Cancer Prevention

Certificate in Cancer Prevention Admissions Requirements

Admission deadlines (for submission of on-line applications and all required documentation) for matriculation in to the fall academic semester.

Applicants should have a sufficient educational background in the biological or biomedical sciences prior to admission to the program. J or H Visa international students may apply to this program. All applications must include: 

  • A grade point average (GPA) no lower than B (3.0 in a 4.0 system) in the last 60 hours of coursework for a BS/BA degree or a GPA of at least 3.0 for applicants with a MS degree.
  • All transcripts from foreign institutions must be evaluated by an accredited credentialing agency (https://www.naces.org/). Evaluations must include 1.) a listing of all courses in English and 2.) a final grade point average (4.0 scale) of all courses taken, not just science courses. 
  • A minimum score of 84 on the internet based version of the Test of English as a Foreign Language (TOEFL), a band score of 7 on the academic version of the International English Language Testing System (IELTS) or a minimum score of 115 on the Duolingo English Test, for applicants from countries where English is not the native language. Scores on TOEFL, IELTS or Duolingo tests taken more than two years prior to the date of matriculation will not be accepted.
  • Three Letters of recommendation attesting to the applicant's readiness for graduate level studies in translational science. If a matriculated graduate student has a supervising professor, one letter must be provided by this individual.
  • A personal statement (1-2 pages) that includes a brief description of the applicant’s background, long term research and/or career goals, and an indication of the basis for application into the CCP Program including how this program fits into the applicant’s career objectives.
  • A current curriculum vitae.

Certificate in Cancer Prevention Certificate Requirements

Twelve semester credit hours of didactic coursework are required to obtain the CCP.  Satisfactory completion of required and elective coursework is also needed in order to be recommended for awarding of the certificate.

Certificate in Cancer Prevention Sample Plan of Study

First Year
FallCredit Hours
TSCI 5070Responsible Conduct of Research2
TSCI 5071Patient-Oriented Clinical Research Methods-12
TSCI 5072Patient-Oriented Clinical Research Biostatistics-12
TSCI 6105Topics in Cancer Prevention1
TSCI 6001Introduction To Translational Science1
 Total Credit Hours: 8.0
First Year
SpringCredit Hours
TSCI 6106Practicum in Cancer Prevention Science0.5-1
TSCI Elective course (see list below)  4
 Total Credit Hours: 4.5-5.0

CCP Elective Courses (may be taken in any semester when offered)

TSCI 5073Integrated Molecular Biology With Patient-Oriented Clinical Research1
TSCI 5074Data Management, Quality Control And Regulatory Issues2
TSCI 5075Scientific Communication2
TSCI 5077Translational Science Training (TST) Practicum1-3
TSCI 5080Integrating Molecular Biology with Patient-Oriented Clinical Research Practicum1
TSCI 6060Patient-Oriented Clinical Research Methods-22
TSCI 6061Patient-Oriented Clinical Research Biostatistics-22
TSCI 6065Health Services Research2
TSCI 6069Statistical Issues, Planning, And Analysis Of Contemporary Clinical Trials2
TSCI 6070Biostatistics Methods For Longitudinal Studies2
TSCI 6100Practicum In IACUC Procedures1
TSCI 6101Topics In Translational Science1
TSCI 6102Practicum In IRB Procedures1
TSCI 5201Statistical Principles of Machine Learning for Biomedical Data3
TSCI 5230Analytical Programming for Biomedical Data Science3
TSCI 6201Data Science Leadership in Healthcare1
TSCI 6202Data Visualization and Building Applications2
TSCI 6203Practicum in Biomedical Data Science1

Certificate in Cancer Prevention Objectives and Program Outcomes

The goal of this program is to provide graduate students, postdoctoral fellows, faculty and other health care professionals with formal education in the essential components of the science of cancer prevention. 

Specific aims are to support the intellectual environment at UT Health San Antonio for cancer prevention science and to provide fundamental curricular activities in science of cancer prevention to UT Health San Antonio students, postdoctoral trainees, clinical residents and fellows, and faculty from the Schools of Medicine, Nursing, Dentistry, Health Professions, and the Graduate School of Biomedical Sciences, as well as from local organizations that are partnered with UT Health San Antonio. The aims will be achieved via participation and successful completion of required didactic coursework.

Certificate in Cancer Prevention Program-Specific Policies for Laptop Computers

Students are required to have a laptop computer that can connect to and operate over a wireless network. 

Software Required:

  • Microsoft Office Suite  (A personal copy of the latest version can be purchased at the health science center bookstore at student pricing with a student ID).

Laptops with an Apple based operating system must be able to also operate using a Windows based operating system.

TSCI 5070. Responsible Conduct of Research. 2 Credit Hours.

This foundational course introduces students to core ethical content necessary for responsible research conduct. Through interactive seminars, students will learn about (1) scientists as responsible members of society (contemporary ethical issues in biomedical research and environmental/social impacts of research), (2) policies for research with human subjects and vertebrate animals, (3) collaborative research, (4) conflicts of interest (personal, professional, financial), (5) data acquisition and laboratory tools (management, sharing, ownership), (6) responsible authorship and publication, (7) mentor/trainee responsibilities and relationships, (8) peer review (9) research misconduct (forms of misconduct and management policies) (10) informed consent, privacy regulations, good clinical practice, and special populations in clinical investigations.

TSCI 5071. Patient-Oriented Clinical Research Methods-1. 2 Credit Hours.

This interdisciplinary course is the first in a two-semester sequence designed to train participants in the conduct of patient-oriented clinical research. Students will have the opportunity to learn to and, by the end of the course, be required to: (1) define a research question; (2) effectively conduct a systematic review of the scientific literature; (3) design strategies for recruitment into a study; (4) delineate strategies for minimizing bias in cross-sectional and retrospective studies; and (5) read and interpret research reports of cross-sectional and case-control investigations.

TSCI 5072. Patient-Oriented Clinical Research Biostatistics-1. 2 Credit Hours.

This interdisciplinary course is the first in a two-semester sequence designed to train participants in the analysis and biostatistics of patient-oriented clinical research. Students will have the opportunity to learn to and, by the end of the course, be required to: (1) identify and summarize different categories of data; (2) set up and perform tests of hypotheses; (3) estimate sample sizes for survey and case-control studies; and (4) use statistical software packages to enter, summarize, graph, visualize, and analyze data.

TSCI 5073. Integrated Molecular Biology With Patient-Oriented Clinical Research. 1 Credit Hour.

This interdisciplinary course is designed to train participants on integrating molecular biology methods into patient-oriented clinical research. Students will have the opportunity to learn to: (1) appropriately use molecular terms in clinical investigation; (2) describe the events involved in protein synthesis; (3) describe the principles involved in molecular techniques (e.g., polymerase chain reactions, southern blots); (4) identify the appropriate specimens, collection, and handling requirements for each molecular technique; (5) identify and correct common sources of error in performing molecular techniques; (6) cite examples of clinical applications of molecular techniques in clinical medicine; and (7) apply molecular techniques in the laboratory to specific clinical problems.

TSCI 5074. Data Management, Quality Control And Regulatory Issues. 2 Credit Hours.

This interdisciplinary course is designed to train participants in the necessary data management and quality control procedures required for the conduct of patient-oriented clinical research. It consists of three segments: (1.) introduction to data management principles and standard practices; (2) development of the student's own mentored research; and (3) introduction to bioinformatics.

TSCI 5075. Scientific Communication. 2 Credit Hours.

This interdisciplinary course is designed to train participants to write effectively in all aspects of conducting patient-oriented clinical research. Students will have the opportunity to learn to and, by the end of the course, be required to: (1) recognize and avoid errors in grammar, punctuation, and usage that are common in scientific writing; (2) construct units of writing whose structure, style, and logical continuity allows instant and clear comprehension; (3) construct concise, informative titles; (4) develop clear, comprehensive, abstracts for papers and grant proposals; (5) construct complete, well-rationalized sets of specific aims for grant proposals; and (6) effectively apply the 4-Point Rule (What is the question? How did we approach it? What happened? What does it mean?) to all forms of scientific writing.

TSCI 5077. Translational Science Training (TST) Practicum. 1-3 Credit Hours.

This elective course provides an opportunity for participation in unique clinical and translational research activities that are highly individualized for each student on the basis of prior experience and research interests.

TSCI 5080. Integrating Molecular Biology with Patient-Oriented Clinical Research Practicum. 1 Credit Hour.

This is the required practicum to TSCI 5073. This practicum is designed to provide the opportunity for highly individualized research activities for integrating molecular biology methods into patient-oriented clinical research.

TSCI 5201. Statistical Principles of Machine Learning for Biomedical Data. 3 Credit Hours.

This class offers a hands-on approach to machine learning and data science. The class discusses the application of supervised and unsupervised techniques for machine learning including random forests, support vector machines, boosting, deep learning, K-means clustering and mixture models. The course focuses on real data application with open source implementations in Python and R. Prerequisites: Introductory-level course in probability and statistics; comfort with a programming language (R and/or Python) will be essential for completing the homework assignments; basic linear algebra and calculus are plus.

TSCI 5230. Analytical Programming for Biomedical Data Science. 3 Credit Hours.

This class offers a hands-on approach to data science programming for biomedical research. We will introduce R, Python, SQL, and the software tools that interoperate with them. We will also cover cross-cutting best practices for organizing one's work to facilitate collaboration, reproducibility, and portability. Students who already have data they want to analyze are encouraged to use it in their assignments.

TSCI 6001. Introduction To Translational Science. 1 Credit Hour.

This elective course provides an in-depth overview of the essential components encompassed by translational science. Content is provided through a series of lectures, assigned readings, literature reviews, class presentations, and discussions with faculty.

TSCI 6060. Patient-Oriented Clinical Research Methods-2. 2 Credit Hours.

This interdisciplinary course is the second in a two-semester sequence designed to train participants in the conduct of patient-oriented clinical research. Students will have the opportunity to learn to and, by the end of the course be required to: (1) define criteria for inferring causation from observational studies; (2) design strategies for subject retention in a prospective study; (3) design strategies for monitoring progress in a randomized control trial; (4) delineate strategies for minimizing bias in cohort studies and randomized control trials; (5) compare and contrast the uses, strengths, and weaknesses of different clinical trial designs; (6) read and interpret research reports of cohort studies and randomized control trials; and (7) describe the steps in conducting a meta-analysis. Prerequisites: TSCI 5071.

TSCI 6061. Patient-Oriented Clinical Research Biostatistics-2. 2 Credit Hours.

This interdisciplinary course is the second in a two-semester sequence designed to train participants in the biostatistical analysis and patient-oriented clinical research. Students will have the opportunity to learn to and, by the end of the course, be required to: (1) perform a two-way analysis of variance and explain the results; (2) perform survival analysis; (3) compare and contrast the purpose and characteristics of different forms of interventional trials; and (4) plan the sample size, analysis, and stopping rules of a randomized clinical trial. Prerequisites: TSCI 5072.

TSCI 6065. Health Services Research. 2 Credit Hours.

This course focuses on concepts and methods used in research focusing on health care quality, utilization, access, and safety. The seminar will utilize skills-based learning, small group activities, and outside assignments. By the end of the course, candidates will be required to: (1) Articulate underlying core concepts; (2) Describe basic methods used in health services research; (3) Identify relevant databases and data sources for health services research; (4) Critically appraise and interpret published reports of health services research; (5) Discuss current issues in HSR; (6) Understand how to incorporate health services concepts, methods, or tools into current research. Prerequisites: TSCI 5071 and TSCI 6060.

TSCI 6069. Statistical Issues, Planning, And Analysis Of Contemporary Clinical Trials. 2 Credit Hours.

This elective course will serve as an in-depth survey of the various clinical trial designs, analysis, and regulatory issues. Students will learn to apply statistical principles in designing clinical trials to minimize risk to patients while maximizing generalizable discovery. Specific topics include Phase I-V studies, adaptive designs, longitudinal and survival studies. Students will learn to specify the primary outcome and to estimate the required sample size for common trial designs. Clinical trial design and analysis is often complicated by idiosyncrasies such as missing data, and the methodology for handling these will be covered. Prerequisites: TSCI 5072 and TSCI 6061.

TSCI 6070. Biostatistics Methods For Longitudinal Studies. 2 Credit Hours.

This elective course will discuss a broad range of statistical techniques for deriving statistical inference from longitudinal studies. Main topics include design of longitudinal studies (power analyses and sample size estimation), analyses of repeated measured outcomes (continuous and discrete), analyses of time to event outcomes, techniques to address challenges associated with missing data and confounding, and rigorous casual modeling approaches. Students will learn to identify feasible and efficient statistical design of longitudinal; studies and to conduct rigorous and robust statistical methods to analyze data arising from longitudinal studies. The goal is to develop students' biostatistical competencies in conducting high-quality longitudinal studies in medical research. Prerequisites: TSCI 5072 and TSCI 6061.

TSCI 6100. Practicum In IACUC Procedures. 1 Credit Hour.

This elective course presents an in-depth introduction to the institutional program that provides oversight and regular review of projects that involve the care and use of animals. This includes consideration of the operational procedures of the Institutional Animal Care and Use Committee (IACUC) of the UT Health Science Center at San Antonio. Course objectives are achieved through a combination of readings, monthly attendance at selected IACUC meetings, and discussions with faculty.

TSCI 6101. Topics In Translational Science. 1 Credit Hour.

This research seminar course is designed to introduce graduate students to the field of Translational Science and to members of academic, business, health, and scientific communities who are actively engaged in Translational Science. This course will also provide a forum for students to discuss their own Translational Science research.

TSCI 6102. Practicum In IRB Procedures. 1 Credit Hour.

This elective course presents an in-depth introduction to the institutional program that provides oversight and regular review of research projects that involve human subjects. This includes consideration of the operational procedures of the multiple Institution Review Boards (IRB) of the UT Health Science Center at San Antonio. Course objectives are achieved through a combination of readings, monthly attendance at selected IRB meetings, and discussions with faculty.

TSCI 6105. Topics in Cancer Prevention. 1 Credit Hour.

This course address current topics in cancer prevention science through a series of didactic lectures and discussions with cancer prevention faculty. Topics span the continuum of cancer prevention from basic cancer epidemiology and carcinogenesis, to cancers of special relevance in South Texas and interventions. An exposure to prevention clinical trials and disparity research will also be presented. Consent of instructor is required for registration.

TSCI 6106. Practicum in Cancer Prevention Science. 0.5-1 Credit Hours.

This elective course provides an opportunity for participation in unique clinical and laboratory cancer prevention research activities that are highly individualized for each student on the basis of prior experience and research interests. Consent of the instructor is needed for registration.

TSCI 6201. Data Science Leadership in Healthcare. 1 Credit Hour.

This class offers a hands-on approach to data science operations in biomedical science. The class discusses the management of data science teams, collaboration within healthcare organizations, and the social and ethical responsibility of data scientists. The course focuses on real world applications.

TSCI 6202. Data Visualization and Building Applications. 2 Credit Hours.

This class offers a hands-on approach to data visualization for biomedical data science. The class uses R, Python and Javascript and the software tools that interoperate with them. Some cross-cutting best practices. The course focuses on real world applications. Prerequisites: Introductory-level courses in probability and statistics; comfort with a programming language will be helpful to completing the homework assignments.

TSCI 6203. Practicum in Biomedical Data Science. 1 Credit Hour.

This elective course provides an opportunity for participation in unique biomedical data science and translational research activities that are highly individualized for each student on the basis of prior experience and research interests.