Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 65,428 bioRxiv papers from 289,803 authors.
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in category cancer biology
2,132 results found. For more information, click each entry to expand.
1,229 downloads cancer biology
Matthew A. Reyna, David Haan, Marta Paczkowska, Lieven P.C. Verbeke, Miguel Vazquez, Abdullah Kahraman, Sergio Pulido Tamayo, Jonathan Barenboim, Lina Wadi, Priyanka Dhingra, Raunak Shrestha, Gad Getz, Michael S Lawrence, Jakob Skou Pedersen, Mark A Rubin, David A Wheeler, Søren Brunak, Jose MG Izarzugaza, Ekta Khurana, Kathleen Marchal, Christian von Mering, S. Cenk Sahinalp, Alfonso Valencia, Jüri Reimand, Joshua M Stuart, Ben Raphael, on behalf of the PCAWG Drivers and Functional Interpretation Group and the ICGC/TCGA Pan-Cancer Analysis of Whole Genome Network
The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes, we performed multi-faceted pathway and network analyses of non-coding mutations across 2,583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project. While few non-coding genomic elements were recurrently mutated in this cohort, we identified 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We found that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing was primarily targeted by non-coding mutations in this cohort, with samples containing non-coding mutations exhibiting similar gene expression signatures as coding mutations in well-known RNA splicing factors. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.
1,228 downloads cancer biology
This letter presents the agarose floor technique to obtain single-cell suspensions from oral cancer cells in nonadherent conditions.
1,228 downloads cancer biology
Collin M Blakely, Thomas B.K. Watkins, Wei Wu, Beatrice Gini, Jacob J. Chabon, Caroline E McCoach, Nicholas McGranahan, Gareth A. Wilson, Nicolai J. Birkbak, Victor R Olivas, Julia Rotow, Ashley Maynard, Victoria Wang, Matthew A Gubens, Kimberly C. Banks, Richard B Lanman, Aleah F. Caulin, John St. John, Anibal R. Cordero, Petros Giannikopoulos, Philip C Mack, David R Gandara, Hatim Husain, Robert C. Doebele, Jonathan W. Riess, Maximilian Diehn, Charles Swanton, Trever G. Bivona
The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide8,9, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFRT790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.
1,220 downloads cancer biology
Objective: Cancer stem cells (CSCs) have been hypothesized to initiate and drive tumor growth and recurrence due to their self-renewal ability. If correct, this hypothesis implies that successful therapy must focus primarily on eradication of this CSC fraction. However, recent evidence suggests stemness is niche dependent and may represent one of many phenotypic states that can be accessed by many cancer genotypes when presented with specific environmental cues. A better understanding of the relationship of stemness to niche-related phenotypic plasticity could lead to alternative treatment strategies. Methods: Here we investigate the role of environmental context in the expression of stem-like cell properties through in-silico simulation of ductal carcinoma. We develop a two-dimensional hybrid discrete-continuum cellular automata model to describe the single cell scale dynamics of multi-cellular tissue formation. Through a suite of simulations we investigate interactions between a phenotypically heterogeneous cancer cell population and a dynamic environment. Results: We generate homeostatic ductal structures that consist of a mixture of stem and differentiated cells governed by both intracellular and environmental dynamics. We demonstrate that a wide spectrum of tumor-like histologies can result from these structures by varying microenvironmental parameters. Conclusion: Niche driven phenotypic plasticity offers a simple first-principle explanation for the diverse ductal structures observed in histological sections from breast cancer. Significance: Conventional models of carcinogenesis largely focus on mutational events. We demonstrate that variations in the environmental niche can produce intraductal cancers independent of genetic changes in the resident cells. Therapies targeting the microenvironmental niche, may offer an alternative cancer prevention strategy.
1,219 downloads cancer biology
Lisanne F. van Dessel, Job van Riet, Minke Smits, Yanyun Zhu, Paul Hamberg, Michiel S. van der Heijden, Andries M. Bergman, Inge M. van Oort, Ronald de Wit, Emile E. Voest, Neeltje Steeghs, Takafumi N. Yamaguchi, Julie Livingstone, Paul C. Boutros, John W.M. Martens, Stefan Sleijfer, Edwin Cuppen, Wilbert Zwart, Harmen JG van de Werken, Niven Mehra, Martijn P. Lolkema
Metastatic castration-resistant prostate cancer (mCRPC) has a highly complex genomic landscape. With the recent development of novel treatments, accurate stratification strategies are needed. Here we present the whole-genome sequencing (WGS) analysis of fresh-frozen metastatic biopsies from 197 mCRPC patients. Using unsupervised clustering based on genomic features, we define eight distinct genomic clusters. We observe potentially clinically relevant genotypes, including microsatellite instability (MSI), homologous recombination deficiency (HRD) enriched with genomic deletions and BRCA2 aberrations, a tandem duplication genotype associated with CDK12-/- and a chromothripsis-enriched subgroup. Our data suggests that stratification on WGS characteristics may improve identification of MSI, CDK12-/- and HRD patients. From WGS and ChIP-seq data, we show the potential relevance of recurrent alterations in non-coding regions identified with WGS and highlight the central role of AR signaling in tumor progression. These data underline the potential value of using WGS to accurately stratify mCRPC patients into clinically actionable subgroups.
1,209 downloads cancer biology
Tumor recurrence in glioblastoma multiforme (GBM) is often attributed to acquired resistance to the standard chemotherapeutic agent temozolomide (TMZ). Promoter methylation of the DNA repair gene MGMT has been associated with sensitivity to TMZ, while increased expression of MGMT has been associated with TMZ resistance. Clinical studies have observed a downward shift in MGMT methylation percentage from primary to recurrent stage tumors. However, the evolutionary processes driving this shift, and more generally the emergence and growth of TMZ-resistant tumor subpopulations, are still poorly understood. Here we develop a mathematical model, parameterized using clinical and experimental data, to investigate the role of MGMT methylation in TMZ resistance during the standard treatment regimen for GBM (surgery, chemotherapy and radiation). We first find that the observed downward shift in MGMT promoter methylation status between detection and recurrence cannot be explained solely by evolutionary selection. Next, our model suggests that TMZ has an inhibitory effect on maintenance methylation of MGMT after cell division. Finally, incorporating this inhibitory effect, we study the optimal number of TMZ doses per adjuvant cycle for GBM patients with high and low levels of MGMT methylation at diagnosis.
1,203 downloads cancer biology
André F Rendeiro, Thomas Krausgruber, Nikolaus Fortelny, Fangwen Zhao, Thomas Penz, Matthias Farlik, Linda C Schuster, Amelie Nemc, Szabolcs Tasnády, Marienn Réti, Zoltán Mátrai, Donat Alpar, Csaba Bödör, Christian Schmidl, Christoph Bock
Chronic lymphocytic leukemia (CLL) is a genetically, epigenetically, and clinically heterogeneous disease. Despite this heterogeneity, the Bruton tyrosine kinase (BTK) inhibitor ibrutinib provides effective treatment for the vast majority of CLL patients. To define the underlining regulatory program, we analyzed high-resolution time courses of ibrutinib treatment in closely monitored patients, combining cellular phenotyping (flow cytometry), single-cell transcriptome profiling (scRNA-seq), and chromatin mapping (ATAC-seq). We identified a consistent regulatory program shared across all patients, which was further validated by an independent CLL cohort. In CLL cells, this program starts with a sharp decrease of NF-κB binding, followed by reduced regulatory activity of lineage-defining transcription factors (including PAX5 and IRF4) and erosion of CLL cell identity, finally leading to the acquisition of a quiescence-like gene signature which was shared across several immune cell types. Nevertheless, we observed patient-to-patient variation in the speed of its execution, which we exploited to predict patient-specific dynamics in the response to ibrutinib based on pre-treatment samples. In aggregate, our study describes the cellular, molecular, and regulatory effects of therapeutic B cell receptor inhibition in CLL at high temporal resolution, and it establishes a broadly applicable method for epigenome/transcriptome-based treatment monitoring.
1,201 downloads cancer biology
The nature and extent of immune cell infiltration into solid tumours are key determinants of therapeutic response. Here, using a novel DNA methylation-based approach to tumour cell fraction deconvolution, we report the integrated analysis of tumour composition and genomics across a wide spectrum of solid cancers. Initially studying head and neck squamous cell carcinoma, we identify two distinct tumour subgroups: 'immune hot' and 'immune cold', which display differing prognosis, mutation burden, cytokine signalling, cytolytic activity, and oncogenic driver events. We demonstrate the existence of such tumour subgroups pan-cancer, link clonal-neoantigen burden to hot tumours, and show that transcriptional signatures of hot tumours are selectively engaged in immunotherapy responders. We also find that treatment-naive hot tumours are markedly enriched for known immune-resistance genomic alterations and define a catalogue of novel and known mediators of active antitumour immunity, deriving biomarkers and potential targets for precision immunotherapy.
1,193 downloads cancer biology
Chloe Chong, Markus Muller, HuiSong Pak, Dermot Harnett, Florian Huber, Delphine Grun, Marion Leleu, Aymeric Auger, Marion Arnaud, Brian J Stevenson, Justine Michaux, Ilija Bilic, Antje Hirsekorn, Lorenzo Calviello, Laia Simo-Riudalbas, Evarist Planet, Jan Lubinski, Marta Bryskiewicz, Maciej Wiznerowicz, Ioannis Xenarios, Lin Zhang, Didier Trono, Alexandre Harari, Uwe Ohler, George Coukos, Michal Bassani-Sternberg
Efforts to precisely identify tumor human leukocyte antigen (HLA) bound peptides capable of mediating T cell-based tumor rejection still face important challenges. Recent studies suggest that non-canonical tumor-specific HLA peptides that derive from annotated non-coding regions could elicit anti-tumor immune responses. However, sensitive and accurate mass-spectrometry (MS)-based proteogenomics approaches are required to robustly identify these non-canonical peptides. We present an MS-based analytical approach that characterizes the non-canonical tumor HLA peptide repertoire, by incorporating whole exome sequencing, bulk and single cell transcriptomics, ribosome profiling, and a combination of two MS/MS search tools. This approach results in the accurate identification of hundreds of shared and tumor-specific non-canonical HLA peptides and of an immunogenic peptide from a downstream reading frame in the melanoma stem cell marker gene ABCB5. It holds great promise for the discovery of novel cancer antigens for cancer immunotherapy.
1,192 downloads cancer biology
Alejandro Jimenez-Sanchez, Paulina Cybulska, Katherine Lavigne, Tyler Walther, Ines Nikolovski, Yousef Mazaheri, Britta Weigelt, Dennis S. Chi, Kay J. Park, Travis Hollmann, Dominique-Laurent Couturier, Alberto Vargas, James D. Brenton, Evis Sala, Alexandra Snyder, Martin Miller
In metastatic cancer, the role of heterogeneity at the tumor-immune microenvironment, its molecular underpinnings and clinical relevance remain largely unexplored. To understand tumor-immune dynamics at baseline and upon chemotherapy treatment, we performed unbiased pathway and cell type-specific immunogenomics analysis of treatment-naive (38 samples from 8 patients) and paired chemotherapy treated (80 paired samples from 40 patients) high-grade serous ovarian cancer (HGSOC) samples. Whole transcriptome analysis and image- based quantification of T cells from treatment-naive tumors revealed ubiquitous variability in immune signaling and distinct immune microenvironments co-existing within the same individuals and within tumor deposits at diagnosis. To systematically explore cell type composition of the tumor microenvironment using bulk mRNA, we derived consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods, providing improved accuracy and sensitivity when compared to HGSOC immunostaining and leukocyte methylation data sets. Cell-type deconvolution and pathway analyses revealed that Myc and Wnt signaling associate with immune cell exclusion in untreated HGSOC. To evaluate the effect of chemotherapy on the intrinsic tumor-immune heterogeneity, we compared site- matched and site-unmatched tumors before and after neoadjuvant chemotherapy. Transcriptomic and T-cell receptor sequencing analyses showed that site-matched samples had increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, which was not seen in site-unmatched samples where heterogeneity could not be accounted for. These results demonstrate that the tumor-immune interface in advanced HGSOC is intrinsically heterogeneous, and thus requires site-specific analysis to reliably unmask the impact of therapy on the tumor-immune microenvironment.
1,188 downloads cancer biology
Large-scale analyses of cancer genomes are revealing patterns of mutations that suggest biologically significant ideas about many aspects of cancer, including carcinogenesis, classification, and preventive and therapeutic strategies. Among those patterns is “mutual exclusivity”, a phenomenon observed when two or more mutations that are commonly observed in samples of a type of cancer are not found combined in individual tumors. We have been studying a striking example of mutual exclusivity: the absence of co-existing mutations in the KRAS and EGFR proto-oncogenes in human lung adenocarcinomas, despite the high individual frequencies of such mutations in this common type of cancer. Multiple lines of evidence suggest that toxic effects of the joint expression of KRAS and EGFR mutant oncogenes, rather than loss of any selective advantages conferred by a second oncogene that operates through the same signaling pathway, are responsible for the observed mutational pattern. We discuss the potential for understanding the physiological basis of such toxicity, for exploiting it therapeutically, and for extending the studies to other examples of mutual exclusivity.
1,185 downloads cancer biology
The sequential changes occurring with cancer progression are now being harnessed with therapeutic intent. Yet, there is no understanding of the chemical thermodynamics of proteomic changes associated with cancer progression/ cancer stage. This manuscript reveals a strong correlation of a chemical thermodynamic measure (known as Gibbs free energy) of protein-protein interaction networks for several cancer types and 5-year overall survival and stage in patients with cancer. Earlier studies have linked degree entropy of signaling networks to patient survival data, but not with stage. It appears that Gibbs free energy is a more general metric and accounts better for the underlying energetic landscape of protein expression in cells, thus correlating with stage as well as survival. This is an especially timely finding because of improved ability to obtain and analyze genomic/ proteomic information from individual patients. Yet, at least at present, only candidate gene imaging (FISH or immunohistochemistry) can be used for entropy computations. With continually expanding use of genomic information in clinical medicine, there is an ever-increasing need to understand the thermodynamics of protein-protein interaction networks.
1,179 downloads cancer biology
Four gene expression subtypes of high-grade serous ovarian cancer (HGSC) have been previously described. In these studies, a fraction of samples that did not fit well into the four subtype classifications were excluded. Therefore, we sought to systematically determine the concordance of transcriptomic HGSC subtypes across populations without removing any samples. We created a bioinformatics pipeline to independently cluster the five largest mRNA expression datasets using k-means and non-negative matrix factorization (NMF). We summarized differential expression patterns to compare clusters across studies. While previous studies reported four subtypes, our cross-population comparison does not support four. Because these results contrast with previous reports, we attempted to reproduce analyses performed in those studies. Our results suggest that early results favoring four subtypes may have been driven by including serous borderline tumors. In summary, our analysis suggests that either two or three, but not four, gene expression subtypes are most consistent across datasets.
1,176 downloads cancer biology
Benjamin Werner, Jack Case, Marc J Williams, Kate Chkhaidze, Daniel Temko, Javier Fernandez-Mateos, George D Cresswell, Daniel Nichol, William Cross, Inmaculada Spiteri, Weini Huang, Ian Tomlinson, Chris P Barnes, Trevor A. Graham, Andrea Sottoriva
Cancer is driven by complex evolutionary dynamics involving billions of cells. Increasing effort has been dedicated to sequence single tumour cells, but obtaining robust measurements remains challenging. Here we show that multi-region sequencing of bulk tumour samples contains quantitative information on single-cell divisions that is accessible if combined with evolutionary theory. Using high-throughput data from 16 human cancers, we measured the in vivo per-cell point mutation rate (mean: 1.69*10^(-8) bp per cell division) and per-cell survival rate (mean: 0.57) in individual patient tumours from colon, lung and renal cancers. Per-cell mutation rates varied 50-fold between individuals, and per-cell survival rates were between nearly-homeostatic and almost perfect cell doublings, equating to tumour ages between 1 and 19 years. Furthermore, reanalysing a recent dataset of 89 whole-genome sequenced healthy haematopoietic stem cells, we find 1.14 mutations per genome per cell division and near perfect cell doublings (per-cell survival rate: 0.96) during early haematopoietic development. Our analysis measures in vivo the most fundamental properties of human cancer and healthy somatic evolution at single-cell resolution within single individuals.
1,172 downloads cancer biology
Meifang Yu, Yanqing Huang, Amit Deorukhkar, Tara N Fujimoto, Suman Govindaraju, Jessica M Molkentine, Daniel Lin, Ya’an Kang, Eugene J Koay, Jason B. Fleming, Sonal Gupta, Anirban Maitra, Cullen M Taniguchi
Pancreatic cancer is a highly lethal disease whose aggressive biology that is driven by mitochondrial oxidative metabolism. Mitochondria normally form a network of fused organelles, but we find that patient-derived and genetically engineered murine pancreatic cancer cells exhibit highly fragmented mitochondria with robust oxygen consumption rates (OCR). When mitochondrial fusion was activated by the genetic or pharmacological inhibition Drp1, the morphology and metabolism of human and murine pancreatic cancer cells more closely resembled that of normal pancreatic epithelial cells. This reduced metabolism was correlated with slower tumor growth, fewer metastases, and enhanced survival in a syngeneic orthotopic model. Similarly, directly activating mitochondrial fusion by overexpression of Mfn2 also reduced tumor growth and metastases. Mitochondrial fusion in pancreatic cancer cells was associated with reduced mitochondrial mass and Complex I expression and function. Thus, these data suggest that enhancing mitochondrial fusion through Drp1 inhibition or enhanced Mfn2 expression or function has strong tumor suppressive activity against pancreatic cancer and may thus represent a highly novel and efficacious therapeutic target.
1,163 downloads cancer biology
Chengpei Zhu, Yanling Lv, Liangcai Wu, Jinxia Guan, Xue Bai, Jianzhen Lin, Tingting Liu, Zhang Haohai, Wang Anqiang, Xie Yuan, Wan Xueshuai, Zheng Yongchang, Yang Xiaobo, Miao Ruoyu, C. Robson Simon, Sang Xinting, Chenghai Xue, Haitao Zhao
Most hepatocellular carcinoma (HCC) patients are diagnosed at advanced stages and suffer limited treatment options. Challenges in early stage diagnosis may be due to the genetic complexity of HCC. Gene fusion plays a critical function in tumorigenesis and cancer progression in multiple cancers, yet the identities of fusion genes as potential diagnostic markers in HCC have not been investigated.Paired-end RNA sequencing was performed on noncancerous and cancerous lesions in two representative HBV-HCC patients. Potential fusion genes were identified by STAR-Fusion in STAR software and validated by four publicly available RNA-seq datasets. Fourteen pairs of frozen HBV-related HCC samples and adjacent non-tumor liver tissues were examined by RT-PCR analysis for gene fusion expression.We identified 2,354 different gene fusions in the two HBV-HCC patients. Validation analysis against the four RNA-seq datasets revealed only 1.8% (43/2,354) as recurrent fusions that were supported by public datasets. Comparison with four fusion databases demonstrated that three (HLA-DPB2-HLA-DRB1, CDH23-HLA-DPB1, and C15orf57-CBX3) out of 43 recurrent gene fusions were annotated as disease-related fusion events. Nineteen were novel recurrent fusions not previously annotated to diseases, including DCUN1D3-GSG1L and SERPINA5-SERPINA9. RT-PCR and Sanger sequencing of 14 pairs of HBV-related HCC samples confirmed expression of six of the new fusions, including RP11-476K15.1-CTD-2015H3.2.Our study provides new insights into gene fusions in HCC and could contribute to the development of anti-HCC therapy. RP11-476K15.1-CTD-2015H3.2 may serve as a new therapeutic biomarker in HCC.
1,154 downloads cancer biology
Here we report the design, synthesis and characterization of bifunctional chemical ligands that induce the association of Ras with ubiquitously expressed immunophilin proteins such as FKBP12 and cyclophilin A. We show this approach is applicable to two distinct Ras ligand scaffolds, and that both the identity of the immunophilin ligand and the linker chemistry affect compound efficacy in biochemical and cellular contexts. These ligands bind to Ras in an immunophilin-dependent fashion and mediate the formation of tripartite complexes of Ras, immunophilin and the ligand. The recruitment of cyclophilin A to GTP-bound Ras blocks its interaction with B-Raf in biochemical assays. Our study demonstrates the feasibility of ligand-induced association of Ras with intracellular proteins and suggests it as a promising therapeutic strategy for Ras-driven cancers.
1,152 downloads cancer biology
Successful treatment decisions in cancer depend on the accurate assessment of patient risk. To improve our understanding of the molecular alterations that underlie deadly malignancies, we analyzed genomic profiles from 33,036 solid tumors with known patient outcomes. Contrary to expectations, we find that mutations in cancer driver genes are almost never associated with patient survival time. In contrast, copy number changes in these same genes are broadly prognostic. Analysis of methylation, microRNA, mRNA, and protein expression patterns in primary tumors define several additional prognostic patterns, including signatures of tumor mitotic activity and tissue de-differentiation. Co-expression analysis with a cell cycle meta-gene distinguished proliferation-dependent and -independent prognostic features, allowing us to construct multivariate survival models with improved stratification power. In total, our analysis provides a comprehensive resource for biomarker and therapeutic target identification, and suggests that copy number and methylation profiling should complement tumor sequencing efforts to improve patient risk assessment.
1,149 downloads cancer biology
Patient-derived xenografts (PDXs) have become a prominent model for studying human cancer in vivo. The underlying assumption is that PDXs faithfully represent the genomic features of primary tumors, retaining their molecular characteristics throughout propagation. However, the genomic stability of PDXs during passaging has not yet been evaluated systematically. Here we monitored the dynamics of copy number alterations (CNAs) in 1,110 PDX samples across 24 cancer types. We found that new CNAs accumulated quickly, such that within four passages an average of 12% of the genome was affected by newly acquired CNAs. Selection for pre-existing minor clones was a major contributor to these changes, leading to both gains and losses of CNAs. The rate of CNA acquisition in PDX models was correlated with the extent of both aneuploidy and genetic heterogeneity observed in primary tumors of the same tissue. However, the specific CNAs acquired during PDX passaging differed from those acquired during tumor evolution in patients, suggesting that PDX tumors are subjected to distinct selection pressures compared to those that exist in human hosts. Specifically, several recurrent CNAs observed in primary tumors gradually disappeared in PDXs, indicating that events undergoing positive selection in humans can become dispensable during propagation in mice. Finally, we found that the genomic stability of PDX models also affected their responses to chemotherapy and targeted drugs. Our findings thus highlight the need to couple the timing of PDX molecular characterization to that of drug testing experiments. These results suggest that while PDX models are powerful tools, they should be used with caution.
1,149 downloads cancer biology
Pancreatic ductal adenocarcinoma (PDAC) is the most common malignancy of the pancreas and has one of the highest mortality rates of any cancer type with a 5-year survival rate of < 5% and median overall survival of typically six months from diagnosis. Recent transcriptional studies of PDAC have provided several competing stratifications of the disease. However, the development of therapeutic strategies will depend on a unique and coherent classification of PDAC. Here, we use an integrative meta-analysis of four different PDAC gene expression studies to derive the consensus PDAC classification. Despite the fact that immunotherapies have yet to have an impact in treatment of PDAC, the gene expression signatures that stratify PDAC across studies are immunologic. We define these as adaptive, innate and immune-exclusion immunologic signatures, which are prognostic across independent cohorts. An appreciation of the immune composition of PDAC with prognostic significance is an opportunity to understand distinct immune escape mechanisms in development of the disease and design novel immune-oncology therapeutic strategies to overcome current barriers.
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