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Principal Investigator: Christine Elissa Eyler
Organization: DUKE UNIVERSITY
Fiscal Year: 2024
Award: $239,693
Funding agency: National Cancer Institute
PROJECT SUMMARY/ABSTRACT
Locally advanced rectal cancer, defined by spread to lymph nodes or extension through the full rectal wall
thickness, is diagnosed in over 15,000 US patients yearly. Standard treatment for locally advanced rectal
cancer in the US involves chemotherapy and radiation therapy (chemoradiation, CRT) prior to surgical removal
of the entire rectum. Patients may experience undesirable post-surgical consequences such as permanent
colostomy or altered anorectal function. In light of this, much ongoing research focuses on strategies to avoid
surgical intervention in the subset of patients who might be cured with CRT alone. At the time of surgery, 10-
30% of tumors are eradicated by CRT (i.e., they demonstrate a pathologic complete response) while other
tumors show little to no response. This variability in response is incompletely understood, but likely relates to
the fact that one tumor may contain numerous different tumor cell subpopulations, all with different genotypes
and epigenetic (or non-genetic) features. These diverse subpopulations and variable genetic/epigenetic
features can interact, resulting in a dynamic and evolving tumor cell network that is poorly understood. In an
increasing number of cancers, there is evidence supporting the emergence of treatment-induced evolutionary
“traps,” or “collateral sensitivities”, where resistance to one therapy results in sensitivity to another therapy.
Whether this occurs in rectal cancer, and how to leverage it into treatment strategies, is unclear. To address
these questions, it is crucial to select a representative experimental model. Thus, the current proposal
leverages an already-established co-clinical pipeline from which patient derived tumor samples are used to
generate paired, patient-specific organoid and xenograft models. Two broad analytic approaches will be
undertaken to identify trends in CRT-induced tumor evolution and elucidate potential synergistic approaches to
improve CRT response. Specific Aim 1 will dissect CRT-induced changes using genomic, epigenomic, and
single cell profiling techniques, including an advanced method combining single cell RNA-seq with lineage
tracing. Specific Aim 2 employs an innovative iterative paired CRISPR/high throughput drug screen approach
to identify evolving collateral sensitivities in CRT-treated rectal cancer. To validate the findings in both Aims,
advanced patient-derived rectal cancer organoid and xenograft models will be utilized. Research, scientific
instruction, and career development will be supported by an expert panel of mentors and collaborators and a
structured training plan. Successful completion of both Aims will be promoted by the expertise and existing
screening and genomic infrastructure in the co-mentors’ laboratories and leverages a unique co-clinical
platform already established by close institutional collaborators. This research will establish a patient-derived
platform for interrogating CRT-induced tumor evolution, establishing a scientific niche to facilitate success
during the transition to scientific independence.
Terms: <Abscission><Address><Antioncogene Protein p53><Architecture><Benchmarking><Best Practice Analysis><C-K-RAS><CRISPR><CRISPR approach><CRISPR based approach><CRISPR method><CRISPR methodology><CRISPR technique><CRISPR technology><CRISPR tools><CRISPR-CAS-9><CRISPR-based method><CRISPR-based technique><CRISPR-based technology><CRISPR-based tool><CRISPR/CAS approach><CRISPR/Cas method><CRISPR/Cas system><CRISPR/Cas technology><CRISPR/Cas9><CRISPR/Cas9 technology><Cancer Model><Cancer Patient><CancerModel><Cancers><Cas nuclease technology><Cell Body><Cells><Cellular Tumor Antigen P53><Chemotherapy and Radiation><Chemotherapy and/or radiation><Clinical><Clustered Regularly Interspaced Short Palindromic Repeats><Clustered Regularly Interspaced Short Palindromic Repeats approach><Clustered Regularly Interspaced Short Palindromic Repeats method><Clustered Regularly Interspaced Short Palindromic Repeats methodology><Clustered Regularly Interspaced Short Palindromic Repeats technique><Clustered Regularly Interspaced Short Palindromic Repeats technology><Collaborations><Colostomy><Colostomy Procedure><Combination Drug Therapy><Cytotoxic Chemotherapy><Cytotoxic Therapy><Data><Development><Diagnosis><Disease><Disorder><Drug Screening><Effectiveness><Engineering / Architecture><Epigenetic><Epigenetic Change><Epigenetic Mechanism><Epigenetic Process><Evaluation><Evolution><Excision><Experimental Models><Extirpation><Foundations><Genetic><Genetic Alteration><Genetic Change><Genetic defect><Genomics><Genotype><Goals><Human><Implant><In complete remission><Induction Therapy><Infrastructure><Institution><Instruction><K-RAS2A><K-RAS2B><K-Ras><K-Ras 2A><K-Ras-2 Oncogene><KRAS><KRAS2><KRAS2 gene><Ki-RAS><Laboratories><Light><Lymph Node Reticuloendothelial System><Lymph node proper><Lymphatic nodes><Malignant Neoplasms><Malignant Tumor><Mentors><Methods><Modeling><Modern Man><Mutation><NEOADJ><Neoadjuvant><Neoadjuvant Therapy><Neoadjuvant Treatment><Oncogene K-Ras><Oncoprotein p53><Operative Procedures><Operative Surgical Procedures><Organoids><P53><PDX model><Pathologic><Patient derived xenograft><Patients><Phenotype><Phosphoprotein P53><Phosphoprotein pp53><Photoradiation><Polychemotherapy><Protein TP53><RASK2><Radiation therapy><Radiotherapeutics><Radiotherapy><Rectal Cancer><Rectal Carcinoma><Rectal Neoplasms><Rectal Tumors><Rectum><Rectum Neoplasms><Rectum Tumor><Removal><Research><Research Specimen><Resistance><Sampling><Specimen><Structure><Surgical><Surgical Interventions><Surgical Procedure><Surgical Removal><TP53><TP53 gene><TRP53><Techniques><Thick><Thickness><Time><Training><Treatment outcome><Tumor Cell><Tumor Protein p53><Tumor Protein p53 Gene><Tumor Volume><Variant><Variation><Xenograft Model><advanced disease><advanced illness><benchmark><career development><chemo-/radio-therapy><chemo-radio-therapy><chemo-radiotherapy><chemo/radiation therapy><chemoradiation><chemoradiation therapy><chemoradiation treatment><chemoradiotherapy><chemotherapy><chemotherapy and radiotherapy><combination chemotherapy><combination pharmacotherapy><complete response><design><designing><developmental><drug sensitivity><epigenetically><epigenomics><experience><genome mutation><genome scale><genome-wide><genomewide><high-throughput drug screening><improved><induction therapies><innovate><innovation><innovative><knowledge base><lymph gland><lymph nodes><lymphnodes><malignancy><mutant><neoplasm/cancer><neoplastic cell><new therapeutic approach><new therapeutic intervention><new therapeutic strategies><new therapy approaches><new treatment approach><new treatment strategy><non-genetic><nongenetic><novel><novel therapeutic approach><novel therapeutic intervention><novel therapeutic strategies><novel therapy approach><p53 Antigen><p53 Genes><p53 Tumor Suppressor><patient derived xenograft model><patient subclass><patient subcluster><patient subgroups><patient subpopulations><patient subsets><patient subtypes><protein p53><radiation or chemotherapy><radiation resistant><radiation treatment><radio-chemo-therapy><radio-chemotherapy><radiochemotherapy><radioresistant><resection><resistance mechanism><resistance to therapy><resistant><resistant mechanism><resistant to radiation><resistant to therapy><response><scRNA-seq><screening><screenings><single cell RNA-seq><single cell RNAseq><single cell expression profiling><single cell transcriptomic profiling><single-cell RNA sequencing><standard care><standard treatment><sub-clonal heterogeneity><subclonal heterogeneity><success><surgery><targeted drug therapy><targeted drug treatments><targeted therapeutic><targeted therapeutic agents><targeted therapy><targeted treatment><therapeutic resistance><therapeutic target><therapy resistant><treatment resistance><treatment strategy><treatment with radiation><trend><tumor><tumor eradication><v-Ki-RAS2 Kirsten Rat Sarcoma 2 Viral Oncogene Homolog><xenograft transplant model><xenotransplant model>