What is the brain that it can understand science?What is science that it can understand the brain?These two basic questions (with homage to Warren McCulloch in the framing) have guided my career, aiming to understand the brain and an effort to understand science. This journey has taken me from academic lab work to clinical research oversight and government policy to the emerging health & science technology industry and back to academia. It has now led me to co-lead, along with Dr. Jennifer Lovejoy of the Institute of Systems Biology, this section of Frontiers in Systems Biology -Systems Concepts, Theory and Policy in Biology and Medicine. Our journal Chief Editor, Dr. Yoram Vodovotz, has laid out the overarching vision for this and the other sections (Vodovotz, 2021). This Grand Challenge is an effort to add another layer of detail to the portions of that broad scope contained in our Systems Concepts section (Lovejoy, 2024).Systems biology and systems medicine have roots going back to at least World War II, when biologists and physiologists were recruited into the war effort in the United States and Britain, trained in computational approaches, and joined with engineers and mathematicians to solve complex problems with communications, radar, anti-aircraft guns and more (Churchill, 1949). This alignment led to the foundation of the field of cybernetics and the related Macy Conferences in the U.S. postwar, while in Britain, "This coalescing of biological, engineering, and mathematics frameworks would continue to great effect a few years later as the Ratio Club," (Husbands, 2008). In the decades that followed, this robust milieu of ideas would foster the development of everything from general systems theory and information theory to artificial intelligence (AI) and cognitive science (Pickering, 2010). Despite this early alignment, it would be decades before systems biology and systems medicine arose as formal fields of inquiry (Green, 2017).Science has arguably been the most effective way of generating and validating new knowledge for the past few centuries. New technologies and computing approaches now provide us with novel tools to accelerate this process. While early work is being done to explore the use of these new tools for science, these have been limited in success to real-world application to detailed aspects of biology and medicine (McCoy, 2024). A comprehensive conceptual framework may be a more effective way to realize the value of technology in accelerating science. Modern science is not a simple holistic process, but an amalgam of processes and interests that have accumulated over centuries.By analyzing this system of science, we can better synthesize a new approach to using the array of emerging technologies now available. This will require us to revisit the current human and institutional processes that govern the creation of new scientific knowledge. A human and machine hybrid approach, aligned with a governance in the classic cybernetic style (i.e. control and communication in humans and machines), may allow us to optimize our scientific efforts and advance knowledge for the betterment of all of humanity.There has been much excitement about the potential of emerging technologies applied to science in recent yearsfrom AI to applications of blockchain technologies and web3 applied as decentralized science (DeSci) (Weidener, 2024). In these nascent efforts there has often been an oversimplification of science in order to capture technical requirements to automate or simulate biomedical research.Science is not done by a single person or organization. Science embodies the contribution of multiple individualswhose brains are themselves collections of dozens of subsystems (Kirby, 2024)processed through a series of refinement and testing. The results of these are moved through a longitudinal process of validation, contextual framing against prior accumulated knowledge, and consensus determination of evidence level and confidence in the results. Only then does this new knowledge contribute to the body of generalized knowledge we applied to the real world.Creating a new technology-accelerated knowledge system for biomedical science -what I'm calling here Scientia Machinamay be best approached through first articulating the conceptual and epistemological framework of the current system of biomedical science as it moves from data to information to evidence to knowledge and its application. Along the way it passes through layers of trust and is eventually captured in the artifacts of biomedical science we have come to rely on and expect. For applications of emerging technologysuch as the automated complex information processing of AI and the automated trust and governance of blockchainto be most beneficial to science, we should use them to systematically augment and accelerate these processes and creation of the artifacts of science while maintaining or improving the basic conceptual framework of biomedical knowledge discovery and implementation. Eventually parts of the current system may be sundowned leading to an even greater acceleration of science.This Scientia Machina framework starts with identifying key layers of trust in the biomedical bench to bedside process of evidence based medicine. Here I have proposed five layers of trust along with examples of their current artifacts and processes, plus potential approaches to augmenting these with technology and related adjustment to the current workflow (Figure 1).Data Layer -Data are collected in experimental and/or clinical context, often based on specific methodology. The principal investigator (PI) and team, along with the equipment and techniques used, are trusted to produce and capture explainable and reproducible data. This layer is only sometimes made transparent and rarely validated.Future of Data -Data are verifiable through trackable provenance and alignment with related metadata (e.g. demographics, treatment delivery details, device and equipment specifications, etc.). Data can be accessed for querying and algorithm training without moving, copying or exposing the data.Information Layer -Data are combined in datasets with contextual meta-data (e.g. demographics of research participants). The PI and team are trusted to compile, store and manage this data. It is increasingly becoming requested by funders and publishers to be made available. Some programs promote dataset sharing through centralized repositories or direct PI to PI contact.Future of Information -Data confidence fabrics allow sorting combined datasets based on confidence levels for each data point related to their associated metadata, with deployable programming to temporarily convert non-standard data into a calculable or trainable standard.Evidence Layer -Analysis of the datasets and testing hypotheses produces results that interpreted as findings. These are presented as novel assertion, backed by the data and methods, and put into the context of previously identified findings in the field in the form of a manuscript submitted for peerreview. The journal editors and peer-reviewers are trusted to confirm the assertions are supported by the evidence, fit (or convincingly contradict) previously established knowledge in the field.Future of Evidence -Swarm approach, i.e. networked, auditable crowd-sourcing, to peer review with a wider array of contributors with inputs weighted based on preset governance and continuous crowd feedback for nearer to real-time review with broader, multi-discipline input.Knowledge Layer -Combined sets of published articles are reviewed by a group of experts against certain criteria to answer specific questions about the state of evidence in the field as systematic reviews and meta-analyses to provide the most up-to-date knowledge in the specific area of focus.The groups of authors along with editors and peer-reviewers of those systematic reviews and metaanalyses are trusted to have executed and validated, respectively, a thorough and sound assessment of the evidence for the area in question to provide new knowledge.Future of Knowledge -Swarm approach (see above) to systematic review with network on demand request for new or updated reviews of existing evidence along with evidence threshold signals (i.e. sufficient new evidence in a particular areas prompts new or updated systematic review).Applied Knowledge Layer -Applications of knowledge can come in various forms, including pharmaceuticals, devices and procedures. The application of knowledge is periodically assessed for incorporation into clinical practice guidelines (CPG) and similar clinical guidance documents. The CPG group is trusted to have found and appropriately graded all of the available evidence and refined knowledge on a topic area to best inform clinicians how to address the area optimally.Future of Knowledge Application -Networked clinical practice guideline wiki (collaboratively edited living document) allowing for continuous, network refereed input and update of new knowledge.Each of these layers and their future states can be augmented, enhanced, accelerated and potentially replaced with appropriate applications of an array of automated processing and trust technologies. Additional administrative areas of biomedical research such as gap analysis, funding, regulatory review and more can be similarly improved.The call to action for this Grand Challenge is to: a) Consider the core elements of what we need to maintain and continue to elevate from our past and current successful biomedical research and knowledge translation effort, along with areas where those efforts have been flawed, corrupt or unsuccessful. b) Critique (and adjust or replace as needed) the Scientia Machina framework proposed here as the backbone for the layers of trust that are the core elements to be maintained as we continue to bring new technologies into biomedical research to accelerate and improve science. c) Capture and assess those current pilots to apply emerging technology -especially within AI (complex information processing) and DeSci (automated governance, auditing and/or incentivization) as umbrella categories for these effortsand place them in the context of a broader framework of what we are trying to achieve with biomedical research. d) Conceptualize gaps in our current efforts along with bridges from the current status quo to the desired future that may give us a better chance of success at transformational change to the systems of biomedical research and knowledge translation. e) Communicate all aspects of the above areas in appropriate venues of biology, medicine, technology and policy. This includes formal submissions of manuscript on any related topics to this journal section and its partnered sections as appropriate.This proposed conceptual framework is merely a jumping off point for broader consideration of how to maintain the core elements of the trust we have imbued in biomedical research as we continue to explore applications of emerging technology to improve its quality, manage its costs, and accelerate its contribution to the health and well-being of everyone. In the not so distant future, it is conceivable that we may be able to make all available relevant data on a topic or a patient accessible to any researcher to make AI-augmented and blockchain-audited hypothesis testing to provide near realtime, peer-validated contributions to evidence-based medicine. This could allow clinicians to query and access this near real-time evidence as part of compressing the 17 years it takes to go from bench to bedside by a factor of 10,000xgiving us new, actionable evidence-based precision medicine for patients in under a day. This future is within reach. Aligning behind a shared framework like Scientia Machina can bring it into our reality even faster. Better science. Cheaper research. Faster Miracles.STM is the sole author, having conceived, written, and edited this manuscript.
We, as oral physicians, do an extensive literature search to find out the best diagnostic investigation or best therapeutic option for a disease that we encounter in clinical practice. But do we pause for a moment and look at the literature to see whether the researchers have formulated the most specific focused research question in their works? Failure in this first step to formulate the most appropriate research question would subsequently affect the entire research process. In the arena of research, there are numerous players whose expectations need to be taken into consideration before a good research question is formulated. Foremost among them are our clients â the patients for whom we are doing research. We need to initially ascertain what the patient is expecting from us as a treatment for his ailment and what changes he is expecting in his Quality of Life. The second is our (investigator) views about the intended endpoints for a particular problem we are trying to solve. Third, unfortunately, we often neglect to ascertain the opinions of our co-workers regarding our proposed work. They might have a different perspective on our thought process. Finally, if we have agencies to fund our work, we need to ascertain that they are on board with us to support our research, agreeing with the problem for which we are trying to find a solution. If we analyze from the point of each stake holder mentioned above, each view is logical and it becomes a herculean task for the investigator to formulate and evolve the most appropriate research question. As a guide, researchers could follow the following criteria[1]: - The most appropriate question which is important to patient well-being - The most appropriate question relevant to our knowledge levels - The most appropriate question that can be addressed in a specific time frame - The most appropriate question that would interest you, your team and your patients the most - The most appropriate question that is likely to repeatedly present itself in your practice. As a piece of advice, I would state that, the scientific community always recognizes and appreciates researchers who address problems of diseases faced in their own local community and not some diseases which are very rare in a particular geographic setting. A researcher should always formulate an âAnswerableâ question. Here, a large broad topic needs to be split into smaller manageable units, which can then be addressed through a standardized protocol.[2] A young researcher by nature would be too ambitious to make a path breaking research to solve all problems. But, seldom does it happen. If your research question is too wide, you end up, lacking rigor in methodology. If your question lacks focus, it is almost close to impossible to replace it with another question once your work is commenced or completed. All questions you want to answer should follow the PICO format. This format is suggested because it helps you to specifically narrow down, refine and formulate your question to address one specific problem. Though PICO format is meant to address interventions, other research questions (diagnostic, prognostic, patient expectations) can be reframed to follow PICO format. The next key element of good scientific research is choosing the appropriate study design. We need to mandatorily sit with trained âBIOSTATISTICIANSâ, explain our intended work and zero in on the most appropriate study design. Researchers need to do a thorough data search to find out how a similar question was designed and studied. As you navigate this process you will find your primary research question getting more and more focused which would help you to reframe your PICO components. The above exercise is definitely time consuming and test your patience, but remember â the extra time spent in this stage would save you many hours later if you proceed with an irrelevant research question, inappropriate study design or work on a topic which has already been exhaustively analyzed. Researchers feel quantitative research where you can categorize all parameters with numerical data is superior to qualitative research. But we oral physicians deal with a plethora of disorders especially oro-facial pain where the need to address emotions, feelings are more important than aiming at numerical value changes as a proof of your successful patient management. Qualitative research design are better suited address research questions dealing with feelings and emotions.[3] The NHMRC evidence hierarchy categorizes the most appropriate study design for specific type of research questions â interventional, diagnostic accuracy, prognosis, etiology, and screening.[4] On the contrary, in qualitative research, it is advisable to follow a typical practice-based approach to analyze the data through either a case study, grounded theory, phenomenology, ethnography,ethno methodology and narrative research. To conclude, researchers need to focus on the two essential pillars â the most appropriate answerable focused clinical question and choosing the most appropriate study design to specifically answer the formulated question. However well a question is framed and study is designed, the results will open the door for a next question to be investigated. That is how science grows and progresses!!
Classical Pragmatism, Particularly The Work of John Dewey, has been foundational to the development of design as a discipline, although rarely directly acknowledged within the literature on design (Dixon 6â7). Recognizing the ways in which the dominant design paradigm reproduces coloniality and modernity (Akama et al. 60â62), I argue that going back to design's roots in pragmatism can aid in building a more embodied, situated, and pluralistic design practice. In an attempt to counter the epistemic and ontological injustices perpetuated by design, I support the effort of redesigning design by drawing on pragmatist thinking to present alternative design practices aimed at building reflexivity. In doing so, I bring forward demonstrations of how design practice might act as âengaged philosophy,â practically addressing issues in their social context (Hamington and Bardwell-Jones 1â6), with the aim of supporting intentional adaptation within a pluralistic, democratic society.Before I begin, it is important for me to position that I am writing this from Oslo, Norway, the city with the largest urban population of SĂĄmi people, an Indigenous people that inhabit and have been stewarding the land across large northern parts of Norway, Sweden, Finland, and Russia for thousands of years. I grew up as a settler of Dutch ancestry on the land of the Anishinabewaki and Mississauga First Nations on Turtle Island, or what is now commonly known as Ontario, Canada. I am grateful for the opportunity to work and learn on these lands and thankful to all of the generations of people who have taken care of this land. I also want to acknowledge the historic and present-day injustices faced by Indigenous peoples, which require our collective responsibility and commitment to challenge and address. Recognizing the ways in which our democracies are entangled in coloniality, working intentionally toward decolonizing our societal structures is fundamental to respecting plurality with democracies.The design practice and research that I present here has taken place within the context of health and care systems in Canada, Sweden, and Norway. This work is positioned in relation to institutionalized Western medical systems that continue to perpetuate epistemic and ontological injustice, justifying the exclusion of divergent ways of knowing and being. Health care systems are recognized as carriers of modernity, perpetuating social structures that reflect care as a commodifiable resource (Gallagher 65â67). Design is entangled within these systems both implicitly, through the intentional actions of a wide variety of health care stakeholders, and explicitly in the work of a growing number of professional designers hired within Western health care systems (Mager 9; Molloy 16â18). Take, for example, Bardwell-Jones's study of placental ethics within hospital settings in Hawaiâi. She illustrates how the universal health policies associated with âmodernâ biomedical approaches can actively undermine local knowledges, in this case, of Indigenous Hawaiians (103). Here, I position this research in response to Bardwell-Jones's call for health care administrators to cultivate epistemic humility and resistant imaginations (108). I bring forward design practices that may aid in integrating the incommensurability of a perplexing situation (Addams 20) and support people's ability to stay curious about other ways of being within and across diverse communities.I enter into this dialogue by first opening up the conversation about the role of the dominant design paradigm in advancing âthe modernity projectâ and highlighting the need to decolonize design. I move into explorations of how we might redesign design by focusing on building reflexivity and sharing stories of alternative design approaches that draw on the thinking of both classic and feminist pragmatists. Finally, I end with a discussion of the role of design as an everyday world-making practice that can aid in resisting epistemic injustice and ontological occupation to nurture plurality amid democracy.Design is an intentional world-making practice in which people shape their environment and, in turn, the environment shapes people (Willis, âOntological Designingâ 70). The dominant Eurocentric design practice emphasizes commercialized, standardized, and disembodied practices of designing, inadvertently, and sometimes even overtly, contributing to the erosion of democratic life. As highlighted by Willis (Design Philosophy Reader 2), âwhen a question of a philosophical character is posed, such as âwhat is design?â the answer is mostly already over-determined by the model of professional design as the model of all designing.â In this way, globally dominant Eurocentric professional design practice has become synonymous with what is understood as being within the boundaries of the design discipline (Fry, âDesign for/by âThe Global Southââ 25). This dominant understanding of design undermines the domestic design work that women have been doing in the home for centuries (Weltge 58) and relegates traditional forms of design in Indigenous communities and the Global South to the distinct label of âcraftâ (Tunstall 235).Increasingly, the design profession has adopted common frameworks to guide design practice, such as the double diamond (popularized by the UK Design Council), which presents a universal approach to problem solving, and a variety of human-centered design toolkits that tout the applicability of design methods to support problem solving across contexts (Akama et al. 60â62). Through these frameworks and toolkits, the designer convinces ânon-design experts,â from other professions to grassroots communities, that following their structured, universal process can get the desired results (Ansari, âPolitics and Methodâ). In this way, design methods are seen as something that can be separated from the practicing designer, exported and commodified for repeatability (Akama and Prendiville 32). The portability of methods within human-centered design has the potential to undermine the deep cultural differences within local contexts (Duan et al. 272; Lee 21). For example, the application of a common design method, often referred to as the âuser journey,â where a person maps the steps of a âuserâ as they move through the use of a product or service, emphasizes the individual experience and may inadvertently undermine the importance of relations, which are central in cultures that emphasize collectivity.Popular practices of superficial empathy within these design methods often promote single-mindedness, projection, and otherness (Vink and Oertzen 473). In addition, some popularized methods associated with âdesign thinking,â such as the use of Post-it Notes to brainstorm ideas, emphasize the Cartesian divide between mind and body, furthering a cognitivist perspective that inadvertently downplays the role of the body (Wetter-Edman et al. 5). While the common narrative is that these methods allow for creative participation, there is growing acknowledgment that many design methods act as effective tools of coloniality, disciplining participantsâ perception of the world (Tlostanova 53). Design tools are not value-neutral, as is often claimed, but are rather created through the politics of their makers (Ansari, âPolitics and Methodâ). These methods often suppress the mess and multiplicity of realities, directing participants toward a predefined understanding of what is good [Vink et al., âDesigning Good(s)?â 967]. Such tools often perpetuate imperialism by reinforcing the hierarchy of Western design companies and undermining local ways of designing (Tunstall 236). This dominant practice of design, honed in the Global North, is a product of colonialism working to further Eurocentric notions of progress and modernity (Fry, âDesign for/by âThe Global Southââ 7).To exemplify the ways in which dominant design practice can to the of coloniality and modernity, I draw from experience as a I to work on the design of a for in the The First and between the of and in Ontario, Canada. 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Abstract Curriculum that is truly interdisciplinary reflects the emerging consensus definition of interdisciplinarity and addresses the core elements of interdisciplinarity. These elements include (1) addressing a complex problem or focus question that cannot be resolved by using a single disciplinary approach, (2) drawing on insights generated by disciplines, interdisciplines, or schools of thought, including non-disciplinary knowledge formations, (3) integrating insights, and (4) producing an interdisciplinary understanding of the problem or question. Integrating these dements into curriculum at all levels should reduce much of the semantic evasiveness surrounding the term interdisciplinary, foster integrative learning, and enhance meaningful assessment of interdisciplinary courses and programs. Introduction Writing in the Chronicle of Higher Education, Jeffrey N. Wasserstrom (2006, January 20) complains that interdisciplinarity has become so fuzzy that a university's commitment to it is close to meaningless (p. B5). If programs claiming to be interdisciplinarity are fuzzy in their understanding of what interdisciplinarity is, then their curriculum will not provide the proven educational outcomes for students that interdisciplinarity promises. This, in turn, will severely compromise meaningful assessment of these programs. Klein (1999) argues in Mapping Interdisciplinary Studies that interdisciplinary curriculum must make sense locally and yet, to achieve quality, also ought to be informed by research and the national conversation (p. 16). interdisciplinary curriculum, therefore, requires familiarity with the extensive literature on interdisciplinarity. This literature addresses theory, research process, innovative pedagogies, assessment, institutional context, and faculty support strategies, and can be mined profitably for core design elements that typically characterize interdisciplinarity curriculum. Two essays by Newell provide a good place to start: Designing Interdisciplinary (1994) provides a step-by-step guide to designing interdisciplinary courses, examines their theoretical rationale, and identifies expected learning outcomes; and Powerful Pedagogies (2001b) examines new assessment techniques, educational benefits of integrative learning, and ancillaries to formal courses such as learning communities, experiential learning, and study abroad. The essays in Interdisciplinary General Education: Questioning Outside the Lines edited by Seabury (1999) explain how to design general education curricula that will build students' integrative skills. Davis (1995) in Interdisciplinary Courses and Team Teaching: New Arrangements for Learning traces the development of five interdisciplinary courses at the University of Denver from conception and planning to evaluation and revision. The essays in Innovations in Interdisciplinary Teaching edited by Haynes (2002) provide invaluable insights into interdisciplinary teaching, learning, and curriculum design for new and experienced faculty. The Association for Integrative Studies (AIS) website offers a wealth of information on curricula design, including papers, syllabi, back issues of Issues in Integrative Studies, and useful links. Designers of interdisciplinary curriculum should also consult recent work on interdisciplinary assessment, the psychology of cognitive interdisciplinarity, and the interdisciplinary research process. Until recently, interdisciplinary assessment lacked clear guidelines, meaning that faculty and administrators had to rely on discipline-based measures that privileged tests as proof that a student had command of key concepts and skills (Klein, 1999, pp. 18-19). Works by Field, Lee, and Field (1994), Farmer and Napieralski (1997), Schilling (2001), McGann (2001), Tommerup (2001), Field and Stowe (2002), and Wolfe and Haynes (2003), as well as the several reports by Harvard University's Project Zero, document the shift from quantitative to qualitative approaches, from summative to formative evaluation, and from reliance on inputs to emphasis on outcomes. âŚ
The current dogma of cancer research is that the accumulation of gene mutations in a single cell is responsible for the development and progression of human cancers. âAlmost everybody believes that cancer requires certain gene mutations,â noted Christoph Lengauer, Ph.D., associate professor of oncology at Johns Hopkins University, Baltimore. âSeveral genes have to be affected in order to generate cancer, and genetic instability [caused by gene mutations] allows for the accumulation of [these] mistakes.â But this theory is open to debate. Robert Weinberg, Ph.D., professor of cancer research at the Massachusetts Institute of Technology, Cambridge, agrees with Lengauer and believes that tumor cells arise from disruptions in critical signaling pathways as a result of mutations in various oncogenes and tumor suppressor genes. However, Peter Duesberg, Ph.D., professor of molecular and cellular biology at the University of California at Berkeley, believes that aneuploidy, an abnormal number or complement of chromosomes, is the critical mutation responsible for all solid human cancers, independent of specific gene mutations. Both theories have plenty of researchâand unanswered questionsâbehind them. As codiscoverer of viral oncogenes in the 1970s, Duesberg spent 10 years testing the hypothesis that cellular oncogenes cause cancer, but was unsuccessful. âI had my own interests at stake,â said Duesberg. âI realized that the fundamental difference that set apart human oncogenes from viral oncogenes was that viral oncogenes have very strong promoters and express [the gene product] 1000-fold higher. We cannot find such a dominant human oncogene.â Because of this, he criticizes the widespread use of viral promoters in already aneuploid cells, such as NIH3T3, to prove that an oncogene causes cancer. Duesberg began to explore alternative cancer theories. âAll of a sudden you see a forest when you were looking for trees,â said Duesberg on aneuploidy, predicted to be the cause of cancer almost a century ago. âAneuploidy is a very solid correlation.â It is present in nearly all nonviral, solid cancers, and it explains the growing list of nonmutagenic carcinogens and why human oncogenes cannot turn human cells into cancer cells. In addition, âaneuploidy changes thousands of cellular pathways,â he noted, explaining the unique properties of cancer cells. He said he believes that aneuploidy is the only somatic mutation that explains all of the characteristics of a cancer cell. William Brinkley, Ph.D., vice president and dean of Baylor College of Medicine, Houston, is also examining the relationship between aneuploidy and cancer. âMy view is that aneuploidy is an essential mutation for transformation to malignancy. Aneuploidy is brought about by defects in the mitotic apparatus that result in cell progeny with chromosomal imbalance. Therefore, a defective mitosis leading to aneuploidy is a decisive event in the initiation of genomic instability, a complex process that results largely in cell death but also favors selective clonal outgrowth of tumor cells.â However, Brinkley believes that aneuploidy âmust be preceded by additional mutations or altered gene expression that results in defective mitosis.â He is examining the role of a specific mitosis gene that he believes is involved in this process. Duesberg believes that carcinogens generate defects in the mitotic apparatus by directly targeting the spindle apparatus or fragmenting the chromosomes. In addition to causing cancer, Duesberg predicts that aneuploidy, by reassortment of the chromosomes, is responsible for tumor recurrence and multidrug resistance observed in cancer patients. âMost people believe that aneuploidy is important for cancer development,â said Lengauer, who supports Duesbergâs work. âBut [Duesberg] goes a little too far in his belief that cancer can occur independent of gene mutations.â Lengauer agrees that carcinogens may be able to induce aneuploidy in the absence of gene mutations, but he does not believe that this by itself can cause cancer. Weinberg believes that aneuploidy is only a consequence of the cancer process, and may not even be a requirement. âOver the last 25 years, no one had ever succeeded in taking a normal human cell and transforming it into a tumor cell through the introduction of mutant genes,â said Weinberg. However, Weinberg and colleagues did just that. In Nature last year, they described the first genetically defined human tumor cells, by adding three mutant genes to two normal human cell lines, embryonic kidney and fibroblasts. In this study, four cellular pathways were important. An oncoprotein of SV40 virus (large T antigen) simultaneously knocked out two tumor suppressor proteins, p53 and Rb. âAnd both of them must be inactivated, we believe, in order to create a human tumor cell. At the same time, hTERT [telomerase] must be upregulated [to enable cells to grow indefinitely], and finally the mitogenic growth-promoting pathway indicated by ras must also be upregulated.â The resulting cells were anaplastic, highly angiogenic, minimally invasive, and nonmetastatic. âThey set the stage for the long process of trying to relate the genes that are damaged in a human genome with the complex behavioral phenotype of the cancer cell,â noted Weinberg. âOf course, thereâs much that lies ahead because the genes that weâve introduced are hardly representative of those that are found mutated in spontaneously arising human tumors.â In response to Weinbergâs publication, Duesberg analyzed the cells and published his observations in Proceedings of the National Academy of Sciences, arguing that what was important about the tumor cells was their aneuploidy, not the introduced genes. âAnd in fact,â noted Weinberg, âhe argued that this was a troubled hypothesis [gene mutation], and these genes were really an epiphenomenon of the whole process of cancer formation, rather than being at the center of the process.â Weinberg recently had the cells re-examined at the National Cancer Institute, and mentioned that one of the cell lines was found to be diploid, in complete contradiction to Duesbergâs observation. Weinberg believes this is proof that âaneuploidy is not an essential prerequisite to the creation of a transformed human malignant cell.â âIf present at the scene of a crime, you are a suspect. If not present, you are excused,â noted Duesberg, an analogy to the observation that ânot one gene [mutation] has been identified that is consistently found in a highly specific cancer.â Weinberg and others believe that many of the identified oncogenes/tumor suppressor genes lie in the same critical pathways that need to be disrupted for cancer development. Lengauer pointed out that 88% of nonhereditary colon cancers have a mutation in the APC gene, and a nonoverlapping 10% have a mutated β-catenin gene. Both of these genes lie in the same cellular pathway. But can gene mutations and aneuploidy really work independently to cause cancer? Can they work together? âCurrently, I believe both may be involved in some cancers,â said Baylor College of Medicineâs Brinkley. âCarcinogens that are mutagens may target oncogenes that ultimately destabilize mitosis, setting conditions for errors that lead to aneuploidy. In the case of nongenotoxic carcinogens such as asbestos, aneuploidy appears to be sufficient to cause cancer. The fact that non-mutagenic agents can cause cancer, and the fact that it has been impossible to isolate cellular genes from cancer cells that transform normal human cells, leads me to seriously question whether gene mutation alone (without aneuploidy) can cause cancer.â Dr. Robert Weinberg Dr. Peter Duesberg The photos above show the 46 chromosomes (plus x and y) from a normal diploid cell (left) and the chromosomes from a cancer cell that exhibits aneuploidyâit has 85 chromosomes.