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Immune checkpoint blockade (ICB) has shown immense promise for treating patients with various cancer types, but its effectiveness relies on our ability to identify likely responders. Here, we examined the association between mutations in 25 core DNA repair genes and ICB outcomes in 6619 patients across 9 cancer types with advanced disease and MSK-IMPACT tumor sequencing. Notably, we observed that mutations in 7 of the DNA repair genes (ATM, ATR, POLE, ERCC4, NBN, RAD50, PARP1) were significantly associated with improved overall survival in ICB-treated patients (p0.05 for all) and had significant interaction with treatment (p

Purpose:Perineural invasion (PNI) is associated with aggressive tumor behavior, recurrence, and metastasis, and can influence the administration of adjuvant treatment. However, standard histopathologic examination has limited sensitivity in detecting PNI and does not provide insights into its mechanistic underpinnings.Experimental Design:A multivariate Cox regression was performed to validate associations between PNI and survival in 2,029 patients across 12 cancer types. Differential expression and gene set enrichment analysis were used to learn PNI-associated programs. Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E) slides by a board-certified pathologist helped determine whether the classifier could improve occult histopathologic detection of PNI.Results:PNI associated with both poor overall survival [HR, 1.73; 95% confidence interval (CI), 1.27–2.36; P < 0.001] and disease-free survival (HR, 1.79; 95% CI, 1.38–2.32; P < 0.001). Neural-like, prosurvival, and invasive programs were enriched in PNI-positive tumors (Padj < 0.001). Although PNI-associated features likely reflect in part the increased presence of nerves, many differentially expressed genes mapped specifically to malignant cells from single-cell atlases. A PNI gene expression classifier was derived using random forest and evaluated as a tool for occult histopathologic detection. On a blinded H&E re-review of sections initially described as PNI negative, more specimens were reannotated as PNI positive in the high classifier score cohort compared with the low-scoring cohort (P = 0.03, Fisher exact test).Conclusions:This study provides salient biological insights regarding PNI and demonstrates a role for gene expression classifiers to augment detection of histopathologic features.

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Pancreatic ductal adenocarcinoma (PDAC) is projected to be the second leading cause of cancer mortality in the United States by 2030. Given that resistance to cytotoxic therapy is pervasive, there is a critical need to elucidate salient gene expression programs and spatial relationships among malignant and stromal cells in the tumor microenvironment (TME), particularly in residual disease. We developed and applied a single-nucleus RNA-seq (snRNA-seq) technique to 43 banked frozen primary PDAC specimens that either received neoadjuvant therapy (n=25) or were treatment-naïve (n=18). We discovered expression programs across malignant cell and fibroblast profiles that formed the basis for a refined molecular taxonomy, including a novel neural-like progenitor (NRP) malignant program enriched with neoadjuvant treatment in tumors and organoids, and associated with the worst prognosis in bulk profiles from independent cohorts. To elucidate how neoadjuvant treatment and cancer cell- and fibroblast-intrinsic programs modulate the composition of multicellular neighborhoods, we performed spatial profiling with the GeoMx[1] platform (NanoString) on 21 formalin-fixed paraffin-embedded sections using the human whole transcriptome atlas (WTA). Each tumor showed intra-tumoral heterogeneity in tissue architecture and regions of interest (ROIs) with diverse patterns of neoplastic cells, cancer-associated fibroblasts (CAFs), and immune cells were selected for profiling. We deconvolved the WTA data with our snRNA-seq cell type signatures and mapped expression programs onto the tumor architecture to reveal three distinct multicellular neighborhoods, which we annotated as classical, squamoid-basaloid, and treatment-enriched. The observed enrichment in post-treatment residual disease of multiple spatially-defined receptor-ligand interactions and a neighborhood featuring the NRP program, neurotropic CAF program, and CD8+ T cells may open new therapeutic opportunities. Next, we mapped malignant/CAF programs and immune cell subsets at single-cell spatial resolution by performing spatial molecular imaging (SMI[2]; NanoString CosMx) using a panel of 960 RNA targets on a subset of seven tumors (2 untreated, 5 treated) and captured over 200,000 cells with an average of more than 450 transcripts detected per cell. Correlating ROIs from whole-transcriptome DSP to matched fields of view in kiloplex SMI enabled further dissection of PDAC architecture and treatment-associated remodeling of cell type distributions and receptor-ligand interactions. Ongoing functional studies have begun to elucidate the key regulatory elements underlying the distinct treatment-associated NRP malignant program and its interactions with the TME. Overall, the complementary combination of snRNA-seq, whole-transcriptome DSP, and kiloplex SMI provides a high-resolution molecular framework that can be harnessed to augment precision oncology efforts in pancreatic cancer. [1] GeoMx DSP is for Research Use Only and not for use in diagnostic procedures. [2] CosMx SMI is for Research Use Only and not for use in diagnostic procedures. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Carina Shiau, Jennifer Su, Payman Yadollahpour, Jason W. Reeves, Youngmi Kim, Sean Kim, Mark Gregory, Prajan Divakar, Eric Miller, Michael Rhodes, Sarah Warren, Erroll Rueckert, Kit Fuhrman, Daniel R. Zollinger, Robin Fropf, Joseph M. Beechem, Arnav Mehta, Toni Delorey, Cristin McCabe, Jaimie L. Barth, Piotr Zelga, Cristina R. Ferrone, Motaz Qadan, Keith D. Lillemoe, Rakesh K. Jain, Jennifer Y. Wo, Theodore S. Hong, Ramnik Xavier, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Carlos Fernandez-Del Castillo, Andrew S. Liss, Mari Mino-Kenudson, David T. Ting, Tyler Jacks, Aviv Regev. Multicellular spatial community featuring a novel neuronal-like malignant phenotype is enriched in pancreatic cancer after neoadjuvant chemotherapy and radiotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr SY12-04.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal and treatment-refractory cancer. Molecular stratification in pancreatic cancer remains rudimentary and does not yet inform clinical management or therapeutic development. Here, we construct a high-resolution molecular landscape of the cellular subtypes and spatial communities that compose PDAC using single-nucleus RNA sequencing and whole-transcriptome digital spatial profiling (DSP) of 43 primary PDAC tumor specimens that either received neoadjuvant therapy or were treatment naive. We uncovered recurrent expression programs across malignant cells and fibroblasts, including a newly identified neural-like progenitor malignant cell program that was enriched after chemotherapy and radiotherapy and associated with poor prognosis in independent cohorts. Integrating spatial and cellular profiles revealed three multicellular communities with distinct contributions from malignant, fibroblast and immune subtypes: classical, squamoid-basaloid and treatment enriched. Our refined molecular and cellular taxonomy can provide a framework for stratification in clinical trials and serve as a roadmap for therapeutic targeting of specific cellular phenotypes and multicellular interactions.

Genomic alterations are highly frequent across cancers, but their prognostic impact is not well characterized in pan-cancer cohorts. Here, we use pan-cancer cohorts from TCGA and MSK-IMPACT to evaluate the associations of common genomic alterations with poor clinical outcome.Genomic alterations in commonly altered genes were extracted from Pan-Cancer TCGA and MSK-IMPACT cohorts. Multivariable Cox regression analyses stratified by cancer type defined adjusted hazard ratios (AHRs) for disease-specific survival (DSS), progression-free survival (PFS) and overall survival (OS).Using TCGA we identified 32 mutated genes, and 15 copy number (CN) genes with frequency= 4% in 9,104 patients across 28 cancers. On UVA, having a TP53-mutations or any mutation in the 31 genes (mut31) were associated with worse PFS (HR: 1.22,TP53-mutations, CDKN2A-deletion, PTEN-deletion, and MYC-amplification are independent pan-cancer prognostic genomic alterations.

Pancreatic cancer is a challenging disease which lacks a robust precision oncology framework. Prior work has demonstrated that transcriptional subtypes in pancreatic cancer can stratify patients by response to chemotherapy and overall survival. These include classical and basal-like as the predominant subtypes in untreated disease, as well as a transdifferentiated neural-like malignant subtype enriched after standard-of-care chemotherapy. Nonetheless, our understanding of transcriptional subtypes remains critically limited by genetic and culture-based confounders in preclinical models. Furthermore, most murine pancreatic cancer models do not fully reflect the classical vs. basal-like divide observed in humans, preventing faithful in vivo investigation. Collectively, these challenges have hindered the study of and development of therapeutic strategies against these transcriptional subtypes. To enable systematic study of the classical, basal-like and neural-like subtypes, we developed isogenic KP (KrasG12D/+;Trp53FL/FL) organoids and leveraged CRISPR activation to endogenously overexpress state-specific transcription factors. Our data revealed that Gata6 and dNTrp63 drove classical and basal-like identity, respectively, supporting prior studies. Furthermore, through in silico approaches, we identified candidate drivers of the neural-like state, including Glis3, a zinc finger protein that mediates neuroendocrine fate during pancreatic development. We confirmed that Glis3 overexpression results in neural-like transdifferentiation in cancerous organoids through RNA-seq and proteomics, and that GLIS3 knockout abrogates neural-like identity in human cell lines. To study their malignant potential in vivo, we performed orthotopic transplants into murine pancreata, and observed that Glis3 and dNTrp63 accelerated tumor formation and progression, corresponding to clinical outcomes observed in patients. These models may therefore provide a means for in vivo interrogation of subtype biology and vulnerabilities. Finally, to model and predict therapeutic sensitivities, we performed ex vivo treatment assays with chemotherapy and emerging KRASG12D inhibitors. A selection assay showed that basal-like and neural-like organoids were starkly enriched by multi-agent chemotherapy, while classical organoids were depleted. Finally, we learned that the neural-like subtype exhibits differential sensitivity to KRASG12D inhibition through an RTK-associated mechanism. Taken together, we provide a foundational system for interrogating subtype-specific vulnerabilities in pancreatic cancer. Citation Format: Jimmy A. Guo, Jennifer Su, Carina Shiau, Ananya Jambhale, Annan Yang, Westley Wu, Junning Wang, Connor Hennessey, Patrick Yu, Brendan Parent, Giselle Uribe, Julien Dilly, Laleh Abbassi, Qijia Yu, Arnav Mehta, David Ting, Brian Wolpin, William Freed-Pastor, Joseph Mancias, Tyler Jacks, William L. Hwang, Andrew J. Aguirre. GLIS3 drives a neural-like malignant state enriched after neoadjuvant treatment in pancreatic cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5775.

Pancreatic ductal adenocarcinoma (PDAC) features abundant perineural invasion (PNI). Intra-tumoral nerves play critical roles in cancer initiation, progression, recurrence, treatment-resistance, metastasis, and mortality for many malignancies but the diverse molecular mechanisms underlying tumor-nerve crosstalk remain largely unknown—hindering the development of therapies targeting this key pathological process. To address this gap, we performed whole transcriptome digital spatial profiling on twelve custom tissue microarrays (n=288 cores) derived from intratumorally-matched regions with and without PNI in primary PDAC specimens (n=31 patients) and independently measured gene expression from cancer cells, fibroblasts, and nerves. We undertook a differential gene expression analysis comparing malignant cells in PNI-present and -absent regions. We quantified the growth kinetics of dorsal root ganglia (DRG) sensory neurons cultured with exogenous candidate proteins, which validated that some candidates augment (e.g., Lgals1) and others inhibit (e.g., Sema3b) neurite outgrowth. Next, we mapped our previously discovered malignant cell programs onto the epithelial segments and observed a significant enrichment of the mesenchymal, basal-like, and neural-like progenitor (NRP) programs versus depletion of the classical program in PNI-present regions. To determine the effects of malignant subtype on nerve outgrowth, we engineered isogenic KrasG12D/+;Trp53FL/FL;Rosa26-dCas9-VPR (KP;dCas9-VPR) organoids to overexpress the master transcription factors (TFs) for each malignant subtype (e.g., Gata6 for classical, Glis3 for NRP). We then performed the DRG neuronal outgrowth assay using conditioned media from each subtype-specific organoid line versus an off-target control and observed that the classical line suppressed neurite outgrowth, the mesenchymal and basal-like lines were neutral, and the NRP line enhanced neurite outgrowth dynamics comparable to the Ngf positive control. Taken together, our findings suggest that the mechanisms underlying nerve recruitment/outgrowth and perineural invasion may be partly decoupled. To further test this hypothesis, we are performing transwell invasion assays comparing KP;dCas9-VPR cancer cell lines that overexpress each of the candidate PNI-associated genes and malignant subtype TFs. We anticipate that this study will transform our understanding of how cancer cells and the peripheral nervous system collaborate and guide prioritization for therapeutic intervention in the burgeoning cancer neuroscience field. Citation Format: William L. Hwang, Jennifer Su, Carina Shiau, Peter L. Wang, Jimmy A. Guo, Nicole A. Lester, Jaimie L. Barth, Hannah I. Hoffman, Prajan Divakar, Jason W. Reeves, Eric Miller, Joseph M. Beechem, Andrew J. Aguirre, Lei Zheng, David T. Ting, Mari Mino-Kenudson, Tyler Jacks. Distinct cancer-intrinsic mechanisms mediate nerve recruitment/outgrowth versus perineural invasion [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2513.

With increasing attention on the essential roles of the tumour microenvironment in recent years, the nervous system has emerged as a novel and crucial facilitator of cancer growth. In this Review, we describe the foundational, translational, and clinical advances illustrating how nerves contribute to tumour proliferation, stress adaptation, immunomodulation, metastasis, electrical hyperactivity and seizures, and neuropathic pain. Collectively, this expanding knowledge base reveals multiple therapeutic avenues for cancer neuroscience that warrant further exploration in clinical studies. We discuss the available clinical data, including ongoing trials investigating novel agents targeting the tumour-nerve axis, and the therapeutic potential for repurposing existing neuroactive drugs as an anti-cancer approach, particularly in combination with established treatment regimens. Lastly, we discuss the clinical challenges of these treatment strategies and highlight unanswered questions and future directions in the burgeoning field of cancer neuroscience.

While restriction enzymes (REs) remain the gold-standard for manipulating DNA in vitro, they have notable drawbacks including a dependence on short binding motifs that constrain their ability to cleave DNA substrates. Here we overcome limitations of REs by developing an optimized molecular workflow that leverages the PAMless nature of a CRISPR-Cas enzyme named SpRY to cleave DNA at practically any sequence. Using SpRY for DNA digests (SpRYgests), we establish a method that permits the efficient cleavage of DNA substrates at any base pair. We demonstrate the effectiveness of SpRYgests using more than 130 gRNAs, illustrating the versatility of this approach to improve the precision of and simplify several cloning workflows, including those not possible with REs. We also optimize a rapid and simple one-pot gRNA synthesis protocol, which reduces cost and makes the overall SpRYgest workflow comparable to that of RE digests. Together, SpRYgests are straightforward to implement and can be utilized to improve a variety of DNA engineering applications.

Methods for in vitro DNA cleavage and molecular cloning remain unable to precisely cleave DNA directly adjacent to bases of interest. Restriction enzymes (REs) must bind specific motifs, whereas wild-type CRISPR-Cas9 or CRISPR-Cas12 nucleases require protospacer adjacent motifs (PAMs). Here we explore the utility of our previously reported near-PAMless SpCas9 variant, named SpRY, to serve as a universal DNA cleavage tool for various cloning applications. By performing SpRY DNA digests (SpRYgests) using more than 130 guide RNAs (gRNAs) sampling a wide diversity of PAMs, we discovered that SpRY is PAMless in vitro and can cleave DNA at practically any sequence, including sites refractory to cleavage with wild-type SpCas9. We illustrate the versatility and effectiveness of SpRYgests to improve the precision of several cloning workflows, including those not possible with REs or canonical CRISPR nucleases. We also optimize a rapid and simple one-pot gRNA synthesis protocol to streamline SpRYgest implementation. Together, SpRYgests can improve various DNA engineering applications that benefit from precise DNA breaks.

Intratumoral nerves play important and versatile roles in cancer initiation, progression, recurrence, treatment-resistance, metastasis, morbidity, and mortality for many malignancies but the diverse molecular mechanisms underlying tumor-nerve crosstalk remain largely unknown. One of the differentiating hallmarks of pancreatic ductal adenocarcinoma (PDAC) is an exceptionally high frequency of perineural invasion (PNI), a histopathologic manifestation of tumor-nerve crosstalk whereby cancer cells recruit, migrate towards, and envelop or invade peripheral nerves. Evidence for some neurochemicals/neurotrophins involved in PNI have been uncovered, but most of the underlying work was limited by a lack of cell-type specificity, spatial context, and fragmented focus on individual pathways. To address these shortcomings, we set out to comprehensively identify cell-type specific genes spatially linked to PNI in patient tumors and then dissect the functional roles of these genes through live imaging of dorsal root ganglia (DRG) sensory neurons incubated in conditioned media from cancer cell organoids overexpressing candidate genes via CRISPR activation (CRISPRa). First, we performed whole transcriptome digital spatial profiling (NanoString GeoMx) on twelve custom tissue microarrays (n=288 cores) derived from intratumorally-matched malignant regions with and without PNI in primary resected PDAC specimens (n=31 patients). Differential gene expression (DE) analysis (FDR < 0.001) for PNI demonstrated that for malignant cells there were 271 enriched and 65 depleted genes, and for fibroblasts there were 16 enriched and 27 depleted genes. We further evaluated associations between PNI and expression of malignant subtypes previously identified from single-nucleus RNA-seq applied to 43 primary resected PDAC specimens. We found that malignant cells engaged in PNI were enriched in the mesenchymal, basaloid and neural-like progenitor (NRP) subtypes and depleted in the classical subtype. To test these associations functionally, we generated isogenic murine organoid lines (KrasG12D/+;Trp53FL/FL;R26-dCas9-VPR) overexpressing subtype-driving transcription factors and collected conditioned media. DRG sensory neurons demonstrate enhanced and suppressed growth kinetics when grown in NRP and classical conditioned media, respectively; mesenchymal and basal-like conditioned media do not appear to influence growth kinetics. These results suggest that while mesenchymal, basaloid, and NRP cells likely all play a role in cancer cell invasion of nerves, NRP cells may have an additional role in tumor-nerve tropism. Additional experiments exploring the functional effects of the top enriched and depleted genes from the DE analysis are ongoing. We anticipate that this study will provide a high-resolution understanding of critical intercellular interactions in the PDAC tumor microenvironment that facilitate PNI and tumor-nerve crosstalk more broadly to guide novel therapeutic strategies. Citation Format: William L. Hwang, Jennifer Su, Jimmy A. Guo, Carina Shiau, Jaimie L. Barth, Hannah I. Hoffman, Prajan Divakar, Jason W. Reeves, Eric Miller, Grissel Cervantes-Jaramillo, William Freed-Pastor, Vanessa Funes, Jennifer Y. Wo, Theodore S. Hong, Carlos Fernandez-del Castillo, Lei Zheng, Andrew J. Aguirre, David T. Ting, Mari Mino-Kenudson, Tyler Jacks. Identifying mediators of perineural invasion in pancreatic cancer using spatial transcriptomics [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr C052.

Transcriptional states in pancreatic cancer can stratify patients by response to chemotherapy and clinical outcomes. These include the classical and basal-like states as well as a newly identified neural-like progenitor (NRP) state, which we have previously found to be enriched in primary patient tumors treated with neoadjuvant chemotherapy and radiotherapy. While several transcription factor drivers of classical and basal-like identity have been described, key regulators of the NRP state are unknown. Through in silico approaches, we identified candidate transcription factors of the NRP state, including GLIS3, a Krüppel-like zinc finger protein that mediates neuroendocrine fate during pancreatic development and differentiation of human embryonic stem cells into posterior neural progenitor cells. Our understanding of biologic and clinically-relevant attributes of transcriptional cell states remains limited by state-specific biases in various preclinical models. Existing human cell lines maintained as two-dimensional cultures tend to preferentially represent the basal-like state, whereas human three-dimensional organoid models grown in standard culture conditions best reflect the classical state. These phenotypes are therefore impacted by culture conditions as well as underlying genetic features. Furthermore, most murine pancreatic cancer models do not fully reflect the classical vs. basal-like state heterogeneity observed in humans. To enable systematic study of the classical, basal-like and NRP phenotypes, we developed isogenic KP (KrasG12D/+;Trp53FL/FL) murine organoids with a germline dCas9-VPR system to enable facile overexpression of state-specific transcription factors through CRISPR activation approaches. Quantitative PCR, RNA-sequencing, and proteomics confirmed Gata6, deltaN Trp63, and Glis3 as drivers of classical, basal-like, and NRP identity, respectively. DeltaN Trp63 organoids were further differentiated by loss of luminal morphology. Pairwise comparisons of global transcriptional alterations suggest the greatest similarities between the Gata6- and Glis3-overexpressed models, which is consistent with enhanced associations between classical and NRP states in patient tumors. Finally, although basal-like and NRP states are associated with poorer response to multi-agent chemotherapy, state-specific therapeutic sensitivities to other treatments remain incompletely defined. We therefore performed drug sensitivity assays with a panel of targeted therapies and unveiled state-specific sensitivities. These data were corroborated by drug sensitivity profiling of human patient-derived organoids and cell lines. Taken together, these results suggest a framework for defining cell state-specific vulnerabilities that may aid in stratifying and treating pancreatic cancer patients with new therapies. Citation Format: Jimmy A. Guo, Jennifer Su, Ananya Jambhale, Julien Dilly, Connor J. Hennessey, Carina Shiau, Patrick Yu, Steven Wang, Junning Wang, Laleh Abbassi, James Neiswender, Tate Bertea, Annan Yang, Qijia Yu, Peter Westcott, Jason Schenkel, Daniel Y. Kim, Hannah I. Hoffman, Grissel Cervantes Jaramillo, Giselle A. Uribe, Westley W. Wu, Arnav Mehta, David Ting, Julian A. Pacheco, Amy Deik, Clary Clish, Francisca Vazquez, Brian Wolpin, Aviv Regev, William A. Freed-Pastor, Joseph D. Mancias, Tyler Jacks, William L. Hwang, Andrew J. Aguirre. Systematic dissection of transcriptional states in pancreatic cancer [abstract]. In: Proceedings of the AACR Special Conference on Pancreatic Cancer; 2022 Sep 13-16; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2022;82(22 Suppl):Abstract nr A052.

CRISPR-Cas9 nuclease-based gene drives have been developed toward the aim of control of the human malaria vector Anopheles gambiae . Gene drives are based on an active source of Cas9 nuclease in the germline that promotes super-Mendelian inheritance of the transgene by homology-directed repair (“homing”). Understanding whether CRISPR-induced off-target mutations are generated in Anopheles mosquitoes is an important aspect of risk assessment before any potential field release of this technology. We compared the frequencies and the propensity of off-target events to occur in four different gene-drive strains, including a deliberately promiscuous set-up, using a nongermline restricted promoter for SpCas9 and a guide RNA with many closely related sites (two or more mismatches) across the mosquito genome. Under this scenario we observed off-target mutations at frequencies no greater than 1.42%. We witnessed no evidence that CRISPR-induced off-target mutations were able to accumulate (or drive) in a mosquito population, despite multiple generations’ exposure to the CRISPR-Cas9 nuclease construct. Furthermore, judicious design of the guide RNA used for homing of the CRISPR construct, combined with tight temporal constriction of Cas9 expression to the germline, rendered off-target mutations undetectable. The findings of this study represent an important milestone for the understanding and managing of CRISPR-Cas9 specificity in mosquitoes, and demonstrates that CRISPR off-target editing in the context of a mosquito gene drive can be reduced to minimal levels.

Prognostication for patients with cancer is important for clinical planning and management, but remains challenging given the large number of factors that can influence outcomes. As such, there is a need to identify features that can robustly predict patient outcomes. We evaluated 8608 patient tumor samples across 16 cancer types from The Cancer Genome Atlas and generated distinct survival classifiers for each using clinical and histopathological data accessible to standard oncology workflows. For cancers that had poor model performance, we deployed a random-forest-embedded sequential forward selection approach that began with an initial subset of the 15 most predictive clinicopathological features before sequentially appending the next most informative gene as an additional feature. With classifiers derived from clinical and histopathological features alone, we observed cancer-type-dependent model performance and an area under the receiver operating curve (AUROC) range of 0.65 to 0.91 across all 16 cancer types for 1- and 3-year survival prediction, with some classifiers consistently outperforming those for others. As such, for cancers that had poor model performance, we posited that the addition of more complex biomolecular features could enhance our ability to prognose patients where clinicopathological features were insufficient. With the inclusion of gene expression data, model performance for 3 select cancers (glioblastoma, stomach/gastric adenocarcinoma, ovarian serous carcinoma) markedly increased from initial AUROC scores of 0.66, 0.69, and 0.67 to 0.76, 0.77, and 0.77, respectively. As a whole, this study provides a thorough examination of the relative contributions of clinical, pathological, and gene expression data in predicting overall survival and reveals cancer types for which clinical features are already strong predictors and those where additional biomolecular information is needed.

High tumor mutation burden (TMB) and total mutation count (TMC) can be predictive of better response to immune checkpoint blockade (ICB). Nevertheless, TMB and TMC are limited by variation across cancers and inconsistent definitions due to different profiling methods (targeted vs whole genome sequencing). Our objective was to identify genomic alterations (GAs) associated with ICB response and builds a novel genomic signature predictive of ICB response, independent of TMB/TMC.This was a pan-cancer next generation sequencing (NGS)-association study using January 2014-May 2016 data from AACR Project Genomics Evidence Neo-plasia Information Exchange (GENIE). Participants included 6619 patients with metastatic or un-resectable cancer across 9 cancer types (including 1572 ICB-treated patients). GA data was collected using next-generation sequencing (NGS) assays and downloaded from cbioportal.org. Predictive analyses for ICB response were performed to develop the signature (ImmGA).GAs in 16 genes were associated with improved OS in ICB-treated patients (p 0.005). 13 GAs were associated with an OS benefit in ICB-treated patients (PA novel signature predictive of ICB response (ImmGA) was developed from 13 GAs. Further investigation of the utility of ImmGA for treatment and trial selection is warranted.

Pancreatic ductal adenocarcinoma (PDAC) is a treatment-refractory malignancy in urgent need of a molecular framework for guiding therapeutic strategies. Bulk transcriptomic efforts over the past decade have yielded two broad consensus subtypes: classical pancreatic/epithelial versus basal-like/squamous/quasi-mesenchymal. Although this binary classification enables prognostic stratification, it does not currently inform the administration of treatments uniquely sensitive to either subtype. Furthermore, bulk mRNA studies are challenged by distinguishing contributions from the neoplastic compartment versus other cell types in the microenvironment, which is accentuated in PDAC given that neoplastic cellularity can be low. The application of single-cell transcriptomics to pancreatic tumors has generally lagged behind other cancer types due in part to the difficulty of extracting high-quality RNA from enzymatically degradative tissue, but emerging studies have and will continue to shed light on intratumoral heterogeneity, malignant–stromal interactions, and subtle transcriptional programs previously obscured at the bulk level. In conjunction with insights provided by single-cell/nucleus dissociative techniques, spatially resolved technologies should also facilitate the contextualization of gene programs and inferred cell–cell interactions within the tumor architecture. Finally, given that patients often receive neoadjuvant chemotherapy and/or chemoradiotherapy even in resectable disease, deciphering the gene programs enriched in or induced by cytotoxic therapy will be crucial for developing insights into complementary treatments aimed at eradicating residual cancer cells. Taken together, single-cell and spatial technologies provide an unprecedented opportunity to refine the foundations laid by prior bulk molecular studies and significantly augment precision oncology efforts in pancreatic cancer.

Purpose: Perineural invasion (PNI) is associated with aggressive tumor behavior, recurrence, and metastasis, and can influence the administration of adjuvant treatment. However, standard histopathologic examination has limited sensitivity in detecting PNI and does not provide insights into its mechanistic underpinnings. Experimental Design: A multivariate Cox regression was performed to validate associations between PNI and survival in 2,029 patients across 12 cancer types. Differential expression and gene set enrichment analysis were used to learn PNI-associated programs. Machine learning models were applied to build a PNI gene expression classifier. A blinded re-review of hematoxylin and eosin (H&E) slides by a board-certified pathologist helped determine whether the classifier could improve occult histopathologic detection of PNI. Results: PNI associated with both poor overall survival [HR, 1.73; 95% confidence interval (CI), 1.27–2.36; P < 0.001] and disease-free survival (HR, 1.79; 95% CI, 1.38–2.32; P < 0.001). Neural-like, prosurvival, and invasive programs were enriched in PNI-positive tumors (Padj < 0.001). Although PNI-associated features likely reflect in part the increased presence of nerves, many differentially expressed genes mapped specifically to malignant cells from single-cell atlases. A PNI gene expression classifier was derived using random forest and evaluated as a tool for occult histopathologic detection. On a blinded H&E re-review of sections initially described as PNI negative, more specimens were reannotated as PNI positive in the high classifier score cohort compared with the low-scoring cohort (P = 0.03, Fisher exact test). Conclusions: This study provides salient biological insights regarding PNI and demonstrates a role for gene expression classifiers to augment detection of histopathologic features.

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

CRISPR–Cas genome-editing nucleases hold substantial promise for developing human therapeutic applications1–6 but identifying unwanted off-target mutations is important for clinical translation7. A well-validated method that can reliably identify off-targets in vivo has not been described to date, which means it is currently unclear whether and how frequently these mutations occur. Here we describe ‘verification of in vivo off-targets’ (VIVO), a highly sensitive strategy that can robustly identify the genome-wide off-target effects of CRISPR–Cas nucleases in vivo. We use VIVO and a guide RNA deliberately designed to be promiscuous to show that CRISPR–Cas nucleases can induce substantial off-target mutations in mouse livers in vivo. More importantly, we also use VIVO to show that appropriately designed guide RNAs can direct efficient in vivo editing in mouse livers with no detectable off-target mutations. VIVO provides a general strategy for defining and quantifying the off-target effects of gene-editing nucleases in whole organisms, thereby providing a blueprint to foster the development of therapeutic strategies that use in vivo gene editing. A strategy developed to define off-target effects of gene-editing nucleases in whole organisms is validated and leveraged to show that CRISPR–Cas9 nucleases can be used effectively in vivo without inducing detectable off-target mutations.

Summary CRISPR/Cas9 and Cas12a (Cpf1) nucleases are two of the most powerful genome editing tools in plants. In this work, we compared their activities by targeting maize glossy2 gene coding region that has overlapping sequences recognized by both nucleases. We introduced constructs carrying SpCas9‐guide RNA (gRNA) and LbCas12a‐CRISPR RNA (crRNA) into maize inbred B104 embryos using Agrobacterium‐mediated transformation. On‐target mutation analysis showed that 90%–100% of the Cas9‐edited T0 plants carried indel mutations and 63%–77% of them were homozygous or biallelic mutants. In contrast, 0%–60% of Cas12a‐edited T0 plants had on‐target mutations. We then conducted CIRCLE‐seq analysis to identify genome‐wide potential off‐target sites for Cas9. A total of 18 and 67 potential off‐targets were identified for the two gRNAs, respectively, with an average of five mismatches compared to the target sites. Sequencing analysis of a selected subset of the off‐target sites revealed no detectable level of mutations in the T1 plants, which constitutively express Cas9 nuclease and gRNAs. In conclusion, our results suggest that the CRISPR/Cas9 system used in this study is highly efficient and specific for genome editing in maize, while CRISPR/Cas12a needs further optimization for improved editing efficiency.

Targeted therapies for molecularly-defined subtypes have led to immense clinical benefit for many cancer types but have generally not been successful for pancreatic cancer. Given that the mainstay of treatment remains multi-agent chemotherapy with FOLFIRINOX or gemcitabine/nab-paclitaxel, there remains an urgent need to identify novel actionable vulnerabilities for subsets of PDAC patients. Toward this end, we conducted an integrative, genome-scale examination of genetic dependencies and cell surface targets for PDAC by leveraging CRISPR and RNAi screening data from The Cancer Dependency Map Project, genomic data of bulk patient tumors from The Cancer Genome Atlas, and custom single-nucleus RNA-seq of a 43-patient cohort comprised of untreated and treated specimens. Our results re-affirm the prominence of Ras/MAPK signaling and a synthetically-lethal interaction between VPS4A/B, but also reveal recurrent susceptibilities to genes within the fatty acid metabolism, vesicular transport and exocytosis, and nucleobase synthesis pathways that otherwise have minor to moderate depleting effects on the majority of cell lines. Aberrations in frequent tumor suppressor genes and chromosomal arm-level variations appear to modify the strength of dependencies, including that of KRAS, CCND1, and GPX4, and may serve as predictive biomarkers of response. In addition, we leveraged mRNA profiling of bulk primary tumors as well as metastatic organoid models to conduct a genome-wide search for cell surface targets that are highly-expressed in tumors while lowly or not expressed in other toxicity-prone, non-malignant tissues. These putative drug targets do not need to be cancer dependencies and can be compatible with antibody-based therapeutic strategies that leverage alternative modes of cellular toxicity. Our approach identifies MSLN, NECTIN4, TROP2, and other antigens which have previously been shown to be largely tumor-specific but also reveals the expression of multiple putative targets within the CEACAM, claudin, and tetraspanin families. Finally, molecular subtyping efforts over the past decade have yielded classical and basal-like as consensus subtypes with variations therein, but genetic dependencies and cell surface expression patterns unique to either are insufficiently understood. We identified CLDN18, CEACAM5, and CEACAM6 as cell surface antigens for the classical subtype and MSLN, AQP5, and SLC6A14 for basal-like. Dependency on TLK2 and CCND1 is associated with the basal-like and classical subtype, respectively. Taken together, our integrative genomic approach may provide a precision medicine blueprint for stratifying and targeting pancreatic cancer. Citation Format: Jimmy A. Guo, Daniel Zhao, Scott P. Ginebaugh, Steven Wang, Ananya D. Jambhale, Patrick Z. Yu, Westley W. Wu, Peter Chen, Maryann Zhao, Kristen E. Lowder, Kevin S. Kapner, Hannah I. Hoffman, Stephanie W. Cheng, Daniel Y. Kim, Rebecca Boiarsky, Francois Aguet, Brenton Paolella, John M. Krill-Burger, James M. McFarland, Tobiloba Oni, Tyler Jacks, Aviv Regev, Gad Getz, William L. Hwang, Harshabad Singh, Andrew J. Aguirre. Integrative genomic characterization of therapeutic targets for pancreatic cancer [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2021 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2021;81(22 Suppl):Abstract nr PR-006.

Long noncoding RNAs are thought to regulate gene expression by organizing protein complexes through unclear mechanisms. XIST controls the inactivation of an entire X chromosome in female placental mammals. Here we develop and integrate several orthogonal structure-interaction methods to demonstrate that XIST RNA-protein complex folds into an evolutionarily conserved modular architecture. Chimeric RNAs and clustered protein binding in fRIP and eCLIP experiments align with long-range RNA secondary structure, revealing discrete XIST domains that interact with distinct sets of effector proteins. CRISPR-Cas9-mediated permutation of the Xist A-repeat location shows that A-repeat serves as a nucleation center for multiple Xist-associated proteins and m6A modification. Thus modular architecture plays an essential role, in addition to sequence motifs, in determining the specificity of RBP binding and m6A modification. Together, this work builds a comprehensive structure-function model for the XIST RNA-protein complex, and suggests a general strategy for mechanistic studies of large ribonucleoprotein assemblies., The long noncoding RNA XIST plays a central role in sex-specific gene expression in humans by silencing one of two X chromosomes in female cells. Here the authors show that higher order secondary structure creates the modular domain structure of XIST ribonucleoprotein complex and spatial separation of functions.

A molecular classification of pancreatic ductal adenocarcinoma (PDAC) that informs clinical management remains elusive. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-like, and (2) basal-like. Basal-like tumors were associated with worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for banked frozen PDAC specimens and studied a cohort of untreated resected primary tumors (n ~ 20). Gene expression programs learned across malignant cell and cancer-associated fibroblast (CAF) profiles uncovered a clinically-relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Digital spatial profiling revealed an association between malignant cells expressing basal-like programs and greater immune infiltration with relatively fewer macrophages, whereas those exhibiting classical-like programs were linked to inflammatory CAFs and macrophage-predominant microniches. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment impacts residual tumor cells and their interactions with other cell types in the tumor microenvironment to identify additional therapeutic vulnerabilities that can be exploited. Towards this end, we performed snRNA-seq on an unmatched cohort of neoadjuvant-treated resected primary tumors (n ~ 25) with most cases involving FOLFIRINOX chemotherapy followed by chemoradiation. Remarkably, the quality of single-nucleus mRNA profiles was comparable between heavily pre-treated and untreated specimens. We identified differentially expressed genes between treated and untreated samples to infer cell-type specific reprogramming in the residual tumor. This analysis revealed that in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into compartment-specific therapies. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Payman Yadollahpour, Jason Reeves, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Orr Ashenberg, Clifton Rodrigues, Domenic Abbondanza, Toni Delorey, Devan Phillips, Jorge Roldan, Debora Ciprani, Marina Kern, Jaimie L. Barth, Daniel R. Zollinger, Kit Fuhrman, Robin Fropf, Joseph Beechem, Colin Weekes, Cristina R. Ferrone, Jennifer Y. Wo, Theodore S. Hong, Orit Rozenblatt-Rosen, Andrew J. Aguirre, Mari Mino-Kenudson, Carlos Fernandez-del- Castillo, Andrew S. Liss, David T. Ting, Tyler Jacks, Aviv Regev. Multi-compartment reprogramming and spatially-resolved interactions in frozen pancreatic cancer with and without neoadjuvant chemotherapy and radiotherapy at single-cell resolution [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 94.

Molecular subtyping of pancreatic ductal adenocarcinoma (PDAC) remains in its nascent stages and does not currently inform clinical management or therapeutic development. Previously identified bulk expression subtypes in the untreated setting were influenced by contaminating stroma whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Two consensus subtypes have arisen from these prior efforts: (1) classical-pancreatic, encompassing a spectrum of pancreatic lineage precursors, and (2) basal-like/squamous/quasi-mesenchymal, characterized by loss of endodermal identity and aberrations in chromatin modifiers. Basal-like tumors were associated with poorer responses to chemotherapy and worse survival in the metastatic setting but attempts to refine this binary classification have failed to further stratify patient survival. Recent clinical trials have supported the increasing adoption of neoadjuvant therapy to aggressively address the risk of micro-metastatic spread and to circumvent concerns of treatment tolerance in the postoperative setting. There is an urgent need to understand how preoperative treatment reprograms residual tumor cells to identify additional therapeutic vulnerabilities that can be exploited in combination with neoadjuvant CRT. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors (n = 15) and those that received neoadjuvant CRT (n = 11). Gene expression programs learned across malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification (median survival: 11.2 months in highest risk group to 44.7 months in lowest risk group) compared to prior classifications. Moreover, in the neoadjuvant treatment context, there was lower expression of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. These results suggest that differentiated endodermal phenotypes are only prevalent enough to be detected under treatment selection pressure and when observed in treatment-naïve bulk studies, may reflect normal cell contamination. Spatially-resolved transcriptomics revealed an association between malignant cells expressing basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to distinct therapeutic susceptibilities. Our refined molecular taxonomy and spatial resolution may help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system. Citation Format: William L. Hwang, Karthik A. Jagadeesh, Jimmy A. Guo, Hannah I. Hoffman, Eugene Drokhlyansky, Nicholas Van Wittenberghe, Samouil Farhi, Denis Schapiro, Jason Reeves, Daniel R. Zollinger, George Eng, Jason M. Schenkel, William A. Freed-Pastor, Clifton Rodrigues, Domenic Abbondanza, Debora Ciprani, Jennifer Y. Wo, Theodore S. Hong, Andrew J. Aguirre, Orit Rozenblatt-Rosen, Mari Mino-Kenudson, Carlos Fernandez-del Castillo, Andrew S. Liss, Tyler E. Jacks, Aviv Regev. Single-nucleus and spatial transcriptomics of archival pancreatic ductal adenocarcinoma reveals multi-compartment reprogramming after neoadjuvant treatment [abstract]. In: Proceedings of the AACR Virtual Special Conference on Pancreatic Cancer; 2020 Sep 29-30. Philadelphia (PA): AACR; Cancer Res 2020;80(22 Suppl):Abstract nr PR-007.

3621 Background: Tumor invasion of nerves, blood vessels, and lymphatics are a primary means of local recurrence and escape from the local microenvironment, resulting in metastases and poor clinical outcomes. However, the genetic drivers that are most pertinent to these malignant processes are not well understood, and few therapeutics successfully target perineural invasion (PNI) and lympho-vascular invasion (LVI). Identifying genetic drivers and biomarkers can be valuable for therapeutic targeting and prognostication. Methods: We analyzed surgical pathology reports and bulk RNA-seq data of 1,624 patients across 12 cancer types from The Cancer Genome Atlas (TCGA). Differential gene expression analysis between patients with and without PNI/LVI was performed using DEseq2 in Python while adjusting for age, sex, race, and cancer type. Genes with an adjusted p-value < 0.001 were then used to derive parsimonious signatures using random forest classifier and recursive feature selection algorithms. Results: To assess whether these invasive histological phenotypes have clinical ramifications, we examined outcomes data and found that patients with PNI or LVI have reduced overall (OS) and disease-free survival (DFS) ( p < 0.05) relative to those without. In addition, patients with both PNI and LVI have the lowest DFS from our pan-cancer analysis, suggesting that each may have non-redundant contributions to poor outcomes. From the differential gene expression analysis, we identified a set of 621 and 606 genes that were highly associated with PNI and LVI, respectively (padj < 0.001). Many of these genes such as TEKT5 (padj = 3.18 x 10−64), which is canonically associated with ciliary and flagellar microtubules, and SCRIB (padj = 1.60 x 10−21), which helps establish apico-basal cell polarity, have not been described previously in relevance to PNI and LVI, and warrant further scientific and clinical investigation. These genes were ultimately condensed into a signature that optimizes for both model simplicity and goodness of fit with up to 90% accuracy as determined by trials on both a logistic regression and neural network model. Conclusions: We concluded from a pan-cancer analysis that PNI and LVI are associated with poor outcomes, and we were able to robustly identify sets of genes that characterize each invasive mechanism for further functional investigation.

4633 Background: Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease and existing molecular subtypes do not inform clinical decisions. Previously identified bulk transcriptomic subtypes of PDAC were often unintentionally driven by “contaminating” stroma. RNA extraction from pancreatic tissue is difficult and prior single-cell RNA-seq efforts have been limited by suboptimal dissociation/RNA quality and poor performance in the setting of neoadjuvant treatment. We developed a robust single-nucleus RNA-seq (sNuc-seq) technique compatible with frozen archival PDAC specimens. Methods: Single nuclei suspensions were extracted from frozen primary PDAC specimens (n = 27) derived from patients with (borderline)-resectable PDAC who underwent surgical resection with or without neoadjuvant chemoradiotherapy (CRT). Approximately 170,000 nuclei were processed with the 10x Genomics Single Cell 3’ v3 pipeline and gene expression libraries were sequenced (Illumina HiSeq X). Results: Distinct nuclei clusters with gene expression profiles/inferred copy number variation analysis consistent with neoplastic, acinar, ductal, fibroblast, endothelial, endocrine, lymphocyte, and myeloid populations were identified with proportions similar to corresponding multiplexed ion beam imaging. Non-negative matrix factorization revealed intra-tumoral heterogeneity shared across patients. Neoplastic cells featured eight distinct transcriptional topics characterized by developmental (epithelial, mesenchymal, endoderm progenitor, neural progenitor) and environmental (anabolic, catabolic, cycling, hypoxic) programs. CAFs exhibited four different transcriptional topics (activated/desmoplastic, myofibroblast, neurogenic, osteochondral). Differential gene expression and gene set enrichment analyses demonstrated that CRT was associated with an enrichment in myogenic programs in CAFs, activation pathways in immune cells, and type I/II interferons in malignant cells. CRT was also associated with a depletion in developmental programs within malignant cells. Conclusions: We uncovered significant intratumoral heterogeneity and treatment-associated differences in the malignant, fibroblast, and immune compartments of PDAC using sNuc-seq. Deconvolution of clinically-annotated bulk RNA-seq cohorts and characterization of intercellular interactions with receptor-ligand analysis and spatial transcriptomics are ongoing.

Circularization for in vitro reporting of cleavage effects by sequencing (CIRCLE-seq) is a sensitive and unbiased method for defining the genome-wide activity (on-target and off-target) of CRISPR–Cas9 nucleases by selective sequencing of nuclease-cleaved genomic DNA (gDNA). Here, we describe a detailed experimental and analytical protocol for CIRCLE-seq. The principle of our method is to generate a library of circularized gDNA with minimized numbers of free ends. Highly purified gDNA circles are treated with CRISPR–Cas9 ribonucleoprotein complexes, and nuclease-linearized DNA fragments are then ligated to adapters for high-throughput sequencing. The primary advantages of CIRCLE-seq as compared with other in vitro methods for defining genome-wide genome editing activity are (i) high enrichment for sequencing nuclease-cleaved gDNA/low background, enabling sensitive detection with low sequencing depth requirements; and (ii) the fact that paired-end reads can contain complete information on individual nuclease cleavage sites, enabling use of CIRCLE-seq in species without high-quality reference genomes. The entire protocol can be completed in 2 weeks, including time for gRNA cloning, sequence verification, in vitro transcription, library preparation, and sequencing. This protocol describes CIRCLE-seq (circularization for in vitro reporting of cleavage effects by sequencing), a sensitive and unbiased method for defining the on-target and off-target activity of CRISPR–Cas9 nucleases genome-wide.

Modular domains of long non-coding RNAs can serve as scaffolds to bring distant regions of the linear genome into spatial proximity. Here, we present HiChIRP, a method leveraging bio-orthogonal chemistry and optimized chromosome conformation capture conditions, which enables interrogation of chromatin architecture focused around a specific RNA of interest down to approximately ten copies per cell. HiChIRP of three nuclear RNAs reveals insights into promoter interactions (7SK), telomere biology (telomerase RNA component) and inflammatory gene regulation (lincRNA-EPS). HiChIRP combines a modified chromosome conformation capture protocol with enrichment of RNA-associated chromosome conformation to visualize genome-wide looping linked to an RNA of interest.

Adipose tissue is a rich source of cells with emerging promise for tissue engineering and regenerative medicine. The stromal vascular fraction (SVF), in particular, is an eclectic composite of cells with progenitor activity that includes preadipocytes, mesenchymal stem cells, pericytes, endothelial cells, and macrophages. SVF has enormous potential for therapeutic application and is being investigated for multiple clinical indications including lipotransfer, diabetes-related complications, nerve regeneration, burn wounds and numerous others. In Part 2 of our review, we explore the basic science behind the regenerative success of the SVF and discuss significant mechanisms that are at play. The existing literature suggests that angiogenesis, immunomodulation, differentiation, and extracellular matrix secretion are the main avenues through which regeneration and healing is achieved by the stromal vascular fraction.

Stromal Vascular Fraction (SVF) is a heterogeneous collection of cells contained within adipose tissue that is traditionally isolated using enzymes such as collagenase. With the removal of adipose cells, connective tissue and blood from lipoaspirate, comes the SVF, a mix including mesenchymal stem cells, endothelial precursor cells, T regulatory cells, macrophages, smooth muscle cells, pericytes and preadipocytes. In part 1 of our 2-part series, we review the literature with regards to the intensifying interest that has shifted toward this mixture of cells, particularly due to its component synergy and translational potential. Trials assessing the regenerative potential of cultured Adipose Derived Stem Cells (ADSCs) and SVF demonstrate that SVF is comparably effective in treating conditions ranging from radiation injuries, burn wounds and diabetes, amongst others. Aside from their use in chronic conditions, SVF enrichment of fat grafts has proven a major advance in maintaining fat graft volume and viability. Many SVF studies are currently in preclinical phases or are moving to human trials. Overall, regenerative cell therapy based on SVF is at an early investigative stage but its potential for clinical application is enormous.

Although lipotransfer, or fat grafting, is a commonly used procedure in aesthetic and reconstructive surgery, there is still variability in graft survival and neoadipogenesis from one procedure to the next. A better understanding of the sequential molecular events occurring with grafting would allow us to strategize methods to improve the regenerative potency of the grafted tissue. These steps begin with an autophagic process, followed by the inclusion of stromal vascular fraction and matrix components. By tailoring and modifying each of these steps for a particular type of aesthetic or reconstructive procedure, strategic sequencing represents a dynamic approach to lipotransfer with the aim of maximizing adipocyte viability and growth. In the implementation of the strategic sequence, it remains important to consider the clinical viability of each step and its compliance with the US Food and Drug Administration regulations. This review highlights the basic science behind clinically translatable approaches to supplementing various fat grafting procedures.

CRISPR-Cas genome-editing nucleases hold substantial promise for human therapeutics1–5 but identifying unwanted off-target mutations remains an important requirement for clinical translation6, 7. For ex vivo therapeutic applications, previously published cell-based genome-wide methods provide potentially useful strategies to identify and quantify these off-target mutation sites8–12. However, a well-validated method that can reliably identify off-targets in vivo has not been described to date, leaving the question of whether and how frequently these types of mutations occur. Here we describe Verification of In Vivo Off-targets (VIVO), a highly sensitive, unbiased, and generalizable strategy that we show can robustly identify genome-wide CRISPR-Cas nuclease off-target effects in vivo. To our knowledge, these studies provide the first demonstration that CRISPR-Cas nucleases can induce substantial off-target mutations in vivo, a result we obtained using a deliberately promiscuous guide RNA (gRNA). More importantly, we used VIVO to show that appropriately designed gRNAs can direct efficient in vivo editing without inducing detectable off-target mutations. Our findings provide strong support for and should encourage further development of in vivo genome editing therapeutic strategies.

Tiling screens using CRISPR-Cas technologies provide a powerful approach to map regulatory elements to phenotypes of interest, but computational methods that effectively model these experimental approaches for different CRISPR technologies are not readily available. Here we present CRISPR-SURF, a deconvolution framework to identify functional regulatory regions in the genome from data generated by CRISPR-Cas nuclease, CRISPR interference (CRISPRi), or CRISPR activation (CRISPRa) tiling screens. We validated CRISPR-SURF on previously published and new data, identifying both experimentally validated and new potential regulatory elements. With CRISPR tiling screens now being increasingly used to elucidate the regulatory architecture of the non-coding genome, CRISPRSURF provides a generalizable and accessible solution for the discovery of regulatory elements.