzed 14,046 publications from the academic literature where the search terms were “point-of-care” in the titles and/or abstracts of the publications.  Figure 1 presents a word cloud that shows a pictorial representation of the abundance of various terms within this space as a means to illustrate the dataset which we harvested.  Most of the data was collected in 2015 and therefore it represents the current scenario of the field.

    We subsequently sought to understand the nature of the POC diagnostics field by examining the geographic source of these publications—is this a concentrated marketplace or is it truly global in nature, vis-à-vis research and publications in this field.  Figure 2 presents the geographic breakout and this clearly shows that POC diagnostics is a global field.

  • Click Image To Enlarge +
    Figure 3. Growth of publications in the POC diagnostics space.

    The U.S. dominates publications in this space with 39% of total but it’s important to note the breakout is truly global in nature and attests to the fragmented nature of research in this field.

    We also sought to understand the pace of growth of this field—if the hypothesis is that the POC diagnostics field is expanding we should observe a steep climb in the growth of publications—Figure 3 presents this data, which shows a clear expanding space and this begs the question as to where the growth in the field is coming from. To address this question, we examined the compound annual growth rates (CAGRs) of the various segments of the broader POC diagnostics space and this data (not presented in this article) suggest that specific segments of the POC space are outperforming the growth of the broader POC diagnostics space and there are opportunities for applications development in these particular spaces.

  • Click Image To Enlarge +
    Figure 4. Cardiovascular disease classes are an important component of the POC space.

    Infectious diseases are a strong theme in the overall POC diagnostics field and estimates suggest that infectious diseases account for 70% of the overall POC diagnostics marketplace.  Our industry research however also suggests that the oncology space is experiencing growth in the POC diagnostics arena and this suggests to us that the technology development taking place in POC diagnostics is starting to branch out and impact other market segments.  Another space we investigated as part of our industry analyses was the impact of POC diagnostics into the cardiovascular diseases space.  Figure 4 presents the publications landscape of POC diagnostics impacting various cardiovascular disease classes.

  • Click Image To Enlarge +
    Figure 5. In POC, specific biomarkers are an almost unexplored space.

    Even though POC diagnostics seeks to interrogate biological marker[s], the specific biomarker[s] that are implicated in POC diagnostics are generally not well characterized and indeed studies of biomarkers do not crossover into POC diagnostics.  We interpret this data to mean that the majority of the efforts in the POC diagnostics field are focused on technology development, approaches for deployment into the point-of-need setting rather than the molecular characterization of the biomarkers that are the underlying molecular entities associating the readout with the biological phenotype studied. This is especially true in the cancer biomarkers space where there is an extensive body of literature where specific biomarkers or signatures thereof are associated either as prognostic or diagnostic biomarkers with specific pathological states—such levels of association are not observed in the POC diagnostics field.  This will evolve over time and such molecular associations of the lesions will be described.  Figure 5 presents the publications landscape of specific biomarkers that have been described thus far in the POC diagnostics space.

  • Click Image To Enlarge +
    Figure 6a. In the POC space, the penetrance of cancer is growing, albeit small currently.

    POC diagnostics are suited ideally for high-impact diseases for which quick time to diagnosis and treatments are crucial, cardiovascular diseases for example as well as infectious disease where time to diagnosis is a key determinant of the therapeutic regimen that is deployed.  The broader cancer space impact on POC diagnostics is small at the present time, but growing.  We believe that the impact of minimally invasive diagnostics such as biofluid/liquid biopsies will increase the penetrance and impact of POC diagnostics into the cancer diagnostics space.

    The impact of molecular diagnostics tools onto the POC diagnostics space is expanding, and we believe that this trend will drive the interrogation of specific molecular species [biomarkers] in the POC context.  In this vein, we have noted that the penetrance of PCR amplification in POC diagnostics is growing suggesting the potential move of molecular testing, MDx, precision medicine into the POC diagnostics space.  We will continue to monitor this trend closely as the impact of nucleic acid analyses into POC diagnostics is an important theme and will enable precision medicine at the molecular level in the point-of-need setting.

    Earlier in this article, we alluded to the observation that in the point-of-care diagnostics setting cancer is currently a small contributor but is a growing space—Figure 6a illustrates this trend.

  • Click Image To Enlarge +
    Figure 6b. Segmentation of cancer classes by penetrance by POC diagnostics.

    We have further characterized this market segment and found that specific cancers are represented to various degrees—breast cancer is the most penetrant.  Figure 6bbreaks-down the various cancer classes vis-à-vis their penetrance into the POC diagnostics space and the trends observed are very interesting as they reflect on clinical practices in cancer screening as well as early diagnostics testing.  We seek to analyze this trend over the coming year to observe shifts in cancer POC diagnostics with the mounting interest in the liquid biopsy space—liquid biopsy can be viewed as a POC diagnostic since it is minimally invasive and can be performed in out-patient settings—a hallmark of the POC diagnostics space.

  • In summary, we have framed the current landscape of POC diagnostics, seeking to bring together various disease classes and describing their impact on the overall POC diagnostics field.  We continue to monitor this space as it evolves and is impacted by other fields, such as liquid biopsies, which will affect the character and dynamics of this space. We believe that not only will new technologies (such as microfluidics) drive the POC diagnostics field forward in resource-rich and resource-limited settings but also the impact of new biomarkers and biomarker classes will drive the field forward as more precise tailored-medicine becomes the norm in clinical practice.  Therefore even though currently POC diagnostics is deployed for high-impact diseases, the trend is moving toward its utilization in many niches of clinical unmet need.

  • Click Image To Enlarge +

    At the 2nd Annual Biofluid Biopsies and High Value Diagnostics 2015 conference Select Biosciences brings together academic researchers, industry researchers, as well as biotechnology and pharmaceutical companies to explore the expanding and evolving field whereby Circulating Biomarkers of various classes are being evaluated for their potential to be developed into diagnostics for cancer as well as other disease classes.

 

 

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Diagnostic Revelations

Larry H. Bernstein, MD, FCAP, Curator

LPBI

New Liquid Biopsy Test Uses Platelet RNA as Cancer Diagnostic

  • Click Image To Enlarge +
    Using platelet RNA, scientists have been able to detect the presence of cancer and pinpoint its primary location. [Best et al., 2015, Cancer Cell 28, 1–11]

    The age of fast, accurate, and noninvasive cancer screening is rapidly becoming reality. The power of next-generation sequencing has allowed molecular diagnostic techniques to sample small amounts of blood for the genetic hallmarks of tumorigenesis. These liquid biopsy procedures, as they have been dubbed, typically search for circulating tumor DNA (ctDNA) that has made its way into the systemic circulation from tumor cells that have died or enrich for circulating tumor cells (CTCs) that have broken off from the primary cancer site.

    Now, a team of researchers lead by scientists at Massachusetts General Hospital (MGH), have developed a new diagnostic test that analyzes the tumor RNA picked up in circulating platelets. The investigators believe this new method could become even more useful than other molecular technologies for diagnosing cancer since it can also determine the primary location of the tumor and provide insight to potential therapeutic approaches.

    “By combining next-generation-sequencing gene expression profiles of platelet RNA with computational algorithms we developed, we were able to detect the presence of cancer with 96 percent accuracy,” explains co-senior author Bakhos Tannous, Ph.D., associate professor Harvard Medical School and associate neuroscientist at MGH. “Platelet RNA signatures also provide valuable information on the type of tumor present in the body and can guide the selection of the most optimal treatment for individual patients.

    The findings from this study were published recently in Cancer Cell through an article entitled “RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics.”

    In the current study the research team describes finding that the RNA profiles of tumor-educated platelets (TEPs)—those that have taken up molecules shed by tumors—can distinguish among blood samples of healthy individuals and those of patients with six types of cancer, determine the location of the primary tumor, and identify tumors carrying mutations that can guide therapeutic decision-making.

    Over the past several years, the scientific literature has shown that in addition to their role in promoting blood clotting, platelets take up protein and RNA molecules from tumors, possibly playing a role in tumor growth and metastasis. Dr. Tannous and his colleagues set out to determine whether tumor RNA carried in platelets could be used to diagnose and classify common types of cancer.

    The investigators isolated platelets from blood samples taken from 55 healthy donors, 39 individual with early-stage cancer and 189 patients with advanced, metastatic cancer. Among those patients with cancer, they were diagnosed with non-small-cell lung cancer, colorectal cancer, glioblastoma, pancreatic cancer, hepatobiliary cancer, or breast cancer.

    The comparison of RNA profiles from the healthy donors to those of the cancer patients identified increased levels of approximately 1,500 RNA molecules—many involved in cancer-associated processes—and a reduction of almost 800 in samples from cancer patients. Using their novel algorithm, the MGH group was able to examine close to 1,000 RNAs from almost 300 individuals with 96% accuracy for the presence of cancer.

    Additionally, the platelet mRNA profiles were able to identify the particular type of cancer within each patient participant, including distinguishing among three types of gastrointestinal adenocarcinoma: colorectal cancer, pancreatic cancer, and hepatobiliary cancer. Platelets from patients with tumors driven by mutations in KRAS or EGFR proteins—biomarkers that can guide the use of drugs targeting those mutations—proved to have unique RNA profiles as well.

    The researchers were excited by their findings and emphasize the uniqueness of their approach as currently utilized liquid biopsy approaches have been unable to diagnose cancer while simultaneously pinpointing the location of the primary tumor.

    “We observed that the mRNA profiles of tumor-educated platelets have the sensitivity and specificity to detect cancer, even in early, non-metastasized tumors,” noted Dr. Tannous. “We are further assessing the potential of TEP-based screening for therapeutic decision making and also investigating how non-cancerous diseases may further influence the RNA repertoire of TEPs.”

  • RNA-Seq of Tumor-Educated Platelets Enables Blood-Based Pan-Cancer, Multiclass, and Molecular Pathway Cancer Diagnostics

Myron G. Best Nik Sol, Jihane Tannous, Bart A. Westerman, François Rustenburg, Pepijn Schellen, Heleen Verschueren, Edward Post, Jan Koster, Bauke Ylstra, Irsan Kooi, et al.
Highlights

Tumors “educate” platelets (TEPs) by altering the platelet RNA profile

TEPs provide a RNA biosource for pan-cancer, multiclass, and companion diagnostics

TEP-based liquid biopsies may guide clinical diagnostics and therapy selection

A total of 100–500 pg of total platelet RNA is sufficient for TEP-based diagnostics

mRNA Profiles of Tumor-Educated Platelets Are Distinct from Platelets of Healthy Individuals

Summary

Tumor-educated blood platelets (TEPs) are implicated as central players in the systemic and local responses to tumor growth, thereby altering their RNA profile. We determined the diagnostic potential of TEPs by mRNA sequencing of 283 platelet samples. We distinguished 228 patients with localized and metastasized tumors from 55 healthy individuals with 96% accuracy. Across six different tumor types, the location of the primary tumor was correctly identified with 71% accuracy. Also, MET or HER2-positive, and mutant KRAS, EGFR, orPIK3CA tumors were accurately distinguished using surrogate TEP mRNA profiles. Our results indicate that blood platelets provide a valuable platform for pan-cancer, multiclass cancer, and companion diagnostics, possibly enabling clinical advances in blood-based “liquid biopsies”.

Figure thumbnail fx1

http://www.cell.com/cms/attachment/2039645414/2053235278/fx1.jpg

Significance

Blood-based “liquid biopsies” provide a means for minimally invasive molecular diagnostics, overcoming limitations of tissue acquisition. Early detection of cancer, clinical cancer diagnostics, and companion diagnostics are regarded as important applications of liquid biopsies. Here, we report that mRNA profiles of tumor-educated blood platelets (TEPs) enable for pan-cancer, multiclass cancer, and companion diagnostics in both localized and metastasized cancer patients. The ability of TEPs to pinpoint the location of the primary tumor advances the use of liquid biopsies for cancer diagnostics. The results of this proof-of-principle study indicate that blood platelets are a potential all-in-one platform for blood-based cancer diagnostics, using the equivalent of one drop of blood.

Introduction

Cancer is primarily diagnosed by clinical presentation, radiology, biochemical tests, and pathological analysis of tumor tissue, increasingly supported by molecular diagnostic tests. Molecular profiling of tumor tissue samples has emerged as a potential cancer classifying method (Akbani et al., 2014, Golub et al., 1999, Han et al., 2014, Hoadley et al., 2014, Kandoth et al., 2013,Ramaswamy et al., 2001, Su et al., 2001). In order to overcome limitations of tissue acquisition, the use of blood-based liquid biopsies has been suggested (Alix-Panabières et al., 2012, Crowley et al., 2013, Haber and Velculescu, 2014). Several blood-based biosources are currently being evaluated as liquid biopsies, including plasma DNA (Bettegowda et al., 2014, Chan et al., 2013, Diehl et al., 2008, Murtaza et al., 2013, Newman et al., 2014, Thierry et al., 2014) and circulating tumor cells (Bidard et al., 2014, Dawson et al., 2013, Maheswaran et al., 2008, Rack et al., 2014). So far, implementation of liquid biopsies for early detection of cancer has been hampered by non-specificity of these biosources to pinpoint the nature of the primary tumor (Alix-Panabières and Pantel, 2014,Bettegowda et al., 2014).

It has been reported that tumor-educated platelets (TEPs) may enable blood-based cancer diagnostics (Calverley et al., 2010, McAllister and Weinberg, 2014,Nilsson et al., 2011). Blood platelets—the second most-abundant cell type in peripheral blood—are circulating anucleated cell fragments that originate from megakaryocytes in bone marrow and are traditionally known for their role in hemostasis and initiation of wound healing (George, 2000, Leslie, 2010). More recently, platelets have emerged as central players in the systemic and local responses to tumor growth. Confrontation of platelets with tumor cells via transfer of tumor-associated biomolecules (“education”) is an emerging concept and results in the sequestration of such biomolecules (Klement et al., 2009,Kuznetsov et al., 2012, McAllister and Weinberg, 2014, Nilsson et al., 2011,Quail and Joyce, 2013). Moreover, external stimuli, such as activation of platelet surface receptors and lipopolysaccharide-mediated platelet activation (Denis et al., 2005, Rondina et al., 2011), induce specific splicing of pre-mRNAs in circulating platelets (Power et al., 2009, Rowley et al., 2011, Schubert et al., 2014). Platelets may also undergo queue-specific splice events in response to signals released by cancer cells and the tumor microenvironment—such as stromal and immune cells. The combination of specific splice events in response to external signals and the capacity of platelets to directly ingest (spliced) circulating mRNA can provide TEPs with a highly dynamic mRNA repertoire, with potential applicability to cancer diagnostics (Calverley et al., 2010, Nilsson et al., 2011) (Figure 1A). In this study, we characterize the platelet mRNA profiles of various cancer patients and healthy donors and investigate their potential for TEP-based pan-cancer, multiclass cancer, and companion diagnostics.

  
Results

We prospectively collected and isolated blood platelets from healthy donors (n = 55) and both treated and untreated patients with early, localized (n = 39) or advanced, metastatic cancer (n = 189) diagnosed by clinical presentation and pathological analysis of tumor tissue supported by molecular diagnostics tests. The patient cohort included six tumor types, i.e., non-small cell lung carcinoma (NSCLC, n = 60), colorectal cancer (CRC, n = 41), glioblastoma (GBM, n = 39), pancreatic cancer (PAAD, n = 35), hepatobiliary cancer (HBC, n = 14), and breast cancer (BrCa, n = 39) (Figure 1B; Table 1; Table S1). The cohort of healthy donors covered a wide range of ages (21–64 years old, Table 1).

Table 1Summary of Patient Characteristics
PATIENT GROUP TOTAL (N) GENDER M (%)A AGE (SD)B METASTASIS (%) MUTATION PRESENCE (%)
TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION TRAINING VALIDATION
HD 39 16 21 (54) 6 (38) 41 (13) 38 (16)
GBM 23 16 18 (78) 10 (63) 59 (16) 62 (14) 0 (0) 0 (0)
NSCLC 36 24 14 (39) 14 (58) 60 (11) 59 (12) 33 (92) 23 (96) KRAS 15 (42) 11 (46)
EGFR 14 (39) 7 (29)
MET-overexpression 5 (14) 3 (13)
CRC 25 16 13 (52) 9 (56) 59 (13) 63 (16) 20 (80) 15 (94) KRAS 7 (28) 8 (50)
PAAD 21 14 12 (57) 7 (50) 66 (9) 66 (10) 15 (71) 9 (64) KRAS 13 (62) 9 (64)
BrCa 23 16 0 (0) 0 (0) 59 (11) 59 (11) 16 (70) 9 (56) HER2+ 7 (30) 5 (31)
PIK3CA 6 (26) 2 (13)
triple negative 5 (22) 3 (19)
HBC 8 6 6 (75) 2 (33) 68 (13) 62 (16) 6 (75) 4 (67) KRAS 3 (38) 1 (17)

HD, healthy donors; GBM, glioblastoma; NSCLC, non-small cell lung cancer; CRC, colorectal cancer; PAAD, pancreatic cancer; BrCa, breast cancer; HBC, hepatobiliary cancer. See also Table S1.

aIndicated are number of male individuals.
bIndicated is mean age in years.

Platelet purity was confirmed by morphological analysis of randomly selected and freshly isolated platelet samples (contamination is 1 to 5 nucleated cells per 10 million platelets, see Supplemental Experimental Procedures), and platelet RNA was isolated and evaluated for quality and quantity (Figure S1A). A total of 100–500 pg of platelet total RNA (the equivalent of purified platelets in less than one drop of blood) was used for SMARTer mRNA amplification and sequencing (Ramsköld et al., 2012) (Figures 1C and S1A). Platelet RNA sequencing yielded a mean read count of ∼22 million reads per sample. After selection of intron-spanning (spliced) RNA reads and exclusion of genes with low coverage (seeSupplemental Experimental Procedures), we detected in platelets of healthy donors (n = 55) and localized and metastasized cancer patients (n = 228) 5,003 different protein coding and non-coding RNAs that were used for subsequent analyses. The obtained platelet RNA profiles correlated with previously reported mRNA profiles of platelets (Bray et al., 2013, Kissopoulou et al., 2013, Rowley et al., 2011, Simon et al., 2014) and megakaryocytes (Chen et al., 2014) and not with various non-related blood cell mRNA profiles (Hrdlickova et al., 2014) (Figure S1B). Furthermore, DAVID Gene Ontology (GO) analysis revealed that the detected RNAs are strongly enriched for transcripts associated with blood platelets (false discovery rate [FDR] < 10−126).

Among the 5,003 RNAs, we identified known platelet markers, such as B2M, PPBP, TMSB4X, PF4, and several long non-coding RNAs (e.g., MALAT1). A total of 1,453 out of 5,003 mRNAs were increased and 793 out of 5,003 mRNAs were decreased in TEPs as compared to platelet samples of healthy donors (FDR < 0.001), while presenting a strong correlation between these platelet mRNA profiles (r = 0.90, Pearson correlation) (Figure 1D). Unsupervised hierarchical clustering based on the differentially detected platelet mRNAs distinguished two sample groups with minor overlap (Figure 1E; Table S2). DAVID GO analysis revealed that the increased TEP mRNAs were enriched for biological processes such as vesicle-mediated transport and the cytoskeletal protein binding while decreased mRNAs were strongly involved in RNA processing and splicing (Table S3). A correlative analysis of gene set enrichment (CAGE) GO methodology, in which 3,875 curated gene sets of the GSEA database were correlated to TEP profiles (see Experimental Procedures), demonstrated significant correlation of TEP mRNA profiles with cancer tissue signatures, histone deacetylases regulation, and platelets (Table 2). The levels of 20 non-protein coding RNAs were altered in TEPs as compared to platelets from healthy individuals and these show a tumor type-associated RNA profile (Figure S1C).

Thumbnail image of Figure 1. Opens large image

http://www.cell.com/cms/attachment/2039645414/2053235279/gr1.jpg

Tumor-Educated Platelet mRNA Profiling for Pan-Cancer Diagnostics

(A) Schematic overview of tumor-educated platelets (TEPs) as biosource for liquid biopsies.

(B) Number of platelet samples of healthy donors and patients with different types of cancer.

(C) TEP mRNA sequencing (mRNA-seq) workflow, as starting from 6 ml EDTA-coated tubes, to platelet isolation, mRNA amplification, and sequencing.

(D) Correlation plot of mRNAs detected in healthy donor (HD) platelets and cancer patients’ TEPs, including highlighted increased (red) and decreased (blue) TEP mRNAs.

(E) Heatmap of unsupervised clustering of platelet mRNA profiles of healthy donors (red) and patients with cancer (gray).

(F) Cross-table of pan-cancer SVM/LOOCV diagnostics of healthy donor subjects and patients with cancer in training cohort (n = 175). Indicated are sample numbers and detection rates in percentages.

(G) Performance of pan-cancer SVM algorithm in validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages.

(H) ROC-curve of SVM diagnostics of training (red), validation (blue) cohort, and random classifiers, indicating the classification accuracies obtained by chance of the training and validation cohort (gray).

(I) Total accuracy ratios of SVM classification in five subgroups, including corresponding predictive strengths. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S1 and Tables S1, S2, S3, and S4.

Table 2Pan-Cancer CAGE Gene Ontology
TOP 25 GO CORRELATIONS
# LOWESTA HIGHESTA
DOWN
Translation 10 −0.865 −0.890
Immune, T cell 5 −0.853 −0.883
Cancer-associated 2 −0.875 −0.887
Viral replication 2 −0.875 −0.878
IL-signaling 2 −0.869 −0.874
RNA processing 1 −0.886
Ago2-Dicer-silencing 1 −0.882
Protein metabolism 1 −0.879
Receptor processing 1 −0.869
UP
Cancer-associated 6 −0.783 −0.906
Infection 3 −0.798 −0.853
HDAC 3 −0.795 −0.852
Platelet 3 −0.837 −0.906
Cytoskeleton 2 −0.801 −0.886
Hypoxia 2 −0.763 −0.937
Protease 1 −0.854
Immunodeficiency 1 −0.812
Differentiation 1 −0.810
Immune differentiation 1 −0.801
Methylation 1 −0.778
Metabolism 1 −0.768

Top-ranking correlations of platelet-mRNA profiles with 3,875 Broad Institute curated gene sets. CAGE, Correlative Analysis of Gene Set Enrichment; GO, gene ontology; #, number of hits per annotation; IL, interleukin; HDAC, histone deacetylase.

aIndicated are lowest and highest correlations per annotation.

Next, we determined the diagnostic accuracy of TEP-based pan-cancer classification in the training cohort (n = 175), employing a leave-one-out cross-validation support vector machine algorithm (SVM/LOOCV, see Experimental Procedures; Figures S1D and S1E), previously used to classify primary and metastatic tumor tissues (Ramaswamy et al., 2001, Su et al., 2001, Vapnik, 1998, Yeang et al., 2001). Briefly, the SVM algorithm (blindly) classifies each individual sample as cancer or healthy by comparison to all other samples (175 − 1) and was performed 175 times to classify and cross validate all individuals samples. The algorithms we developed use a limited number of different spliced RNAs for sample classification. To determine the specific input gene lists for the classifying algorithms we performed ANOVA testing for differences (as implemented in the R-package edgeR), yielding classifier-specific gene lists (Table S4). For the specific algorithm of the pan-cancer TEP-based classifier test we selected 1,072 RNAs (Table S4) for the n = 175 training cohort, yielding a sensitivity of 96%, a specificity of 92%, and an accuracy of 95% (Figure 1F). Subsequent validation using a separate validation cohort (n = 108), not involved in input gene list selection and training of the algorithm, yielded a sensitivity of 97%, a specificity of 94%, and an accuracy of 96% (Figure 1G), with an area under the curve (AUC) of 0.986 to detect cancer (Figure 1H) and high predictive strength (Figure 1I). In contrast, random classifiers, as determined by multiple rounds of randomly shuffling class labels (permutation) during the SVM training process (see Experimental Procedures), had no predictive power (mean overall accuracy: 78%, SD ± 0.3%, p < 0.01), thereby showing, albeit an unbalanced representation of both groups in the study cohort, specificity of our procedure. A total of 100 times random class-proportional subsampling of the entire dataset in a training and validation set (ratio 60:40) yielded similar accuracy rates (mean overall accuracy: 96%, SD: ± 2%), confirming reproducible classification accuracy in this dataset. Of note, all 39 patients with localized tumors and 33 of the 39 patients with primary tumors in the CNS were correctly classified as cancer patients (Figure 1I). Visualization of 22 genes previously identified at differential RNA levels in platelets of patients with various non-cancerous diseases (Gnatenko et al., 2010, Healy et al., 2006, Lood et al., 2010,Raghavachari et al., 2007), revealed mixed levels in our TEP dataset (Figure S1F), suggesting that the platelet RNA repertoire in patients with non-cancerous disease is distinct from patients with cancer.

Tumor-Specific Educational Program of Blood Platelets Allows for Multiclass Cancer Diagnostics

In addition to the pan-cancer diagnosis, the TEP mRNA profiles also distinguished healthy donors and patients with specific types of cancer, as demonstrated by the unsupervised hierarchical clustering of differential platelet mRNA levels of healthy donors and all six individual tumor types, i.e., NSCLC, CRC, GBM, PAAD, BrCa, and HBC (Figures 2A, all p < 0.0001, Fisher’s exact test, and S2A; Table S5), and this resulted in tumor-specific gene lists that were used as input for training and validation of the tumor-specific algorithms (Table S4). For the unsupervised clustering of the all-female group of BrCa patients, male healthy donors were excluded to avoid sample bias due to gender-specific platelet mRNA profiles (Figure S2B). SVM-based classification of all individual tumor classes with healthy donors resulted in clear distinction of both groups in both the training and validation cohort, with high sensitivity and specificity, and 38/39 (97%) cancer patients with localized disease were classified correctly (Figures 2B and S2C). CAGE GO analysis showed that biological processes differed between TEPs of individual tumor types, suggestive of tumor-specific “educational” programs (Table S6). We did not detect sufficient differences in mRNA levels to discriminate patients with non-metastasized from patients with metastasized tumors, suggesting that the altered platelet profile is predominantly influenced by the molecular tumor type and, to a lesser extent, by tumor progression and metastases.

 We next determined whether we could discriminate three different types of adenocarcinomas in the gastro-intestinal tract by analysis of the TEP-profiles, i.e., CRC, PAAD, and HBC. We developed a CRC/PAAD/HBC algorithm that correctly classified the mixed TEP samples (n = 90) with an overall accuracy of 76% (mean overall accuracy random classifiers: 42%, SD: ± 5%, p < 0.01,Figure 2C). In order to determine whether the TEP mRNA profiles allowed for multiclass cancer diagnosis across all tumor types and healthy donors, we extended the SVM/LOOCV classification test using a combination of algorithms that classified each individual sample of the training cohort (n = 175) as healthy donor or one of six tumor types (Figures S2D and S2E). The results of the multiclass cancer diagnostics test resulted in an average accuracy of 71% (mean overall accuracy random classifiers: 19%, SD: ± 2%, p < 0.01,Figure 2D), demonstrating significant multiclass cancer discriminative power in the platelet mRNA profiles. The classification capacity of the multiclass SVM-based classifier was confirmed in the validation cohort of 108 samples, with an overall accuracy of 71% (Figure 2E). An overall accuracy of 71% might not be sufficient for introduction into cancer diagnostics. However, of the initially misclassified samples according to the SVM algorithms choice with strongest classification strength the second ranked classification was correct in 60% of the cases. This yields an overall accuracy using the combined first and second ranked classifications of 89%. The low validation score of HBC samples can be attributed to the relative low number of samples and possibly to the heterogenic nature of this group of cancers (hepatocellular cancers and cholangiocarcinomas).
large Image

Tumor-Educated Platelet mRNA Profiles for Multiclass Cancer Diagnostics

(A) Heatmaps of unsupervised clustering of platelet mRNA profiles of healthy donors (HD; n = 55) (red) and patients with non-small cell lung cancer (NSCLC; n = 60), colorectal cancer (CRC; n = 41), glioblastoma (GBM; n = 39), pancreatic cancer (PAAD, n = 35), breast cancer (BrCa; n = 39; female HD; n = 29), and hepatobiliary cancer (HBC; n = 14).

(B) ROC-curve of SVM diagnostics of healthy donors and individual tumor classes in both training (left) and validation (right) cohort. Random classifiers, indicating the classification accuracies obtained by chance, are shown in gray.

(C) Confusion matrix of multiclass SVM/LOOCV diagnostics of patients with CRC, PAAD, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(D) Confusion matrix of multiclass SVM/LOOCV diagnostics of the training cohort consisting of healthy donors (healthy) and patients with GBM, NSCLC, PAAD, CRC, BrCa, and HBC. Indicated are detection rates as compared to the actual classes in percentages.

(E) Confusion matrix of multiclass SVM algorithm in a validation cohort (n = 108). Indicated are sample numbers and detection rates in percentages. Genes, number of mRNAs included in training of the SVM algorithm.

See also Figure S2 and Tables S4, S5, and S6.

Companion Diagnostics Tumor Tissue Biomarkers Are Reflected by Surrogate TEP mRNA Onco-signatures

Blood provides a promising biosource for the detection of companion diagnostics biomarkers for therapy selection (Bettegowda et al., 2014, Crowley et al., 2013,Papadopoulos et al., 2006). We selected platelet samples of patients with distinct therapy-guiding markers confirmed in matching tumor tissue. Although the platelet mRNA profiles contained undetectable or low levels of these mutant biomarkers, the TEP mRNA profiles did allow to distinguish patients with KRASmutant tumors from KRAS wild-type tumors in PAAD, CRC, NSCLC, and HBC patients, and EGFR mutant tumors in NSCLC patients, using algorithms specifically trained on biomarker-specific input gene lists (all p < 0.01 versus random classifiers, Figures 3A–3E ; Table S4). Even though the number of samples analyzed is relatively low and the risk of algorithm overfitting needs to be taken into account, the TEP profiles distinguished patients with HER2-amplified, PIK3CA mutant or triple-negative BrCa, and NSCLC patients with MET overexpression (all p < 0.01 versus random classifiers, Figures 3F–3I).

 We subsequently compared the diagnostic accuracy of the TEP mRNA classification method with a targeted KRAS (exon 12 and 13) and EGFR (exon 20 and 21) amplicon deep sequencing strategy (∼5,000× coverage) on the Illumina Miseq platform using prospectively collected blood samples of patients with localized or metastasized cancer. This method did allow for the detection of individual mutant KRAS and EGFR sequences in both plasma DNA and platelet RNA (Table S7), indicating sequestration and potential education capacity of mutant, tumor-derived RNA biomarkers in TEPs. Mutant KRAS was detected in 62% and 39%, respectively, of plasma DNA (n = 103, kappa statistics = 0.370, p < 0.05) and platelet RNA (n = 144, kappa statistics = 0.213, p < 0.05) of patients with a KRAS mutation in primary tumor tissue. The sensitivity of the plasma DNA tests was relatively poor as reported by others (Bettegowda et al., 2014, Thierry et al., 2014), which may partly be attributed to the loss of plasma DNA quality due to relatively long blood sample storage (EDTA blood samples were stored up to 48 hr at room temperature before plasma isolation). To discriminate KRAS mutant from wild-type tumors in blood, the TEP mRNA profiles provided superior concordance with tissue molecular status (kappa statistics = 0.795–0.895, p < 0.05) compared to KRAS amplicon sequencing analysis of both plasma DNA and platelet RNA (Table S7). Thus, TEP mRNA profiles can harness potential blood-based surrogate onco-signatures for tumor tissue biomarkers that enable cancer patient stratification and therapy selection.
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Tumor-Educated Platelet mRNA Profiles for Molecular Pathway Diagnostics

Cross tables of SVM/LOOCV diagnostics with the molecular markers KRAS in (A) CRC, (B) PAAD, and (C) NSCLC patients, (D) KRAS in the combined cohort of patients with either CRC, PAAD, NSCLC, or HBC, (E) EGFR and (F) MET in NSCLC patients, (G) PIK3CA mutations, (H) HER2-amplification, and (I) triple negative status in BrCa patients. Genes, number of mRNAs included in training of the SVM algorithm. See alsoTables S4 and S7.

TEP-Profiles Provide an All-in-One Biosource for Blood-Based Liquid Biopsies in Patients with Cancer

Unequivocal discrimination of primary versus metastatic nature of a tumor may be difficult and hamper adequate therapy selection. Since the TEP profiles closely resemble the different tumor types as determined by their organ of origin—regardless of systemic dissemination—this potentially allows for organ-specific cancer diagnostics. Hence we selected all healthy donors and all patients with primary or metastatic tumor burden in the lung (n = 154), brain (n = 114), or liver (n = 127). We performed “organ exams” and instructed the SVM/LOOCV algorithm to determine for lung, brain, and liver the presence or absence of cancer (96%, 91%, and 96% accuracy, respectively), with cancer subclassified as primary or metastatic tumor (84%, 93%, and 90% accuracy, respectively) and in case of metastases to identify the potential organ of origin (64%, 70%, and 64% accuracy, respectively). The platelet mRNA profiles enabled assignment of the cancer to the different organs with high accuracy (Figure 4). In addition, using the same TEP mRNA profiles we were able to again indicate the biomarker status of the tumor tissues (90%, 82%, and 93% accuracy, respectively) (Figure 4).

large Image

Organ-Focused TEP-Based Cancer Diagnostics

SVM/LOOCV diagnostics of healthy donors (n = 55) and patients with primary or metastatic tumor burden in the lung (n = 99; totaling 154 tests), brain (n = 62; totaling 114 tests), or liver (n = 72; totaling 127 tests), to determine the presence or absence of cancer, with cancer subclassified as primary or metastatic tumor, in case of metastases the identified organ of origin, and the correctly identified molecular markers. Of note, at the exam level of mutational subtypes some samples were included in multiple classifiers (i.e., KRAS, EGFR, PIK3CA,HER2-amplification, MET-overexpression, or triple negative status), explaining the higher number in mutational tests than the total number of included samples. TP, true positive; FP, false positive; FN, false negative; TN, true negative. Indicated are sample numbers and detection rates in percentages.

Discussion

The use of blood-based liquid biopsies to detect, diagnose, and monitor cancer may enable earlier diagnosis of cancer, lower costs by tailoring molecular targeted treatments, improve convenience for cancer patients, and ultimately supplements clinical oncological decision-making. Current blood-based biosources under evaluation demonstrate suboptimal sensitivity for cancer diagnostics, in particular in patients with localized disease. So far, none of the current blood-based biosources, including plasma DNA, exosomes, and CTCs, have been employed for multiclass cancer diagnostics (Alix-Panabières and Pantel, 2014, Bettegowda et al., 2014, Skog et al., 2008), hampering its implementation for early cancer detection. Here, we report that molecular interrogation of blood platelet mRNA can offer valuable diagnostics information for all cancer patients analyzed—spanning six different tumor types. Our results suggest that platelets may be employable as an all-in-one biosource to broadly scan for molecular traces of cancer in general and provide a strong indication on tumor type and molecular subclass. This includes patients with localized disease possibly allowing for targeted diagnostic confirmation using routine clinical diagnostics for each particular tumor type.

Since the discovery of circulating tumor material in blood of patients with cancer (Leon et al., 1977) and the recognition of the clinical utility of blood-based liquid biopsies, a wealth of studies has assessed the use of blood for cancer diagnostics, prognostication and treatment monitoring (Alix-Panabières et al., 2012, Bidard et al., 2014, Crowley et al., 2013, Haber and Velculescu, 2014). By development of highly sensitive targeted detection methods, such as targeted deep sequencing (Newman et al., 2014), droplet digital PCR (Bettegowda et al., 2014), and allele-specific PCR (Maheswaran et al., 2008, Thierry et al., 2014), the utility and applicability of liquid biopsies for clinical implementation has accelerated. These advances previously allowed for a pan-cancer comparison of various biosources and revealed that in >75% of cancers, including advanced stage pancreas, colorectal, breast, and ovarian cancer, cell-free DNA is detectable although detection rates are dependent on the grade of the tumor and depth of analysis (Bettegowda et al., 2014). Here, we show that the platelet RNA profiles are affected in nearly all cancer patients, regardless of the type of tumor, although the abundance of tumor-associated RNAs seems variable among cancer patients. In addition, surrogate RNA onco-signatures of tissue biomarkers, also in 88% of localized KRAS mutant cancer patients as measured by the tumor-specific and pan-cancer SVM/LOOCV procedures, are readily available from a minute amount (100–500 pg) of platelet RNA. As whole blood can be stored up to 48 hr on room temperature prior to isolation of the platelet pellet, while maintaining high-quality RNA and the dominant cancer RNA signatures, TEPs can be more readily implemented in daily clinical laboratory practice and could potentially be shipped prior to further blood sample processing.

Blood platelets are widely involved in tumor growth and cancer progression (Gay and Felding-Habermann, 2011). Platelets sequester solubilized tumor-associated proteins (Klement et al., 2009) and spliced and unspliced mRNAs (Calverley et al., 2010, Nilsson et al., 2011), whereas platelets do also directly interact with tumor cells (Labelle et al., 2011), neutrophils (Sreeramkumar et al., 2014), circulating NK-cells (Palumbo et al., 2005, Placke et al., 2012), and circulating tumor cells (Ting et al., 2014, Yu et al., 2013). Interestingly, in vivo experiments have revealed breast cancer-mediated systemic instigation by supplying circulating platelets with pro-inflammatory and pro-angiogenic proteins, supporting outgrowth of dormant metastatic foci (Kuznetsov et al., 2012). Using a gene ontology methodology, CAGE, we correlated TEP-cancer signatures with publicly available curated datasets. Indeed, we identified widespread correlations with cancer tissues, hypoxia, platelet-signatures, and cytoskeleton, possibly reflecting the “alert” and pro-tumorigenic state of TEPs. We observed strong negative correlations with RNAs implicated in RNA translation, T cell immunity, and interleukin-signaling, implying diminished needs of TEPs for RNAs involved in these biological processes or orchestrated translation of these RNAs to proteins (Denis et al., 2005). We observed that the tumor-specific educational programs in TEPs are predominantly influenced by tumor type and, to a lesser extent, by tumor progression and metastases. Although we were not able to measure significant differences between non-metastasized and metastasized tumors, we do not exclude that the use of larger sample sets could allow for the generation of SVM algorithms that do have the power to discriminate between certain stages of cancer, including those with in situ carcinomas and even pre-malignant lesions. In addition, different molecular tumor subtypes (e.g., HER2-amplified versus wild-type BrCa) result in different effects on the platelet profiles, possibly caused by different “educational” stimuli generated by the different molecular tumor subtypes (Koboldt et al., 2012). Altogether, the RNA content of platelets in patients with cancer is dependent on the transcriptional state of the bone-marrow megakaryocyte (Calverley et al., 2010, McAllister and Weinberg, 2014), complemented by sequestration of spliced RNA (Nilsson et al., 2011), release of RNA (Clancy and Freedman, 2014, Kirschbaum et al., 2015, Rak and Guha, 2012, Risitano et al., 2012), and possibly queue-specific pre-mRNA splicing during platelet circulation. Partial or complete normalization of the platelet profiles following successful treatment of the tumor would enable TEP-based disease recurrence monitoring, requiring the analysis of follow-up platelet samples. Future studies will be required to address the tumor-specific “educated” profiles on both an (small non-coding) RNA (Laffont et al., 2013, Landry et al., 2009, Leidinger et al., 2014, Lu et al., 2005) and protein (Burkhart et al., 2014,Geiger et al., 2013, Klement et al., 2009) level and determine the ability of gene ontology, blood-based cancer classification.

In conclusion, we provide robust evidence for the clinical relevance of blood platelets for liquid biopsy-based molecular diagnostics in patients with several types of cancer. Further validation is warranted to determine the potential of surrogate TEP profiles for blood-based companion diagnostics, therapy selection, longitudinal monitoring, and disease recurrence monitoring. In addition, we expect the self-learning algorithms to further improve by including significantly more samples. For this approach, isolation of the platelet fraction from whole blood should be performed within 48 hr after blood withdrawal, the platelet fraction can subsequently be frozen for cancer diagnosis. Also, future studies should address causes and anticipated risks of outlier samples identified in this study, such as healthy donors classified as cancer patients. Systemic factors such as chronic or transient inflammatory diseases, or cardiovascular events and other non-cancerous diseases may also influence the platelet mRNA profile and require evaluation in follow-up studies, possibly also including individuals predisposed for cancer.

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Corina E. Antal, Andrew M. Hudson, Emily Kang, Ciro Zanca, Christopher Wirth, Natalie L. Stephenson, Eleanor W. Trotter, Lisa L. Gallegos, Crispin J. Miller, Frank B. Furnari, Tony Hunter, John Brognard, Alexandra C. Newton
Cell, Vol. 160, Issue 3, p489–502
Published online: January 22, 2015
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Cell, Vol. 160, Issues 1-2, p7
Published in issue: January 15, 2015
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Amelia J. Johnston, Kate T. Murphy, Laura Jenkinson, David Laine, Kerstin Emmrich, Pierre Faou, Ross Weston, Krishnath M. Jayatilleke, Jessie Schloegel, Gert Talbo, Joanne L. Casey, Vita Levina, W. Wei-Lynn Wong, Helen Dillon, Tushar Sahay, Joan Hoogenraad, Holly Anderton, Cathrine Hall, Pascal Schneider, Maria Tanzer, Michael Foley, Andrew M. Scott, Paul Gregorevic, Spring Yingchun Liu, Linda C. Burkly, Gordon S. Lynch, John Silke, Nicholas J. Hoogenraad
Cell, Vol. 162, Issue 6, p1365–1378
Published in issue: September 10, 2015
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Levi A. Garraway, Eric S. Lander
Cell, Vol. 153, Issue 1, p17–37
Published in issue: March 28, 2013

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Hector L. Franco, W. Lee Kraus
Cell, Vol. 163, Issue 1, p28–30
Published in issue: September 24, 2015

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