||5U2CCA252971-02 Interpret this number
||University Of Southern California
||Usc Pe-Gcs: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies
Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos are the largest
and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US.
Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group.
For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African
Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting,
demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age
and with higher stage, and we have previously reported that Mexican H/L in California have the greatest
proportion of young (<50 years of age) diagnoses compared to other H/L subgroups. Moreover, Mexican H/L
showed higher prevalence of rectal cancer cases compared to other H/L and NHW. Although socio-economics
and access to care might influence these differences, we need to take a complete look at the biology of disease
in this ethnic group to determine once and for all if these clinical differences are related to differences in molecular
etiology. The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594
cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed
assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability
to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices
may not been investigated to identify best practices for accruing and consenting patients into clinical translational
biomedical research studies. This concept of Participant Engagement is critically important for both the patients
and the translational cancer research community. Optimizing and improving our approaches for directly
engaging patients at initial contact, throughout the course of a translational genomic study, and during the time
of return of results is likely to lead to stronger relationships between the medical community and patients, but
could also lead to significant improvement in outcomes for patients and for the cancer care community as a
whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in
Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic
Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant
Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in
all relevant areas of research for genomic characterization, participant engagement, and engagement
optimization. We have an established platform for consenting patients into cancer genomics studies that will
serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement
optimization and CRC genomic research that will be shared with the broader community to distribute best
practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.
Priorities to Promote Participant Engagement in the Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network.
, Crossnohere N.L.
, Bachini M.
, Blair C.K.
, Carpten J.D.
, Claus E.B.
, Colditz G.A.
, Ding L.
, Drake B.F.
, Fields R.C.
, et al.
Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2023-04-03; 32(4), p. 487-495.
Barriers and Facilitators to Genetic Education, Risk Assessment, and Testing: Considerations on Advancing Equitable Genetics Care.
, Ricker C.
, Stoffel E.M.
, Syngal S.
Gastroenterology, 2023 Jan; 164(1), p. 5-8.
Transcriptome analysis provides critical answers to the "variants of uncertain significance" conundrum.
, Culver J.O.
, Ricker C.
, Craig D.W.
Human mutation, 2022 Nov; 43(11), p. 1590-1608.