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Determining the likelihood of malignancy in women with pelvic masses

, 26 August 2020/in Featured Articles /by 3wmedia

The ROMA (Risk of Ovarian Malignacy) algorithm uses the CA-125 and HE4 blood markers to determine the likelihood that a pelvic mass is malignant. The test has been shown to aid gynaecologists in referring women to gynaecologic oncologists for surgery.

by Dr Zivjena Vucetic

Ovarian cancer is the leading cause of death from gynaecologic malignancies in the United States with annual incidence of 22,000 cases. Estimated annual mortality rate is approximately 15,460 cases [1]. Ovarian cancer has a good prognosis if detected in its early stages and if treated by specialised gynaecologic oncology surgeons [2], however more than three-quarters of cases are diagnosed in the advanced stage and are associated with poor survival rates of 10-30% [3]. These poor outcomes reflect the lack of effective tools for early detection of ovarian cancer and the limitations of current treatment options for ovarian cancer, which generally include cytoreductive surgery followed by adjuvant chemotherapy.

Recent studies have shown that women with ovarian cancer develop non-specific symptoms, including pelvic or abdominal pain, increased abdominal size, bloating, urinary urgency and difficulty eating or feeling full quickly, months before diagnosis [4]. However, ovarian cancer is commonly discovered on surgery for an adnexal mass. It is estimated that 5–10% of women at some point in their lives will undergo surgical evaluation of an adnexal mass and up to one fifth of surgically removed masses will have a diagnosis of ovarian cancer [5]. In premenopausal women, the risk of a mass being malignant is 7-13%, while in the postmenopausal women is 30-40% [6]. Thus, the presence of symptoms and the findings of an adnexal mass increase the risk of malignancy and should prompt thorough diagnostic evaluation.

The primary goals of diagnostic evaluation of women who present with adnexal masses are to confirm that adnexal mass is of ovarian origin and to differentiate whether it is benign or malignant. In order to determine the most appropriate management strategy that would ensure the optimal outcome for the woman with adnexal mass it is essential to effectively triage the risk for malignancy. Combination of multiple diagnostic modalities improves the physician’s ability to preoperatively assess women with adnexal mass. Diagnostic techniques that are commonly used are: clinical exam and thorough medical history, imaging (e.g. transvaginal ultrasound) and serum tumour maker (e.g. CA125) measurements. According to a study by the US Agency for Healthcare Research and Quality, which assessed diagnostic strategies for distinguishing benign from malignant masses, all current diagnostic modalities showed significant trade-offs between sensitivity and specificity [7]. Although the serum CA125 test does not have FDA-cleared indication as preoperative diagnostic aid in women with ovarian masses that are suspected to be malignant, CA125 is commonly used and recommended by the American Congress of Obstetricians and Gynecologists (ACOG) and the Society of Gynecologic Oncologists (SGO) for this indication [8,9]. The main clinical disadvantage of CA125 for adnexal mass assessment is its insufficient sensitivity for detecting early stage cancer and decreased specificity, due to false elevations in benign obstetric-gynaecologic conditions such as endometriosis, leiomyomas, pelvic inflammatory disease and pregnancy [10].

HE4 – ovarian cancer specific biomarker
HE4 (Human epididymis protein 4) is a member of a family of four disulphide core (WFDC) domain proteins and the function of this protein is unknown [11]. The HE4 gene is elevated in serum from women with ovarian cancer and its expression in normal tissues, including ovary, is low [12]. Several studies have indicated that using HE4 alone or in combination with CA125 may improve the accuracy for detection of ovarian cancer. In a study by Moore et al that evaluated nine known biomarkers for ovarian cancer, HE4 showed the highest sensitivity at a set specificity for the detection of ovarian cancer, particularly in early stage disease [13]. In this study, the combination of HE4 and CA 125 was a more accurate predictor of malignancy than either marker alone, with a sensitivity of 76% and a specificity of 95%. Additional studies confirmed that measuring serum HE4 concentrations along with CA 125 concentrations may provide higher accuracy for detecting ovarian cancer, and may improve the accuracy for detection of ovarian cancer at an earlier stage.

Additionally, a number of studies demonstrated improved specificity of HE4 for discriminating ovarian cancers from benign gynaecologic disease. Huhtinen et al was first to report that serum concentration of HE4 was significantly higher in patients with endometrial and ovarian cancer than in patients with ovarian endometriomas or other types of endometriosis [14]. These results were later confirmed in studies reported by Montagnana et al and Holcomb et al [15,16]. Recently, in a large study of 1042 pre- and postmenopausal women with benign gynaecological disorders HE4 was found to be less frequently elevated than CA125 in several benign diseases [17]. For example, HE4 was elevated in only 3% of premenopausal women with endometriosis, while in the same group CA125 was elevated in 72% of women. Unlike CA125, which can be elevated in one fourth of pregnant women and a third of patients with pelvic inflammatory diseases (PID), HE4 is not elevated in pregnancy and PID [16,18]. In addition, in healthy premenopausal women HE4 does not appear to oscillate during the menstrual cycle [19].

ROMA test: an aid in determining the likelihood of malignancy in women who
present with an adnexal mass
In September 2011, the ROMA test received clearance from the FDA as an aid in assessing whether a premenopausal or postmenopausal woman who presents with an adnexal mass is at high or low likelihood of having a malignancy. ROMA is a qualitative serum test that combines the results of two biomarkers, HE4 + CA 125, and menopausal status into a single score and is indicated for women who meet the following criteria: over age 18 and adnexal mass present for which surgery is planned.

The effectiveness of ROMA to aid in estimating the risk of malignancy was determined in a prospective, multi-centre, blinded clinical trial of 461 women over 18 years old (240 pre- and 221 post-menopausal) presenting with an adnexal mass that required surgical intervention [20]. For each patient, an initial cancer risk assessment (ICRA) was completed by a non-gynaecological oncologist, providing the generalist’s assessment of the patient’s mass as benign (negative) or malignant (positive) based upon the information available to the generalist during his/her work-up of the patient. The corresponding histopathology reports were collected and the stratification into low and a high risk groups for finding malignancy on surgery was determined using ROMA. The incidence of ovarian cancers was 10%. ROMA achieved 100% sensitivity at 74.5% specificity, a positive predictive value (PPV) of 13.8% and a negative predictive value (NPV) of 100% for stratification of premenopausal women with epithelial ovarian cancer into low likelihood and high likelihood groups of having malignancy. In postmenopausal women, ROMA had 92.3% sensitivity at 76.8% specificity, a PPV of 50.0% and NPV of 97.5% for stratification into low and high likelihood groups of having malignancy. When considering all women together ROMA had a sensitivity of 93.8%, a specificity of 74.9% and a NPV of 99.0%.

In a separate prospective, multicentre trial conducted at 12 US tertiary care institutions, 566 women undergoing surgery for adnexal mass were classified using ROMA into high and low likelihood groups for having epithelial ovarian cancer [21]. The incidence of ovarian cancers in this cohort was 23%. In the postmenopausal group at specificity of 75.0%, ROMA had sensitivity of 92.3%. In the premenopausal group at the specificity of 74.8% ROMA provided a sensitivity of 76.5% for classifying into high likelihood and low likelihood groups for having malignancy.

Additionally, seven distinct, single centre, multinational studies were published that validated the use of ROMA for adnexal mass risk stratification [22-28]. Combined, these studies assessed over 4,000 women with adnexal mass that were scheduled to undergo surgery in the United States, Europe and Asia. The range of sensitivity for ROMA test was from 75 % – 94%, at specificity from 75% – 95%. ROMA demonstrated consistent and reliable performance for classifying women with adnexal mass into high risk and low likelihood groups for epithelial ovarian cancer.

Conclusions
In the US, women with adnexal masses present primarily to gynaecologists, primary care physicians or general surgeons for initial diagnostic evaluation. According to a Practice Bulletin from the American Congress of Obstetrics and Gynecology (ACOG) an important dilemma is faced by these physicians as to which patients are appropriate for referral to a gynaecologic oncologist, and/or to an institution experienced in gynaecologic cancer surgery. Several recent studies have demonstrated that ovarian cancer patients managed by gyneacologic oncologists and at high volume institutions are more likely to undergo complete surgical staging, and optimal cytoreductive surgery with fewer complications and better survival rates than patients treated by surgeons less familiar with the management of ovarian cancer. Based on the available clinical evidence, ROMA test represents an important tool for improved triage of women diagnosed with an adnexal mass which can ultimately lead to improved patient outcomes.

References
1. Jemal A et al. CA Cancer J Clin 2010; 60(5): 277-300.
2. Giede KC et al. Gynecol Oncol 2005; 99(2):447-61.
3. 1999-2006 National Cancer Institute –Surveillance Epidemiology and End Results (NCI-SEER)
4. Goff BA et al. Cancer 2007; 109: 221-27.
5. Trimble EL. Gynecol Oncol 1994 ; 55(3 Pt 2): S1-3.
6. Danforth’s Obstetrics and Gynecology, ed. B.Y.K. Ronald S. Gibbs, Arthur F. Haney, Ingrid Nygaard. 2008: Lippincott Williams & Wilkins.
7. Myers ER et al. 2006; 130: 1-145.
8. ACOG Practice Bulletin. Obstet Gynecol. 2007; 110: 201-213.
9. The Society of Gynecologic Oncologists. Gynecol Oncol 2000; 78(3 Pt 2): S1-13
10. Jacobs I, Bast RC Jr. Hum Reprod 1989; 4(1): 1-12
11. Bouchard D et al. Lancet Oncol 2006; 7: 167-74.
12. Drapkin R et al. Cancer Res 2006; 65: 2162-69.
13. Moore RG et al. Gynecologic Oncol 2008; 108: 402-408.
14. Hutinen K et al. Br J Cancer 2009; 100: 1315-1319.
15. Montagnana M et al. Br J Cancer 2009; 101(3): 548.
16. Holcomb K et al. Am J Obstet Gynecol Am J Obstet Gynecol 2011; 205(4): 358.e1-6.
17. Moore RG et al. Am J Obstet Gynecol 2012; 206(4): 351.e1-8.
18. Moore RG et al. Am J Obstet Gynecol 2012; 206(4): 349.e1-7.
19. Hallamaa M et al. Gynecol Oncol 2012 Mar 14. [Epub ahead of print]
20. Moore RG et al. Obstet Gynecol 2011; 118(2, Part 1): 280-288.
21. Moore RG et al. Gynecol Oncol 2009; 112(1): 40-6.
22. Van Gorp T et al. Br J Cancer 2011; 104(5): 863-870.
23. Jacob F et al. Gynecol Oncol 2011; 121(3): 487-491.
24. Lenhard M et al. Clin Chem Lab Med 2011 Sep 16.
25. Molina R et al. Tumour Biol 2011; 32(6): 1087-95.
26. Montagnana M et al. Clin Chem Lab Med 2011; 49(3): 521-525.
27. Ruggeri G et al. Clin Chim Acta 2011; 412(15-16): 1447-1453.
28. Kim YM et al. Clin Chem Lab Med 2011; 49(3): 527-534.

The author
Zivjena Vucetic, PhD
Fujirebio Diagnostics, Inc.

Factors impacting on sample collection for urinary schistosomiasis research in Abeokuta, Nigeria

, 26 August 2020/in Featured Articles /by 3wmedia

Sample collection is an important aspect of scientific work because it shapes, to a great extent, the study design and methodology, both of which may influence the outcomes of scientific research. However, often in scientific evaluations of studies which involve both field sample collection and laboratory work, only the laboratory research aspect receives serious attention, while other factors such as the socio-cultural, ecological and belief values of subjects who donate samples for laboratory studies are much less emphasised. These factors and how they play out in any particular study area are critical determinants of successful field sample collection especially in the developing countries.

by Dr Olufunmilola Ibironke, Dr Samuel Asaolu and Dr Clive Shiff

Urinary schistosomiasis is caused by a trematode worm, Schistosoma haematobium [1]. Infection with this parasite has been shown to be the commonest cause of haematuria and urogenital diseases in endemic areas. Thus, detection of haematuria in urine has been proposed as a valid indicator of schistosome infection, and has been widely adopted in many national schistosomiasis control programmes [2,3]. Diagnostic procedures in control programmes accordingly involve collection of urine samples from patients.

Most studies of urinary schistosomiasis in Nigeria and other endemic countries have targeted schoolchildren [4-8], because they represent the prime reservoir for the parasite, and children are amenable to mass chemotherapy [9]. However, studies have shown the debilitating effect of the parasite among adults in communities where it is endemic [10-13] and so this population also needs to be studied. As opposed to urine sample collection from children which is mostly done in schools, collection of urine from adults is difficult, particularly among persons who do not consider schistosomiasis as their major health problem when compared to malaria. In a school-based setting, after obtaining clearance from government health and school administrative authorities, researchers usually work with school teachers to get permission from pupils’ parents, and to educate the children involved in the study about how to follow urine sample collection instructions. However, for studies which involve adults, researchers, with the help of local health officers, would have to deal with patients directly to seek their individual involvement in the study, the acceptance of which depends on a number of the above mentioned factors.

Few studies have investigated the sociology of communities involved in such studies. We present here a study on urinary schistosomiasis in two villages in Ogun State, Nigeria, involving collection of urine samples from adults, to investigate the factors that drive their acceptance or refusal for inclusion in the study.

Methods and study sites
The study involved adults between the ages of 20 and 55 years who were mobilised to school halls in each village through the respective heads of the villages. Participants were informed of their right to accept or reject inclusion in the study. Many adults refused to come to school halls, many others who came rejected inclusion in the study. Some others accepted inclusion and collected urine sample containers but never came back while others accepted full participation. People in endemic communities show negative attitudes to urine sample collection for different reasons. To find out villagers’ attitudes to the urine sample collection process, we asked consenting participants why their friends or family refused to participate and in the process we identified some factors responsible for their attitudes. We also visited some households either to seek consent for inclusion or to understand reasons for refusing inclusion in the study.

This study was conducted in July, 2010, in Ogun State, Nigeria as a part of a study on the diagnosis of urinary schistosomiasis in six villages. For the purpose of comparison, two villages, Apojola located in Odeda Local Government Area (LGA), and Ogbere in Ijebu-east LGA, were selected. Apojola is located on Oyan Dam Reservoir. The inhabitants are all immigrant fishermen and their families, and are a mixture of Moslem Hausas and Christian Idomas. Awawa River serves Ogbere community. The inhabitants are mainly Christian Yorubas, and a mixture of farmers and Local Government Area civil servants. Ethical consideration, the data collection process, the population of each village, vegetation types and locations of each local government area have been reported previously [14].

Observations and discussion
Socio-cultural aspect
Several urinary schistosomiasis studies had been conducted in Nigeria, most of which involved urine sample collection, so there is a high level of awareness about the importance of control programmes. However, in the process of field studies there is often confusion in the minds of the participants leading to fear of exposure to strangers which was found to prevail among the villagers. Frequently researchers are mistaken for government agents visiting for revenue collections. If the researcher can work with members of the community to change these opinions it would likely improve level of cooperation for inclusion in the study. We explored this aspect in Apojola, a community located on the heavily schistosome-infested Oyan dam reservoir. We made the first attempt to recruit participants through the community leader, followed by the religious leader, a nurse and a school teacher. The number of participants recruited through the assistance of the different leaders according to age and gender are shown in Table 1a. In Table 1b, it was shown that the community leader is the most effective in helping to mobilise the villagers of both genders for urine collection.

There is also an increasing cynicism about the disease among adult patients in endemic communities. Many members of the communities who admit passing blood in the urine do not perceive it as an indication of a serious disease. They consider it as a sign of virility and puberty which is a familiar sign among adults in other villages around them. A few others who have experienced some discomfort and thought it might be a major health problem were either ashamed of their disease status or ashamed of bringing their ‘red’ urine. Past studies have noted that individuals’ perceptions on the aetiology and impact of urinary schistosomiasis differed with their levels of education and gender [13]. Lack of knowledge about the cause and effect of the disease affects patient’s turnout for sample collection and this in turn has a direct influence on field data coverage and research quality.

Apart from lack of health education on the cause of the disease, the willingness to participate in the urine sample collection process is seemingly greater among patients with some level of education than among the uneducated. We investigated how patient’s level of education impacts turnout for urine sample collection in Ogbere community. Ogbere inhabitants are a mixture of uneducated farmers, who have nought to six years of formal education, and the educated comprising teachers and Local Government Area civil servants, who have from seven to 16 years of formal education. In Table 2, data from both groups are presented for comparison to show turnout according to education level and gender.

This Table shows the percentage contributions by the Community Leader (CL), Nurse (N), Teacher (T) and Religious Leader (RL) on the total number of respondents. CL is best for mobilising males in the community (P = 0.00155). CL is also best for mobilising male and female with calculated P = 0.052 just higher than 0.05. N is best for mobilising females but this is not statistically significant.

Ecological aspect
Transmission of urinary schistosomiasis is through freshwater snails, Bulinus species, as intermediate hosts and varies with different ecological factors. In many endemic communities, the ecological factors which favour disease transmission also promote agricultural practices such as farming, cattle rearing and fishing. Therefore, transmission to humans often occurs as a result of irrigation systems for agricultural purposes or when visits are made to the rivers for washing and swimming. As such, the rate of transmission to humans varies, to a great extent, with occupation.
However, since diagnosis is by urine testing, many peasant farmers and fishermen who are thought to be the most impacted with S. haematobium because of frequent water contact may remain undiagnosed and untreated. Urine sample collection for the diagnosis of urinary schistosomiasis is preferably done between the hours of 10:00 and 14:00 for optimum egg passage [9]. These hours coincide with the time during which farmers go to farm and fishermen set nets for fish catching. This coincidence might affect turnout for sample collection and estimation of overall disease prevalence in the community.

To evaluate the impact of patient’s occupation on turnout for urine sample collection, we compared turnout of farmers and civil servants in Ogbere community. For statistical purpose, farmers, cattle rearers and fishermen are classified as farming, while students, teachers and local government workers are classified as civil servants, see Table 2. In total, there are 84 participants out of which 33 are farmers (39.2%) and 51 are civil servants (60.7%). In all, more women (79.8%) turned out for sample collection.

According to the community leader, the total adults’ population in Ogbere is 3121 and the ratio of farmers to civil servants is approximately 20:1.

Z- Distribution test was used to compare the response level between the two groups using the formula:

(see picture number 4)

where p is the difference of proportions, N1 = 149 = Educated population and N2 = 2972 = Uneducated population. At all levels of significance 0.05, 0.01 and 0.001, response from the educated civil servant population was significantly higher than response from the uneducated farmer population.

Belief structures
Christians in Apojola and Ogbere communities were relatively unhindered by religious belief regarding their willingness to come forward for education about the project and provision of their urine samples. However there was gender problem with urine collection among the Muslim families at Apojola. The Muslim families at Apojola have the culture of restricting married women within the family household compounds and forbiding male visitors of adolescent age and older from entering the compounds or visiting the women. In order to be able to collect urine samples from these Muslim women, the local community nurse and a female member of our research team were accompanied by a local female Muslim field assistant and interpreter before being allowed access to the compounds to explain the importance of the disease and purpose of the study.

Conclusion
This study attempts to find out patients‘ attitudes to scientific research especially during a field sample collection process and suggests possible reasons for rejection of inclusion in scientific research by patients. In general, this study showed that social and ecological values including educational background, occupation, religious practices and poor knowledge about the aims and objectives of the study, strongly influence turnout for urine sample collection. Therefore, such values are worth considering for a holistic understanding of the scientific study results.

References
1. Edungbola LD, Asaolu SO, Omonisi MK, Aiyedun BA. Schistosoma haematobium infection among schoolchildren in the Babana district, Kwara State, Nigeria. Afr J Med Sci 1988; 7: 187-193.
2. Koukounari A, Gabrielli AF, Toure S, Bosque-Oliva E, Zhang Y, Sellin B, Donnelly CA, Fenwick A, Webster JP. Schistosoma haematobium infection and morbidity before and after large-scale administration of praziquantel in Burkina Faso. J Infect Dis 2007; 196: 659-669.
3. Webster JP, Koukounari A, Lamberton PH, Stothard JR, Fenwick A. Evaluation and application of potential schistosome-associated morbidity markers within large-scale mass chemotherapy programmes. Parasitology 2009; 136: 1789-1799.
4. Abdel-Wahab MF, Esmat G, Ramzy I, Fouad R, Abdel-Rahman M, Yosery A, Narooz S, Strickland GT. Schistosoma haematobium infection in Egyptian schoolchildren: demonstration of both hepatic and urinary tract morbidity by ultrasonography. Trans R Soc Trop Med Hyg 1992; 86: 406-409.
5. Fenwick A, Webster JP, Bosque-Oliva E, Blair L, Fleming FM, Zhang Y, Garba A, Stothard JR, Gabrielli AF, Clements AC, Kabatereine NB, Toure S, Dembele R, Nyandindi U, Mwansa J et al. The Schistosomiasis Control Initiative (SCI): rationale, development and implementation from 2002-2008. Parasitology 2009; 136: 1719-1730.
6. French MD, Rollinson D, Basanez MG, Mgeni AF, Khamis IS, Stothard JR. School-based control of urinary schistosomiasis on Zanzibar, Tanzania: monitoring micro-haematuria with reagent strips as a rapid urological assessment. J Pediatr Urol 2007; 3: 364-368.
7. Nduka FO, Ajaero CM, Nwoke BE. Urinary schistosomiasis among school children in an endemic community in south-eastern Nigeria. Appl Parasitol 1995; 36: 34-40.
8. Okoli EI, Odaibo AB. Urinary schistosomiasis among schoolchildren in Ibadan, an urban community in south-western Nigeria. Trop Med Int Health 1999; 4: 308-315.
9. Ibironke OA, Phillips AE, Garba A, Lamine SM, Shiff C. Diagnosis of Schistosoma haematobium by detection of specific DNA fragments from filtered urine samples. Am J Trop Med Hyg 2011; 84: 998-1001.
10. Koukounari A, Webster JP, Donnelly CA, Bray BC, Naples J, Bosompem K, Shiff C. Sensitivities and specificities of diagnostic tests and infection prevalence of Schistosoma haematobium estimated from data on adults in villages northwest of Accra, Ghana. Am J Trop Med Hyg 2009; 80: 435-441.
11. Mostafa MH, Sheweita SA, O’Connor PJ. Relationship between schistosomiasis and bladder cancer. Clin Microbiol Rev 1999; 12: 97-111.
12. Mungadi IA,.Malami SA. Urinary bladder cancer and schistosomiasis in North-Western Nigeria. West Afr J Med 2007; 26: 226-229.
13. Sarkinfada F, Oyebanji AA, Sadiq IA, Ilyasu Z. Urinary schistosomiasis in the Danjarima community in Kano, Nigeria. J Infect Dev Ctries 2009; 3: 452-457.
14. Ibironke O, Koukounari A, Asaolu S, Moustaki I, Shiff C. Validation of a new test for Schistosoma haematobium based on detection of Dra1 DNA fragments in urine: evaluation through latent class analysis. PLoS Negl Trop Dis 2012; 6: e1464.

The authors
Dr Olufunmiola Ibironke*
Cell and DNA Repository
Rutgers, The State University of New Jersey
New Brunswick
New Jersey, USA
e-mail: oai5@rutgers.edu

Dr Clive Shiff
Department of Molecular Microbiology and Immunology
Johns Hopkins Bloomberg School of Public Health
Baltimore, MD, USA
e-mail: cshiff@jhsph.edu

Dr Samuel Asaolu
Department of Zoology
Obafemi Awolowo University
Ile-Ife
Nigeria

*Corresponding author

The ‘Virtual Patient’ in healthcare: IT Future of Medicine

, 26 August 2020/in Featured Articles /by 3wmedia

To be able to mobilise our healthcare system to treat patients as individuals rather than as members of larger, divergent groups, the IT Future of Medicine (ITFoM) initiative proposes to develop a new, data rich computation-based individualised medicine of the future, based on integrated molecular, physiological and anatomical models of every person (‘Virtual Patient’) in the healthcare system. The establishment of such ‘Virtual Patient’ models is now possible due to the enormous progress in analytical techniques, particularly in the ‘omics’ technology areas and in imaging, as well as sensor technologies. Complemented by continuing developments in ICT, these technological developments could, over the coming years, make the ‘Virtual Patient’ a key component in healthcare and disease therapy and prevention. ITFoM is an European consortium combining unparalleled expertise in medicine, analytics and ICT to develop the ‘Virtual patient’.

by the ITFoM consortium

Today´s medicine
Currently medicine assesses patients as parts of large, often inhomogeneous groups. Rather than as individuals, patients are treated as members of a group for which a specific therapy has been statistically shown to be more effective than other therapies. This is even regardless of the fact that this therapy might very well make the majority of patients more ill than they would be without treatment.

Today’s medicine does not take into account the tremendous diversity between human individuals. Moreover, diseases are not homogenous either in regard to clinical manifestation or underlying causative effects. In cancer this is taken to an extreme with each tumour being different, because each of these tumours is the product of a specific and unique accumulation of mutational events.

Symptoms and signs of disease often appear only late in disease progression when a large portion of the involved organ has already failed. The symptoms might be non-specific, making a diagnosis difficult. Today´s routine clinical workup of sick patients can be extensive, expensive and can have side effects. For these reasons, many advocate preventive measures that mandate predefined checkups to be carried out by primary care physicians. Only a few preventive measures are currently useful including blood pressure control, blood sugar and lipid measurements, colonoscopy in older people, gynaecological tests in women and last but not least weight control. Both in the presence or absence of symptoms and signs of diseases, the knowledge of the full genome, the metabolome, the proteome, the microbiome and the total exposure to toxins from the environment, would have a tremendous impact on both disease workup and preventive measures.

Tomorrow´s medicine
The medicine of the future will use a ‘Virtual Patient’ system that can integrate all molecular, physiological and anatomical data into personalised models of individual people, enabling prediction of the result of lifestyle choices and medical interventions on a tailored case-by-case basis. This innovative approach will revolutionise healthcare systems, with enormous benefits for prevention, diagnosis and therapy of patients. The possibility to personalise the models allows tailor-made therapy and treatment strategies for each individual. With the model-based decision of which drug or which doses of drugs will have the optimal effect in an individual patient, the model approach will help to optimise treatment and reduce side-effects dramatically. A model-based approach will also serve as a research tool to discover and validate new compounds for drug development, potential drug treatments and applications, but also new commercial opportunities in ICT, analytics and healthcare.

ITFoM: IT Future of Medicine
ITFoM – one of the six pilot initiatives within the European Future and Emerging Technologies Flagship scheme competing for a total of 1 billion EUR over a time span of 10 years – will lay the groundwork for a project that will integrate medicine, analytical techniques and IT hardware and software development for the IT driven, data-rich, individualised medicine of the future.
By now, it has become quite conceivable to develop sequencing strategies allowing the determination of the genome, epigenome and transcriptome of a tumour, for instance, in parallel to its surgical removal, allowing the surgeon to scale the extent of the operation based on the real time computational modelling of its detailed genomic, epigenomic and transcriptomic characterisation. Dramatic improvements are also expected in the capabilities of other molecular analysis techniques, such as proteomics and metabolomics.

Why ITFoM makes the difference in ‘personalised medicine’: next generation of molecular analytics
The generation of the first draft of the human genome was a worldwide concerted action that had a strong impact on the development of new technologies for molecular biology. During the last ten years high throughput technologies have been emerging not only for DNA sequencing, but also for protein and metabolite analysis. These high throughput technologies are called ‘omics’ technologies, highly parallelised approaches aiming at the generation of information on complete sets of molecules in organelles, cells, whole pathways or even organs in order to get a comprehensive view of a biological system. A variety of ‘omics’ subdisciplines have emerged, each developing its own instruments, techniques and processes. With the increasing amount of data generated by the ‘omics’ technologies, development of tools for intelligent mathematical analysis and data mining are needed. This demand has developed into a completely new area in biology, namely bioinformatics.

For the first driver of the ‘omics’ technologies, DNA sequencing, currently the so-called ‘third generation’ sequencing technology is already appearing on the market. This innovation will allow the sequencing of a whole genome within one day, the costs for sequencing are in almost free fall, it can be anticipated that very soon the goal of sequencing a whole genome for less than 1.000 $ will be reached. These innovations open the door to allowing the sequencing of the genome of each single patient and using this information for truly personalised medicine. DNA sequencing is also used to study transcriptional expression, microRNA, DNA methylation, hydroxymethylation, transcription factor
occupancy, histone modification at specific sites in the genome and overall organisation of genomes in cells.

The personal genome information will be a very important basis for future medicine, but more ‘omics’ information will be integrated: information about proteins and metabolites will allow a much more precise picture of the physiological status of a person. The aim for protein and metabolite analysis now is to apply a method that allows the detection of all proteins and all metabolites in a given sample or tissue. The same holds true for the information about protein modifications and interactions.

Other lab technologies for molecular analysis including imaging and sensor technology are also starting to increase in speed, precision, application range and information output.

Another level of complexity takes into account life style and environmental factors, and more specifically the microorganisms interacting with the human body.

All these technologies allow the generation of highly detailed information about an individual’s genetic make-up and physiological status to give an unprecedented insight into the functioning of a person’s cells, tissues, organs and even the individual as a whole.

Systems biology is a solution that provides the methodologies and tools for mathematical analysis, integration and interpretation of biological data, employing mathematical models of biological processes. Mathematical models support the understanding of data sets on a large scale and integrate existing knowledge for interpretation. Model approaches in the ITFoM will drive the development further into models that are able to generate computational simulations to predict what cannot be measured directly. The translation of these novel approaches into clinical application will allow identification of the optimal therapy or medical treatment for each person based on the individual data available.

To generate the models and implement the ‘Virtual Patient’ model into clinical practice, substantial advances must be made in underpinning hardware and software infrastructures, computational paradigms, human computer interfaces and visualisation, as well as in the instrumentation and automation of techniques required to gather and process all relevant information. Examples of the major challenges in the information and communication technologies are interoperability, data storage and processing, efficient use of computing power, statistics and medical informatics. Integration of the individual datasets is realised via the ITFoM ‘Virtual Patient’ models enabling the provision of concrete health advice on a personal basis.

The authors
IT Future of Medicine Consortium (ITFoM)
Max Planck Institute for Molecular Genetics
Ihnestrasse 63-73
14195 Berlin
Germany