Publications by authors named "Ash A Alizadeh"

111 Publications

Single cell analysis reveals distinct immune landscapes in transplant and primary sarcomas that determine response or resistance to immunotherapy.

Nat Commun 2020 12 17;11(1):6410. Epub 2020 Dec 17.

Department of Pharmacology and Cancer Biology, Duke University Medical Center, Durham, NC, 27708, USA.

Immunotherapy fails to cure most cancer patients. Preclinical studies indicate that radiotherapy synergizes with immunotherapy, promoting radiation-induced antitumor immunity. Most preclinical immunotherapy studies utilize transplant tumor models, which overestimate patient responses. Here, we show that transplant sarcomas are cured by PD-1 blockade and radiotherapy, but identical treatment fails in autochthonous sarcomas, which demonstrate immunoediting, decreased neoantigen expression, and tumor-specific immune tolerance. We characterize tumor-infiltrating immune cells from transplant and primary tumors, revealing striking differences in their immune landscapes. Although radiotherapy remodels myeloid cells in both models, only transplant tumors are enriched for activated CD8+ T cells. The immune microenvironment of primary murine sarcomas resembles most human sarcomas, while transplant sarcomas resemble the most inflamed human sarcomas. These results identify distinct microenvironments in murine sarcomas that coevolve with the immune system and suggest that patients with a sarcoma immune phenotype similar to transplant tumors may benefit most from PD-1 blockade and radiotherapy.
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http://dx.doi.org/10.1038/s41467-020-19917-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7746723PMC
December 2020

A mathematical model of ctDNA shedding predicts tumor detection size.

Sci Adv 2020 Dec 11;6(50). Epub 2020 Dec 11.

Canary Center for Cancer Early Detection, Department of Radiology, Stanford University School of Medicine, Palo Alto, CA 94304, USA.

Early cancer detection aims to find tumors before they progress to an incurable stage. To determine the potential of circulating tumor DNA (ctDNA) for cancer detection, we developed a mathematical model of tumor evolution and ctDNA shedding to predict the size at which tumors become detectable. From 176 patients with stage I to III lung cancer, we inferred that, on average, 0.014% of a tumor cell's DNA is shed into the bloodstream per cell death. For annual screening, the model predicts median detection sizes of 2.0 to 2.3 cm representing a ~40% decrease from the current median detection size of 3.5 cm. For informed monthly cancer relapse testing, the model predicts a median detection size of 0.83 cm and suggests that treatment failure can be detected 140 days earlier than with imaging-based approaches. This mechanistic framework can help accelerate clinical trials by precomputing the most promising cancer early detection strategies.
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http://dx.doi.org/10.1126/sciadv.abc4308DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732186PMC
December 2020

Mutations Predict Lung Cancer Radiation Resistance That Can Be Targeted by Glutaminase Inhibition.

Cancer Discov 2020 Dec 18;10(12):1826-1841. Epub 2020 Oct 18.

Department of Radiation Oncology, Stanford University, Stanford, California.

Tumor genotyping is not routinely performed in localized non-small cell lung cancer (NSCLC) due to lack of associations of mutations with outcome. Here, we analyze 232 consecutive patients with localized NSCLC and demonstrate that and mutations are predictive of high rates of local recurrence (LR) after radiotherapy but not surgery. Half of LRs occurred in tumors with mutations, indicating that they are major molecular drivers of clinical radioresistance. Next, we functionally evaluate mutations in our radiotherapy cohort and demonstrate that only pathogenic mutations are associated with radioresistance. Furthermore, expression of NFE2L2 target genes does not predict LR, underscoring the utility of tumor genotyping. Finally, we show that glutaminase inhibition preferentially radiosensitizes -mutant cells via depletion of glutathione and increased radiation-induced DNA damage. Our findings suggest that genotyping for mutations could facilitate treatment personalization and provide a potential strategy for overcoming radioresistance conferred by these mutations. SIGNIFICANCE: This study shows that mutations in and predict for LR after radiotherapy but not surgery in patients with NSCLC. Approximately half of all LRs are associated with these mutations and glutaminase inhibition may allow personalized radiosensitization of -mutant tumors..
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http://dx.doi.org/10.1158/2159-8290.CD-20-0282DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7710558PMC
December 2020

Noninvasive Early Identification of Therapeutic Benefit from Immune Checkpoint Inhibition.

Cell 2020 Oct 1;183(2):363-376.e13. Epub 2020 Oct 1.

Department of Radiation Oncology, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA. Electronic address:

Although treatment of non-small cell lung cancer (NSCLC) with immune checkpoint inhibitors (ICIs) can produce remarkably durable responses, most patients develop early disease progression. Furthermore, initial response assessment by conventional imaging is often unable to identify which patients will achieve durable clinical benefit (DCB). Here, we demonstrate that pre-treatment circulating tumor DNA (ctDNA) and peripheral CD8 T cell levels are independently associated with DCB. We further show that ctDNA dynamics after a single infusion can aid in identification of patients who will achieve DCB. Integrating these determinants, we developed and validated an entirely noninvasive multiparameter assay (DIREct-On, Durable Immunotherapy Response Estimation by immune profiling and ctDNA-On-treatment) that robustly predicts which patients will achieve DCB with higher accuracy than any individual feature. Taken together, these results demonstrate that integrated ctDNA and circulating immune cell profiling can provide accurate, noninvasive, and early forecasting of ultimate outcomes for NSCLC patients receiving ICIs.
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http://dx.doi.org/10.1016/j.cell.2020.09.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7572899PMC
October 2020

Evaluating upfront high-dose consolidation after R-CHOP for follicular lymphoma by clinical and genetic risk models.

Blood Adv 2020 09;4(18):4451-4462

Department of Medicine III, University Hospital, Ludwig-Maximilians University (LMU) Munich, Munich, Germany.

High-dose therapy and autologous stem cell transplantation (HDT/ASCT) is an effective salvage treatment for eligible patients with follicular lymphoma (FL) and early progression of disease (POD). Since the introduction of rituximab, HDT/ASCT is no longer recommended in first remission. We here explored whether consolidative HDT/ASCT improved survival in defined subgroups of previously untreated patients. We report survival analyses of 431 patients who received frontline rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) for advanced FL, and were randomized to receive consolidative HDT/ASCT. We performed targeted genotyping of 157 diagnostic biopsies, and calculated genotype-based risk scores. HDT/ASCT improved failure-free survival (FFS; hazard ratio [HR], 0.8, P = .07; as-treated: HR, 0.7, P = .04), but not overall survival (OS; HR, 1.3, P = .27; as-treated: HR, 1.4, P = .13). High-risk cohorts identified by FL International Prognostic Index (FLIPI), and the clinicogenetic risk models m7-FLIPI and POD within 24 months-prognostic index (POD24-PI) comprised 27%, 18%, and 22% of patients. HDT/ASCT did not significantly prolong FFS in high-risk patients as defined by FLIPI (HR, 0.9; P = .56), m7-FLIPI (HR, 0.9; P = .91), and POD24-PI (HR, 0.8; P = .60). Similarly, OS was not significantly improved. Finally, we used a machine-learning approach to predict benefit from HDT/ASCT by genotypes. Patients predicted to benefit from HDT/ASCT had longer FFS with HDT/ASCT (HR, 0.4; P = .03), but OS did not reach statistical significance. Thus, consolidative HDT/ASCT after frontline R-CHOP did not improve OS in unselected FL patients and subgroups selected by genotype-based risk models.
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http://dx.doi.org/10.1182/bloodadvances.2020002546DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7509878PMC
September 2020

Molecular and Immunologic Signatures are Related to Clinical Benefit from Treatment with Vocimagene Amiretrorepvec (Toca 511) and 5-Fluorocytosine (Toca FC) in Patients with Glioma.

Clin Cancer Res 2020 Dec 18;26(23):6176-6186. Epub 2020 Aug 18.

Tocagen Inc., San Diego, California.

Purpose: High-grade gliomas (HGGs) are central nervous system tumors with poor prognoses and limited treatment options. Vocimagene amiretrorepvec (Toca 511) is a retroviral replicating vector encoding cytosine deaminase, which converts extended release 5-fluorocytosine (Toca FC) into the anticancer agent, 5-fluorouracil. According to preclinical studies, this therapy kills cancer cells and immunosuppressive myeloid cells in the tumor microenvironment, leading to T-cell-mediated antitumor immune activity. Therefore, we sought to elucidate this immune-related mechanism of action in humans, and to investigate potential molecular and immunologic indicators of clinical benefit from therapy.

Patients And Methods: In a phase I clinical trial (NCT01470794), patients with recurrent HGG treated with Toca 511 and Toca FC showed improved survival relative to historical controls, and some had durable complete responses to therapy. As a part of this trial, we performed whole-exome DNA sequencing, RNA-sequencing, and multiplex digital ELISA measurements on tumor and blood samples.

Results: Genetic analyses suggest mutations, copy-number variations, and neoantigens are linked to survival. Quantities of tumor immune infiltrates estimated by transcript abundance may potentially predict clinical outcomes. Peak values of cytokines in peripheral blood samples collected during and after therapy could indicate response.

Conclusions: These results support an immune-related mechanism of action for Toca 511 and Toca FC, and suggest that molecular and immunologic signatures are related to clinical benefit from treatment.
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http://dx.doi.org/10.1158/1078-0432.CCR-20-0536DOI Listing
December 2020

Autologous tumor cell vaccine induces antitumor T cell immune responses in patients with mantle cell lymphoma: A phase I/II trial.

J Exp Med 2020 09;217(9)

Division of Oncology, Stanford University, Stanford, CA.

Here, we report on the results of a phase I/II trial (NCT00490529) for patients with mantle cell lymphoma who, having achieved remission after immunochemotherapy, were vaccinated with irradiated, CpG-activated tumor cells. Subsequently, vaccine-primed lymphocytes were collected and reinfused after a standard autologous stem cell transplantation (ASCT). The primary endpoint was detection of minimal residual disease (MRD) within 1 yr after ASCT at the previously validated threshold of ≥1 malignant cell per 10,000 leukocyte equivalents. Of 45 evaluable patients, 40 (89%) were found to be MRD negative, and the MRD-positive patients experienced early subsequent relapse. The vaccination induced antitumor CD8 T cell immune responses in 40% of patients, and these were associated with favorable clinical outcomes. Patients with high tumor PD-L1 expression after in vitro exposure to CpG had inferior outcomes. Vaccination with CpG-stimulated autologous tumor cells followed by the adoptive transfer of vaccine-primed lymphocytes after ASCT is feasible and safe.
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http://dx.doi.org/10.1084/jem.20191712DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7478738PMC
September 2020

Integrating genomic features for non-invasive early lung cancer detection.

Nature 2020 04 25;580(7802):245-251. Epub 2020 Mar 25.

Stanford Cancer Institute, Stanford University, Stanford, CA, USA.

Radiologic screening of high-risk adults reduces lung-cancer-related mortality; however, a small minority of eligible individuals undergo such screening in the United States. The availability of blood-based tests could increase screening uptake. Here we introduce improvements to cancer personalized profiling by deep sequencing (CAPP-Seq), a method for the analysis of circulating tumour DNA (ctDNA), to better facilitate screening applications. We show that, although levels are very low in early-stage lung cancers, ctDNA is present prior to treatment in most patients and its presence is strongly prognostic. We also find that the majority of somatic mutations in the cell-free DNA (cfDNA) of patients with lung cancer and of risk-matched controls reflect clonal haematopoiesis and are non-recurrent. Compared with tumour-derived mutations, clonal haematopoiesis mutations occur on longer cfDNA fragments and lack mutational signatures that are associated with tobacco smoking. Integrating these findings with other molecular features, we develop and prospectively validate a machine-learning method termed 'lung cancer likelihood in plasma' (Lung-CLiP), which can robustly discriminate early-stage lung cancer patients from risk-matched controls. This approach achieves performance similar to that of tumour-informed ctDNA detection and enables tuning of assay specificity in order to facilitate distinct clinical applications. Our findings establish the potential of cfDNA for lung cancer screening and highlight the importance of risk-matching cases and controls in cfDNA-based screening studies.
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http://dx.doi.org/10.1038/s41586-020-2140-0DOI Listing
April 2020

Outcomes of Observation vs Stereotactic Ablative Radiation for Oligometastatic Prostate Cancer: The ORIOLE Phase 2 Randomized Clinical Trial.

JAMA Oncol 2020 05;6(5):650-659

Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Importance: Complete metastatic ablation of oligometastatic prostate cancer may provide an alternative to early initiation of androgen deprivation therapy (ADT).

Objective: To determine if stereotactic ablative radiotherapy (SABR) improves oncologic outcomes in men with oligometastatic prostate cancer.

Design, Setting, And Participants: The Observation vs Stereotactic Ablative Radiation for Oligometastatic Prostate Cancer (ORIOLE) phase 2 randomized study accrued participants from 3 US radiation treatment facilities affiliated with a university hospital from May 2016 to March 2018 with a data cutoff date of May 20, 2019, for analysis. Of 80 men screened, 54 men with recurrent hormone-sensitive prostate cancer and 1 to 3 metastases detectable by conventional imaging who had not received ADT within 6 months of enrollment or 3 or more years total were randomized.

Interventions: Patients were randomized in a 2:1 ratio to receive SABR or observation.

Main Outcomes And Measures: The primary outcome was progression at 6 months by prostate-specific antigen level increase, progression detected by conventional imaging, symptomatic progression, ADT initiation for any reason, or death. Predefined secondary outcomes were toxic effects of SABR, local control at 6 months with SABR, progression-free survival, Brief Pain Inventory (Short Form)-measured quality of life, and concordance between conventional imaging and prostate-specific membrane antigen (PSMA)-targeted positron emission tomography in the identification of metastatic disease.

Results: In the 54 men randomized, the median (range) age was 68 (61-70) years for patients allocated to SABR and 68 (64-76) years for those allocated to observation. Progression at 6 months occurred in 7 of 36 patients (19%) receiving SABR and 11 of 18 patients (61%) undergoing observation (P = .005). Treatment with SABR improved median progression-free survival (not reached vs 5.8 months; hazard ratio, 0.30; 95% CI, 0.11-0.81; P = .002). Total consolidation of PSMA radiotracer-avid disease decreased the risk of new lesions at 6 months (16% vs 63%; P = .006). No toxic effects of grade 3 or greater were observed. T-cell receptor sequencing identified significant increased clonotypic expansion following SABR and correlation between baseline clonality and progression with SABR only (0.082085 vs 0.026051; P = .03).

Conclusions And Relevance: Treatment with SABR for oligometastatic prostate cancer improved outcomes and was enhanced by total consolidation of disease identified by PSMA-targeted positron emission tomography. SABR induced a systemic immune response, and baseline immune phenotype and tumor mutation status may predict the benefit from SABR. These results underline the importance of prospective randomized investigation of the oligometastatic state with integrated imaging and biological correlates.

Trial Registration: ClinicalTrials.gov Identifier: NCT02680587.
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http://dx.doi.org/10.1001/jamaoncol.2020.0147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7225913PMC
May 2020

Circulating Tumor DNA Analysis to Assess Risk of Progression after Long-term Response to PD-(L)1 Blockade in NSCLC.

Clin Cancer Res 2020 06 11;26(12):2849-2858. Epub 2020 Feb 11.

Department of Radiation Oncology, Stanford University, Stanford, California.

Purpose: Treatment with PD-(L)1 blockade can produce remarkably durable responses in patients with non-small cell lung cancer (NSCLC). However, a significant fraction of long-term responders ultimately progress and predictors of late progression are unknown. We hypothesized that circulating tumor DNA (ctDNA) analysis of long-term responders to PD-(L)1 blockade may differentiate those who will achieve ongoing benefit from those at risk of eventual progression.

Experimental Design: In patients with advanced NSCLC achieving long-term benefit from PD-(L)1 blockade (progression-free survival ≥ 12 months), plasma was collected at a surveillance timepoint late during/after treatment to interrogate ctDNA by Cancer Personalized Profiling by Deep Sequencing. Tumor tissue was available for 24 patients and was profiled by whole-exome sequencing ( = 18) or by targeted sequencing ( = 6).

Results: Thirty-one patients with NSCLC with long-term benefit to PD-(L)1 blockade were identified, and ctDNA was analyzed in surveillance blood samples collected at a median of 26.7 months after initiation of therapy. Nine patients also had baseline plasma samples available, and all had detectable ctDNA prior to therapy initiation. At the surveillance timepoint, 27 patients had undetectable ctDNA and 25 (93%) have remained progression-free; in contrast, all 4 patients with detectable ctDNA eventually progressed [Fisher < 0.0001; positive predictive value = 1, 95% confidence interval (CI), 0.51-1; negative predictive value = 0.93 (95% CI, 0.80-0.99)].

Conclusions: ctDNA analysis can noninvasively identify minimal residual disease in patients with long-term responses to PD-(L)1 blockade and predict the risk of eventual progression. If validated, ctDNA surveillance may facilitate personalization of the duration of immune checkpoint blockade and enable early intervention in patients at high risk for progression.
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http://dx.doi.org/10.1158/1078-0432.CCR-19-3418DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299781PMC
June 2020

Profiling Cell Type Abundance and Expression in Bulk Tissues with CIBERSORTx.

Methods Mol Biol 2020 ;2117:135-157

Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.

CIBERSORTx is a suite of machine learning tools for the assessment of cellular abundance and cell type-specific gene expression patterns from bulk tissue transcriptome profiles. With this framework, single-cell or bulk-sorted RNA sequencing data can be used to learn molecular signatures of distinct cell types from a small collection of biospecimens. These signatures can then be repeatedly applied to characterize cellular heterogeneity from bulk tissue transcriptomes without physical cell isolation. In this chapter, we provide a detailed primer on CIBERSORTx and demonstrate its capabilities for high-throughput profiling of cell types and cellular states in normal and neoplastic tissues.
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http://dx.doi.org/10.1007/978-1-0716-0301-7_7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695353PMC
February 2021

Functional significance of U2AF1 S34F mutations in lung adenocarcinomas.

Nat Commun 2019 12 13;10(1):5712. Epub 2019 Dec 13.

Stanford Cancer Institute, Stanford University, Stanford, USA.

The functional role of U2AF1 mutations in lung adenocarcinomas (LUADs) remains incompletely understood. Here, we report a significant co-occurrence of U2AF1 S34F mutations with ROS1 translocations in LUADs. To characterize this interaction, we profiled effects of S34F on the transcriptome-wide distribution of RNA binding and alternative splicing in cells harboring the ROS1 translocation. Compared to its wild-type counterpart, U2AF1 S34F preferentially binds and modulates splicing of introns containing CAG trinucleotides at their 3' splice junctions. The presence of S34F caused a shift in cross-linking at 3' splice sites, which was significantly associated with alternative splicing of skipped exons. U2AF1 S34F induced expression of genes involved in the epithelial-mesenchymal transition (EMT) and increased tumor cell invasion. Finally, S34F increased splicing of the long over the short SLC34A2-ROS1 isoform, which was also associated with enhanced invasiveness. Taken together, our results suggest a mechanistic interaction between mutant U2AF1 and ROS1 in LUAD.
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http://dx.doi.org/10.1038/s41467-019-13392-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6911043PMC
December 2019

Circulating Tumor DNA Analysis for Detection of Minimal Residual Disease After Chemoradiotherapy for Localized Esophageal Cancer.

Gastroenterology 2020 02 9;158(3):494-505.e6. Epub 2019 Nov 9.

Department of Radiation Oncology, Stanford University, Stanford, California; Stanford Cancer Institute, Stanford University, Stanford, California; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California. Electronic address:

Background & Aims: Biomarkers are needed to risk stratify after chemoradiotherapy for localized esophageal cancer. These could improve identification of patients at risk for cancer progression and selection of additional therapy.

Methods: We performed deep sequencing (CAncer Personalized Profiling by deep Sequencing, [CAPP-Seq]) analyses of plasma cell-free DNA collected from 45 patients before and after chemoradiotherapy for esophageal cancer, as well as DNA from leukocytes and fixed esophageal tumor biopsy samples collected during esophagogastroduodenoscopy. Patients were treated from May 2010 through October 2015; 23 patients subsequently underwent esophagectomy, and 22 did not undergo surgery. We also sequenced DNA from blood samples from 40 healthy control individuals. We analyzed 802 regions of 607 genes for single-nucleotide variants previously associated with esophageal adenocarcinoma or squamous cell carcinoma. Patients underwent imaging analyses 6-8 weeks after chemoradiotherapy and were followed for 5 years. Our primary aim was to determine whether detection of circulating tumor DNA (ctDNA) after chemoradiotherapy is associated with risk of tumor progression (growth of local, regional, or distant tumors, detected by imaging or biopsy).

Results: The median proportion of tumor-derived DNA in total cell-free DNA before treatment was 0.07%, indicating that ultrasensitive assays are needed for quantification and analysis of ctDNA from localized esophageal tumors. Detection of ctDNA after chemoradiotherapy was associated with tumor progression (hazard ratio, 18.7; P < .0001), formation of distant metastases (hazard ratio, 32.1; P < .0001), and shorter disease-specific survival times (hazard ratio, 23.1; P < .0001). A higher proportion of patients with tumor progression had new mutations detected in plasma samples collected after chemoradiotherapy than patients without progression (P = .03). Detection of ctDNA after chemoradiotherapy preceded radiographic evidence of tumor progression by an average of 2.8 months. Among patients who received chemoradiotherapy without surgery, combined ctDNA and metabolic imaging analysis predicted progression in 100% of patients with tumor progression, compared with 71% for only ctDNA detection and 57% for only metabolic imaging analysis (P < .001 for comparison of either technique to combined analysis).

Conclusions: In an analysis of cell-free DNA in blood samples from patients who underwent chemoradiotherapy for esophageal cancer, detection of ctDNA was associated with tumor progression, metastasis, and disease-specific survival. Analysis of ctDNA might be used to identify patients at highest risk for tumor progression.
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http://dx.doi.org/10.1053/j.gastro.2019.10.039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010551PMC
February 2020

Predicting HLA class II antigen presentation through integrated deep learning.

Nat Biotechnol 2019 11 14;37(11):1332-1343. Epub 2019 Oct 14.

Department of Medicine, Division of Oncology, Stanford Cancer Institute, Stanford University, Stanford, CA, USA.

Accurate prediction of antigen presentation by human leukocyte antigen (HLA) class II molecules would be valuable for vaccine development and cancer immunotherapies. Current computational methods trained on in vitro binding data are limited by insufficient training data and algorithmic constraints. Here we describe MARIA (major histocompatibility complex analysis with recurrent integrated architecture; https://maria.stanford.edu/ ), a multimodal recurrent neural network for predicting the likelihood of antigen presentation from a gene of interest in the context of specific HLA class II alleles. In addition to in vitro binding measurements, MARIA is trained on peptide HLA ligand sequences identified by mass spectrometry, expression levels of antigen genes and protease cleavage signatures. Because it leverages these diverse training data and our improved machine learning framework, MARIA (area under the curve = 0.89-0.92) outperformed existing methods in validation datasets. Across independent cancer neoantigen studies, peptides with high MARIA scores are more likely to elicit strong CD4 T cell responses. MARIA allows identification of immunogenic epitopes in diverse cancers and autoimmune disease.
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http://dx.doi.org/10.1038/s41587-019-0280-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7075463PMC
November 2019

Dynamic Risk Profiling Using Serial Tumor Biomarkers for Personalized Outcome Prediction.

Cell 2019 07 4;178(3):699-713.e19. Epub 2019 Jul 4.

Division of Oncology, Department of Medicine, Stanford University, Stanford, CA, USA; Division of Hematology, Department of Medicine, Stanford University, Stanford, CA, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA; Stanford Cancer Institute, Stanford University, Stanford, CA, USA. Electronic address:

Accurate prediction of long-term outcomes remains a challenge in the care of cancer patients. Due to the difficulty of serial tumor sampling, previous prediction tools have focused on pretreatment factors. However, emerging non-invasive diagnostics have increased opportunities for serial tumor assessments. We describe the Continuous Individualized Risk Index (CIRI), a method to dynamically determine outcome probabilities for individual patients utilizing risk predictors acquired over time. Similar to "win probability" models in other fields, CIRI provides a real-time probability by integrating risk assessments throughout a patient's course. Applying CIRI to patients with diffuse large B cell lymphoma, we demonstrate improved outcome prediction compared to conventional risk models. We demonstrate CIRI's broader utility in analogous models of chronic lymphocytic leukemia and breast adenocarcinoma and perform a proof-of-concept analysis demonstrating how CIRI could be used to develop predictive biomarkers for therapy selection. We envision that dynamic risk assessment will facilitate personalized medicine and enable innovative therapeutic paradigms.
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http://dx.doi.org/10.1016/j.cell.2019.06.011DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7380118PMC
July 2019

Targetable genetic alterations of () drive immunoglobulin expression in diffuse large B cell lymphoma.

Sci Transl Med 2019 06;11(497)

Department of Lymphoma/Myeloma, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.

The activated B cell (ABC-like) subtype of diffuse large B cell lymphoma (DLBCL) is characterized by chronic activation of signaling initiated by immunoglobulin μ (IgM). By analyzing the DNA copy number profiles of 1000 DLBCL tumors, we identified gains of 18q21.2 as the most frequent genetic alteration in ABC-like DLBCL. Using integrative analysis of matched gene expression profiling data, we found that the () transcription factor gene was the target of these alterations. Overexpression of in ABC-like DLBCL cell lines led to its occupancy on immunoglobulin () and gene enhancers and increased expression of these genes at the transcript and protein levels. Inhibition of TCF4 activity with dominant-negative constructs was synthetically lethal to ABC-like DLBCL cell lines harboring DNA copy gains, highlighting these gains as an attractive potential therapeutic target. Furthermore, the gene was one of the top BRD4-regulated genes in DLBCL cell lines. BET proteolysis-targeting chimera (PROTAC) ARV771 extinguished TCF4, MYC, and IgM expression and killed ABC-like DLBCL cells in vitro. In DLBCL xenograft models, ARV771 treatment reduced tumor growth and prolonged survival. This work highlights a genetic mechanism for promoting immunoglobulin signaling in ABC-like DLBCL and provides a functional rationale for the use of BET inhibitors in this disease.
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http://dx.doi.org/10.1126/scitranslmed.aav5599DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6724184PMC
June 2019

Determining cell type abundance and expression from bulk tissues with digital cytometry.

Nat Biotechnol 2019 07 6;37(7):773-782. Epub 2019 May 6.

Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, CA, USA.

Single-cell RNA-sequencing has emerged as a powerful technique for characterizing cellular heterogeneity, but it is currently impractical on large sample cohorts and cannot be applied to fixed specimens collected as part of routine clinical care. We previously developed an approach for digital cytometry, called CIBERSORT, that enables estimation of cell type abundances from bulk tissue transcriptomes. We now introduce CIBERSORTx, a machine learning method that extends this framework to infer cell-type-specific gene expression profiles without physical cell isolation. By minimizing platform-specific variation, CIBERSORTx also allows the use of single-cell RNA-sequencing data for large-scale tissue dissection. We evaluated the utility of CIBERSORTx in multiple tumor types, including melanoma, where single-cell reference profiles were used to dissect bulk clinical specimens, revealing cell-type-specific phenotypic states linked to distinct driver mutations and response to immune checkpoint blockade. We anticipate that digital cytometry will augment single-cell profiling efforts, enabling cost-effective, high-throughput tissue characterization without the need for antibodies, disaggregation or viable cells.
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http://dx.doi.org/10.1038/s41587-019-0114-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610714PMC
July 2019

Reply to J. Wang et al.

J Clin Oncol 2019 03 12;37(9):755-757. Epub 2019 Feb 12.

David M. Kurtz, MD, PhD; Florian Scherer, MD; Michael C. Jin; Joanne Soo; Alexander F.M. Craig, MPhil; Mohammad S. Esfahani, PhD; Jacob J. Chabon, PhD; Henning Stehr, PhD; Chih Long Liu, PhD; Robert Tibshirani, PhD; Lauren S. Maeda, MD; Neel K. Gupta, MD; Michael S. Khodadoust, MD, PhD; Ranjana H. Advani, MD; and Aaron M. Newman, PhD, Stanford University, Stanford, CA; Ulrich Dührsen, MD; and Andreas Hüttmann, MD, University Hospital Essen, Essen, Germany; Michel Meignan, MD, PhD, Hôpitaux Universitaires Henri Mondor, Creteil, France; Olivier Casasnovas, MD, Centre Hospitalier Universitaire, Dijon, France; Jason R. Westin, MD, The University of Texas MD Anderson Cancer Center, Houston, TX; Mark Roschewski, MD; and Wyndham H. Wilson, MD, PhD, National Institutes of Health, Bethesda, MD; Gianluca Gaidano, MD, PhD; and Davide Rossi, MD, PhD, University of Eastern Piedmont, Novara, Italy, Oncology Institute of Southern Switzerland and Institute of Oncology Research, Bellinzona, Switzerland; and Maximilian Diehn, MD, PhD; and Ash A. Alizadeh, MD, PhD, Stanford University, Stanford, CA.

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http://dx.doi.org/10.1200/JCO.18.01907DOI Listing
March 2019

Detection and Surveillance of Bladder Cancer Using Urine Tumor DNA.

Cancer Discov 2019 04 21;9(4):500-509. Epub 2018 Dec 21.

Stanford Cancer Institute, Stanford University, Stanford, California.

Current regimens for the detection and surveillance of bladder cancer are invasive and have suboptimal sensitivity. Here, we present a novel high-throughput sequencing (HTS) method for detection of urine tumor DNA (utDNA) called utDNA CAPP-Seq (uCAPP-Seq) and apply it to 67 healthy adults and 118 patients with early-stage bladder cancer who had urine collected either prior to treatment or during surveillance. Using this targeted sequencing approach, we detected a median of 6 mutations per patient with bladder cancer and observed surprisingly frequent mutations of the promoter (46%), suggesting these mutations represent a useful biomarker for detection of bladder cancer. We detected utDNA pretreatment in 93% of cases using a tumor mutation-informed approach and in 84% when blinded to tumor mutation status, with 96% to 100% specificity. In the surveillance setting, we detected utDNA in 91% of patients who ultimately recurred, with utDNA detection preceding clinical progression in 92% of cases. uCAPP-Seq outperformed a commonly used ancillary test (UroVysion, = 0.02) and cytology and cystoscopy combined ( ≤ 0.006), detecting 100% of bladder cancer cases detected by cytology and 82% that cytology missed. Our results indicate that uCAPP-Seq is a promising approach for early detection and surveillance of bladder cancer. SIGNIFICANCE: This study shows that utDNA can be detected using HTS with high sensitivity and specificity in patients with early-stage bladder cancer and during post-treatment surveillance, significantly outperforming standard diagnostic modalities and facilitating noninvasive detection, genotyping, and monitoring..
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http://dx.doi.org/10.1158/2159-8290.CD-18-0825DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6467650PMC
April 2019

Genomic Feature Selection by Coverage Design Optimization.

J Appl Stat 2018 7;45(14):2658-2676. Epub 2018 Feb 7.

Department of Statistics, Stanford University, 390 Serra Mall, Stanford, CA, USA.

We introduce a novel data reduction technique whereby we select a subset of tiles to "cover" maximally events of interest in large-scale biological datasets (e.g., genetic mutations), while minimizing the number of tiles. A tile is a genomic unit capturing one or more biological events, such as a sequence of base pairs that can be sequenced and observed simultaneously. The goal is to reduce significantly the number of tiles considered to those with areas of dense events in a cohort, thus saving on cost and enhancing interpretability. However, the reduction should not come at the cost of too much information, allowing for sensible statistical analysis after its application. We envisage application of our methods to a variety of high throughput data types, particularly those produced by next generation sequencing (NGS) experiments. The procedure is cast as a convex optimization problem, which is presented, along with methods of its solution. The method is demonstrated on a large dataset of somatic mutations spanning 5000+ patients, each having one of 29 cancer types. Applied to these data, our method dramatically reduces the number of gene locations required for broad coverage of patients and their mutations, giving subject specialists a more easily interpretable snapshot of recurrent mutational profiles in these cancers. The locations identified coincide with previously identified cancer genes. Finally, despite considerable data reduction, we show that our covering designs preserve the cancer discrimination ability of multinomial logistic regression models trained on all of the locations (> 1).
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http://dx.doi.org/10.1080/02664763.2018.1432577DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173524PMC
February 2018

Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma.

J Clin Oncol 2018 10 20;36(28):2845-2853. Epub 2018 Aug 20.

David M. Kurtz, Florian Scherer, Michael C. Jin, Joanne Soo, Alexander F.M. Craig, Mohammad Shahrokh Esfahani, Jacob J. Chabon, Henning Stehr, Chih Long Liu, Robert Tibshirani, Lauren S. Maeda, Neel K. Gupta, Michael S. Khodadoust, Ranjana H. Advani, Ronald Levy, Aaron M. Newman, Maximilian Diehn, and Ash A. Alizadeh, Stanford University, Stanford, CA; Florian Scherer, University Medical Center Freiburg, Freiburg; Ulrich Dührsen and Andreas Hüttmann, University Hospital Essen, Essen, Germany; Michel Meignan, Hôpitaux Universitaires Henri Mondor, Creteil; René-Olivier Casasnovas, Hôpital Le Bocage, Centre Hospitalier Universitaire, Dijon, France; Jason R. Westin, University of Texas MD Anderson Cancer Center, Houston, TX; Mark Roschewski and Wyndham H. Wilson, National Cancer Institute, National Institutes of Health, Bethesda, MD; Gianluca Gaidano and Davide Rossi, University of Eastern Piedmont, Novara, Italy; and Davide Rossi, Oncology Institute of Southern Switzerland and Institute of Oncology Research, Bellinzona, Switzerland.

Purpose: Outcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes.

Patients And Methods: We studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans.

Results: Before therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage settings. In the discovery set, ctDNA levels changed rapidly, with a 2-log decrease after one cycle (early molecular response [EMR]) and a 2.5-log decrease after two cycles (major molecular response [MMR]) stratifying outcomes. In the first validation set, patients receiving front-line therapy achieving EMR or MMR had superior outcomes at 24 months (EMR: EFS, 83% v 50%; P = .0015; MMR: EFS, 82% v 46%; P < .001). EMR also predicted superior 24-month outcomes in patients receiving salvage therapy in the first validation set (EFS, 100% v 13%; P = .011). The prognostic value of EMR and MMR was further confirmed in the second validation set. In multivariable analyses including International Prognostic Index and interim positron emission tomography/computed tomography scans across both cohorts, molecular response was independently prognostic of outcomes, including event-free and overall survival.

Conclusion: Pretreatment ctDNA levels and molecular responses are independently prognostic of outcomes in aggressive lymphomas. These risk factors could potentially guide future personalized risk-directed approaches.
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http://dx.doi.org/10.1200/JCO.2018.78.5246DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6161832PMC
October 2018

Surgical and molecular characterization of primary and metastatic disease in a neuroendocrine tumor arising in a tailgut cyst.

Cold Spring Harb Mol Case Stud 2018 10 1;4(5). Epub 2018 Oct 1.

Department of Bioengineering, Stanford University, Stanford, California 94305, USA.

Neuroendocrine tumors (NETs) arising from tailgut cysts are a rare but increasingly reported entity with gene expression profiles that may be indicative of the gastrointestinal cell of origin. We present a case report describing the unique pathological and genomic characteristics of a tailgut cyst NET that metastasized to liver. The histologic and immunohistochemical findings were consistent with a well-differentiated NET. Genomic testing indicates a germline frameshift in and a few somatic mutations of unknown significance. Transcriptomic analysis suggests an enteroendocrine L cell in the tailgut as a putative cell of origin. Genomic profiling of a rare NET and metastasis provides insight into its origin, development, and potential therapeutic options.
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http://dx.doi.org/10.1101/mcs.a003004DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6169824PMC
October 2018

Combination Approach for Detecting Different Types of Alterations in Circulating Tumor DNA in Leiomyosarcoma.

Clin Cancer Res 2018 06 20;24(11):2688-2699. Epub 2018 Feb 20.

Department of Pathology, Stanford University School of Medicine, Stanford, California.

The clinical utility of circulating tumor DNA (ctDNA) monitoring has been shown in tumors that harbor highly recurrent mutations. Leiomyosarcoma represents a type of tumor with a wide spectrum of heterogeneous genomic abnormalities; thus, targeting hotspot mutations or a narrow genomic region for ctDNA detection may not be practical. Here, we demonstrate a combinatorial approach that integrates different sequencing protocols for the orthogonal detection of single-nucleotide variants (SNV), small indels, and copy-number alterations (CNA) in ctDNA. We employed Cancer Personalized Profiling by deep Sequencing (CAPP-Seq) for the analysis of SNVs and indels, together with a genome-wide interrogation of CNAs by Genome Representation Profiling (GRP). We profiled 28 longitudinal plasma samples and 25 tumor specimens from 7 patients with leiomyosarcoma. We detected ctDNA in 6 of 7 of these patients with >98% specificity for mutant allele fractions down to a level of 0.01%. We show that results from CAPP-Seq and GRP are highly concordant, and the combination of these methods allows for more comprehensive monitoring of ctDNA by profiling a wide spectrum of tumor-specific markers. By analyzing multiple tumor specimens in individual patients obtained from different sites and at different times during treatment, we observed clonal evolution of these tumors that was reflected by ctDNA profiles. Our strategy allows for the comprehensive monitoring of a broad spectrum of tumor-specific markers in plasma. Our approach may be clinically useful not only in leiomyosarcoma but also in other tumor types that lack recurrent genomic alterations. .
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http://dx.doi.org/10.1158/1078-0432.CCR-17-3704DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5984700PMC
June 2018

Profiling Tumor Infiltrating Immune Cells with CIBERSORT.

Methods Mol Biol 2018 ;1711:243-259

Division of Oncology, Department of Medicine, Stanford Cancer Institute, Stanford University, 875 Blake Wilbur Drive, Stanford, CA, 94305, USA.

Tumor infiltrating leukocytes (TILs) are an integral component of the tumor microenvironment and have been found to correlate with prognosis and response to therapy. Methods to enumerate immune subsets such as immunohistochemistry or flow cytometry suffer from limitations in phenotypic markers and can be challenging to practically implement and standardize. An alternative approach is to acquire aggregative high dimensional data from cellular mixtures and to subsequently infer the cellular components computationally. We recently described CIBERSORT, a versatile computational method for quantifying cell fractions from bulk tissue gene expression profiles (GEPs). Combining support vector regression with prior knowledge of expression profiles from purified leukocyte subsets, CIBERSORT can accurately estimate the immune composition of a tumor biopsy. In this chapter, we provide a primer on the CIBERSORT method and illustrate its use for characterizing TILs in tumor samples profiled by microarray or RNA-Seq.
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http://dx.doi.org/10.1007/978-1-4939-7493-1_12DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895181PMC
October 2018

KLHL6 Is Preferentially Expressed in Germinal Center-Derived B-Cell Lymphomas.

Am J Clin Pathol 2017 Nov;148(6):465-476

Department of Pathology.

Objectives: KLHL6 is a recently described BTB-Kelch protein with selective expression in lymphoid tissues and is most strongly expressed in germinal center B cells.

Methods: Using gene expression profiling as well as immunohistochemistry with an anti-KLHL6 monoclonal antibody, we have characterized the expression of this molecule in normal and neoplastic tissues. Protein expression was evaluated in 1,058 hematopoietic neoplasms.

Results: Consistent with its discovery as a germinal center marker, KLHL6 was positive mainly in B-cell neoplasms of germinal center derivation, including 95% of follicular lymphomas (106/112). B-cell lymphomas of non-germinal center derivation were generally negative (0/33 chronic lymphocytic leukemias/small lymphocytic lymphomas, 3/49 marginal zone lymphomas, and 2/66 mantle cell lymphomas).

Conclusions: In addition to other germinal center markers, including BCL6, CD10, HGAL, and LMO2, KLHL6 immunohistochemistry may prove a useful adjunct in the diagnosis and future classification of B-cell lymphomas.
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http://dx.doi.org/10.1093/ajcp/aqx099DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6279122PMC
November 2017

Early Detection of Molecular Residual Disease in Localized Lung Cancer by Circulating Tumor DNA Profiling.

Cancer Discov 2017 12 24;7(12):1394-1403. Epub 2017 Sep 24.

Department of Radiation Oncology, Stanford University, Stanford, California.

Identifying molecular residual disease (MRD) after treatment of localized lung cancer could facilitate early intervention and personalization of adjuvant therapies. Here, we apply cancer personalized profiling by deep sequencing (CAPP-seq) circulating tumor DNA (ctDNA) analysis to 255 samples from 40 patients treated with curative intent for stage I-III lung cancer and 54 healthy adults. In 94% of evaluable patients experiencing recurrence, ctDNA was detectable in the first posttreatment blood sample, indicating reliable identification of MRD. Posttreatment ctDNA detection preceded radiographic progression in 72% of patients by a median of 5.2 months, and 53% of patients harbored ctDNA mutation profiles associated with favorable responses to tyrosine kinase inhibitors or immune checkpoint blockade. Collectively, these results indicate that ctDNA MRD in patients with lung cancer can be accurately detected using CAPP-seq and may allow personalized adjuvant treatment while disease burden is lowest. This study shows that ctDNA analysis can robustly identify posttreatment MRD in patients with localized lung cancer, identifying residual/recurrent disease earlier than standard-of-care radiologic imaging, and thus could facilitate personalized adjuvant treatment at early time points when disease burden is lowest. .
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http://dx.doi.org/10.1158/2159-8290.CD-17-0716DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5895851PMC
December 2017

Data normalization considerations for digital tumor dissection.

Genome Biol 2017 07 5;18(1):128. Epub 2017 Jul 5.

Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Stanford, California, 94305, USA.

In a recently published article in Genome Biology, Li and colleagues introduced TIMER, a gene expression deconvolution approach for studying tumor-infiltrating leukocytes (TILs) in 23 cancer types profiled by The Cancer Genome Atlas. Methods to characterize TIL biology are increasingly important, and the authors offer several arguments in favor of their strategy. Several of these claims warrant further discussion and highlight the critical importance of data normalization in gene expression deconvolution applications.Please see related Li et al correspondence: www.dx.doi.org/10.1186/s13059-017-1256-5 and Zheng correspondence: www.dx.doi.org/10.1186/s13059-017-1258-3.
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http://dx.doi.org/10.1186/s13059-017-1257-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5498978PMC
July 2017

High-throughput sequencing for noninvasive disease detection in hematologic malignancies.

Blood 2017 07 9;130(4):440-452. Epub 2017 Jun 9.

Division of Oncology and.

Noninvasive monitoring of minimal residual disease (MRD) has led to significant advances in personalized management of patients with hematologic malignancies. Improved therapeutic options and prolonged survival have further increased the need for sensitive tumor assessment that can inform treatment decisions and patient outcomes. At diagnosis or relapse of most hematologic neoplasms, malignant cells are often easily accessible in the blood as circulating tumor cells (CTCs), making them ideal targets to noninvasively profile the molecular features of each patient. In other cancer types, CTCs are generally rare and noninvasive molecular detection relies on circulating tumor DNA (ctDNA) shed from tumor deposits into circulation. The ability to precisely detect and quantify CTCs and ctDNA could minimize invasive procedures and improve prediction of clinical outcomes. Technical advances in MRD detection methods in recent years have led to reduced costs and increased sensitivity, specificity, and applicability. Among currently available tests, high-throughput sequencing (HTS)-based approaches are increasingly attractive for noninvasive molecular testing. HTS-based methods can simultaneously identify multiple genetic markers with high sensitivity and specificity without individual optimization. In this review, we present an overview of techniques used for noninvasive molecular disease detection in selected myeloid and lymphoid neoplasms, with a focus on the current and future role of HTS-based assays.
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http://dx.doi.org/10.1182/blood-2017-03-735639DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5881609PMC
July 2017

Antigen presentation profiling reveals recognition of lymphoma immunoglobulin neoantigens.

Nature 2017 03 22;543(7647):723-727. Epub 2017 Mar 22.

Department of Medicine, Division of Oncology, Stanford University, Stanford, California 94305, USA.

Cancer somatic mutations can generate neoantigens that distinguish malignant from normal cells. However, the personalized identification and validation of neoantigens remains a major challenge. Here we discover neoantigens in human mantle-cell lymphomas by using an integrated genomic and proteomic strategy that interrogates tumour antigen peptides presented by major histocompatibility complex (MHC) class I and class II molecules. We applied this approach to systematically characterize MHC ligands from 17 patients. Remarkably, all discovered neoantigenic peptides were exclusively derived from the lymphoma immunoglobulin heavy- or light-chain variable regions. Although we identified MHC presentation of private polymorphic germline alleles, no mutated peptides were recovered from non-immunoglobulin somatically mutated genes. Somatic mutations within the immunoglobulin variable region were almost exclusively presented by MHC class II. We isolated circulating CD4 T cells specific for immunoglobulin-derived neoantigens and found these cells could mediate killing of autologous lymphoma cells. These results demonstrate that an integrative approach combining MHC isolation, peptide identification, and exome sequencing is an effective platform to uncover tumour neoantigens. Application of this strategy to human lymphoma implicates immunoglobulin neoantigens as targets for lymphoma immunotherapy.
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http://dx.doi.org/10.1038/nature21433DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5808925PMC
March 2017