Healthcare analytics, AI solutions for biological big data, providing an AI platform for the biotech, life sciences, medical and pharmaceutical industries, as well as for related technological approaches, i.e., curation and text analysis with machine learning and other activities related to AI applications to these industries.
AI will help reduce time for drug development especially in early phase of discovery but eventually help in all phases
Ganhui: for drug regulators might be more amenable to AI in clinical trials; AI may be used differently by clinicians
nonprofit in Philadelphia using AI to repurpose drugs (this site has posted on this and article will be included here)
Ganhui: top challenge of AI in Pharma; rapid evolution of AI and have to have core understanding of your needs and dependencies; realistic view of what can be done; AI has to have iterative learning; also huge vertical challenge meaning how can we allign the use of AI through the healthcare vertical layer chain like clinicians, payers, etc.
Ganhui sees a challenge for health companies to understand how to use AI in business to technology; AI in AI companies is different need than AI in healthcare companies
95% of AI projects not successful because most projects are very discrete use
2:00-2:20
Building Precision Oncology Infrastructure in Low- and Middle-Income Countries
globally 60 precision initiatives but there really are because many in small countries
three out of five individuals in India die of cancer
precision medicine is a must and a hub and spoke model is needed in these places; Italy does this hub and spoke; spokes you enable the small places and bring them into the network so they know how and have access to precision medicine
in low income countries the challenge starts with biopsy: then diagnosis and biomarker is issue; then treatment decision a problem as they may not have access to molecular tumor boards
prevention is always a difficult task in LMICs (low income)
you have ten times more patients in India than in US (triage can be insurmountable)
ICGA Foundation: Indian Cancer Genome Atlas
in India mutational frequencies vary with geographical borders like EGFR mutations or KRAS mutations
genomic landscape of ovarian cancer in India totally different than in TCGA data
even different pathways are altered in ovarian cancer seen in North America than in India
MAY mean that biomarker panels need to be adjusted based on countries used in
the molecular data has to be curated for the India cases to be submitted to a tumor board
twenty diagnostic tests in market like TruCheck for Indian market; uses liquid biopsy
they are also tailoring diagnostic and treatment for India getting FDA fast track approvals
2:20-2:40
Co-targeting KIT/PDGRFA and Genomic Integrity in Gastrointestinal Stromal Tumors
Lori Rink, PhD, Associate Professor, Fox Chase Cancer Center
GIST are most common nesychymal tumor in GI tract
used to be misdiagnosed; was considered a leimyosarcoma
very asymptomatic tumors and not good prognosis
very refractory to genotoxic therapies
RTK KIT/PDGFRA gain of function mutations
Gleevec imatinib for unresectable GIST however vast majority of even responders become resistant to therapy and cancer returns
there is a mutation map for hotspot mutations and sensitivity for gleevec
however resistance emerged to ripretinib; in ATP binding pocket
over treatment get a polyclonal resistance
performed a kinome analysis; Wee1 looked like a potential target
mouse studies (80 day) showed good efficacy
avapiritinib ahs some neurotox and used in PDGFRA mut GIST model which is resistant to imitinib
but if use Wee1 inhibitor with TKI can lower dose of avapiritinib
cotargeting KIT/PDGFRA and WEE1 increases replicative stress
they are using PDX models to test these combinations
Live Conference Coverage: International Dialogue in Gynecological Oncology, From Bench to Bedside, Ovarian Cancer
Reporter: Stephen J. Williams, Ph.D.
Join Live on Wednesday May 22, 2024 for an international discussion on the current state of ovarian cancer diagnostics and therapeutics, and potential therapies and biomarkers, and biotargets. Topics including potential new molecular targets for development of ovarian therapeutics, current changes in ovarian cancer clinical treatment protocols, chemo-resistance, and the use of Artificial Intelligence (AI) in the diagnosis and treatment of cancer will be discussed.
10/15.10 We Have Never Been Only Human: a new perspective to defeat ovarian cancer (C. Martinelli)
Molecular Section
20/15.20 DNA Repair mechanisms: understanding their role in cancer development and chemoresistance (L. Alfano)
35/15.35 Progranulins: a new target for oncological treatment (A. Morrione)
50/15.50 Modulation of gene expression and its applications (M. Cuomo)
10.05/16.05 Commanding the cell cycle: the role of CDKs (S.R. Burk
10.20/16.20 Drug development from nature (M. D’Angelo
Clinical Section
05/17.05 Core principles of Radiologic Diagnosis & Staging in Ovarian Cancer(A. Blandino)
20/17.20 Key Indications for Nuclear Medicine in Ovarian Cancer (S. Baldari)
35/17.35 Cutting Edge Decision: Understanding Surgical Indications and Outcomes in Ovarian Cancer (A. Ercoli)
50/17.50 Gold Standard in Oncology for Ovarian Cancer (N. Silvestris)
12.05/18.05 Role of Radiotherapy in Ovarian Cancer (S. Pergolizzi)
Conclusion
12.20/18.20 AI Applied to medical science (V. Carnevale)
Speakers
– Professor Alfredo Blandino: Professor Blandino holds the esteemed positions of Head of school of Radiology and director of the department of radiology at the University of Messina. He has made significant contributions to diagnostic imaging with over hundreds of publications to his name, Professor Blandino’s work exemplifies excellence and innovation in radiology.
– Professor Alfredo Ercoli, serves as the Director of the Department of Gynecology and Obstetrics at the “G. Martino” University Hospital in Messina. He is also head of school of gynecology and obstetrics at Messina University. Starting his research in France with studies on pelvic anatomy that became a cornerstone in medical literature, He is a pioneer in advanced gynecologic surgery, including laparoscopic and robotic procedures, having performed over thousands of surgical interventions. His research focuses on gynecologic oncology, advanced gynecologic surgery, and endometriosis, urogynecology. Professor Ercoli’s dedication to education and his numerous publications have significantly advanced the field of gynecology.
–Professor Sergio Baldari, an eminent figure in nuclear medicine. Professor Baldari is the Director of the department of nuclear medicine and head of school of nuclear medicine at the University of Messina. He has authored or co-authored over 500 publications, with a focus on diagnostic imaging and the use of PET and radiopharmaceuticals in cancer treatment. His leadership and expertise have been recognized through various prestigious positions and awards within the medical community.
– Professor Nicola Silvestris is the Director of UOC Oncologia Medica at the University of Messina. His extensive research in cancer, has led to over 360 peer-reviewed publications. Professor Silvestris has made significant contributions to translational research and the development of guidelines for managing complex oncological conditions. His work continues to shape the future of cancer treatment.
–Professor Stefano Pergolizzi, a leading expert in radiation oncology. Professor Pergolizzi serves as the Director of the department of radiotherapy and head of the school of radiotherapya at the University of Messina. He is also the president of the Italian Association of Radiotherapy and Clinical Oncology (AIRO) His research focuses on advanced radiotherapy techniques for cancer treatment. With a career spanning several decades, Professor Pergolizzi has published numerous papers and has been instrumental in developing innovative therapeutic approaches. His dedication to patient care and education is exemplary.
Margherita D’angelo: Graduated in Molecular Biology with honors from the Federico II University of Naples.
Third year intern in Food Science at the Luigi Vanvitelli University of Naples.
Research intern in Molecular oncology with the project of developing novel drugs starting from food waste at the Sbarro Institute for Cancer Research and Molecular Medicine at Temple University, Philadelphia (USA), directed by Dr A. Giordano.
Dr. Carnevale is an Associate Professor in the Institute for Computational Molecular Science in the College of Science & Technology, Temple University. He holds multiple NIH RO1 and NSF grants. Vincenzo Carnevale received B.Sc. and M.Sc. degrees in Physics from the University of Pisa and a PhD from SISSA – Scuola Internazionale Superiore di Studi Avanzati in Trieste, Italy. The Carnevale research group uses statistical physics and machine learning approaches to investigate sequence-structure-function relations in proteins. A central theme of the group’s research is how interactions give rise to collective phenomena and complex emergent behaviors. At the level of genes, the group is interested in epistasis – the complex entanglement phenomenon that causes amino acids to evolve in a concerted fashion – and how this shapes molecular evolution. At the cellular level, the group investigates how intermolecular interactions drive biomolecules toward self-organization and pattern formation. A long-term goal of the group is understanding the molecular underpinnings of electrical signaling in excitable cells. Toward these goals, the group applies and actively develops an extensive arsenal of theoretical and computational approaches including statistical (mean)field theories, Monte Carlo and molecular dynamics simulations, statistical inference of generative models, and deep learning.
Professor Andrea Morrione, Ph.D: Research Associate Professor, CST Temple University; After his studies in Biochemistry at Universita’ degli Studi Milano, Milan Italy, Dr. Morrione moved to USA in 1993 and has been working in the field of cancer biology since his postdoctoral training at the Kimmel Cancer Institute, Thomas Jefferson University, Philadelphia, PA in the laboratory of Dr. Renato Baserga, one of the leading experts in IGF-IR oncogenic signaling. In 1997 Dr. Morrione joined the Faculty of Thomas Jefferson University in the Department of Microbiology. In 2002 after receiving an NIH/NIDDK Career Development Award Dr. Morrione joined the Department of Urology at Jefferson where from 2008 to 2018 serves as the Director for Urology Basic Science and Associate Professor. Dr. Morrione joined the Department of Biology and the Sbarro Institute for Cancer Research and Molecular Medicine and Center for Biotechnology as Associate Professor of Research, and he is currently professor of Research and Deputy Director of the Sbarro Institute for Cancer Research and Molecular Medicine and Center for Biotechnology. He is a full member of the AACR.
Canio Martinelli, M.D.: Dr. Marinelli received his MD from Catholic University of the Sacred Heart in Rome, Visiting researcher at SHRO Temple University in Philadelphia, PhD candidate in Translational Molecular Medicine and Surgery & GYN-OB resident at UNIME. He has published numerous clinical papers in gynecologic oncology, risk reduction, and therapy and, most recently investigating clinical utilities of generative AI in gynecologic oncology.
Sharon Burk, Sharon Burk is a PhD student with Professor Antonio Giordano at the University of Siena, Italy in the department of Medical Biotechnologies, studying the role of Cyclin Dependent Kinase 10 in Triple Negative Breast Cancer. She received her Bachelor’s of Arts Degree from the University of California, Berkeley with a double major in molecular and cell biology and Italian studies. She is a member of AACR.
Noninvasive blood test can detect cancer 4 years before conventional diagnosis
Reporter : Irina Robu, PhD
Several international researchers at Fudan University and at Singlera Genomics have developed a noninvasive blood test, PanSeer that can detect whether a patient with five common type of cancers such as stomach, esophageal, colorectal, lung and liver cancer; four years before the condition can be diagnosed by the current methods. Early detection is significant for the reason that the survival of cancer patients increases when the disease is identified at early stages, as the tumor can be surgically removed or treated with suitable drugs. Yet, only a partial number of early screening tests exist for a few cancer types.
The blood test detected cancer in 91 percent of samples from individuals who have been asymptomatic when the samples were collected, but only diagnosed with cancer one to four years later. It was found that the test can accurately detect cancer in 88 percent from samples of 113 patience who were diagnosed. The blood test also detects cancer free samples 95 percent of the time.
What is clear is that the study is unique, in that the scientists had access to blood samples from patients who were asymptomatic but not diagnosed yet. This permitted the researchers to design a test that can find a cancer marker much earlier than conventional diagnosis. The sample were collected as part of 10-year longitudinal study started in 2007 by Fudan University in China.
The researchers highlight that the PanSeer assay is improbable to predict which patients will later go on to develop cancer. As a substitute, it is most possible identifying patients who already have cancerous growths, but continue to be asymptomatic for current detection methods. The team decided that further large-scale longitudinal studies are needed to confirm the potential of the test for the early detection of cancer in pre-diagnosis individuals.
Retrospect on HistoScanning; an AI routinely used in diagnostic imaging for over a decade
Author and Curator: Dror Nir, PhD
3.2.7 Retrospect on HistoScanning: an AI routinely used in diagnostic imaging for over a decade, Volume 2 (Volume Two: Latest in Genomics Methodologies for Therapeutics: Gene Editing, NGS and BioInformatics, Simulations and the Genome Ontology), Part 2: CRISPR for Gene Editing and DNA Repair
This blog-post is a retrospect on over a decade of doing with HistoScanning; an AI medical-device for imaging-based tissue characterization.
Imaging-based tissue characterization by AI is offering a change in imaging paradigm; enhancing the visual information received when using diagnostic-imaging beyond that which the eye alone can see and at the same time simplifying and increasing the cost-effectiveness of patients clinical pathway.
In the case of HistoScanning, imaging is a combination of 3D-scanning by ultrasound with a real-time application of AI. The HistoScanning AI application comprises fast “patterns recognition” algorithms trained on ultrasound-scans and matched histopathology of cancer patients. It classifies millimetric tissue-volumes by identifying differences in the scattered ultrasound characterizing different mechanical and morphological properties of the different pathologies. A user-friendly interface displays the analysis results on the live ultrasound video image.
Users of AI in diagnostic-imaging of cancer patients expect it to improve their ability to:
Detect clinically significant cancer lesions with high sensitivity and specificity
Accurately position lesions within an organ
Accurately estimate the lesion volume
AND; help determine the pre-clinical level of lesion aggressiveness
The last being achieved through real-time guidance of needle biopsy towards the most suspicious locations.
Unlike most technologies that get obsolete as time passes, AI gets better. Availability of more processing power, better storage technologies, and faster memories translate to an ever-growing capacity of machines to learn. Moreover, the human-perception of AI is transforming fast from disbelief at the time HistoScanning was first launched, into total embracement.
During the last decade, 192 systems were put to use at the hands of urologists, radiologists, and gynecologists. Over 200 peer-reviewed, scientific-posters and white-papers were written by HistoScanning users sharing experiences and thoughts. Most of these papers are about HistoScanning for Prostate (PHS) which was launched as a medical-device in 2007. The real-time guided prostate-biopsy application was added to it in late 2013. I have mentioned several of these papers in blog-posts published in this open-access website, e.g. :
For people who are developing AI applications for health-care, retrospect on HistoScanning represents an excellent opportunity to better plan the life cycle of such products and what it would take to bring it to a level of wide adoption by global health systems.
It would require many pages to cover the lessons HistoScanning could teach each and all of us in detail. I will therefore briefly discuss the highlights:
Regulations: Clearance for HistoScanning by FDA required a PMA and was not achieved until today. The regulatory process in Europe was similar to that of ultrasound but getting harder in recent years.
Safety: During more than a decade and many thousands of procedures, no safety issue was brought up.
Learning curve: Many of the reports on HistoScanning conclude that in order to maximize its potential the sonographer must be experienced and well trained with using the system. Amongst else, it became clear that there is a strong correlation between the clinical added value of using HistoScanning and the quality of the ultrasound scan, which is dependant on the sonographer but also, in many cases, on the patient (e.g. his BMI)
Patient’s attitude: PMS reviews on HistoScanning shows that patients are generally excited about the opportunity of an AI application being involved in their diagnostic process. It seems to increase their confidence in the validity of the results and there was never a case of refusal to be exposed to the analysis. Also, some of the early adopters of PHS (HistoScanning for prostate) charged their patients privately for the service and patients were happy to accept that although there was no reimbursement of such cost by their health insurance.
Adoption by practitioners: To date, PHS did not achieve wide market adoption and users’ feedback on it are mixed, ranging from strong positive recommendation to very negative and dismissive. Close examination of the reasons for such a variety of experiences reveals that most of the reports are relying on small and largely varying samples. The reason for it being the relatively high complexity and cost of clinical trials aiming at measuring its performance. Moreover, without any available standards of assessing AI performance, what is good enough for one user can be totally insufficient for another. Realizing this led to recent efforts by some leading urologists to organize large patients’ registries related to routine-use of PHS.
Studies PHS on statistically reasonable number (611) of patients and concluded that “Our study results support supplementing the standard schematic transrectal ultrasound-guided biopsy with a few guided cores harvested using the ultrasound-based prostate HistoScanning true targeting approach in cases for which multiparametric magnetic resonance imaging is not available.”
The ubiquitin system produces a protein that greatly restricts the development of cancerous tumors.
A new study by researchers at the Technion-Israel Institute of Technology could hold one key to control cancer cell growth and development. In a paper published in the April 9, 2015 edition of CELL, the team reports on the discovery of two cancer-suppressing proteins.
Distinguished Professor Aaron Ciechanover. Photographer: Dan Porges
The research was conducted in the laboratory of Distinguished Professor Aaron Ciechanover, of the Technion Rappaport Faculty of Medicine. The team was led by research associate Dr. Yelena Kravtsova-Ivantsiv and , included additional research students and colleagues, as well as physicians from the Rambam, Carmel and Hadassah Medical Centers, who are studying tumors and their treatment.
The heretofore-undiscovered proteins were found during ongoing research on the ubiquitin system, an important and vital pathway in the life of the cell, which is responsible for the degradation of defective proteins that could damage the cell if not removed. The ubiquitin system tags these proteins and sends them for destruction in the cellular complex known as the proteasome. The system also removes functional and healthy proteins that are not needed anymore, thereby regulating the processes that these proteins control.
Usually, the proteins that reach the proteasome are completely broken down, but there are some exceptions, and the current line of research examined p105, a long precursor of a key regulator in the cell called NF-κB. It turns out that p105 can be broken down completely in certain cases following its tagging by ubiquitin, but in other cases it is only cut and shortened and becomes a protein called p50.
NF-κB has been identified as a link between inflammation and cancer. The hypothesis of the connection between inflammatory processes and cancer was first suggested in 1863 by German pathologist Rudolph Virchow, and has been confirmed over the years in a long series of studies. Ever since the discovery (nearly 30 years ago) of NF-κB, numerous articles have been published linking it to malignant transformation. It is involved in tumors of various organs (prostate, breast, lung, head and neck, large intestine, brain, etc.) in several parallel ways, including: inhibition of apoptosis (programmed cell death) normally eliminates transformed cells; acceleration of uncontrolled division of cancer cells; formation of new blood vessels (angiogenesis), which are vital to tumor growth; and increased resistance of cancerous cells to irradiation and chemotherapy.
The dramatic effect of these proteins on cancer growth: above the two tumors in the foreground (the control group) are tumors that express high levels of the proteins
As noted, the precursor p105 is “handled” by the ubiquitin system in one of two parallel and equally prevalent ways. It is either destroyed completely, or shortened and transformed to p50. The current research deciphers the decision-making mechanism that determines which process will be applied to the protein: when a ubiquitin system component called KPC1 is involved in the process and attaches ubiquitin to p105, the protein is shortened to become p50. When ubiquitination is mediated by another component of the system (and without KPC1), p105 is degraded.
The ubiquitin molecule within all living cells
The decision between these two options has significant implications on the cell, as the presence of high levels of KPC1 (which generates p50) and p50 (the product of the process) – with the accompanying disruption of the normal ratios between the processes – suppresses the malignant growth and apparently protects the healthy tissue. The current research was conducted on models of human tumors grown in mice, as well as on samples of human tumors, and a strong connection was discovered between the suppression of malignancy and the level of the two proteins, clearly indicating that the increased presence of KPC1 and/or p50 in the tissue can protect it from cancerous tumors.
Professor Ciechanover, who is also the president of the Israel Cancer Society, notes that many more years are required “to establish the research and gain a solid understanding of the mechanisms behind the suppression of the tumors. The development of a drug based on this discovery is a possibility, although not a certainty, and the road to such a drug is long and far from simple.”
Professor Ciechanover won the Nobel Prize in Chemistry in 2004 (jointly with Professors Avram Hershko – also from the Technion – and Irwin Rose, of the Fox Chase Cancer Center) for the discovery of the ubiquitin system. The current line of research is a continuation of that discovery.
President Reuven Rivlin and Indian Prime Minister Narendra Modi, March 29, 2015 (photo credit: Courtesty Tomer Reichmann)
President Reuven Rivlin and Indian Prime Minister Narendra Modi, March 29, 2015 (photo credit: Courtesty Tomer Reichmann)
Days after the Technion announced that a team led by Nobel Prize laureate Professor Aaron Ciechanover had discovered how proteins could be used to suppress cancer and control tumor growth and development, the institute revealed that it had entered into an exclusive agreement with India’s Sun Pharmaceuticals — the world’s fifth-largest specialty generic pharmaceutical company and India’s top pharmaceutical company.
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Under the agreement, researchers from the Technion and Sun will conduct studies on how high concentrations of two proteins can protect tissue from tumors. A study published in the medical journal Cell this week discussed how the proteins can suppress malignancies.
Along with Ciechanover, the research team included Dr. Gila Maor and Professor Ofer Binah. In a statement, Ciechanover said that the research held a great deal of promise of an effective drug for treating cancer, “although this is not a certainty, and the road to such a drug is long and far from simple.”
The deal with Sun is just one of several R&D ventures between Israel and India, on both the business and government levels. So far, the two countries have signed seven bilateral economic and R&D agreements, including one that fosters joint projects on space travel and satellite development.
The joint program aims at attracting additional, world-class support from institutions and individuals who are dedicated to eradicating cancer through focused and efficient research.
Two of the world’s preeminent academic and research institutions — New York University’s Langone Medical Center and Haifa’sTechnion-Israel Institute of Technology — have made a “groundbreaking step forward to advance global collaboration in the fight against cancer formally.
On Wednesday night, they announced a $9 million gift from philanthropists Laura and Isaac Perlmutter that will fund two major, joint research endeavors with potentially far-reaching impact in advancing cancer research. The joint program aims at attracting additional, world-class support from institutions and individuals who are dedicated to eradicating cancer through focused and efficient research, they said in a joint statement.
The first $3 million of the grant will finance six cancer-focused research projects to be conducted by teams spearheaded by co-investigators from both NYU and the Technion. The remaining $6 million will be used to establish a state-of-the-art research facility on Technion’s campus that will support these and other research projects and focus mainly on the emerging field of cancer metabolomics.
“NYU Langone and the Technion have a shared, longstanding commitment to advancing cancer research,” said Dr. Dafna Bar-Sagi, senior vice president and vice dean for science at the New York hospital, chief science officer at NYU School of Medicine and a principal architect of the NYU Langone-Technion partnership. “We are now at a great moment in our institutions’ illustrious histories, a point from which we can jointly leverage the talent and creativity of our researchers toward accelerating breakthroughs. The foresight and the generosity of the Perlmutters, particularly at this time of financial challenge in funding for basic research, will have tremendous impact.”
“Bringing together the unique expertise of researchers from both NYU and the Technion will hopefully enable us to overcome some of the most difficult challenges in treating cancer patients,” said Technion Prof. Aaron Ciechanover, the 2004 Nobel Prize Laureate in Chemistry and Distinguished Research Professor and head of the David and Janet Polak Cancer and Vascular Biology Research Center at the Technion Faculty of Medicine.
Renowned cancer biologist Dr. Benjamin Neel, an expert in the field of cell signal transduction, recently joined the Langone faculty as director of the Perlmutter Cancer Center, and Dr. Eyal Gottlieb, a world leader in cancer metabolism, has been recruited to lead the new research facility at the Technion funded by the Perlmutter gift. Neel will work closely with Ciechanover to lead the collaborative cancer research effort between the two institutions, they said.
In addition, Neel will oversee at NYU the building of world-class translational programs in immunotherapy, cancer genetics/targeted therapies and epigenetics, imaging, as well as expanded programs in clinical care, community outreach and supportive oncology.
The innovative method, developed at the Technion, identifies persons at risk for developing stomach cancer and for detecting tumors at an earlier stage. The prestigious journal Gut, which published the research, notes that the detection method is quick, simple, inexpensive and non-invasive.
Innovative gastric cancer-detection technology
Innovative gastric cancer-detection technology developed by the Technion can be used for the early detection of stomach cancer and for identifying persons at risk for developing the disease. The new detection method, based on breath analysis, has significant advantages over the existing detection technology: Gut reports that the new method is quick, simple, inexpensive and non-invasive.
Gastric cancer is one of the most lethal forms of cancer and in most cases, its diagnosis involves an endoscopy (the insertion of a tube into the esophagus, requiring that the patient fast and receive an intravenous sedative). Treatment is aggressive chemotherapy, radiation and the full or partial removal of the stomach. The disease develops in a series of well-defined steps, but there’s currently no effective, reliable, and non-invasive screening test for picking up these changes early on. Thus, many people succumb to stomach cancer only because it was not diagnosed in time.
The new technology, developed by Prof. Hossam Haick of the Wolfson Faculty of Chemical Engineering, can be used to detect premalignant lesions at the earliest stage, when healthy cells start becoming cancerous.
The research, published in Gut as part of the doctoral thesis of Mr. Haitham Amal, was conducted in conjunction with a Latvian research group headed by Prof. Marcis Leja, based on the largest population sample ever in a trial of this type. 484 people participated in the trial, 99 of whom had already been diagnosed with stomach cancer. All the participants were tested for Helicobacter pylori, a bacterium known to increase the risk for stomach cancer, and two breath samples were taken from each person.
The first sample from each participant was analyzed using the GCMS technique, which measures volatile organic substances in exhaled breath. The researchers noted that GCMS technology cannot be used to detect stomach cancer because the testing is very expensive and requires lengthy processing times and considerable expertise to operate the equipment.
The second breath sample was tested using nanoarray analysis, the unique technology developed by Prof. Haick, combined with a pattern recognition algorithm.
The findings:
Based on the concentrations of 8 specific substances (out of 130) in the oral cavity, the new technology can distinguish between three groups: gastric cancer patients, persons who have precancerous stomach lesions, and healthy individuals.
The new technology accurately distinguishes between the various pre-malignant stages.
The new technology can be used to identify persons at risk for developing gastric cancer.
The diagnosis is accurate, regardless of other factors such as age, sex, smoking habits, alcohol consumption and the use of anti-oxidant drugs.
In short, the nano-array analysis method developed by Prof. Haick is accurate, sensitive technology that provides a simple and inexpensive alternative to existing tests (such as GCMS). This new technology offers early, effective detection of persons at risk for developing stomach cancer, without unnecessary invasive tests (endoscopy). In order to assess the accuracy and effectiveness of the new, a wide-scale clinical trial is currently under way in Europe, with thousands of participants who have cancerous or pre-cancerous tumors.
About Prof. Hossam Haick
Prof. Hossam Haick, who joined the senior staff at the Technion Wolfson Faculty of Chemical Engineering in 2006, has been working since that year on the development of innovative, non-invasive technology for detecting cancer and other diseases. This technology is based on an “electronic nose” – an apparatus capable of detecting illnesses by analyzing a patient’s exhaled breath.
Prof. Haick, a native of Nazareth, completed his Ph.D. studies at the Technion by the time he was 27 and went to the Weizmann Institute of Science in Rehovot and Caltech Institute of Technology in California. He returned to the Technion in 2006 and his research group was awarded one million euros in grants by the European Union, which was very impressed by his research into artificial olfactory systems. Today he heads a consortium that includes Siemens and several universities, research institutes and companies in Germany, Austria, Finland, Ireland, Latvia and Israel. Since joining the senior faculty in the Chemical Engineering Department in 2006, Prof. Haick has won dozens of awards, grants and international honors. These include the Marie Curie Excellence Grant, European Research Council (ERC) grant and the Bill & Melinda Gates Award. Prof. Haick was nominated to MIT’s list of the 35 leading young scientists worldwide, received the Knight of the Order of Academic Palms, from the French Government and won the Hershel Rich Technion Innovation Award (twice), as well as the Tenne Prize for Excellence in the Science of Nanotechnology. He has also been recognized for his outstanding teaching skills and is the recipient of the Yanai Prize for Academic Excellence. In 2014, at the initiative of the president of the Technion, Prof. Haick headed an MOOC (Massive Open Online Course) in nanotechnology and nano-sensors that had an enrollment of 42,000.
This month is Breast Cancer Awareness Month in Israel and around the world. Innovative technology developed at the Technion Faculty of Biomedical Engineering will enable the prediction of cancer metastasis after the appearance of breast cancer. The technology, whose efficacy has been proven in preliminary laboratory-trials, is entering into advanced testing using cells from patients undergoing surgery.
In contrast to benign cells (right), metastatic cells (left) penetrate into the gel and disappear inside it, thanks to their unique characteristics
Assistant Professor Daphne Weihs recently achieved a research breakthrough: the unique technology that she developed – a biomechanical method for early detection of metastatic cancer – was approved by the Ethics Committee. This means that the technology that was found to be effective in tests on cell lines will advance to trials with tumor cells collected directly after surgery, in cooperation with Rambam Healthcare Campus.
According to Assistant Professor Weihs, the practical concept is that “during or immediately after a biopsy or surgery on a malignant tumor, the system will enable the medical team to quantitatively evaluate the likelihood of the presence or development of tumor metastases in other organs, and to propose which organ or organs are involved. Such knowledge will make it possible to act at a very early stage to identify and curb these metastases and, moreover, to prevent the primary tumor from metastasizing further.
Cancer is a general name for a wide family of diseases – more than 200 – whose common denominator is that the cell division rate becomes uncontrolled and the cells become immortal. In other words, the cancer mechanism disrupts the normal cell division process and converts it into “wild” and rapid division. Since the cells do not age and do not die, the original, primary tumor expands, invades and takes over more and more nearby tissue. In addition, apart from spreading to its immediate vicinity, a tumor that has become very aggressive “knows” how to send metastases to more distant tissues through the lymph and circulatory systems. Metastases (secondary tumors) are usually more dangerous than the primary tumor because it is difficult to identify them at their inception. When they are detected at an advanced stage, treating them medically is more complicated and the medical prognosis is typically not good.
“In fact, most cancer-related deaths are caused by metastases rather than by the primary tumor, and therefore vast resources are invested in developing methods for early detection of metastases,” explains Assistant Professor Daphne Weihs. “Early detection means timely and more effective treatment. The new approach that we are developing will enable early prediction of the likelihood of the formation of metastases and where in the body their development is probable. This prediction is based on identifying the biomechanics of the primary tumor cells, and does not require us to know the specific genetic makeup of the tumor.”
Diagnostic system developed by Technion professor is to pair with tiny smell-sensitive sensor that can go anywhere
By David Shamah February 3, 2015, 2:05 pm
A patient uses the NaNose breathalyzer (Photo credit: Courtesy Technion)
Writers
David Shamah
An innovative early disease detection system that uses the sense of smell is going mobile.
The NaNose breathalyzer technology developed by Professor Hossam Haick of the Technion will soon be installed in a mobile phone – to be called, appropriately, the SniffPhone. A tiny smell-sensitive sensor will be installed onto a phone add-on, and using specially designed software, the phone will be able to “smell” users’ breath to determine if they have cancer, among other serious diseases.
By identifying the special “odor” emitted by cancer cells, the NaNose system can detect the presence of tumors, both benign and malignant, more quickly, efficiently and cheaply than previously possible, said Haick.
“Current cancer diagnosis techniques are ineffective and impractical,” he said. NaNose technology, he said, “could facilitate faster therapeutic intervention, replacing expensive and time-consuming clinical follow-up that would eventually lead to the same intervention.”
According to research done by Haick’s team, the NaNose system has a 90 percent accuracy rate.
The smartphone device is just a vehicle to implement the NaNose technology that can be taken anywhere and used in any circumstances, including in rural areas of the developing world where bringing in sophisticated testing equipment is impossible.
The plan calls for a chip with NaNose technology to be installed in a device that is attached to a smartphone, and for an app to read the sensor data, analyzing it on the device or uploading it to the cloud for processing.
NaNose technology will be especially useful in battling lung cancer, said Haick. According to US government statistics, lung cancer kills more Americans annually than the next three most common cancers — colon, breast, and pancreatic — combined. The reason, doctors say, is because lung cancer is so difficult to detect. Currently, the only way to detect early-stage lung cancer is through an extensive process involving blood tests, biopsies, CT scans, ultrasound tests, and other procedures — and even then, detection is difficult.
“Mostly the patient arrives for diagnosis when the symptoms of the sickness have already begun to appear,” said Haick, describing the drawbacks in current detection protocols. “Months pass before a real analysis in completed. And the process requires complicated and expensive equipment such as CT and mammography imaging devices. Each machine costs millions of dollars, and ends up delivering rough, inaccurate results.”
Dr. Hossam Haick (Photo credit: Courtesy)
The NaNose-based system, on the other hand, doesn’t require anything more than a patient’s breathing into the device in order to come up with an initial diagnosis. Lung cancer tumors produce chemicals called volatile organic compounds (VOCs), which easily evaporate into the air and produce a discernible scent profile. Haick’s NaNose chip detects the unique “signature” of VOCs in exhaled breath. In four out of five cases, the device differentiated between benign and malignant lung lesions and even different cancer subtypes.
The project is being funded by the European Commission, which has given the consortium developing it a six million euro grant. The developers include universities and research institutes from Germany, Austria, Finland, Ireland and Latvia, as well as Irish cell biology research firm Cellix, with the NaNose system the centerpiece of the technology. That Israeli-developed component will be delivered by an Israeli start-up called NanoVation-GS, a spinoff of the Technion. Professor Haick serves as the start-up’s Chief Science Officer.
“The SniffPhone is a winning solution. It will be made tinier and cheaper than disease detection solutions currently, consume little power, and most importantly, it will enable immediate and early diagnosis that is both accurate and non-invasive,” said Haick. “Early diagnosis can save lives, particularly in life-threatening diseases such as cancer.”
Anyone who knows a person in the midst of chemotherapy is aware that anti-cancer drugs often take a very harsh toll on the body. This is one reason scientists have been trying to develop improved means of drug delivery for years. Now, a Technion research team discovered a way to improve drug delivery to tumors using Nanostructured Porous Silicon (PSi) particles (instead of an IV drip), a method that’s emerging as a promising new platform for drug delivery. In the future, PSi could be used in cancer treatments, potentially offering an alternative to traditional chemotherapy, which is notorious for its agonizing side effects.
The silicon “carriers” used in this study to deliver chemotherapy drugs behave differently in cancerous tumors than they do in healthy tissues. Therefore, the findings could help scientists to design nano-carriers that deliver drugs to tumors, instead of treating patients with traditional, intravenous chemotherapy. However, it would take years to develop and apply this new type of drug delivery method, which would potentially be taken orally.
So far, these nano-silicon “containers” have been studied in vitro – outside of a living organism – rather than in an environment that behaves more closely to that of a tumor in a cancer patient’s body. The Technion research team looked at what happens to PSi particles when they’re injected into the area around the tumor in mice. The significant differences in the area around a cancerous growth and regular healthy tissue have been widely described and studied; however, the effect on these porous silicon “containers,” or carriers, was unknown until now.
Prof. Ester Segal of the Technion – Israel Institute of Technology, who led this joint study with the Massachusetts Institute of Technology (MIT) and the Harvard Medical School, said the team has “shown for the first time that bio-materials in general, and Nanostructured Porous Silicon in particular, behave differently when they are injected (or implanted) at the tumor micro-environment.”
Revolutionizing cancer treatments
Silicon materials could revolutionize treatments in a way that no existing drug delivery does. Prof. Segal tells NoCamels that the silicon containers “could deliver drugs over a long period of time – weeks or even months”, something no existing chemotherapeutic delivery mechanism can do currently.
Cancer cells
The special properties of these porous nano-silicon carriers lie in their large surface area, which can ferry many or large drug molecules. Additionally, due to their biodegradability they’re able to break down into harmless silicic acid, which is expelled through urination. They are also biocompatible, so they do not stimulate any inflammation or clotting. Another benefit to these nano-silicon containers is their versatility. They can be ingested, injected or implanted, and they can be designed to carry a wide range of dosage sizes. In the process of their study, lab members also developed an approach to determining how biomaterials will react in settings more similar to their eventual clinical purpose – treating cancer, for example.
In a separate study, Tel Aviv University scientists recently founda strategy that would stop brain tumor cell proliferation with similar nano-particles. “It is a basic, elegant mechanism and much less toxic than chemotherapy,” TAU’s Prof. Dan Peer said in a statement.
These works underline the importance of such studies in successfully developing bio-delivery materials that will have therapeutic benefits in the near future.
“Nano-skeletons’ (in red) delivered to human tissue infected by prostate cancer. The infected cells are colored in blue (PIP) and green (cytoplasmic); it is possible to see how the ‘nano-skeletons’ reach them
Florida native Dr. Beth Schoen, is part of a team developing a novel platform for delivering anti-cancerous drugs directly to its mark as part of her postdoctoral research at the Technion
Beth Schoen, born in Hollywood Florida, came to the Technion to conduct her postdoctoral research at age 26. In her very limited spare time she plays soccer for the leading all women’s soccer team – Maccabi Hadera – and studies Hebrew. “The Hebrew thing is no simple matter,” she confesses, “but I’m willing to make the effort, because it’s clear to me that Israel is where I want to live.”
Dr. Beth Schoen completed her undergraduate degree at the University of Florida, and her doctorate at Michigan State University in chemical engineering. “My doctoral studies focused on synthetic organic chemistry, particularly on the development of polymers with unique thermodynamic attributes especially resistant to high temperatures. These types of materials are used in part for the production of jet engine parts, body armor and Nomex (used for making fire-resistant gloves and overalls). One of our tasks was to create soft sheets that were not brittle, to be worn to be both bulletproof and fire resistant. It was a theoretical study, but as part of the process I also produced some of these polymers and tested them.”
Dr. Schoen planned to come to the Technion as part of her doctoral studies, but, she adds, “It didn’t work out, so I started to check where I could best fit in here in my future studies.” She decided to join Prof. Marcelle Machluf’s laboratory, at the Faculty of Biotechnology and Food Engineering, “I was eager to move from chemistry to biology and pursue cancer research in particular. I was very glad for the tremendous opportunity that Marcelle gave me in taking me on – perhaps it was because of my experience in nanomaterials and polymers.”
Prof. Marcelle Machluf’s research team consists of 17 female and 3 males students, researchers and technicians working on two main projects: (1) the development of scaffolds to rehabilitate damaged heart-tissue, and (2) the development of new technology to deliver drug treatment to damaged (sick) tissue (specifically related to cancer therapy). In an interview with her she focused on the second project.
“The current treatment for cancer involves radiotherapy and chemotherapy usually administered through intravenous infusion. The cancer drugs available are extremely effective, yet the way they are put to use in present day treatment, they also cause damage to healthy tissues. These are very potent drugs – they are intended to kill cancer cells – and on their way they also end up killing healthy ones.”
“The greatest damage is caused to rapidly dividing cells, which are similar to cancer cells. Hair follicle cells, for example, are a type of rapidly dividing cells and they damage easily from these types of treatment, which explains the hair loss in patients undergoing chemotherapy. Other side-effects include nausea and hearing loss, sometimes even leading to deafness. The drug Cisplatin for example, is a type of chemo drug used to treat various types of lung and breast cancers; some of its side-effects include damage to renal and immune system functioning, putting patients at risk to infections and diseases.”
These impediments are what fuel Prof. Machluf’s drive to develop a new drug delivery platforms capable of delivering anti-cancer drugs directly to the tumor without damaging healthy tissues on its way. “This is the top priority of cancer treatment: to develop a ‘magic bullet’ that target cancer cells,” explains Prof. Machluf. “And our new platform may be the solution to this great challenge.”
The new platform is based on ‘depleting’ specific cells – mesenchymal stem cells – so that there is nothing left of them save for the membrane. This membrane, called a ghost cells can be down sized to nano-vesicles, termed nano-ghosts, which can be loaded with any drug and delivered by injection directly into the blood stream. The immune system falls for the trap and does not recognize the ‘intruder,’ instead it treats these cells as if they were naturally part of the system and sends them to the afflicted area. On the way to their target they do not release the drug they are carrying and therefore do not do any damage to healthy tissues. Only upon reaching the malignant tissue, which they know how to identify, do they break down and secrete their contents at the site of the tumor cells.
This original idea was tested in a long series of experiments, and the results are very impressive: these nano-ghosts are in fact tumor selective, no matter the type of tumor. They ‘dash’ straight to the malignant tissue without emitting their drug on the way and without damaging healthy cells. Moreover, this unique ‘parcel’ increases the effectiveness of the treatment by ten-fold. Animal studies have shown that the employment of nano-ghosts for anti-cancer drug delivery have led to an 80% delay of prostate cancer – an unprecedented rate.
Still, there is a lot of work ahead, as Prof. Machluf’s research team works on improving the mechanism of this novel new platform: some of them are focusing on compatibility with specific drugs while others, like Dr. Beth Schoen, are concentrating on improving the nano-ghosts “This platform must be very precise,” explains Schoen. “It must be able to endure travelling through the entire human body, and release its contents only inside the tumor.”
BioDetego, A cancer diagnostics development company (see meeting announcement here)
Monday, December 14, 2015, 6:30PM; at the Chesterbrook (Wayne, PA) Embassy Suites Hotel (directions below)
Sponsored by:
To register please click on www.rxpcci.com and follow directions
BioDetego is developing the next generation of cancer diagnostics – identifying people that will benefit from chemotherapy with unprecedented accuracy.
Today there are no clear treatment guidelines for many people with cancer and routinely people are undertreated (the lack of chemotherapy treatment for people at risk of disease relapse) or overtreated (the unnecessary, harmful treatment of people not at risk). The resulting human and economic burden is enormous. Those undertreated face increased mortality at a cost of >$150,000 per relapse, and those overtreated suffer the harmful effects of unnecessary chemotherapy at a cost of $25,000 per person.
Supported by compelling clinical data in multiple cancer types, BioDetego is developing VASPfore, a disruptive cancer diagnostic platform that addresses this critical gap in cancer care by accurately determining each person’s risk of relapse and need for chemotherapy. The lead product, VASPfore-CRC, is poised to change the standard of care in colorectal cancer diagnosis and treatment. The test will:
– Accurately determine individual risk of relapse and chemotherapy need
– Provide 100% actionable information to reduce harmful under- and overtreatment
– Improve health outcomes
– Deliver savings by reducing payor costs
BioDetego’s lead product VASPfore-CRC targets 150,000 patients per year diagnosed with stage II or III a/b colorectal cancer in the US, Europe and Australia excluding those unsuitable for chemotherapy due to age or health. Based on pricing of a competitor test with payor coverage the target market is valued at $1Billion. Ongoing development of the VASPfore platform in additional cancer types (e.g. breast, lung and prostate) will substantially increase market size. The total addressable market for the VASPfore platform is comprised of the 1.5 million patients per year diagnosed with an early/intermediate stage epithelial cancer in the US, Europe and Australia and is valued at $6.5 Billion.
PROGRAM
6:30: Cocktails and Dinner; there will be a cash bar and a special two-entrée buffet
8:00 David Zuzga PhD, CEO, will deliver the Company”s “Elevator” pitch to the group.
8:20: A panel consisting of Maria Maccecchini, Dennis Fujii and Caroline Hoedemaker will address three major issues crucial to helping the Company reach the next level. BioDetego has submitted the following questions:
BioDetego is a virtual company without full-time employees and is open-minded about the composition of itd eventual management team. Given the company’s planned next steps, what mix of experience and commitment (potentially draw from its founders, current advisory board members, or from outside the company) would be desirable to potential investors?
VASPfore has the potential to inform oncology clinical trials where enrolling cancer patients likely to relapse may increase the power of a study to determine treatment efficacy. How might BioDetego pursue and structure a co-development deal with a potential strategic partner?
Clinical development milestones, such as the completion of large clinical validation studies and expansion of the platform to additional cancers, represent significant value inflection points. How should these inflection points be integrated into an exit strategy which best manages investor risk and potential for return.
9:00: Q&A session
Remember to register: click on www.rxpcci.com and follow directions
Dinner price for members is a flat $40; Parking is free!
Lifetime dues for new members are still $100; join PCCI and your first dinner will be ON US!
Bring a friend and/or a business colleague! You know that our meetings a livelier and more interesting than ever.
The Embassy Suites Hotel provides an excellent facility, more room and a fine menu.
Every PCCI meeting is webcast. The webcast recording of the PCCI meetings will be posted on the PCCI website “rxpcci.com” and webcast live via the internet during the event.
Directions: Take Rt 202 to the Chesterbrook exit (that’s two exits South of the Devon exit), turn Right at the end of the Exit ramp and you’ll see the hotel at your Right. If you are going North on 202, get off at the Chesterbrook Exit and turn Left at the traffic light and drive back over Rt 202. You’ll see the hotel at your Right. Proceed to the traffic light and turn Right into the parking lot of the hotel. Their phone is: 610 647 6700.
An international team led by investigators in Sweden team used a series of array-based expression and methylomic profiling experiments to put together a so-called gene regulatory network for T cells differentiating into four T helper cell groups.
NEW YORK (GenomeWeb) – The regulatory network controlling differentiation of the immune system’s T cells may contain markers of disease that differ in individuals’ blood samples even before symptoms appear, according to a new study in Science Translational Medicine.
A validated gene regulatory network and GWAS identifies early regulators of T cell–associated diseases
Mika Gustafsson1,2,*,†, Danuta R. Gawel1,†, Lars Alfredsson3, Sergio Baranzini4, Janne Björkander5, Robert Blomgran6, Sandra Hellberg7, Daniel Eklund8, et al.
Diseases may be easier to treat if caught early. However, means of identifying early disease—especially before symptoms appear—are in short supply. Now, Gustafsson et al.identify early regulators of T cell–mediated disease by finding transcription factors involved in T cell differentiation that are enriched in disease-associated polymorphisms. Three such experimentally validated transcription factors—GATA3, MAF, and MYB—and their targets were found to be differentially expressed in asymptomatic stages of two different T cell–mediated diseases—multiple sclerosis and seasonal allergic rhinitis. These data not only provide potential markers of disease development but also shed light on the mechanistic underpinning of T cell–mediated disease.
By cross-referencing transcription factors from this analysis with information from past genome-wide association studies on common human diseases, the group narrowed in on three transcription factors showing disease-related differences in their expression, SNP profiles, and splice variant patterns.
To test their hypothesis that the transcription factors might offer a window on symptom development, the researchers then tracked their expression in the blood of individuals with two relapsing diseases: multiple sclerosis and seasonal allergic rhinitis. Indeed, their results pointed to distinct expression profiles in those with or without symptoms, suggesting similar T-cell regulators could help in finding, treating, or perhaps preventing other common diseases down the road.
“[We think] that different functional variants of these three transcription factors or their expression levels … can be used to predict many T cell-associated diseases with high accuracy,” senior author Mikael Benson, a physician researcher with Linköping University’s Centre for Individualized Medicine in Sweden, told GenomeWeb.
“But,” he cautioned, “to really make it clinically relevant, I think you have to perform more studies of at-risk populations for certain diseases and study many different types of molecules, like methylation and proteins, and pick the most discriminating molecules for discriminating purposes.”
For the most part, diseases aren’t successfully diagnosed until symptoms are obvious, creating problems for those tasked with trying to treat conditions that may already have caused irreparable damage, Benson noted. Along with suffering for patients, this treatment failure leads to health care costs associated with both ineffective drugs and new drug development.
“Ideally, you should actually start treatment for preventing disease before symptoms occur, early in the disease process,” he explained.
In their search for early blood markers of disease, Benson and his colleagues drew from their ongoing work on T cells — a group of white blood cells tasked with patrolling the body to find and stave off forms of disease ranging from metabolic conditions and heart disease to inflammatory conditions and cancer.
“If you can tap into that information — what’s happening in those T cells — ideally you could diagnose disease processes early before symptoms occur,” Benson said.
With that in mind, the researchers did array-based gene expression and methylation profiling on T cells over time as they differentiated into four subsets of T helper cells, hoping to find regulators relevant to early-stage disease.
After assessing such in vitro T-cell differentiation events at six time points in four replicate experiments, the researchers plugged their data into a mathematical model designed by first author Mika Gustafsson, also at Linköping University, to tease apart factors involved in T-cell differentiation regulation.
And from the set of transcription factors pinned to T cell differentiation, the team narrowed in further by folding in information on the genes and variants implicated in common human diseases through past GWAS.
The search led to three transcription factors — GATA3, MYB, and MAF — that were confirmed as T-cell regulators through the researchers’ subsequent chromatin immunoprecipitation sequencing, gene expression profiling, and gene knockdown experiments in differentiated T helper 1 and T helper 3 cells.
From publicly available gene expression data, the researchers found that these three transcription factors and/or their target genes were differentially expressed in T cell-associated diseases such as rheumatoid arthritis, acute myeloid leukemia, or systemic lupus erythematosus.
Meanwhile, their own experiments in T cell samples from individuals with seasonal allergic rhinitis, individuals with MS, and unaffected control individuals suggested splicing patterns and gene expression of the three transcription factor markers shifted as symptoms appear in each of the relapsing diseases.
While there may not be a clear clinical need to test for allergic seasonal rhinitis, Benson explained, he and his colleagues believe a similar approach could be used for finding informative markers in individuals at risk of certain diseases such as hereditary breast cancer, for example, to diagnose, treat, or attempt to prevent disease.
“A likely continuation would be to study various forms of common cancer in at-risk populations to show clinical feasibility,” he said. “We believe that it’s probably easier to find drugs that can stop earlier disease processes than established ones.”
More generally, Benson said, it would be ideal to start testing markers identified through these sorts of studies over decades in prospective studies of thousands or hundreds of thousands of individuals who start out healthy, using longitudinal blood samples such as those planned for President Obama’s Precision Medicine Initiative.
sjwilliamspa
Seems odd to me that they had done microarray as T cell differentiate. I would have felt this has been done with other methodology such as differential display. The finding of GATA3 does not seem unique though as this factor is commonly differenctially expressed as cells differentiate and is involved in the differentiation of many cell types. It only seems to me coincidental that a cross search in expression databases revealed GATA involved in disease states, which it is however does not seem a fair comparison. They would need to constitutively express GATA3 in an autologous transfer to see if mice develop symtomology of these diseases, which does not seem totally plausible.
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.
•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”.
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).
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).
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.
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).
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.
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.
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).
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.
References
Authors Title
Source
Akbani, R., Ng, P.K.S., Werner, H.M.J., Shahmoradgoli, M., Zhang, F., Ju, Z., Liu, W., Yang, J.-Y., Yoshihara, K., Li, J. et al. A pan-cancer proteomic perspective on The Cancer Genome Atlas.
Bettegowda, C., Sausen, M., Leary, R.J., Kinde, I., Wang, Y., Agrawal, N., Bartlett, B.R., Wang, H., Luber, B., Alani, R.M. et al. Detection of circulating tumor DNA in early- and late-stage human malignancies.
Bidard, F.-C., Peeters, D.J., Fehm, T., Nolé, F., Gisbert-Criado, R., Mavroudis, D., Grisanti, S., Generali, D., Garcia-Saenz, J.A., Stebbing, J. et al. Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data.
Bray, P.F., McKenzie, S.E., Edelstein, L.C., Nagalla, S., Delgrosso, K., Ertel, A., Kupper, J., Jing, Y., Londin, E., Loher, P. et al. The complex transcriptional landscape of the anucleate human platelet.
Burkhart, J.M., Gambaryan, S., Watson, S.P., Jurk, K., Walter, U., Sickmann, A., Heemskerk, J.W.M., and Zahedi, R.P. What can proteomics tell us about platelets?.
Katherine A. Hoadley, Christina Yau, Denise M. Wolf, Andrew D. Cherniack, David Tamborero, Sam Ng, Max D.M. Leiserson, Beifang Niu, Michael D. McLellan, Vladislav Uzunangelov, Jiashan Zhang, Cyriac Kandoth, Rehan Akbani, Hui Shen, Larsson Omberg, Andy Chu, Adam A. Margolin, Laura J. van’t Veer, Nuria Lopez-Bigas, Peter W. Laird, Benjamin J. Raphael, Li Ding, A. Gordon Robertson, Lauren A. Byers, Gordon B. Mills, John N. Weinstein, Carter Van Waes, Zhong Chen, Eric A. Collisson, The Cancer Genome Atlas Research Network, Christopher C. Benz, Charles M. Perou, Joshua M. Stuart
Pau Creixell, Erwin M. Schoof, Craig D. Simpson, James Longden, Chad J. Miller, Hua Jane Lou, Lara Perryman, Thomas R. Cox, Nevena Zivanovic, Antonio Palmeri, Agata Wesolowska-Andersen, Manuela Helmer-Citterich, Jesper Ferkinghoff-Borg, Hiroaki Itamochi, Bernd Bodenmiller, Janine T. Erler, Benjamin E. Turk, Rune Linding
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
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
2012pharmaceutical
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