The overarching goal of our research program is to develop a better understanding of the initiation, maintenance, progression, and treatment response of carcinomas. Our work focuses on two main areas:
1. Normal and cancer stem cell biology and its implications for cancer therapy.
2. Development of genomics-based biomarkers for identifying the presence of malignant cells, prognostication, and predicting response to therapy.
Specific areas of focus include cancers of the lung, breast, and gastrointestinal system. We employ tools of genomics, stem cell biology, mouse genetics, and computational biology. Clinically, Dr. Diehn specializes in the treatment of lung cancer and leads an active clinical research program. Our ultimate goal is to develop improved treatments for patients with lung, breast, and gastrointestinal cancers.
Associate Professor of Radiation Oncology (Radiation Therapy)
Distinct biological subtypes and patterns of genome evolution in lymphoma revealed by circulating tumor DNA
SCIENCE TRANSLATIONAL MEDICINE
2016; 8 (364)
Patients with diffuse large B cell lymphoma (DLBCL) exhibit marked diversity in tumor behavior and outcomes, yet the identification of poor-risk groups remains challenging. In addition, the biology underlying these differences is incompletely understood. We hypothesized that characterization of mutational heterogeneity and genomic evolution using circulating tumor DNA (ctDNA) profiling could reveal molecular determinants of adverse outcomes. To address this hypothesis, we applied cancer personalized profiling by deep sequencing (CAPP-Seq) analysis to tumor biopsies and cell-free DNA samples from 92 lymphoma patients and 24 healthy subjects. At diagnosis, the amount of ctDNA was found to strongly correlate with clinical indices and was independently predictive of patient outcomes. We demonstrate that ctDNA genotyping can classify transcriptionally defined tumor subtypes, including DLBCL cell of origin, directly from plasma. By simultaneously tracking multiple somatic mutations in ctDNA, our approach outperformed immunoglobulin sequencing and radiographic imaging for the detection of minimal residual disease and facilitated noninvasive identification of emergent resistance mutations to targeted therapies. In addition, we identified distinct patterns of clonal evolution distinguishing indolent follicular lymphomas from those that transformed into DLBCL, allowing for potential noninvasive prediction of histological transformation. Collectively, our results demonstrate that ctDNA analysis reveals biological factors that underlie lymphoma clinical outcomes and could facilitate individualized therapy.
View details for DOI 10.1126/scitranslmed.aai8545
View details for Web of Science ID 000389448100006
View details for PubMedID 27831904
Role of KEAP1/NRF2 and TP53 Mutations in Lung Squamous Cell Carcinoma Development and Radiation Resistance.
Lung squamous cell carcinoma (LSCC) pathogenesis remains incompletely understood, and biomarkers predicting treatment response remain lacking. Here, we describe novel murine LSCC models driven by loss of Trp53 and Keap1, both of which are frequently mutated in human LSCCs. Homozygous inactivation of Keap1 or Trp53 promoted airway basal stem cell (ABSC) self-renewal, suggesting that mutations in these genes lead to expansion of mutant stem cell clones. Deletion of Trp53 and Keap1 in ABSCs, but not more differentiated tracheal cells, produced tumors recapitulating histologic and molecular features of human LSCCs, indicating that they represent the likely cell of origin in this model. Deletion of Keap1 promoted tumor aggressiveness, metastasis, and resistance to oxidative stress and radiotherapy (RT). KEAP1/NRF2 mutation status predicted risk of local recurrence after RT in patients with non-small lung cancer (NSCLC) and could be noninvasively identified in circulating tumor DNA. Thus, KEAP1/NRF2 mutations could serve as predictive biomarkers for personalization of therapeutic strategies for NSCLCs.We developed an LSCC mouse model involving Trp53 and Keap1, which are frequently mutated in human LSCCs. In this model, ABSCs are the cell of origin of these tumors. KEAP1/NRF2 mutations increase radioresistance and predict local tumor recurrence in radiotherapy patients. Our findings are of potential clinical relevance and could lead to personalized treatment strategies for tumors with KEAP1/NRF2 mutations. Cancer Discov; 7(1); 86-101. ©2016 AACR.This article is highlighted in the In This Issue feature, p. 1.
View details for PubMedID 27663899
View details for PubMedCentralID PMC5222718
Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients
Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment.
View details for DOI 10.1038/ncomms11815
View details for Web of Science ID 000378007200001
View details for PubMedID 27283993
View details for PubMedCentralID PMC4906406
Integrated digital error suppression for improved detection of circulating tumor DNA
2016; 34 (5): 547-555
High-throughput sequencing of circulating tumor DNA (ctDNA) promises to facilitate personalized cancer therapy. However, low quantities of cell-free DNA (cfDNA) in the blood and sequencing artifacts currently limit analytical sensitivity. To overcome these limitations, we introduce an approach for integrated digital error suppression (iDES). Our method combines in silico elimination of highly stereotypical background artifacts with a molecular barcoding strategy for the efficient recovery of cfDNA molecules. Individually, these two methods each improve the sensitivity of cancer personalized profiling by deep sequencing (CAPP-Seq) by about threefold, and synergize when combined to yield ∼15-fold improvements. As a result, iDES-enhanced CAPP-Seq facilitates noninvasive variant detection across hundreds of kilobases. Applied to non-small cell lung cancer (NSCLC) patients, our method enabled biopsy-free profiling of EGFR kinase domain mutations with 92% sensitivity and >99.99% specificity at the variant level, and with 90% sensitivity and 96% specificity at the patient level. In addition, our approach allowed monitoring of NSCLC ctDNA down to 4 in 10(5) cfDNA molecules. We anticipate that iDES will aid the noninvasive genotyping and detection of ctDNA in research and clinical settings.
View details for DOI 10.1038/nbt.3520
View details for Web of Science ID 000375735000036
View details for PubMedID 27018799
View details for PubMedCentralID PMC4907374
An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage
2014; 20 (5): 552-558
Circulating tumor DNA (ctDNA) is a promising biomarker for noninvasive assessment of cancer burden, but existing ctDNA detection methods have insufficient sensitivity or patient coverage for broad clinical applicability. Here we introduce cancer personalized profiling by deep sequencing (CAPP-Seq), an economical and ultrasensitive method for quantifying ctDNA. We implemented CAPP-Seq for non-small-cell lung cancer (NSCLC) with a design covering multiple classes of somatic alterations that identified mutations in >95% of tumors. We detected ctDNA in 100% of patients with stage II-IV NSCLC and in 50% of patients with stage I, with 96% specificity for mutant allele fractions down to ∼0.02%. Levels of ctDNA were highly correlated with tumor volume and distinguished between residual disease and treatment-related imaging changes, and measurement of ctDNA levels allowed for earlier response assessment than radiographic approaches. Finally, we evaluated biopsy-free tumor screening and genotyping with CAPP-Seq. We envision that CAPP-Seq could be routinely applied clinically to detect and monitor diverse malignancies, thus facilitating personalized cancer therapy.
View details for DOI 10.1038/nm.3519
View details for Web of Science ID 000335710700028