Texas Regional Excellence in Cancer (TREC) @Texas A&M University Cancer Prevention Registry and Repository
Conditions: Cancer, Genetics, Disease, Diet, Lifestyle Factors
Sponsor: Texas A&M University

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
1
1.
Protocol title: 
The TREC@TAMU Cancer Prevention Registry and Repository (referred to hereafter as 
“Protocol”) Version Date 11/01/2024:
2.
Study team
Principal investigator:
Kenneth S. Ramos, MD, PhD
Alkek Chair of Medical Genetics
Center for Genomic and Precision Medicine
Professor of Translational Medical Sciences, Texas A&M College of Medicine
Executive Director, Texas A&M Institute of Biosciences and Technology
Associate Vice President, Texas A&M University Health Science Center
Assistant Vice Chancellor for Health Services, The Texas A&M University System
 2121 W. Holcombe Blvd
Houston, TX. 77030
Tel. 713.677.7440
kramos@tamu.edu 
Co-Investigator(s)
Gabriel Neal, MD
Gabriel Neal MD MA (Bioethics) FAAFP
Clinical Professor& Department Head
Chief Clinical Officer SOM  
Texas A&M University |  Primary Care and Rural Medicine
Rick Silva, PhD, MBA
Executive Director, Clinical | Translational | Industry Collaborations
Texas A&M Health Science Center
Assistant Professor, Department of Translational Medical Sciences
Marcia Ory, PhD
Regents & Distinguished Professor
Department of Environmental and Occupational Health School of Public Health 
Core faculty, Center for Community Health and Aging 
Fen Wang, PhD
Professor of Translational Medical Sciences, Texas A&M College of Medicine
Texas A&M Institute of Biosciences and Technology, Center for Translational Cancer Research
3.
Objectives:
The Cancer Prevention Clinicogenomic Registry (CPCR) Core will support the Texas Regional 
Excellence in Cancer (TREC) @TAMU Cancer Prevention Registry and Repository 
Program. Documentation of the genetic, environmental, and lifestyle, dimensions is crucial to 
validation and implementation of cancer prevention and treatment strategies. This is often a 
critical unmet need at academic health centers which limits the ability of cancer investigators to 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
2
access biospecimens and complete in silico investigations. A discussion with TREC 
investigators and cancer researchers at Texas A&M University documented the many 
challenges they face accessing biospecimens with patient-matched clinical histories from other 
Texas Centers. Thus, a core facility is needed to provide prospective and retrospective 
collection and curation of specimens and clinical data from populations at-risk of cancer and 
those being screened for cancer at Texas A&M clinics. The service will be provided in 
partnership with the Health Hub and Family Medicine Clinics (located in Bryan and Navasota, 
Texas) of Texas A&M Health. (1, 2). The involvement of two clinical sites is facilitated by the 
overlapping coverage provided by TAMU clinicians at both clinical sites. All study participants 
will have an eCW medical record, but data curation from their medical records will be agnostic 
to the site providing care or the TAMU provider involved.
  
The immediate research aims of the TREC@TAMU Registry Program are to:
1) Measure the impact of a cancer screening program on overall patient satisfaction in at-
risk populations.
2) Collect data on the socio-economic, environmental, and occupational determinants of 
cancer risk longitudinally.
3) Establish a biobank enabling case-matched histories with multi-omic bioanalysis for 
cancer biomarker discovery and validation.
4) Model determinants of cancer event rates across time.
5) Enable decision science, cohort discovery, and risk model training for cancer screening 
and chemoprevention programs. 
6) Measure health economic outcomes in cancer at risk populations by analysis of billing 
and diagnosis entries into the subject’s electronic health record in TAMU’s family 
medicine clinic.
4.
Background: 
There are many predicates of clinicogenomic approaches to combine clinical annotation, 
registries, and biobanks to inform and refine clinical practice across communities of practice and 
organizational boundaries.  
The Framingham Studies (FHS) provided a robust platform from which to build risk models that 
leverage biomarkers to prevent cardiovascular disease.(3) These seminal studies have led to 
marked reductions in mortality from cardiovascular disease over the last 50 years.(4)  A major 
challenge to the implementation of chemoprevention strategies is the lack of reliable surrogate 
biomarkers of disease progression and resolution. (5) Using a definitive cancer diagnosis as a 
direct clinical endpoint renders most randomized controlled chemoprevention trials impractical 
due in part to a large study size and time requirements. Further, genetic, social, and 
environmental factors are difficult to study in the primary and community health settings. 
In most academic medical centers and cancer center settings, where most robust 
clinicogenomic registries reside, the genetics of premalignant lesions (i.e., liquid biopsy material 
from blood) and the natural progression of disease are often not available. In addition, the study 
of social and environmental factors intertwined with genetics is limited because biospecimens 
are collected after a cancer diagnosis is made and retrospective analysis of health records is 
limited to data obtained within the oncology ecosystem. As such, typical registries and biobanks 
do not currently serve the needs of Cancer Interception and Precision Prevention programs, 
thus limiting hypothesis generation in that segment of the patient’s journey. 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
3
A more complete understanding of cancer development, and the validation of strategies that 
prevent cancer in at-risk populations would be aided by use of the Framingham approach that 
takes advantage of digital tools available today to contextualize social and economic disparities 
and their interaction with genetic determinants of cancer outcomes. The first example of a 
longitudinal registry was the Bone Sarcoma Registry, providing both population level and case 
level understanding of bone sarcoma. (6)  Dr. Codman’s commentaries on the registry first 
published in 1924, provides a remarkable perspective on the utility of thoughtfully constructed, 
forward looking registry programs.  Nearly a century later, the same opportunity exists for real 
world clinicogenomic data, but policy and industry structure constraints abound. Cancer 
biorepositories and registries do not provide a deep documentation of the clinical care across 
time, especially prior to the patient’s entry into specialized oncology care. Most cancer registries 
curated by Public Health Cancer Control Programs in the US tend to be limited to demographic 
and census data. (7)  Successful cancer prevention and treatment strategies require 
implementation of systems-based solutions that fully integrate the complexities of cancer.(5)  
More recently, in part due to 21st Century Cures Legislation (8), tumor genotyping, treatment, 
and outcomes data have been generated widely in oncology practice even when patients are 
not participating in a clinical trial, rendering rich real-world data (RWD) and potential for real 
world evidence (RWE) to refine and validate the evolution of oncology practice and guide 
investments in clinical development of new technologies and drugs. (9)   In the era of precision 
medicine, there is a paradox in that the more specific the criteria in a population of interest, the 
less likely a meaningful number can be found at a single institution. (10, 11)  Nonprofit 
organizations like the ORIEN network, an alliance with 18 cancers centers across the US, using 
federated biobanking and data models, have emerged to empower cohort construction and 
enrichment across organization boundaries. (12)  The ORIEN program utilizes the Total Cancer 
Care Protocol, pioneered by Dr. Bill Dalton in collaboration among the Moffitt Cancer Center 
and the James Cancer Center and numerous public and private sector partners. (12)  The Total 
Cancer Care Protocol is framed as a 20 year longitudinal partnership between patient and 
research team (NCT03977402).  
The private sector has invested heavily in cancer clinicogenomics since the rise of next 
generation sequencing (NGS). Foundation Medicine built a business model around targeted 
tumor sequencing in their CLIA lab. Flatiron Health built their business around a medical record 
abstracting service for community oncology clinics to bring unstructured case-level data into a 
computable and structured format. Both companies spawned data that reveal valuable 
demographic, phenotypic, and genetic aspects of cancer at population scale. (13) So much so 
that Roche purchased Foundation Medicine and Flatiron Health for $5.3B and $1.9B, 
respectively. However, the point of entry of patients into the Foundation Medicine and Flatiron 
Health is through oncology practice and their clinicogenomic databases provide only a keyhole 
view of the cancer patient journey, arguably the least tractable period for curative and 
preventative interventions. Tempus has become a major participant in the clinicogenomics 
industry recently due to founder Eric Lefkofsky’s experience when his wife was treated for 
breast cancer at a number of prominent cancer centers in the US.(14)  Lefkofsky cites data 
discontinuity, population scale clinicogenomic infrastructure, and institutional data practices as a 
constraint to leveraging big data in the fight against cancer. Tempus has worked upstream in its 
product and services model to engage populations in cancer screening and pharmacogenomics 
(both populations with chronic disease burden and high cancer risk). In all cases, these 
companies forged robust public-private partnerships with the NCI and NCI-designated Cancer 
Centers to enable their substantial contributions to medicine.  Companies such as Truveta, 
Explorys, and Cerner have built business around clinical decision support and health analytics 
at the intersection of population scale EMR data and AI. Oracle-Cerner and Epic have both 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
4
implemented genomic clinical decision support functions that are AI driven and trained by data 
obtained across their universe of hospital system and provider customers. All examples are 
driven by the curation of case-level data from the EMR. A large community of practice studying 
and sharing knowledge of implementation in PGx has emerged. (2, 15, 16)  Implementation 
science in clinicogenomics is largely about collection and curation of clinicogenomic data and 
then sharing that among the community of practice (industry, practitioners, health systems) to 
move towards standardization of bioanalytic methods, nomenclature, interoperable data 
formats, and workflows.   
Biobank blind-spots: Clinical annotation of specimens in a biobank is correlated with the clinical 
relevance and utility of studies using those specimens. For example, the sequencing of 1000 
lung tumors reveals neurotrophic tropomyosin/tyrosine kinase fusions in 300 cases. This 
information is of limited use by itself- as this is an epidemiological fact, but does not inform 
clinical actionability (11). However, if the medical records of those 1000 cases provide the 
researcher with treatments used and clinical outcomes, it becomes evident that certain drugs 
with kinase inhibitor activity delay tumor recurrence substantially. (10, 17)  Now we can learn 
from the biobank which drugs might warrant clinical trials in patients with tumors that have these 
genetic features.  What if molecular and cellular debris that are shed from these tumors can 
reveal the existence of these tumors very early in the disease process where surgery and 
chemotherapy are highly effective?  Most cancer-related biobanks have a blind-spot: the 
timeframe before the patient is diagnosed with cancer.  What if genetic anomalies like gene 
fusions were an early-stage screening biomarker that could be detected in a blood test? 
Consensus on the clinical benefits does not exist for most cancer types. (18)  In fact, the 
population genomics company GRAIL has undertaken the largest prospective validation trials of 
pan cancer screening biomarker panels to date.  Enrolling a population of patients that might 
develop tumors is an expensive undertaking and requires a high threshold of confidence.   The 
merits of these approaches remain controversial, in large part because the positive predictive 
value of these approaches is expected to be low. (19)  It is argued that mutant allelic fractions of 
circulating tumor DNA correlate with tumor size.  (20)  How does one know this in early-stage 
tumors without prospectively enrolling thousands of patients for a long observational period in 
expectation that a few dozen will have a disease trajectory that is informative.  
In cancer screening and prevention, it becomes a challenge to study cancer biology without a 
tumor, but at the same time the tumor represents just a snapshot in time of the disease process 
and patient journey where social determinants of health (SDOH) and lifestyle factors also 
contribute to disease trajectory.  Therein lies an opportunity for a thoughtfully designed 
longitudinal surveillance program in high-risk populations.  General medical practice now has 
risk-based guidelines for screening for lung cancer, liver cancer, cervical cancer, and breast 
cancer, all areas where we have active programs.  An idealized clinicogenomic registry works 
like a time machine and a teleportation machine (Figure 1).  It provides biospecimens, genetic, 
and regulatory-grade clinical annotation longitudinally, across the patient journey, across time, 
and across organizational boundaries in the healthcare ecosystem.   

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
5
Figure 1.  Adapted from Silva et al., 2022.  Annotating the systems factors in the cancer patient journey.  1) COPD patient at high risk for developing lung cancer 
has periodic low-dose CT screening, screening for participation in the TREC@TAMU Cancer Prevention Registry and Repository Program.  2) patient provides a 
digital and dynamic consent for routine banked specimens to be used for research when a need arises 3) Consent is entered on the digital ledger and digital 
permission is effected through smart contract.  4) data and specimen are now accessible on the Provenance Platform for research use within the scope of consent.  
5} the need arises: the patient is diagnosed with tumors and tumor specimens become available through the TREC@TAMU Cancer Prevention Registry and 
Repository research network with a cancer center the patient is referred to. 6) patient provides a modified consent for tumor specimens (if available) to be added to 
the clinicogenomic registry.  7) a specific research project identifies the patient for inclusion and digitally pings for project specific research consent appropriate for 
inclusion in a retrospective blood liquid biopsy cancer screening validation study.  8) Modified consent is entered on the digital ledger and digital permission is 
effected through smart contract for a commercial user, participant may receive a digital reward for participation. 9) Patient wishes to revoke all consent for research 
on their specimen, medical data, and genetic data in their portal on the Provenance Platform. 10) the data associated with that patient is rendered as null in all 
successive queries.

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
6
The registries associated with the FHS and the Bone Sarcoma Registry are case studies that 
show that predictive science requires patient data and patient participation.  Participants, 
biospecimens, or individual clinical cases might be added to a study to build composite cohorts 
from multiple predecessor cohorts with information technology permitting this within a 
compressed timeframe.  In early years of the FHS cohort, it was estimated it would take 20 
years to accession enough coronary heart disease cases for a statistically significant 
subpopulation for common analysis strategies. (21)   In many instances, inclusion of cases 
under the guise of broad, prospective patient consent and deidentified case level data may 
support study objectives and not require prospective enrollment or participation in a study.  
Such is the case with many of the subsequent studies of the FHS cohorts, thus enabling 
investigators to assemble a subpopulation cohort to test novel hypotheses or explore novel 
cardiovascular disease biomarkers. Biospecimens with robust clinical phenotyping and 
appropriate consent and documentation of provenance theoretically enable development of an 
FHS-like cohort using RWD in a much shorter period.  In the present, computational science 
has an increasingly important role in improving care through information. (2)  Artificial 
intelligence models increasingly underlie clinical decision-support (22) and have great potential 
to simplify the increasing complexity of medical practice. Artificial intelligence technology has 
also been qualified to build external control arms in silico. (23-25) The training of models that 
provide personalized and precision healthcare perspectives will require datasets that transcend 
organization boundaries.  In many respects, the Framingham risk score was an early application 
of a predictive qualitative model trained by a retrospective data set. The emergence of RWD 
sources and machine learning technologies have great potential to accelerate and create more 
dynamic examples of the Framingham risk score.  
Many health systems and research centric institutions have lagged industry in evolving and 
adapting practices to enable the assembly of population scale data sets, especially across 
organizational boundaries in federated collaboration models.  The clinicogenomic registry 
presents data governance challenges that impede the flow of case level genomic data and case 
level clinical annotation from institutions to users such as policy agencies, researchers, drug 
developers, insurers, and the healthcare industry.  Under current US policy frameworks, privacy 
and compliance are the primary constraints to constructing population scale, case-level data 
sets. There are two common workarounds: 1) de-identify the data to share it (this has been 
done at scale (10) albeit primarily in populations of European decent), 2) obtain broad and 
open-ended research authorization from research participants and research subjects.  However, 
de-identified comprehensive case level data, particularly including specimens and DNA 
sequences, render the statutory concept of privacy difficult to impossible to preserve with high 
confidence when sharing data. These workarounds fall short in engaging populations where 
health disparities are greatest.  
In the long term, the TREC@TAMU Registry will be a living laboratory built for RWD and RWE 
in cancer prevention leg of the patient journey, using digital technologies to enable a more 
dynamic model of patient centric data governance. Trust, patient agency, and data governance 
are currently major impediments to collection and curation of medical records and patient 
reported outcomes for many of the populations experiencing socio-economic, environmental, 
and occupational determinants of health disparities in cancer.  We have implemented a 
Provenance Platform to digitize governance and address impediments related to longitudinal 
registry development. The PROVENANCE data platform became operational in July 2024, and 
includes dictionaries for medical record data, genomic data, coding for obscuring HIPAA 
identifiers/de-identification of data sets, and informed consent metadata.  

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
7
The Provenance Platform will enable a staged transition toward dynamic, electronic, patient-
centric clinic data governance. The TREC@TAMU Registry is modeled after the clinicogenomic 
approaches used elsewhere but adding a longitudinal view of patient outcomes and the 
underlying economics of healthcare utilization. TREC@TAMU Registry is intended to be a 
resource of myriad future hypothesis driven studies utilizing subsets of the data in the 
TREC@TAMU Registry.
 
5.
Inclusion and Exclusion Criteria:
Inclusion 
We plan to recruit as many participants as possible from the Texas A&M affiliated Family 
Medicine Clinics. 
Participants will be:  
•
18 years of age and older, and,
•
People participating in the Cancer Prevention and Research Institute of Texas (CPRIT) A 
coordinated cancer screening research program in Bryan and Navasota Family Medicine 
Clinics (Figure 2), and, 
•
People with COPD, liver disease, cervical intraepithelial neoplasia (CIN) lesions, having had 
a colonoscopy or a low dose computed tomography (LDCT) lung scan or cervical exam 
in the last 12 months or scheduled for one, and,
•
Able to give and comprehend the consent process, and,
•
Able to consent to donate blood and urine samples, genetic material through buccal swabs 
for future research, and,
•
Able to understand that their specimens, health record, and changes in health status will be 
followed for a five-year period and shared in deidentified form with the research 
community, and,
•
All sexes and gender identities. 
Exclusion
•
Declines to participate or interact with staff/share their medical status.
•
A diagnosis of Alzheimer’s disease or related dementias in a medical record indicates a 
progressive, debilitating condition that impairs memory, thought processes, and 
functioning Individuals who are unable or unwilling to provide consent will be excluded.
As noted, the TREC@TAMU Registry will recruit as many participants as possible. The estimated 
enrollment in five years is expected to be 2500, but we will not limit recruitment if we 
exceed that number.
6.
Geographic Reach of Research Activities:

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
8
Patients will be referred to the TREC@TAMU Registry from the Texas A&M Family Medicine 
Clinics located in Bryan and Navasota and the CPRIT Cancer Screening programs (Figure 2).  
The Bryan and Navasota programs have common providers and share the same medical 
record. Both sites participate in CPRIT Cancer Screening programs.  Recruitment and 
consenting of patients will be conducted onsite or via a telemedicine encounter at a Texas A&M 
Health Family Care Clinic (Bryan and Navasota) or the Texas A&M Interprofessional 
Pharmacogenomics Clinic in Bryan (2). Clinical research staff that are a part of the practice plan 
workforce will scan appointments for TAMU Health patients meeting risk criteria.  Additionally, 
patients coming in for cancer screening services under the CPRIT programs in Figure 2 will be 
approached to participate. Data will be stored on the cloud (Amazon Web Services or BurstIQ) 
as described in section 9. Long term storage of specimens will be at the Texas A&M Institute of 
Bioscience and Technology (IBT) as described in section 9.  Following immediate collection of 
samples, specimens will be temporarily stored at the Family Medicine Clinic in a dedicated cold 
storage refrigerator under the supervision of trained staff at 4oC until transport for temporary 
storage at the Reynolds building on the TAMU College Station campus by staff with appropriate 
training. Transport from the clinic to Reynolds will comply with the guidelines established in the 
TAMU Biosafety Manual for Risk Group 2. Samples will be processed and aliquoted into smaller 
quantities in a laboratory with biocontainment level 2 and then placed in liquid nitrogen tanks 
before shipping to the IBT in Houston for long-term storage in liquid nitrogen, as outlined in the 
protocol addendum. Shipment to Houston will be performed weekly by a FedEx on dry ice per 
their guidelines: Quality of life (QoL) surveys will be administered electronically such that 
participants can submit them online through an encrypted link to the patient portal for the 
TREC@TAMU Registry research data warehouse described in section 9.  
All participating sites (Navasota and Bryan locations of TAMU Family Health Clinics) will have 
the most current version of the Protocol, informed consent documentation, and HIPAA 
authorization. All planned modifications to the Protocol will be communicated to the various 
primary care sites and implemented upon IRB approval, as required. All engaged participating 
clinics will safeguard data as required by their local information security policies and in 
compliance with HIPPA, CPRIT, and NIH Genomic Data Sharing (GDS) Policy.  All non-
Figure 2  CPRIT Cancer Screening Programs

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
9
compliance with the study protocol or applicable requirements will be reported in accordance 
with TAMU HSPO policy, IRB approval, and as specified in the Protocol.
7.
Study Timelines:
The duration of individual participation in the TREC@TAMU Cancer Prevention Registry and 
Repository is 5 years after the enrollment encounter (Figure 1) for follow-up data collection from 
the electronic medical record (EMR), biannual quality of life surveys, and outcome analysis.   
Patients will also consent to share the specified data from their EMR for the 1 year prior to the 
enrollment date visit. Sometime prior to a patient reaching the 5-year milestone, they will be 
contacted with a digital invitation to participate in the Provenance Platform using BurstIQ which 
involves the use of blockchain tools and tokenization (turning a meaningful piece of data into a 
random set of characters without value if breached) to bring enhanced consent, trust, control, 
and transparency to the longitudinal linkage of health data and genomic data. The Provenance 
platform enables TAMU users to utilize the patient-centric (and IRB approved) data governance 
tools to document patient consent at the case level for use 1) collection of their EMR data, 2) 
use of their remaining specimen in the TREC@TAMU Cancer Prevention Repository, 3) sharing 
of their genetic data for research use. Consent for specimen use and further EMR data or 
claims data collection shall end at 5 years in the absence of an affirmative consent extension on 
the Provenance Platform.  Use and analysis of data collected in this 5-year window of data 
collection will be available for analysis until 2044. Thus, data analysis within the parameters of 
the patient consent is expected to be ongoing until 2044. However patient case-level data from 
the electronic medical record will not be accessed after five years unless the patient opts into an 
extended and expanded consent Provenance Platform. The period of consent for analysis (until 
2044) will allow the research team (listed investigators and people under their supervision) to 
engage in probabilistic or deterministic matching of claims data from commercial claims 
databases (like the All-Payer Claims Database or TX Medicaid databases) to assess their 
healthcare utilization and health outcomes that can be gleaned from health data. Sharing of 
Figure 3.  Timeline of participation, data collection, data accession, and extension of the TREC@TAMU Cancer 
Prevention Repository.  

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
10
clinical data and specimens are clearly voluntary, but if the patient declines to share both, they 
will be excluded from the TREC REGISTRY. They, however, can still participate in other care 
protocols including the CPRIT cancer screening program they may be interacting with.
8.
Procedures Involved & Variables and Outcome Measures:
Sample collection will be conducted by a licensed nurse or trained phlebotomist with standard 
precautions, surface sterilization, and sterile venipuncture. Approximately 35 mL of blood will be 
collected at enrollment. Subsequent blood collection will entail 10 L microsamples using the 
Mitra Device. Samples will be stored at 4oC for a maximum of 6 hours and then processed in a 
biocontainment level 2 environment in the Reynolds Building in College Station, aliquoted, and 
frozen in a dedicated liquid nitrogen tank for transport to the IBT Biobank facility in Houston.
Collected in every patient at enrollment:
EQ-5D-5l with pain visualization (26) will be administered to every patient in the registry at every 
visit to the clinic and at least every 6 months for 5 years after enrollment either in-clinic (on the 
initial visit and if and when they visit the clinic) or electronically (every 6 months, see Figure 3) 
through an encrypted link to the patient research portal.
•
Social determinants of health (SDOH) (EMR).
•
Hospital admissions (abstracted from EMR, from questionnaire).
•
Comorbidities (abstracted from EMR).
•
Healthcare utilization (case level claims data abstracted from eCW or the All-Payer 
Claims Database).
•
Four 8.5 mL (PAX RNA, PBMC, Plasma) and one 2.5 mL (PAX DNA) will be collected 
from a single needle stick, by phlebotomy-trained clinical staff.
•
A urine sample. 
•
2 buccal (cheek) swabs or saliva samples will be collected.
Self-collected in every patient biannually upon request:
•
digitally administered EQ-5D-5L survey to gather data on health status and any 
significant changes.
•
A home-based 10 L patient sample collection of dried bloodspots (Neoteryx Mitra micro 
sampling) for additional analysis of blood chemistry. Subjects will be instructed to mail 
this sample to Texas A&M (at our expense) on the day of blood drop collection.  
At the discretion of research team, per criteria:
•
Georges’ quality of life scale for patients with diagnosed COPD (27)
•
Quality of Life (DQOL) questionnaire for patients with diagnosed diabetes (28)
•
DSM-IV for patients with diagnosed depression (29)
We will not use all these instruments in any given patient, rather discretionary surveys will be 
collected as appropriate at scheduled check-ins. The TREC REGISTRY may collect relevant 
medical history that is not included the medical record at Texas A&M, which they can submit via 
a secure and encrypted portal online or when then visit a Texas A&M clinic or research site.

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
11
There is no specific hypothesis being tested under this protocol.  Data will be accessed for 
future studies approved by the TREC@TAMU Cancer Center of Excellence Leadership, subject 
to acceptable the data and specimen governance process in section 9

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
12
Table 1.  Biospecimen collection for Registry. 
LDT =Laboratory Developed Test
RUO=Research Use Only
Collection Media
Sample Type
Clinical Use 
Regulatory 
Context
Use Case
BioAnalytic
Vendor
Bioanalyte Bioanalysis Method Methodology Protocol Reference
Storage
Aliquot
Sterile Sample Cups
Urine
LDT
Biobank TBD
TBD
TBD
liquid N2
@500 L
Cotton Tipped Applicator
Buccal Swab
LDT
Biobank TBD
TBD
ProbeArray
liquid N2
Whole
Neoteryx Mitra
 dried bloodspot
LDT/RUO Biobank TBD
TBD
TBD
Shen, X., Kellogg, R., Panyard, D.J. et al.  Multi-omics 
microsampling for the profiling of lifestyle-associated changes 
in health. Nat. Biomed. Eng  (2023).
liquid N2
Whole
TBD
TBD
Posevitz-Fejfár, A., et al. (2014) “Effects of blood transportation on 
human peripheral mononuclear cell yield, phenotype and 
function: Implications for immune cell biobanking,” PLoS ONE 
9(12): e115920. doi:10.1371/journal.pone.0115920 
liquid N2
@ 100 L 
remainder
Exosomes
NGS; RNASeq; 
Proteomics
Du K, Sun X, Tang X, et al. Effects of storage temperature and time 
on quality of plasma exosomes extracted by ExoQuick. Chinese 
Journal of Cellular and Molecular Immunology. 2020 
Apr;36(4):330-336. PMID: 32519671.
liquid N2
@1000 L x 1;
PAX RNA
Blood RNA
RUO
Biobank TBD
TBD
,
,
,
,
,
Campbell R, Marmar CR, Hammamieh R, Jett M. Gene expression 
profiling of whole blood: A comparative assessment of RNA-
stabilizing collection methods. PLoS One. 2019 Oct 
liquid N2
@200 L x all
PAX DNA
ccfDNA
RUO
Biobank TBD
TBD
Voss T, Ullius A, Schönborn M, Oelmüller U (2021) Sensitivity 
assessment of workflows detecting rare circulating cell-free DNA 
targets: A study design proposal. PLOS ONE 16(7): e0253401.
liquid N2
Vacutainer CPT Red/Green
PBMC 
RUO
Biobank TBD
TBD
RNA seq
Science of Blood for Peripheral Blood Mononuclear Cell 
(PBMC) Functional Applications. Curr Pathobiol Rep 7, 17–27 
(2019).
liquid N2
@200 L x all
BD P800 Blood Collection 
System
Stable Plasma 
Proteins
RUO
Biobank TBD
TBD
Proteomics
,
p g
,
p y
,
,
p
,
Wynendaele E, De Spiegeleer B. Influence of Blood Collection 
Methods and Long-Term Plasma Storage on Quorum-Sensing 
Peptide Stability. ACS Omega. 2020 Jun 22;5(26):16120-16127. 
liquid N2
@200 L x all
Vacutainer Yellow Top
Whole Blood 
RUO
Biobank TBD
TBD
TBD
liquid N2
@500 L x all
Cotton Tipped Applicator
Buccal Swab
RUO
Biobank TBD
WGS/WES NGS 
liquid N2
Thermo Scientific™ SpeciMAX™ 
Saliva Collection Kit
Saliva
RUO
Biobank TBD
TBD
TBD
liquid N2
TBD
Vacutainer Purple top
Plasma, PBMC
RUO
Biobank

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
13
9.
Biobanking and Clinicogenomic Protocol- Specimen and Data 
Management:
•
See Addendum
10.
Data Analysis:
Because this is a registry and biobank program, data analysis plans will be formulated in the 
future as testable hypotheses arise and are addressable using the data and clinical cases 
enrolled in TREC@TAMU Cancer Prevention Clinicogenomic Registry and Repository at the 
time. 
Analyzed data (aggregated and deidentified data) may be published in accordance with 
informed consent when an analysis meets the standards for peer-reviewed publication. Raw 
case level data will not be openly published with the exception of genomic data to be shared in 
public repositories in accordance with NIH guidelines for sharing such data using practices we 
have previously published.(10, 11) To be clear, sharing of genomic data in NIH sponsored 
repositories will involve limited and deidentified clinical annotation. The TREC@TAMU Cancer 
Prevention Clinicogenomic Registry and Repository is expected to seek future funding from the 
NIH and CPRIT. Express patient consent will be sought separately for case reports that might 
be published.
    
Data from Wole Genome Sequencing will be uploaded to TAMUs AWS cloud enclave. WGS 
sequencing will be conducted on Illumina HiSeq at 30X coverage by the company that has done 
single cell sequencing for the TREC single cell core, Admera.  WGS data will be for research 
use only and will not at any point be reported providers. These data will only be used as 
specified in the section on research data government in the biobanking addendum. Incidental 
findings will not be shared with participants. WGS data will only be accessible to the 
investigators listed herein or third-party research collaborators in accordance with IRB oversight 
of future proposed studies.  Consent forms will be signed with a wet ink signature on a printed 
consent form or as a secure digital signature on the PDF file using the Adobe Sign function and 
attached to the PROVENANCE and WGS metadata using a script developed in the BurstIQ 
platform.
A description of this clinical trial will be available on http://www.ClinicalTrials.gov, as required by 
law. This web site will not include information that can identify you. At most, the web site will 
include a summary of the results. You can search this web site at any time.
11.
Participant Safety:
Participation in the TREC@TAMU Cancer Prevention Clinicogenomic Registry and Repository 
poses minimal risk. The risks to subjects are of a low likelihood of harm and low magnitude of 
harm, limited to privacy risks.  

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
14
It is expected that most study participants will generally remain engaged with the primary care 
clinic from where they were referred. Clinical documentation will be monitored for consistency 
with the protocol by TREC research staff during enrollment, and as needed to ensure complete 
and quality documentation of registry associated outcomes data. 
Data Safety Monitoring Plan.  
Clinical study staff and investigators, under the supervision of the PI will review all data quarterly 
for data completeness and accuracy as well as protocol compliance.  Drs. Ramos, Neal, and 
Silva will review the safety and progress of the study quarterly. Study reports, including patient 
recruitment, retention/attrition, will be produced following each of the quarterly reviews to ensure 
faithful adherence to the protocol.  
12.
Withdrawal of Participants:
It is not expected that the study team would need to remove a participant from the study. 
Attrition will only occur when a participant revokes their consent. Upon revocation of consent, 
the subjects’ alphanumeric identifier will be reassociated with specimens, samples will be 
retrieved, and destruction will be documented and disposed of appropriately. Their clinical 
annotation data will be rendered unavailable on the Provenance Platform using existing 
functions of the BurstIQ data governance system.
15.
 Risks to Participants:
Risks and inconveniences involved: 
•
Time spent in clinic or responding to study related information requests.
•
Phlebotomy, along with its associated risks ranging from ecchymoses, hematoma, nerve 
injury, infection. PL
Key
Probability P  |  Magnitude M  |  Duration D  |  Short S   |  Low L  |  Moderate M  Extensive E
17.
Potential Benefits to Participants:
Benefits for participating patients
The registry is designed in alignment with the principles of Standards in the Conduct of Registry 
Studies for Patient-Centered Outcomes Research – Report to PCORI [11].  
We seek to understand how and when cancer risk becomes clinically actionable. This 
knowledge is unlikely to immediately evolve into clinical, care related benefits for participants in 
the present, but can benefit like patients in the future. The TREC@TAMU Cancer Prevention 
Clinicogenomic Registry and Repository has a high likelihood of helping a participating patient in 
the future by enabling matching of them with appropriate clinical trials if cases when cancer is 
developed.
Benefits of the study for the healthcare and scientific communities

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
15
The potential benefit and reason for requesting the TREC@TAMU Cancer Prevention 
Clinicogenomic Registry and Repository is to develop a cancer screening registry model that 
can account for the important environmental, occupational, genetic, and socio-economic 
determinants of cancer disparities. We might understand the impact of comorbidities such as 
obesity, cardiovascular disease, depression, or cognitive problems in cancer. These 
phenomena are major drivers of high healthcare utilization, with known and unknown genetic 
and social determinants. This registry strategy enables the collection of data underlying these 
factors and aids in understanding the scope and magnitude of these factors in cancer risk and 
outcomes following a cancer diagnosis. It can help inform more holistic clinical decision-making 
in cancer screening and cancer prevention and improve policies that can improve the quality of 
life (greater agency in managing cancer risk) and clinical outcomes for patients (improved 
preventive practices).  
As the enrolled population and our database grow, we might identify novel blood biomarkers for 
screening that empower chemoprevention development and improve risk management through 
holistic cancer prevention programs. Our informed consent form, collaborative structure, and 
contracts will thoughtfully account for the best way to allow for compliant and deidentified 
sharing of the data collected under this protocol with the clinical and scientific communities of 
practice addressing an information gap in cancer prevention upstream of peer-reviewed 
publication.
18.
Vulnerable Populations:
People with cancer may experience some degree of cognitive impairment, either associated 
with cancer, cancer treatment (36), or a somewhat independent covariate (37). The impacts of 
cognitive impairment are poorly understood and warrant study (36-38). Recruitment (40) and 
exclusion (41) of people with cognitive impairment are both ethically fraught approaches in 
clinical research. Patients with cognitive decline will be excluded per revised the exclusion 
criteria.  
No minors, no prisoners will be recruited into this study. 
19.
Sharing of Results with Participants:
While the TREC@TAMU Cancer Prevention Clinicogenomic Registry and Repository is likely to 
attract industry partners willing to perform multi-omic bioanalysis at low or no cost, it is quite 
complicated to share that information with patients or physicians unequipped to interpret it.  
Most bioanalytic work TREC@TAMU Cancer Prevention Clinicogenomic Registry and 
Repository will not be conducted in a CLIA compliant setting. Consequently, there are no 
immediate plans to report findings back to patients as this would be highly impractical to achieve 
in a compliant, responsible, and ethical manner without significant investment in genetic and 
medical counseling, access to CLIA compliant testing, and highly specialized medical expertise. 
This is the expectation that will be set in the informed consent form.
20.
Setting:
Texas A&M University.  Research participants will be recruited from the patients referred to the 
primary care clinics of Texas A&M Health (Bryan and Navasota). Participants will be recruited 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
16
that have elevated risk of cancer, with priority on patients receiving cancer screening under 
CPRIT cancer prevention programs at Texas A&M. The patient consent will be performed by 
clinical or research staff at the clinic site designated by Texas A&M (or via telemedicine when 
that is the format of care delivery for that patient) but some bioanalytic, computational sample, 
and data analysis will occur offsite.  Please see section 6 above regarding geographic 
distribution of research activities. 
No community advisory review board other than what is customary for Texas A&M is considered 
currently. If the decision is made that a community advisory board is indicated, members might 
include those who represent the referring physicians, a community cancer patient advocate, and 
CPRIT designees.
21.
Personnel and Resources Available:
Dr. Ramos MD, PhD, PharmB- Principal Investigator
Dr. Ramos is a licensed physician-scientist with training and certifications in clinical 
pharmacology, toxicology, forensic medicine, pulmonary and integrative medicine. He is an 
inductee in the National Academy of Medicine and a Lifetime Associate of the National 
Academy of Sciences. He is a tenured professor at Texas A&M Health Science Center. Dr. 
Ramos also is Associate Vice President at the Texas A&M University Health Science Center 
and Assistant Vice Chancellor for Health Services for the Texas A&M University System. 
Previously, Dr. Ramos was founding director of the University of Arizona Health Sciences 
Center for Applied Genetics and Genomic Medicine and chief medical and scientific officer of 
the Arizona Precision Medicine Initiative and has been instrumental in developing precision 
health strategies, diagnostic technology, and clinical data strategies to improve health care 
delivery. Dr. Ramos will be the Principal Investigator and be the ultimate decision-maker and 
have supervisory authority for the conduct of the protocol and management of the Registry. Dr, 
Ramos will also participate in data analysis and future research strategies and collaborations 
enabled by the Registry.
Dr. Gabriel Neal MD, Clinical Co-Investigator
Dr. Gabriel Neal is board certified in Family Medicine and received his MD from the University of 
Oklahoma in 2001. Dr. Neal first joined the Department of Family Medicine in 2008 and is 
faculty in the Texas A&M Family Medicine Residency. Over the past decade, he has taught in 
numerous pre-clinical and clinical courses for the College of Medicine. He is the Family 
Medicine Clerkship Director for the A&M Integrated Medicine Program at the Bryan-College 
Station College of Medicine Campus. His teaching illuminates applied evidence-based medical 
care and ethics. He was awarded Clinical Faculty Preceptor of the Year in 2011 and 
Outstanding Faculty in Family Medicine in 2019.  Dr Neal holds several roles: Department 
Head, Primary Care and Rural Medicine; Clinical Professor; Chief Clinical Officer, Texas A&M 
School of Medicine; Family Medicine Clerkship Director, Texas A&M Integrated Medicine 
Program; Faculty, Texas A&M Family Medicine Residency and is involved in several clinical 
research projects. Dr. Neal will assist in the recruitment and consenting of patients who might 
be eligible for, and benefit from participation. Dr. Neal will also participate in data analysis and 
future research strategies and collaborations enabled by the Registry.
Rick Silva PhD, MBA Co-Investigator
Dr. Rick Silva is Executive Director Executive Director, Clinical | Translational | Industry 
Collaborations at Texas A&M Health Science Center. In addition, he holds an academic 
appointment as Assistant Professor of Translational Medical Sciences in the Texas A&M 
Institute of Biosciences and Technology. He has scientific training in physiology and 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
17
neuroendocrinology, with significant experience in implementing and managing clinical and 
translational research programs, including dimensions of regulatory science, diagnostic 
technology development, cohort strategy, and clinical data strategies in clinical translational 
collaborations among academic medical centers and industry. Dr. Silva will serve as coordinator 
of the Registry and implement its data strategy with the Family Medicine Clinics. Dr. Silva will 
also participate in data analysis and future research strategies and collaborations enabled by 
the Registry.
Fen Wang PhD, Co-Investigator
Dr. Wang earned his Bachelor of Science in Microbiology and Master of Science in Cell Biology 
degrees at Xiamen University, and his Ph.D. in Biochemistry and Cell Biology at Clarkson 
University at Potsdam, NY. He undertook postdoctoral studies for Cancer Research and 
Nutrition at Texas A&M University. Dr. Wang joined IBT as Assistant Professor where he was 
promoted to Associate Professor with tenure and Professor with tenure at the Texas A&M 
University System Health Science Center. Dr. Wang will serve as coordinator of the Biobank. 
Dr. Wang will also participate in data analysis and future research strategies and collaborations 
enabled by the Registry.
Marcia Ory PhD Co-Investigator
Is a Regents and Distinguished professor for the Department Environmental and Occupational 
Health at the Texas A&M School of Public Health. With a long-standing interest in aging and 
public health, Dr. Ory is the founding director of the university-wide Center for Population Health 
and Aging, chair of the SPH Health and Wellness Committee and academic partner for the 
Community Research Center for Senior Health with Baylor Scott and White Health. She chairs 
the HSC Opioid Task Force and is working with an interdisciplinary cross-campus group to 
foster innovative research, education and service projects emanating from the health Sciences 
Center. She co-leads Healthy Texas, a new system-wide effort to examine strategies for 
promoting health and wellness for all Texans. Dr. Ory was honored for her sustained 
commitment to her research, receiving The Association of Former Students’ Distinguished 
Achievement Award in Research from Texas A&M University for 2021.  Prior to coming to 
Texas, A&M University, Dr. Ory spent 20 years in federal service as chief of Social Science 
Research on Aging in the Behavioral and Social Research Program at the National Institutes of 
Health's National Institute on Aging. Dr. Ory received her Bachelor of Arts in sociology and 
psychology from the University of Texas, Master of Arts in sociology and human development 
from Indiana University, doctorate in family studies and human development from Purdue 
University and Master of Public Health in chronic disease epidemiology and behavioral sciences 
from John Hopkins University Bloomberg School of Public Health.
22.
Prior Approvals
IRB approval of this registry protocol, and amendments hereto, will be obtained from Texas 
A&M IRB as the IRB of record, and any IRB of future collaborative health systems and research 
institutions.  
23. 
Confidentiality
­
Where and how data or specimens will be stored locally? 
At the point of enrollment, alpha-numeric specimen identifiers will be generated onsite 
using a HIPAA compliant true-randomizer like the Global Unique Identifier (GUID 
Tool).  Keys will be assigned to a designated data steward or honest broker, barcodes 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
18
encoding alpha-numeric specimen identifiers will be linked to all records using 
BarTender software (Seagull Scientific), and specimens will be labeled with barcodes 
for long term storage.
­
How long the data or specimens will be stored locally? 
Five years, unless the patient consents to an extended participation period (Figure 3)
­
Who will have access to the data or specimens locally? 
Investigators and their designated staff will have access to the specimens locally. 
Researchers with approved protocols will have permissioned and password protected 
access to the TREC@TAMU Cancer Prevention Registry and Repository Research 
Data Warehouse.
­
Who is responsible for receipt or transmission of the data or specimens locally? 
A clinical research staff member at the TAMU clinic will hand deliver or ship 
specimens to IBT via qualified courier. Researchers with approved protocols will have 
permissioned and password protected access to the TREC@TAMU Cancer 
Prevention Registry and Repository Research Data Warehouse through the 
Provenance Platform.
­
How data and specimens will be transported locally? 
Local transport of specimens from the Family Medicine Clinic in Bryan to the IBT in 
Houston by a qualified courier. Clinical data will be stored in the eCW EMR on the 
cloud. This is 2015 Edition compliant and has been certified by an ONC-ACB in 
accordance with the applicable certification criteria adopted by the Secretary of Health 
and Human Services. Deidentified research data will be stored on the cloud (AWS). 
24. 
Provisions to Protect the Privacy Interests of Participants:
We will obtain written informed consent for participation, interaction, and collection of medical 
data from a patient. No participant will be required to interact with anyone or share personal 
information with anybody other than their care team providers at their clinic and the 
TREC@TAMU research staff. See exclusion criteria about unwillingness to participate or 
consent. Participants will be made to feel at ease through open communication with 
TREC@TAMU staff and explanation of data use and data sharing and limitations thereof in the 
informed consent form. Participants should feel no more or less uncomfortable than when 
presenting to any general medicine clinic. There is nothing invasive beyond giving urine, blood, 
and a buccal swab. Discomfort about sharing DNA is addressed in the informed consent form 
and consultation, the consent for future use of specimens or forward-looking collection of data 
from the participant’s ongoing medical record will be revocable in the Provenance Platform 
patient portal. Participants will be advised that their information will always be handled 
confidentially. Authorized members of the research and care team will have a password so that 
they can access the secured electronic health record and TREC@TAMU Registry Research 
Data Warehouse. 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
19
25.
Compensation for Research-Related Injury
N/A
The registry is only intended to collect data and specimens. While observational 
outcome data will be collected, this protocol is not intended to evaluate or propose any 
experimental intervention.
26.
Economic Burden to Participants
Patients are responsible for transportation to the clinic as they normally do for routine care. No 
elements of the patient encounter with the TREC@TAMU protocol will trigger reimbursement 
requests from insurance. The costs of the research use for blood testing will be covered by 
TREC research funds or provided cost-free by research partners. Cancer screening is covered 
by other CPRIT grant funds or insurance, not this study.  
27.
Recruitment Methods
(Describe when, where, and how potential participants will be recruited.) 
We will work with the Texas A&M Health Family Medicine clinics (Bryan and Navasota) to refer 
participants who may meet criteria and benefit from cancer screening. The TREC@TAMU will 
be open to any Texas A&M family medicine, primary care clinics or specialty clinics that choose 
to refer their patients to the TREC@TAMU Registry program. Research recruiting will be 
performed by Texas A&M Family Medicine staff and qualified TREC@TAMU clinical or research 
staff.  
Three recruitment collaterals are attached:
1) A telephone script.
2) A recruitment email.
3) A recruitment brochure.
Subject compensation not currently planned.
28.
Consent Process
We will obtain consent in a basic informed consent form [Appendix 1]. 
An individual team member authorized by the principal investigator and IRB can obtain consent 
from potential participants. However, regardless of who is obtaining consent, the Principal 
Investigator is responsible for ensuring the correct procedures are carried out.
­
How will consent for Spanish-speaking participants take place? 
To ensure that Spanish-speaking participants are effectively included in the study, it is 
essential to implement a clear and respectful process for consent and communication 
throughout the research.
**Staff Requirements**  

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
20
1. Bilingual Staffing: Where available we will utilize study staff members who are fluent in 
Spanish to communicate directly with participants. This will promote a comfortable 
environment and ensure accurate information exchange.
2. Qualified Interpreters: If bilingual staff members are unavailable, we will engage 
qualified interpreters who are experienced in medical contexts and culturally competent 
from an existing service used to interpret for care to Spanish speaking patients. These 
interpreters are currently available through the Family Medicine Clinic and will assist in 
all interactions with Spanish-speaking participants.
**Consent Process**  
1. Informed Consent Documents: All consent documents have been be translated into 
Spanish, ensuring they are easily understandable and culturally relevant. These 
documents will be available to participants prior to consent discussions.
During the consent process, staff or interpreters will present the information in Spanish, 
allowing participants to ask questions and seek clarification as needed. Before obtaining 
consent, we will ensure that participants fully understand the study's purpose, 
procedures, risks, and benefits.
2. Documentation: We will document the consent process carefully, noting the use of 
interpreters when applicable, to maintain compliance with ethical guidelines and ensure 
transparency.
­
Where will the consent process take place? 
At the designated Family Care Clinic or IPGx (Interprofessional Pharmacogenomics 
Clinic), or virtually in all instances when telemedicine services are being provided to 
subjects in and out of Brazos Valley. In the case of virtual consent, a verbal recorded 
consent after reading the ICF will be obtained and backed up by an online digitally 
signed version of the informed consent form. The digital consent (eConsent) process will 
be set up using Adobe Acrobat Sign and validated to comply with FDA’s 21 CFR Part 11 
regulatory requirements. The study team will manage digital consent metadata for 
electronic medical record data and genomic data.
­
Any waiting period available between informing the prospective participant and obtaining 
the consent? 
It would be at the discretion of the participant to consent when they decide they are 
comfortable enrolling in the study.
­
Any process to ensure ongoing consent? 
No. Participants will be advised they are consenting for 5 years of prospective and 1 
year of retrospective data collection (Figure 3) and may end their participation at any 
time either via email or phone. Revocation specifically would apply to consent for future 
use of specimens or forward-looking collection of data from the patient’s ongoing 

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
21
medical record. Revocation will be digitally enforced in the Provenance Platform patient 
portal.  Any data in the Registry up to the date of revocation cannot currently be 
forgotten or removed. Specimens would be removed from the registry and destroyed 
upon revocation of ongoing consent. After 5 years, participants would need to 
affirmatively extend their consent to continue to participate in the registry.
­
The role of the individuals listed in the application as being involved in the consent 
process. 
The role of the PI or Clinical Co-Investigator would include answering an enrollee’s 
questions, discussing risk-benefit options and alternatives, reporting back to the 
investigator team, and answering questions in support of regulatory compliance. 
­
The time that will be devoted to the consent discussion. 
As much as needed. It is estimated that a half-hour will be sufficient.
­
Steps that will be taken to minimize the possibility of coercion or undue influence. 
We will make it clear at the outset and in printed materials that TREC@TAMU Registry 
is completely voluntary and unrelated to the receipt of health care. The consent form will 
emphasize this point. Non-participation will not in any way jeopardize the patient’s 
relationship with their doctor, provider, or any other individual. No financial inducements 
will be used.
­
Steps that will be taken to ensure the participants’ understanding. 
Participants will acknowledge in writing they understand what their participation in the 
study entails. 
 
Waiver or Alteration of Consent Process:
NA.
Participants who are not yet adults (infants, children, teenagers)
Minors excluded. This study will focus on adults.
Cognitively Impaired Adults
Please refer to inclusion/exclusion criteria.
Adults Unable to Consent
Please refer to inclusion/exclusion criteria.
30.
Process to Document Consent in Writing:
See Appendix 1- Informed Consent Form

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
22
31.
Drugs or Devices:
Not relevant
32.
Waiver of IND or IDE
Not relevant

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
23
33.
 References
1.
Silva P, Dahlke DV, Smith ML, Charles W, Gomez J, Ory MG, Ramos KS. An Idealized 
Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative 
Technology. J Pers Med. 2022;12(5).
2.
Silva P, Jacobs D, Kriak J, Abu-Baker A, Udeani G, Neal G, Ramos K. Implementation 
of Pharmacogenomics and Artificial Intelligence Tools for Chronic Disease Management in 
Primary Care Setting. Journal of Personalized Medicine. 2021;11(6):443.
3.
Silva PS, N. CHIMERIC COHORTS AND CONSORTIA CAN POWER AND SCALE 
PRECISION MEDICINE. In: Ramos K, editor. Comprehensive Presicion Medicine. London, UK: 
Elsevier; 2023.
4.
Wong ND, Cupples LA, Ostfeld AM, Levy D, Kannel WB. Risk factors for long-term 
coronary prognosis after initial myocardial infarction: the Framingham Study. Am J Epidemiol. 
1989;130(3):469-80.
5.
Meyskens FL, Jr., Curt GA, Brenner DE, Gordon G, Herberman RB, Finn O, et al. 
Regulatory approval of cancer risk-reducing (chemopreventive) drugs: moving what we have 
learned into the clinic. Cancer Prev Res (Phila). 2011;4(3):311-23.
6.
Codman EA. The classic: the registry of bone sarcomas as an example of the end-result 
idea in hospital organization. 1924. Clin Orthop Relat Res. 2009;467(11):2766-70.
7.
White MC, Babcock F, Hayes NS, Mariotto AB, Wong FL, Kohler BA, Weir HK. The 
history and use of cancer registry data by public health cancer control programs in the United 
States. Cancer. 2017;123 Suppl 24(Suppl 24):4969-76.
8.
Kesselheim AS, Avorn J. New “21st Century Cures” legislation: speed and ease vs 
science. JAMA. 2017;317(6):581-2.
9.
Agarwala V, Khozin S, Singal G, O’Connell C, Kuk D, Li G, et al. Real-World Evidence In 
Support Of Precision Medicine: Clinico-Genomic Cancer Data As A Case Study. Health Affairs. 
2018;37(5):765-72.
10.
Silva PJ, Ramos KS. Chapter 53 - Precision medicine at the academic-industry 
interface. In: Faintuch J, Faintuch S, editors. Precision Medicine for Investigators, Practitioners 
and Providers: Academic Press; 2020. p. 545-60.
11.
Silva PJ, Schaibley VM, Ramos KS. Academic medical centers as innovation 
ecosystems to address population -omics challenges in precision medicine. Journal of 
translational medicine. 2018;16(1):28-.
12.
Dalton WS, Sullivan D, Ecsedy J, Caligiuri MA. Patient Enrichment for Precision-Based 
Cancer Clinical Trials: Using Prospective Cohort Surveillance as an Approach to Improve 
Clinical Trials. Clin Pharmacol Ther. 2018;104(1):23-6.
13.
Tamara S, Jeremy S, Leah C, Stella S, Virginia F, Margaret M, Cheryl C-P. Comparison 
of Population Characteristics in Real-World Clinical Oncology Databases in the US: Flatiron 
Health-Foundation Medicine Clinico-Genomic Databases, Flatiron Health Research Databases, 
and the National Cancer Institute SEER Population-Based Cancer Registry. medRxiv. 
2023:2023.01.03.22283682.
14.
Herpner M. Tempus, a well-funded company run by a Groupon billionaire, wants to get 
patients into clinical trials. STAT. 2019 June 3, 2019.
15.
Volpi S, Bult CJ, Chisholm RL, Deverka PA, Ginsburg GS, Jacob HJ, et al. Research 
Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs 
and Projects. Clin Pharmacol Ther. 2018;103(5):778-86.
16.
Silva PR, KS. UTILITY OF PRE-EMPTIVE PHARMACOGENOMICS IN PRECISION 
PREVENTION (submitted). In: Ramos K, editor. Comprehensive Precision Medicine: Elsevier; 
2023.

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
24
17.
Qin H, Patel MR. The Challenge and Opportunity of NTRK Inhibitors in Non-Small Cell 
Lung Cancer. Int J Mol Sci. 2022;23(6).
18.
Schwartzberg L, Broder MS, Ailawadhi S, Beltran H, Blakely LJ, Budd GT, et al. Impact 
of early detection on cancer curability: A modified Delphi panel study. PLoS One. 
2022;17(12):e0279227.
19.
Pons-Belda OD, Fernandez-Uriarte A, Diamandis EP. Multi Cancer Early Detection by 
Using Circulating Tumor DNA-The Galleri Test. Reply to Klein et al. The Promise of Multicancer 
Early Detection. Comment on "Pons-Belda et al. Can Circulating Tumor DNA Support a 
Successful Screening Test for Early Cancer Detection? The Grail Paradigm. Diagnostics 2021, 
11, 2171". Diagnostics (Basel). 2022;12(5).
20.
Strijker M, Soer EC, De Pastena M, Creemers A, Balduzzi A, Beagan JJ, et al. 
Circulating tumor DNA quantity is related to tumor volume and both predict survival in metastatic 
pancreatic ductal adenocarcinoma. International journal of cancer. 2020;146(5):1445-56.
21.
Levy D. 60 years studying heart-disease risk. Nature Reviews Drug Discovery. 
2008;7(9):715-.
22.
Giordano C, Brennan M, Mohamed B, Rashidi P, Modave F, Tighe P. Accessing Artificial 
Intelligence for Clinical Decision-Making. Frontiers in Digital Health. 2021;3.
23.
Fisher CB, Layman DM. Genomics, Big Data, and Broad Consent: a New Ethics Frontier 
for Prevention Science. Prev Sci. 2018;19(7):871-9.
24.
Fisher CK, Smith AM, Walsh JR. Machine learning for comprehensive forecasting of 
Alzheimer's Disease progression. Sci Rep. 2019;9(1):13622.
25.
Patrick Silva NJ, Kenneth S. Ramos, George Udeani,  Lixian Zhong,  Marcia G. Ory, and  
Matthew Lee Smith. Contemporaneous external control arms: identifying a matched cohort 
using real world evidence in real-time for clinical and public health investigations. Front Med Sec 
Regulatory Science. 2023;10.
26.
Janssen MF, Pickard AS, Golicki D, Gudex C, Niewada M, Scalone L, et al. 
Measurement properties of the EQ-5D-5L compared to the EQ-5D-3L across eight patient 
groups: a multi-country study. Quality of Life Research. 2013;22(7):1717-27.
27.
Jones PW, Quirk FH, Baveystock CM. The St George's Respiratory Questionnaire. 
Respir Med. 1991;85 Suppl B:25-31; discussion 3-7.
28.
Burroughs TE, Desikan R, Waterman BM, Gilin D, McGill J. Development and Validation 
of the Diabetes Quality of Life Brief Clinical Inventory. Diabetes Spectrum. 2004;17(1):41.
29.
Niv D, Kreitler S. Pain and quality of life. Pain Pract. 2001;1(2):150-61.
30.
Dameron E. Invited Product Profile: The Mitra Microsampling Device. Point of Care. 
2019;18(1).
31.
Bloem K, Schaap T, Boshuizen R, Kneepkens EL, Wolbink GJ, Vries Ad, Rispens T. 
Capillary blood microsampling to determine serum biopharmaceutical concentration: Mitra® 
microsampler vs dried blood spot. Bioanalysis. 2018;10(11):815-23.
32.
Undre N, Hussain I, Meijer J, Stanta J, Swan G, Dawson I. Quantitation of Tacrolimus in 
Human Whole Blood Samples Using the MITRA Microsampling Device. Ther Drug Monit. 
2021;43(3):364-70.
33.
Shen X, Kellogg R, Panyard DJ, Bararpour N, Castillo KE, Lee-McMullen B, et al. Multi-
omics microsampling for the profiling of lifestyle-associated changes in health. Nature 
Biomedical Engineering. 2023.
34.
Nagels J, Wu S, Gorokhova V. Deterministic vs. Probabilistic: Best Practices for Patient 
Matching Based on a Comparison of Two Implementations. J Digit Imaging. 2019;32(6):919-24.
35.
Oostema JA, Nickles A, Reeves MJ. A Comparison of Probabilistic and Deterministic 
Match Strategies for Linking Prehospital and in-Hospital Stroke Registry Data. Journal of Stroke 
and Cerebrovascular Diseases. 2020;29(10):105151.
36.
Országhová Z, Mego M, Chovanec M. Long-Term Cognitive Dysfunction in Cancer 
Survivors. Frontiers in Molecular Biosciences. 2021;8.

IRB NUMBER: STUDY2024-0008
IRB APPROVAl DATE: 11/6/2024
25
37.
Pendergrass JC, Targum SD, Harrison JE. Cognitive Impairment Associated with 
Cancer: A Brief Review. Innov Clin Neurosci. 2018;15(1-2):36-44.
38.
Van Dyk K, Ganz PA. Cancer-Related Cognitive Impairment in Patients With a History of 
Breast Cancer. JAMA. 2021;326(17):1736-7.
39.
Grill JD, Galvin JE. Facilitating Alzheimer disease research recruitment. Alzheimer Dis 
Assoc Disord. 2014;28(1):1-8.
40.
Slaughter S, Cole D, Jennings E, Reimer MA. Consent and assent to participate in 
research from people with dementia. Nurs Ethics. 2007;14(1):27-40.
41.
Hellström I, Nolan M, Nordenfelt L, Lundh U. Ethical and methodological issues in 
interviewing persons with dementia. Nurs Ethics. 2007;14(5):608-19.