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Pancreatic neuroendocrine tumors (PanNET) comprise two molecular subtypes, relatively benign islet tumors (IT) and invasive, metastasis-like primary (MLP) tumors. Until now, the origin of aggressive MLP tumors has been obscure. Herein, using multi-omics approaches, we revealed that MLP tumors arise from IT via dedifferentiation following a reverse trajectory along the developmental pathway of islet β cells, which results in the acquisition of a progenitor-like molecular phenotype. Functionally, the miR-181cd cluster induces the IT-to-MLP transition by suppressing expression of the Meis2 transcription factor, leading to upregulation of a developmental transcription factor, Hmgb3. Notably, the IT-to-MLP transition constitutes a distinct step of tumorigenesis and is separable from the classic proliferation-associated hallmark, temporally preceding accelerated proliferation of cancer cells. Furthermore, patients with PanNET with elevated HMGB3 expression and an MLP transcriptional signature are associated with higher-grade tumors and worse survival. Overall, our results unveil a new mechanism that modulates cancer cell plasticity to enable malignant progression.Significance:Dedifferentiation has long been observed as a histopathologic characteristic of many cancers, albeit inseparable from concurrent increases in cell proliferation. Herein, we demonstrate that dedifferentiation is a mechanistically and temporally separable step in the multistage tumorigenesis of pancreatic islet cells, retracing the developmental lineage of islet β cells.This article is highlighted in the In This Issue feature, p. 2355

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Cancer evolution determines molecular and morphologic intratumor heterogeneity and challenges the design of effective treatments. In lung adenocarcinoma, disease progression and prognosis are associated with the appearance of morphologically diverse tumor regions, termed histologic patterns. However, the link between molecular and histologic features remains elusive. Here, we generated multiomics and spatially resolved molecular profiles of histologic patterns from primary lung adenocarcinoma, which we integrated with molecular data from >2,000 patients. The transition from indolent to aggressive patterns was not driven by genetic alterations but by epigenetic and transcriptional reprogramming reshaping cancer cell identity. A signature quantifying this transition was an independent predictor of patient prognosis in multiple human cohorts. Within individual tumors, highly multiplexed protein spatial profiling revealed coexistence of immune desert, inflamed, and excluded regions, which matched histologic pattern composition. Our results provide a detailed molecular map of lung adenocarcinoma intratumor spatial heterogeneity, tracing nongenetic routes of cancer evolution.Significance:Lung adenocarcinomas are classified based on histologic pattern prevalence. However, individual tumors exhibit multiple patterns with unknown molecular features. We characterized nongenetic mechanisms underlying intratumor patterns and molecular markers predicting patient prognosis. Intratumor patterns determined diverse immune microenvironments, warranting their study in the context of current immunotherapies.This article is highlighted in the In This Issue feature, p. 1307

Whole-genome doubling (WGD) is a recurrent event in human cancers and it promotes chromosomal instability and acquisition of aneuploidies1–8. However, the three-dimensional organization of chromatin in WGD cells and its contribution to oncogenic phenotypes are currently unknown. Here we show that in p53-deficient cells, WGD induces loss of chromatin segregation (LCS). This event is characterized by reduced segregation between short and long chromosomes, A and B subcompartments and adjacent chromatin domains. LCS is driven by the downregulation of CTCF and H3K9me3 in cells that bypassed activation of the tetraploid checkpoint. Longitudinal analyses revealed that LCS primes genomic regions for subcompartment repositioning in WGD cells. This results in chromatin and epigenetic changes associated with oncogene activation in tumours ensuing from WGD cells. Notably, subcompartment repositioning events were largely independent of chromosomal alterations, which indicates that these were complementary mechanisms contributing to tumour development and progression. Overall, LCS initiates chromatin conformation changes that ultimately result in oncogenic epigenetic and transcriptional modifications, which suggests that chromatin evolution is a hallmark of WGD-driven cancer.

Tissues are organized in niches where cell types interact to implement specific functions. Spatial -omics technologies allow to decode the molecular features and spatial interactions that determine such niches. However, computational approaches to process and interpret spatial molecular profiles are challenged by the scale and diversity of this data. Here, we present CellCharter, an algorithmic framework for the identification, characterization, and comparison of cellular niches from heterogeneous spatial transcriptomics and proteomics datasets comprising multiple samples. CellCharter outperformed existing methods, identified biologically meaningful cellular niches in different contexts, and discovered spatial cancer cell states, characterized by cell-intrinsic features and spatial interactions between tumor and immune cells. In non-small cell lung cancer, CellCharter revealed a cellular niche composed of neutrophils and tumor cells expressing markers of hypoxia and cell migration. Expression of these markers determined a spatial gradient associated with cancer cell state transition and neutrophil infiltration. Moreover, CellCharter showed that similar compositions of immune cell types can exhibit remarkably different spatial organizations in different tumors, highlighting the need for exploring spatial cell interactions to decipher intratumor heterogeneity. Overall, CellCharter is a flexible and scalable framework to explore and compare the spatial organization of normal and malignant tissues.

Data related to paper Lymphoma tissue fragments to anticipate response to targeted therapies Folder structure ├── 10xVisium # spatial transcriptomics data │ ├── LP03 │ │ ├── CTRL │ │ └── Parental │ └── LP08 │ ├── CTRL │ ├── IBR │ ├── IDL │ └── Parental └── scRNAseq # processed single RNA seq data ├── Spleen 1 │ └── qc_data.h5ad └── Spleen 2 └── qc_data.h5ad Each spatial transcriptomics data folders contains ├── NucleiPerSpot.txt ├── bayesprism_updatedReference.rdata ├── filtered_feature_bc_matrix │ ├── barcodes.tsv.gz │ ├── features.tsv.gz │ └── matrix.mtx.gz └── spatial ├── aligned_fiducials.jpg ├── detected_tissue_image.jpg ├── scalefactors_json.json ├── tissue_hires_image.png ├── tissue_lowres_image.png └── tissue_positions_list.csv

Human papillomavirus (HPV) infections are the primary drivers of cervical cancers, and often the HPV DNA gets integrated into the host genome. Although the oncogenic impact of HPV encoded genes (such as E6/E7) is well known, the cis-regulatory effect of integrated HPV DNA on host chromatin structure and gene regulation remains less understood. Here, we investigate the genome-wide patterns of HPV integrations and associated host gene expression changes in the context of chromatin states and topologically associating domains (TADs). We find that HPV integrations are significantly enriched and depleted in active and inactive chromatin regions, respectively. Interestingly, regardless of the chromatin state, the genomic regions flanking HPV integrations showed transcriptional upregulation. Nevertheless, the upregulation (both local and long-range) is mostly confined to the TADs with integration and does not affect the adjacent TADs. Few TADs showed recurrent integrations associated with overexpression of oncogenes within them (such asMYC, PVT1, TP63andERBB2), regardless of the proximity. To further understand the long-range effect, we performed HiC and 4C-seq analyses in HeLa and observed chromatin looping interaction between the integrated HPV andMYC/PVT1regions (situated ∼500 kb apart), leading to allele-specific overexpression of these genes. Again, these chromatin interactions involving integrated HPV are mostly observed within the same TAD. Together, these results suggest the cis-regulatory potential of integrated HPV DNA that drives host gene upregulation at intra-TAD level in cervical cancer. Based on this, we propose HPV integrations can trigger multimodal oncogenic activation to promote cancer progression.

BackgroundSpatial interactions and insulation of chromatin regions are associated with transcriptional regulation. Domains of frequent chromatin contacts are proposed as functional units, favoring and delimiting gene regulatory interactions. However, contrasting evidence supports the association between chromatin domains and transcription.ResultHere, we assess gene co-regulation in chromatin domains across multiple human cancers, which exhibit great transcriptional heterogeneity. Across all datasets, gene co-regulation is observed only within a small yet significant number of chromatin domains. We design an algorithmic approach to identify differentially active domains (DADo) between two conditions and show that these provide complementary information to differentially expressed genes. Domains comprising co-regulated genes are enriched in the less active B sub-compartments and for genes with similar function. Notably, differential activation of chromatin domains is not associated with major changes of domain boundaries, but rather with changes of sub-compartments and intra-domain contacts.ConclusionOverall, gene co-regulation is observed only in a minority of chromatin domains, whose systematic identification will help unravel the relationship between chromatin structure and transcription.

Background: Inflammatory breast cancer (IBC) has a distinctive and aggressive clinical behavior but its underlying biological characteristics have not been fully elucidated. The extended analysis of somatic alterations in The Cancer Genome Atlas (TCGA) highlighted canonical oncogenic pathways that were consistently represented across different tumor subtypes. The aim of this study was to translate such pathway-based characterization to the clinical setting through ctDNA NGS to dissect IBC’s biology and prognosis. Methods: The study retrospectively analyzed 255 metastatic breast cancer (MBC) patients (pts) treated and characterized for ctDNA at Northwestern University (Chicago, IL). ctDNA was analyzed using the Guardant360 NGS assay (Guardant Health). Only non-synonymous alterations were analyzed. Pathway classification was defined based on prior work (Sanchez-Vega F et al, Cell. 2018). Associations among clinical characteristics, pathway classification, and IBC were explored through uni- and multivariate logistic regression; survival was tested though uni- and multivariate Cox regression both for progression-free survival (PFS) and overall survival (OS). Results: Of 255 enrolled pts, 124 (48%) were diagnosed with hormone receptor positive (HR pos) MBC, 75 (30%) with HER2-positive (HER2_pos) MBC and 56 (22%) with triple negative (TNBC) MBC. IBC was diagnosed in 74 pts (30%). Receptor-tyrosine kinase, RTK (130 pts, 51%), p53 (130 pts, 51%), PI3K/Akt (116 pts, 46%), and cell cycle (91 pts, 36%) were the most often altered pathways. The multivariate model highlighted the association of IBC with HER2_pos (OR: 2.19; 95%CI: 1.09 - 4.38; P=0.0276), an increased number of alterations in the p53 pathway (OR: 2.05; 95%CI: 1.12 - 3.75; P=0.0197) and a decreased number of alterations in the RAS pathway (OR: 0.34; 95%CI: 0.14 - 0.80; P=0.0137). Decreased alterations in the ER pathway were borderline significant (OR: 0.48; 95%CI: 0.22 - 1.03; P=0.0584). Only cell cycle alterations had an impact on PFS for IBC (HR: 2.20; 95%CI: 1.18 - 4.08; P=0.0127), while p53 and Wnt had an impact on nonIBC (respectively HR: 2.00; 95%CI: 1.23 - 3.25; P=0.0052 and HR: 3.40; 95%CI: 1.20 - 9.64; P=0.0212). The univariate model showed a significant impact on OS RAF, ER, and cell cycle pathways alterations for IBC, the role of ER and cell cycle pathways alterations was confirmed in the multivariate model (respectively HR: 6.19; 95%CI: 1.63 - 23.48; P=0.0073 and HR: 3.79; 95%CI: 1.04 - 13.75; P=0.0431). The multivariate model showed a prognostic impact only for p53 in the nonIBC subgroup (HR: 2.20; 95%CI: 1.11 - 4.36; P=0.0237) Conclusion: The ctDNA-based oncogenic signaling pathway characterization showed different biological and prognostic features across IBC and nonIBC MBC patients. Alterations of the p53 pathway were more likely to be present in IBC pts, while alterations in the RAS pathway were less represented in this cohort. ER and cell cycle pathways’ alterations impacted the OS of IBC MBC patients. Although preliminary, these results suggest a more comprehensive biological characterization based on ctDNA for treatment selection and clinical decision-making. Main alterations and pathwayGeneNumber of alterations%PathwayTP5318815.58p53PIK3CA14111.68PI3K/AktERBB2725.97RTKESR1705.8ERMYC574.72MycFGFR1463.81RTKEGFR453.73RTKCCNE1383.15Cell cycleMET322.65RTKNF1322.65RAS Citation Format: Lorenzo Gerratana, Andrew A Davis, Marco Mina, Saya L Jacob, Qiang Zhang, Ami N Shah, Paolo D’Amico, Neelima Katam, Firas Wehbe, Elena Vagia, Lisa Flaum, Leonidas Platanias, Amir Behdad, Fabio Puglisi, William J Gradishar, Giovanni Ciriello, Massimo Cristofanilli. Investigating oncogenic signaling pathways in inflammatory metastatic breast cancer (MBC) though circulating tumor DNA (ctDNA) next-generation sequencing (NGS) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-33.

Cancer cells retain genomic alterations that provide a selective advantage. The prediction and validation of advantageous alterations are major challenges in cancer genomics. Moreover, it is crucial to understand how the coexistence of specific alterations alters response to genetic and therapeutic perturbations. In the present study, we inferred functional alterations and preferentially selected combinations of events in >9,000 human tumors. Using a Bayesian inference framework, we validated computational predictions with high-throughput readouts from genetic and pharmacological screenings on 2,000 cancer cell lines. Mutually exclusive and co-occurring cancer alterations reflected, respectively, functional redundancies able to rescue the phenotype of individual target inhibition, or synergistic interactions, increasing oncogene addiction. Among the top scoring dependencies, co-alteration of the phosphoinositide 3-kinase (PI3K) subunit PIK3CA and the nuclear factor NFE2L2 was a synergistic evolutionary trajectory in squamous cell carcinomas. By integrating computational, experimental and clinical evidence, we provide a framework to study the combinatorial functional effects of cancer genomic alterations. Computational analysis of over 9,000 cancer genomes, coupled with functional validation in cell lines, highlights combinations of mutations required for tumor progression. This integrated approach provides a framework to stratify patients on the basis of interdependent genetic aberrations.

Simple Summary Our work establishes that amplification of 4EBP1, as a part of Chr. 8p11, creates a synthetic dependency on FGFR1 signaling in cancer. 4EBP1 is phosphorylated by FGFR1 and PI3K signaling, and accordingly cancer with 4EBP1-FGFR1 amplification is more sensitive to FGFR1 and PI3K inhibition due to inhibition of 4EBP1 phosphorylation. Moreover, we characterize the translational targets of 4EBP1 and identify that 4EBP1 specifically regulates the translation of genes involved in insulin signaling, glucose metabolism, and the inositol pathway that plays a role in cancer progression. The eIF4E translation initiation factor has oncogenic properties and concordantly, the inhibitory eIF4E-binding protein (4EBP1) is considered a tumor suppressor. The exact molecular effects of 4EBP1 activation in cancer are still unknown. Surprisingly, 4EBP1 is a target of genomic copy number gains (Chr. 8p11) in breast and lung cancer. We noticed that 4EBP1 gains are genetically linked to gains in neighboring genes, including WHSC1L1 and FGFR1. Our results show that FGFR1 gains act to attenuate the function of 4EBP1 via PI3K-mediated phosphorylation at Thr37/46, Ser65, and Thr70 sites. This implies that not 4EBP1 but instead FGFR1 is the genetic target of Chr. 8p11 gains in breast and lung cancer. Accordingly, these tumors show increased sensitivity to FGFR1 and PI3K inhibition, and this is a therapeutic vulnerability through restoring the tumor-suppressive function of 4EBP1. Ribosome profiling reveals genes involved in insulin signaling, glucose metabolism, and the inositol pathway to be the relevant translational targets of 4EBP1. These mRNAs are among the top 200 translation targets and are highly enriched for structure and sequence motifs in their 5 ' UTR, which depends on the 4EBP1-EIF4E activity. In summary, we identified the translational targets of 4EBP1-EIF4E that facilitate the tumor suppressor function of 4EBP1 in cancer.

Whole genome doubling promotes tumorigenesis through loss of chromatin segregation and compartment repositioning PART 2 hic_maps_K562.zip:Hi-C maps (.hic format) of K562 samples hic_features.zip hic_features/compartment_domains:contains, for each of the hic matrices, the compartmentdomains imputed by Calder in BED format hic_features/compartment_domain_boundaries:boundaries between adjacent compartment domains in Control andWGD samples from RPE TP53-/- cell line hic_features/compartment_scores:for each compartment domain in Control and WGD samples fromRPE TP53-/- cell line it reports its C-score hic_features/insulation_scores:for each of the Hi-C matrices, the insulation scores computed at50 Kb resolution, in bigwig format ihic_features/nsulation_boundaries:TAD boundaries detected using the insulation score, for each Hi-Csample chipseq.zip chipseq/input_normalized: contains bigwig files of ChIP-seq experiments generatedin this study. Files are log2 input normalized tracks. The "bw_signals_attributes.txt" file can be used to addmetadata to the tracks for visualization in IGV scRNAseq.zip differential_expression: contains the output of the differential expression analysis. A README file is present explaining the meaning of each column in the table expression: gene expression matrix (cell x gene) containing normalized expression value. A table containing metadata of each cell (like sample of origin, uuid) is also available infercnv: copy numbers inferred by INFERCNV. Linkage matrix providing the clustering output of the infercnv data is also provided. copy_numbers.zip ControlFREEC_log2_coverage_ratio_10Kb.seg: .seg file (to be loaded in IGV) containing coverage log2 fold-change between samples and control as computed by ControlFREEC for the detection of CNVs filtered_cnvs.seg: significant CNVs detected by ControlFREEC RPE_cnvs_20wTumors_merged.bed: consensus set of CNVs in RPE TP53-/- 20w post-WGD tumors mutations.zip RPE_somatic_all.maf:MAF file of mutations detected by Mutect2 on RPE TP53-/- sample RPE_somatic_all_FILTER_PASS.tsv: mutations passing the quality filters &nbsp

Cancer evolution is driven by the concerted action of multiple molecular alterations, which emerge and are selected during tumor progression. An alteration is selected when it provides an advantage to the tumor cell. However, the advantage provided by a specific alteration depends on the tumor lineage, cell epigenetic state, and presence of additional alterations. In this case, we say that an evolutionary dependency exists between an alteration and what influences its selection. Epistatic interactions between altered genes lead to evolutionary dependencies (EDs), by favoring or vetoing specific combinations of events. Large-scale cancer genomics studies have discovered examples of such dependencies, and showed that they influence tumor progression, disease phenotypes, and therapeutic response. In the past decade, several algorithmic approaches have been proposed to infer EDs from large-scale genomics datasets. These methods adopt diverse strategies to address common challenges and shed new light on cancer evolutionary trajectories. Here, we review these efforts starting from a simple conceptualization of the problem, presenting the tackled and still unmet needs in the field, and discussing the implications of EDs in cancer biology and precision oncology.

Chromatin folding in the 3D space of the nucleus can be explored through high-throughput chromosome conformation capture (Hi-C) approaches. These experiments quantify the number of interactions between any pair of genomic loci in the genome and, thus, allow building genome-scale maps of intra- and inter-chromosomal contacts (contact maps). Statistical and algorithmic analyses of Hi-C data consist in extracting information from these contact maps. One of the most striking patterns observed in intra-chromosomal Hi-C contact maps emerged from genomic regions that exhibit dense intra-region but sparse inter-region contacts. These have been termed topologically associating domains (TADs). The identification of TADs from Hi-C contact maps is of great interest as they have been shown to act as unit of chromosome organization and, potentially, functional activity. Several approaches have been developed to identify TADs (TAD callers). However, results from these methods are often dependent on data resolution and poorly concordant. In this chapter, we present four TAD callers and we provide detailed protocols for their use. In addition, we show how to compare TADs identified by different callers and how to assess the enrichment for TAD-associated biological features. TAD calling has become a key step in the study of chromatin 3D organization in different cellular contexts. Here we provide guidelines to improve the robustness and quality of these analyses.

Chromatin folding in the 3D space of the nucleus can be explored through high-throughput chromosome conformation capture (Hi-C) approaches. These experiments quantify the number of interactions between any pair of genomic loci in the genome and, thus, allow building genome-scale maps of intra- and inter-chromosomal contacts (contact maps). Statistical and algorithmic analyses of Hi-C data consist in extracting information from these contact maps. One of the most striking patterns observed in intra-chromosomal Hi-C contact maps emerged from genomic regions that exhibit dense intra-region but sparse inter-region contacts. These have been termed topologically associating domains (TADs). The identification of TADs from Hi-C contact maps is of great interest as they have been shown to act as unit of chromosome organization and, potentially, functional activity. Several approaches have been developed to identify TADs (TAD callers). However, results from these methods are often dependent on data resolution and poorly concordant. In this chapter, we present four TAD callers and we provide detailed protocols for their use. In addition, we show how to compare TADs identified by different callers and how to assess the enrichment for TAD-associated biological features. TAD calling has become a key step in the study of chromatin 3D organization in different cellular contexts. Here we provide guidelines to improve the robustness and quality of these analyses.

SUMMARY In this study, we investigate mechanisms leading to inflammation and immunoreactivity in ovarian tumors with homologous recombination deficiency (HRD). BRCA1 loss is found to lead to transcriptional reprogramming in tumor cells and cell-intrinsic inflammation involving type I interferon (IFN) and stimulator of IFN genes (STING). BRCA1-mutated (BRCA1mut) tumors are thus T cell inflamed at baseline. Genetic deletion or methylation of DNA-sensing/IFN genes or CCL5 chemokine is identified as a potential mechanism to attenuate T cell inflammation. Alternatively, in BRCA1mut cancers retaining inflammation, STING upregulates VEGF-A, mediating immune resistance and tumor progression. Tumor-intrinsic STING elimination reduces neoangiogenesis, increases CD8+ T cell infiltration, and reverts therapeutic resistance to dual immune checkpoint blockade (ICB). VEGF-A blockade phenocopies genetic STING loss and synergizes with ICB and/or poly(ADP-ribose) polymerase (PARP) inhibitors to control the outgrowth of Trp53−/−Brca1−/− but not Brca1+/+ ovarian tumors in vivo, offering rational combinatorial therapies for HRD cancers., Graphical abstract, In brief Bruand et al. provide insights into the dual role of STING in promoting tumor-intrinsic mechanisms of both immunoreactivity, driven by DNA sensing and type I IFN, and also VEGF-A-driven immune resistance in BRCA1mut ovarian cancers. STING elimination reduces neoangiogenesis, increases CD8+ T cell infiltration, and reverts therapeutic resistance to dual ICB.