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BACKGROUNDInhibition of Bruton's tyrosine kinase with ibrutinib blocks the function of myeloid-derived suppressor cells (MDSC). The combination of ibrutinib and nivolumab was tested in patients with metastatic solid tumors.METHODSSixteen patients received ibrutinib 420 mg p.o. daily with nivolumab 240 mg i.v. on days 1 and 15 of a 28-day cycle. The effect of ibrutinib and nivolumab on MDSC, the immune profile, and cytokine levels were measured. Single-cell RNA-Seq and T cell receptor sequencing of immune cells was performed.RESULTSCommon adverse events were fatigue and anorexia. Four patients had partial responses and 4 had stable disease at 3 months (average 6.5 months, range 3.5-14.6). Median overall survival (OS) was 10.8 months. Seven days of Bruton's tyrosine kinase (BTK) inhibition significantly increased the proportion of monocytic-MDSC (M-MDSC) and significantly decreased chemokines associated with MDSC recruitment and accumulation (CCL2, CCL3, CCL4, CCL13). Single-cell RNA-Seq revealed ibrutinib-induced downregulation of genes associated with MDSC-suppressive function (TIMP1, CXCL8, VEGFA, HIF1A), reduced MDSC interactions with exhausted CD8+ T cells, and decreased TCR repertoire diversity. The addition of nivolumab significantly increased circulating NK and CD8+ T cells and increased CD8+ T cell proliferation. Exploratory analyses suggest that MDSC and T cell gene expression and TCR repertoire diversity were differentially affected by BTK inhibition according to patient response.CONCLUSIONIbrutinib and nivolumab were well tolerated and affected MDSC and T cell function in patients with solid metastatic tumors.TRIAL REGISTRATIONClinicalTrials.gov NCT03525925.FUNDINGNIH; National Cancer Institute Cancer; National Center for Advancing Translational Sciences; Pelotonia.

Rare cancers and other rare nonmalignant tumors comprise 25% of all cancer diagnoses and account for 25% of all cancer deaths. They are difficult to study due to many factors, including infrequent occurrence, lack of a universal infrastructure for data and/or tissue collection, and a paucity of disease models to test potential treatments. For each individual rare cancer, the limited number of diagnosed cases makes it difficult to recruit sufficient patients for clinical studies, and rare cancer research studies are often siloed. As a result, progress has been slow for many of these cancers. While rare cancer research efforts have increased over time, the breadth of the research landscape is not known. A recent literature search revealed a sharp increase in rare tumor, and rare cancer publications began in the early 2000s. To identify rare cancer research efforts being conducted in the US and globally, we conducted an online search of rare tumor/rare cancer research programs and identified 76 programs. To gain a deeper understanding of these programs, we composed and conducted a survey to ask programs for details about their research efforts. Of the 42 programs contacted to complete the survey, 23 programs responded. Survey results show most programs are collecting clinical data, molecular data, and biospecimens, and many are conducting molecular analyses. This landscape analysis demonstrates that multiple rare cancer research efforts are ongoing, and the rare cancer community may benefit from collaboration among stakeholders to accelerate research and improve patient outcomes., (Published by Oxford University Press 2023.)

Macrophage activation is controlled by a balance between activating and inhibitory receptors 1-7 , which protect normal tissues from excessive damage during infection 8,9 but promote tumour growth and metastasis in cancer 7,10 . Here we report that the Kupffer cell lineage-determining factor ID3 controls this balance and selectively endows Kupffer cells with the ability to phagocytose live tumour cells and orchestrate the recruitment, proliferation and activation of natural killer and CD8 T lymphoid effector cells in the liver to restrict the growth of a variety of tumours. ID3 shifts the macrophage inhibitory/activating receptor balance to promote the phagocytic and lymphoid response, at least in part by buffering the binding of the transcription factors ELK1 and E2A at the SIRPA locus. Furthermore, loss- and gain-of-function experiments demonstrate that ID3 is sufficient to confer this potent anti-tumour activity to mouse bone-marrow-derived macrophages and human induced pluripotent stem-cell-derived macrophages. Expression of ID3 is therefore necessary and sufficient to endow macrophages with the ability to form an efficient anti-tumour niche, which could be harnessed for cell therapy in cancer., (© 2024. The Author(s).)

Homologous recombination (HR) deficiency is associated with DNA rearrangements and cytogenetic aberrations 1 . Paradoxically, the types of DNA rearrangements that are specifically associated with HR-deficient cancers only minimally affect chromosomal structure 2 . Here, to address this apparent contradiction, we combined genome-graph analysis of short-read whole-genome sequencing (WGS) profiles across thousands of tumours with deep linked-read WGS of 46 BRCA1- or BRCA2-mutant breast cancers. These data revealed a distinct class of HR-deficiency-enriched rearrangements called reciprocal pairs. Linked-read WGS showed that reciprocal pairs with identical rearrangement orientations gave rise to one of two distinct chromosomal outcomes, distinguishable only with long-molecule data. Whereas one (cis) outcome corresponded to the copying and pasting of a small segment to a distant site, a second (trans) outcome was a quasi-balanced translocation or multi-megabase inversion with substantial (10 kb) duplications at each junction. We propose an HR-independent replication-restart repair mechanism to explain the full spectrum of reciprocal pair outcomes. Linked-read WGS also identified single-strand annealing as a repair pathway that is specific to BRCA2 deficiency in human cancers. Integrating these features in a classifier improved discrimination between BRCA1- and BRCA2-deficient genomes. In conclusion, our data reveal classes of rearrangements that are specific to BRCA1 or BRCA2 deficiency as a source of cytogenetic aberrations in HR-deficient cells., (© 2023. The Author(s).)

Patient-derived tumor organoids (PDTOs) have emerged as exceptional pre-clinical models as they preserved, in most of the cases, the mutational landscape and tumor-clonal heterogeneity of the primary tumors. Despite being extensively used in disease modelling as well as in precision medicine for drug testing and discovery, they still have some limitations. The main limitation is that during their establishment they lose all components of the tumor microenvironment (TME) which are known modulators of tumor response to therapeutic treatment as well as disease progression. In this review we address the effects of different players of the TME such as immune cells, fibroblasts, endothelial cells and the extracellular matrix composition on tumor behavior and response to treatment as well as the different culture and co-culture strategies that could improve PDTOs value as pre-clinical models leading to the development of next generation PDTOs., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Purpose: The combination of whole-genome and transcriptome sequencing (WGTS) is expected to transform diagnosis and treatment for patients with cancer. WGTS is a comprehensive precision diagnostic test that is starting to replace the standard of care for oncology molecular testing in health care systems around the world; however, the implementation and widescale adoption of this best-in-class testing is lacking., Methods: Here, we address the barriers in integrating WGTS for cancer diagnostics and treatment selection and answer questions regarding utility in different cancer types, cost-effectiveness and affordability, and other practical considerations for WGTS implementation., Results: We review the current studies implementing WGTS in health care systems and provide a synopsis of the clinical evidence and insights into practical considerations for WGTS implementation. We reflect on regulatory, costs, reimbursement, and incidental findings aspects of this test., Conclusion: WGTS is an appropriate comprehensive clinical test for many tumor types and can replace multiple, cascade testing approaches currently performed. Decreasing sequencing cost, increasing number of clinically relevant aberrations and discovery of more complex biomarkers of treatment response, should pave the way for health care systems and laboratories in implementing WGTS into clinical practice, to transform diagnosis and treatment for patients with cancer., Competing Interests: Edwin CuppenConsulting or Advisory Role: Illumina (Inst), InteRNATravel, Accommodations, Expenses: Illumina Olivier ElementoStock and Other Ownership Interests: Volastra Therapeutics, Owkin, OneThree Biotech Richard RosenquistHonoraria: AbbVie, Illumina, Roche, Janssen, AstraZenecaConsulting or Advisory Role: Illumina, AbbVieTravel, Accommodations, Expenses: Illumina Svetlana NikicEmployment: IlluminaStock and Other Ownership Interests: Illumina Maarten IJzermanHonoraria: RTI Health Solutions, IlluminaConsulting or Advisory Role: Creativ-Ceutical, Illumina (Inst)Research Funding: Illumina (Inst)Travel, Accommodations, Expenses: Illumina (Inst) Isabelle Durand ZaleskiHonoraria: Abbott Laboratories, BMS, MSD Oncology, Pfizer, IlluminaConsulting or Advisory Role: BMS, MSD Oncology, Pfizer Geert FrederixHonoraria: Illumina (Inst)Consulting or Advisory Role: Illumina (Inst) Lars-Åke LevinEmployment: JanssenStock and Other Ownership Interests: AstraZenecaResearch Funding: Boehringer Ingelheim (Inst), Janssen (Inst) Charles G. MullighanStock and Other Ownership Interests: AmgenHonoraria: Amgen, IlluminaConsulting or Advisory Role: Illumina, Faze, Beam TherapeuticsSpeakers' Bureau: Amgen, PfizerResearch Funding: Loxo, Pfizer, AbbViePatents, Royalties, Other Intellectual Property: Inventor on a pending patent application related to gene-expression signatures for detection of underlying Philadelphia chromosome “like events and therapeutic targeting in leukemia (PCT/US2012/069228), WO 2021/022076 A1. This Patent Highlight shows representative PROTAC compounds bound to JAK2, where ruxolitinib and baricitinib bind to the human JAK2 JH1. Furthermore, representative data illustrate protein degradation, cytotoxicity, and effect of the JAKSTAT signaling pathway of the PROTAC compounds in MHHCALL-4 cells, Marcus Fisher, Fatemeh Keramatnia, Kevin Mcgowan, Jaeki Min, Gisele A. Nishiguchi, Jeanine Price, Zoran Rankovic, Das Sourav, Charles G. Mullighan, Yunchao Chang 2021 Substituted N-(2-(2,6-Dioxopiperidin-3-YL)-1,3-Dioxoisoindolin-5-YL)Arylsulfonamide Analogs as Modulators of Cereblon Protein, Application No: PCT/US2021/051648 Filed: September 23, 2021. Patent pending (Inst)Travel, Accommodations, Expenses: Amgen, Illumina Reinhard BuettnerStock and Other Ownership Interests: Gnothis IncHonoraria: AstraZeneca, AbbVie, Bayer, Bristol Myers Squibb, Boehringer Ingelheim, Merck Serono, MSD, Novartis, Qiagen, Pfizer, Roche, IlluminaResearch Funding: Roche (Inst) Trevor J. PughHonoraria: Merck, AstraZeneca, Illumina, PACT PharmaConsulting or Advisory Role: Chrysalis Biomedical Advisors, Axiom Healthcare Strategies, Canadian Pension Plan Investment BoardResearch Funding: RochePatents, Royalties, Other Intellectual Property: Hybrid-capture sequencing for dete rmining immune cell clonality Carlos CaldasConsulting or Advisory Role: AstraZeneca/MedImmune, IlluminaResearch Funding: AstraZeneca (Inst), Genentech/Roche (Inst), Servier (Inst) Fabrice AndreStock and Other Ownership Interests: PEGASCYConsulting or Advisory Role: Guardant Health (Inst), MedImmune (Inst), Gilead Sciences (Inst), Relay therapeutics (Inst)Research Funding: AstraZeneca (Inst), Novartis (Inst), Pfizer (Inst), Lilly (Inst), Roche (Inst), Daiichi (Inst)Travel, Accommodations, Expenses: Novartis, Roche, GlaxoSmithKline, AstraZeneca Ilse CustersHonoraria: IlluminaTravel, Accommodations, Expenses: Illumina Elias CampoHonoraria: EUSA Pharma, AstraZeneca, TakedaConsulting or Advisory Role: Illumina, AbbVieResearch Funding: AstraZenecaPatents, Royalties, Other Intellectual Property: Author on a patent licensed to NanoStrig Technologies, Author in the protectedt bioinformatic IgCaller pipeline Hans van SnellenbergResearch Funding: Illumina (Inst) Anna SchuhStock and Other Ownership Interests: Illumina, SERENOxConsulting or Advisory Role: AbbVie, Roche, Janssen, AstraZenecaResearch Funding: Johnson & Johnson, Illumina (Inst), Oxford Nanopore Technologies (Inst)Travel, Accommodations, Expenses: AbbVie, Janssen Oncology Christof von KalleStock and Other Ownership Interests: GeneWerkConsulting or Advisory Role: Roche/Genentech, Novartis, PfizerPatents, Royalties, Other Intellectual Property: Patent applications in molecular diagnostics Torsten HaferlachEmployment: MLL Munich Leukemia LaboratoryLeadership: MLL Munich Leukemia LaboratoryConsulting or Advisory Role: Illumina Stefan FröhlingHonoraria: PharmaMar, Roche, Lilly, AmgenConsulting or Advisory Role: Bayer, Illumina, RocheResearch Funding: AstraZeneca (Inst), PharmaMar (Inst), Pfizer (Inst), Roche (Inst)Travel, Accommodations, Expenses: PharmaMar, Roche, Lilly, Amgen Vaidehi JobanputraHonoraria: IlluminaNo other potential conflicts of interest were reported.

Cyclic AMP (cAMP) signaling is localized to multiple spatially distinct microdomains, but the role of cAMP microdomains in cancer cell biology is poorly understood. Here, we present a tunable genetic system that allows us to activate cAMP signaling in specific microdomains. We uncover a nuclear cAMP microdomain that activates a tumor-suppressive pathway in a broad range of cancers by inhibiting YAP, a key effector protein of the Hippo pathway, inside the nucleus. We show that nuclear cAMP induces a LATS-dependent pathway leading to phosphorylation of nuclear YAP solely at serine 397 and export of YAP from the nucleus with no change in YAP protein stability. Thus, nuclear cAMP inhibition of nuclear YAP is distinct from other known mechanisms of Hippo regulation. Pharmacologic targeting of specific cAMP microdomains remains an untapped therapeutic approach for cancer; thus, drugs directed at the nuclear cAMP microdomain may provide avenues for the treatment of cancer., Competing Interests: Declaration of interests J.H.Z. is a paid consultant and is on the medical advisory board of Hoth Therapeutics, is on the medical advisory board of SHADE, Inc., and is an inventor on US patent 8859213 on the use of antibodies directed against sACs for the diagnosis of melanocytic proliferations. O.E. is a cofounder and equity holder in Volastra Therapeutics and OneThree Biotech, an equity holder and SAB member in Owkin, Freenome, Genetic Intelligence, and Acuamark DX, and receives funding from Eli Lilly, Janssen, and Sanofi. T.M. is consultant for Leap Therapeutics, Immunos Therapeutics, and Pfizer, is a cofounder of Imvaq Therapeutics, has equity in Imvaq Therapeutics, reports grants from Bristol-Myers Squibb, Surface Oncology, Kyn Therapeutics, Infinity Pharmaceuticals, Peregrine Pharmeceuticals, Adaptive Biotechnologies, Leap Therapeutics, and Aprea, and is an inventor on patent applications related to work on oncolytic viral therapy, alphavirus-based vaccines, neo-antigen modeling, CD40, GITR, OX40, PD-1, and CTLA-4., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Interrogating the tumor genome in its entirety by whole-genome sequencing (WGS) offers an unprecedented insight into the biology and pathogenesis of cancer, with potential impact on diagnostics, prognostication and therapy selection. WGS is able to detect sequence as well as structural variants and thereby combines central domains of cytogenetics and molecular genetics. Given the potential of WGS in directing targeted therapeutics and clinical decision-making, we envision a gradual transition of the method from research to clinical routine. This review is one out of three within this issue aimed at facilitating this effort, by discussing in-depth analytical validation, clinical interpretation and clinical utility of WGS. The review highlights the requirements for implementing, validating and maintaining a clinical WGS pipeline to obtain high-quality patient-specific data in accordance with the local regulatory landscape. Every step of the WGS pipeline, which includes DNA extraction, library preparation, sequencing, bioinformatics analysis, and data storage, is considered with respect to its logistics, necessities, potential pitfalls, and the required quality management. WGS is likely to drive clinical diagnostics and patient care forward, if requirements and challenges of the technique are recognized and met., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Precision diagnostics is one of the two pillars of precision medicine. Sequencing efforts in the past decade have firmly established cancer as a primarily genetically driven disease. This concept is supported by therapeutic successes aimed at particular pathways that are perturbed by specific driver mutations in protein-coding domains and reflected in three recent FDA tissue agnostic cancer drug approvals. In addition, there is increasing evidence from studies that interrogate the entire genome by whole-genome sequencing that acquired global and complex genomic aberrations including those in non-coding regions of the genome might also reflect clinical outcome. After addressing technical, logistical, financial and ethical challenges, national initiatives now aim to introduce clinical whole-genome sequencing into real-world diagnostics as a rational and potentially cost-effective tool for response prediction in cancer and to identify patients who would benefit most from 'expensive' targeted therapies and recruitment into clinical trials. However, so far, this has not been accompanied by a systematic and prospective evaluation of the clinical utility of whole-genome sequencing within clinical trials of uniformly treated patients of defined clinical outcome. This approach would also greatly facilitate novel predictive biomarker discovery and validation, ultimately reducing size and duration of clinical trials and cost of drug development. This manuscript is the third in a series of three to review and critically appraise the potential and challenges of clinical whole-genome sequencing in solid tumors and hematological malignancies., (Copyright © 2021. Published by Elsevier Ltd.)

Whole-genome sequencing either alone or in combination with whole-transcriptome sequencing has started to be used to analyze clinical tumor samples to improve diagnosis, provide risk stratification, and select patient-specific therapies. Compared with current genomic testing strategies, largely focused on small number of genes tested individually or targeted panels, whole-genome and transcriptome sequencing (WGTS) provides novel opportunities to identify and report a potentially much larger number of actionable alterations with diagnostic, prognostic, and/or predictive impact. Such alterations include point mutations, indels, copy- number aberrations and structural variants, but also germline variants, fusion genes, noncoding alterations and mutational signatures. Nevertheless, these comprehensive tests are accompanied by many challenges ranging from the extent and diversity of sequence alterations detected by these methods to the complexity and limited existing standardization in interpreting them. We describe the challenges of WGTS interpretation and the opportunities with comprehensive genomic testing., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Aberrant gene expression is a cancer hallmark and it is known that almost every tumor acquires somatic mutations in transcription factors, chromatin regulators, or the DNA regulatory elements that are critical for transcriptional control and cell phenotype. While the role of transcription factors and chromatin regulators has been widely studied, relatively few noncoding driver mutations have been identified and functionally characterized to date. Here, we review the current understanding of somatic variants in noncoding regions of the cancer genome and their impact on chromatin architecture and transcriptional networks. We also discuss approaches and ongoing challenges for noncoding driver discovery, and highlight insights gained from recent studies exploring the nature and impact of noncoding drivers on tumor formation., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Reduced p62 levels are associated with the induction of the cancer-associated fibroblast (CAF) phenotype, which promotes tumorigenesis in vitro and in vivo through inflammation and metabolic reprogramming. However, how p62 is downregulated in the stroma fibroblasts by tumor cells to drive CAF activation is an unresolved central issue in the field. Here we show that tumor-secreted lactate downregulates p62 transcriptionally through a mechanism involving reduction of the NAD + /NADH ratio, which impairs poly(ADP-ribose)-polymerase 1 (PARP-1) activity. PARP-1 inhibition blocks the poly(ADP-ribosyl)ation of the AP-1 transcription factors, c-FOS and c-JUN, which is an obligate step for p62 downregulation. Importantly, restoring p62 levels in CAFs by NAD + renders CAFs less active. PARP inhibitors, such as olaparib, mimick lactate in the reduction of stromal p62 levels, as well as the subsequent stromal activation both in vitro and in vivo, which suggests that therapies using olaparib would benefit from strategies aimed at inhibiting CAF activity., Competing Interests: Declaration of interests J.F.L., T.C.-D., J.M., and M.T.D.-M. are coinventors of a patent issued to Weill Cornell Medical College of Cornell University on “activation of the stroma by PARP-1 inhibitors.” J.M. and M.T.D.-M. are co-founders of Zelambio. O.E. is a scientific adviser and equity holder in Freenome, Owkin, Volastra Therapeutics, and OneThree Biotech. C.M.M. is a member of the Advisory Board of Cell Reports. All other authors declare no competing interests., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

Pan-cancer studies sketched the genomic landscape of the tumor types spectrum. We delineated the purity- and ploidy-adjusted allele-specific profiles of 4,950 patients across 27 tumor types from the Cancer Genome Atlas (TCGA). Leveraging allele-specific data, we reclassified as loss of heterozygosity (LOH) 9% and 7% of apparent copy-number wild-type and gain calls, respectively, and overall observed more than 18 million allelic imbalance somatic events at the gene level. Reclassification of copy-number events revealed associations between driver mutations and LOH, pointing out the timings between the occurrence of point mutations and copy-number events. Integrating allele-specific genomics and matched transcriptomics, we observed that allele-specific gene status is relevant in the regulation of TP53 and its targets. Further, we disclosed the role of copy-neutral LOH in the impairment of tumor suppressor genes and in disease progression. Our results highlight the role of LOH in cancer and contribute to the understanding of tumor progression., Competing Interests: Declaration of interests The authors declare no competing interests. Co-authors D.P. and A.L. are currently at Fondazione Bruno Kessler, Trento, Italy and Biotechnology Research and Innovation Center, University of Copenhagen, Denmark., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Older age is a strong risk factor for several diseases, including cancer. The etiology and biology of age-associated differences among cancers are poorly understood. To address this knowledge gap, we aim to delineate differences in tumor molecular characteristics between younger and older patients across a variety of tumor types from The Cancer Genome Atlas. We show that these groups exhibit widespread molecular differences in select tumor types. Our work shows that tumors in younger individuals exhibit a dysregulated molecular aging phenotype and are associated with hallmarks of premature senescence. Additionally, we find that these tumors are enriched for driver gene mutations, resulting in homologous recombination defects. Lastly, we observe a trend toward decreased immune infiltration and function in older patients and find that, immunologically, young tumor tissue resembles aged healthy tissue. Taken together, we find that tumors from young individuals possess unique characteristics that may be leveraged for therapy., Competing Interests: Declaration of interests O.E. is a scientific advisor and equity holder of Freenome, Owkin, Volastra Therapeutics, and One Three Biotech. A.V. is an employee of Volastra Therapeutics., (Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.)

Standfirst: Artificial intelligence and machine learning techniques are breaking into biomedical research and health care, which importantly includes cancer research and oncology, where the potential applications are vast. These include detection and diagnosis of cancer, subtype classification, optimization of cancer treatment and identification of new therapeutic targets in drug discovery. While big data used to train machine learning models may already exist, leveraging this opportunity to realize the full promise of artificial intelligence in both the cancer research space and the clinical space will first require significant obstacles to be surmounted. In this Viewpoint article, we asked four experts for their opinions on how we can begin to implement artificial intelligence while ensuring standards are maintained so as transform cancer diagnosis and the prognosis and treatment of patients with cancer and to drive biological discovery., (© 2021. ©UT-Battelle, LLC, under exclusive licence to Springer Nature Limited 2021.)

Background: Tumor sample quality and quantity determine the success of somatic mutation analysis. Thus, a rapid on-site evaluation (ROSE) tumor cytology adequacy assessment was incorporated into the workflow of precision oncology at Weill Cornell Medicine in New York City. Optimal samples were obtained from 68 patients with metastatic cancer., Methods: Cytopathologists performed ROSE on fine-needle aspirate samples via telepathology, and subsequently core-needle biopsies were obtained. In a retrospective manner, the concordance between adequacy assessment and the success rate of the procedure was evaluated to obtain sufficient tumor tissue for next-generation sequencing (NGS)., Results: Out of the 68 procedures, 43 were documented as adequate and 25 were documented as inadequate. The diagnostic yield of adequate procedures was 100%. Adequacy evaluation predicted the success rate of molecular profiling in 40 of 43 procedures (93%; 95% CI, 80.9-98.5 procedures). The success rate of molecular testing was significantly higher in the adequate group: 93% compared with 32% in the inadequate group (P < .0005). Seven procedures that failed to provide quality material for mutational analysis and pathological diagnosis were evaluated as inadequate. Cell block provided sufficient DNA for NGS in 6 cases. In 2 cases, a core biopsy could not be performed; hence, the fine-needle aspirate material confirmed the diagnosis and was used for NGS testing., Conclusion: These results support the incorporation of ROSE into the workflow of precision oncology to obtain high-quality tissue samples from metastatic lesions. In addition, NGS testing of concurrent cytology specimens with adequate cellularity can be a surrogate for NGS testing of biopsy specimens., (© 2021 American Cancer Society.)

Background: Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. Although labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still needs to be proved., Materials and Methods: In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 patients with cancer. We applied an NGS test that detects clinically relevant alterations in 33 genes and microsatellite instability (MSI) to analyze plasma cell-free DNA (cfDNA)., Results: The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. The NGS test detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared with 45% of those alterations found in the primary tumor samples (p = .00005). There was 87% agreement on MSI status between the NGS test and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, the NGS test revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in patients with advanced cancer., Conclusion: Our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice., Implications for Practice: This study proposes a solution for decentralized liquid biopsy testing based on validation of a next-generation sequencing (NGS) test that detects four classes of genomic alterations in blood: sequence mutations (single nucleotide substitutions or insertions and deletions), fusions, amplifications, and microsatellite instability (MSI). Although there are reference labs that perform single-site comprehensive liquid biopsy testing, the targeted assay this study validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To the authors' knowledge, this is the first report that validates evaluating an on-site plasma-based NGS test that detects the MSI status along with common sequence alterations encountered in solid tumors., (© 2021 AlphaMed Press.)

Cytosolic DNA is characteristic of chromosomally unstable metastatic cancer cells, resulting in constitutive activation of the cGAS-STING innate immune pathway. How tumors co-opt inflammatory signaling while evading immune surveillance remains unknown. Here, we show that the ectonucleotidase ENPP1 promotes metastasis by selectively degrading extracellular cGAMP, an immune-stimulatory metabolite whose breakdown products include the immune suppressor adenosine. ENPP1 loss suppresses metastasis, restores tumor immune infiltration, and potentiates response to immune checkpoint blockade in a manner dependent on tumor cGAS and host STING. Conversely, overexpression of wild-type ENPP1, but not an enzymatically weakened mutant, promotes migration and metastasis, in part through the generation of extracellular adenosine, and renders otherwise sensitive tumors completely resistant to immunotherapy. In human cancers, ENPP1 expression correlates with reduced immune cell infiltration, increased metastasis, and resistance to anti-PD-1/PD-L1 treatment. Thus, cGAMP hydrolysis by ENPP1 enables chromosomally unstable tumors to transmute cGAS activation into an immune-suppressive pathway. SIGNIFICANCE: Chromosomal instability promotes metastasis by generating chronic tumor inflammation. ENPP1 facilitates metastasis and enables tumor cells to tolerate inflammation by hydrolyzing the immunotransmitter cGAMP, preventing its transfer from cancer cells to immune cells. This article is highlighted in the In This Issue feature, p. 995 ., (©2020 American Association for Cancer Research.)

Artificial intelligence (AI) is rapidly reshaping cancer research and personalized clinical care. Availability of high-dimensionality datasets coupled with advances in high-performance computing, as well as innovative deep learning architectures, has led to an explosion of AI use in various aspects of oncology research. These applications range from detection and classification of cancer, to molecular characterization of tumors and their microenvironment, to drug discovery and repurposing, to predicting treatment outcomes for patients. As these advances start penetrating the clinic, we foresee a shifting paradigm in cancer care becoming strongly driven by AI. SIGNIFICANCE: AI has the potential to dramatically affect nearly all aspects of oncology-from enhancing diagnosis to personalizing treatment and discovering novel anticancer drugs. Here, we review the recent enormous progress in the application of AI to oncology, highlight limitations and pitfalls, and chart a path for adoption of AI in the cancer clinic., (©2021 American Association for Cancer Research.)

Context.—: An increasing number of molecular laboratories are implementing next-generation sequencing platforms to identify clinically actionable and relevant genomic alterations for precision oncology., Objective.—: To describe the validation studies as per New York State-Department of Health (NYS-DOH) guidelines for the Oncomine Comprehensive Panel v2, which was originally tailored to the National Cancer Institute Molecular Analysis for Therapy Choice (NCI-MATCH) trial., Design.—: Accuracy, precision, and reproducibility were investigated by using 130 DNA and 18 RNA samples from cytology cell blocks; formalin-fixed, paraffin-embedded tissues; and frozen samples. Analytic sensitivity and specificity were tested by using ATCC and HapMap cell lines., Results.—: High accuracy and precision/reproducibility were observed for single nucleotide variants and insertion/deletions. We also share our experience in the detection of gene fusions and copy number alterations from an amplicon-based sequencing platform. After sequencing analysis, variant annotation and report generation were performed by using the institutional knowledgebase., Conclusions.—: This study serves as an example for validating a comprehensive targeted next-generation sequencing assay with both DNASeq and RNASeq components for NYS-DOH., (© 2020 College of American Pathologists.)

Cancer genomes often harbor hundreds of somatic DNA rearrangement junctions, many of which cannot be easily classified into simple (e.g., deletion) or complex (e.g., chromothripsis) structural variant classes. Applying a novel genome graph computational paradigm to analyze the topology of junction copy number (JCN) across 2,778 tumor whole-genome sequences, we uncovered three novel complex rearrangement phenomena: pyrgo, rigma, and tyfonas. Pyrgo are "towers" of low-JCN duplications associated with early-replicating regions, superenhancers, and breast or ovarian cancers. Rigma comprise "chasms" of low-JCN deletions enriched in late-replicating fragile sites and gastrointestinal carcinomas. Tyfonas are "typhoons" of high-JCN junctions and fold-back inversions associated with expressed protein-coding fusions, breakend hypermutation, and acral, but not cutaneous, melanomas. Clustering of tumors according to genome graph-derived features identified subgroups associated with DNA repair defects and poor prognosis., Competing Interests: Declaration of Interests J.S.R.-F. reports receiving personal/consultancy fees from VolitionRx, Paige.AI, Goldman Sachs, REPARE Therapeutics, GRAIL, Ventana Medical Systems, Roche, Genentech, and InviCRO outside of the scope of the submitted work., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Endothelial cells adopt tissue-specific characteristics to instruct organ development and regeneration 1,2 . This adaptability is lost in cultured adult endothelial cells, which do not vascularize tissues in an organotypic manner. Here, we show that transient reactivation of the embryonic-restricted ETS variant transcription factor 2 (ETV2) 3 in mature human endothelial cells cultured in a serum-free three-dimensional matrix composed of a mixture of laminin, entactin and type-IV collagen (LEC matrix) 'resets' these endothelial cells to adaptable, vasculogenic cells, which form perfusable and plastic vascular plexi. Through chromatin remodelling, ETV2 induces tubulogenic pathways, including the activation of RAP1, which promotes the formation of durable lumens 4,5 . In three-dimensional matrices-which do not have the constraints of bioprinted scaffolds-the 'reset' vascular endothelial cells (R-VECs) self-assemble into stable, multilayered and branching vascular networks within scalable microfluidic chambers, which are capable of transporting human blood. In vivo, R-VECs implanted subcutaneously in mice self-organize into durable pericyte-coated vessels that functionally anastomose to the host circulation and exhibit long-lasting patterning, with no evidence of malformations or angiomas. R-VECs directly interact with cells within three-dimensional co-cultured organoids, removing the need for the restrictive synthetic semipermeable membranes that are required for organ-on-chip systems, therefore providing a physiological platform for vascularization, which we call 'Organ-On-VascularNet'. R-VECs enable perfusion of glucose-responsive insulin-secreting human pancreatic islets, vascularize decellularized rat intestines and arborize healthy or cancerous human colon organoids. Using single-cell RNA sequencing and epigenetic profiling, we demonstrate that R-VECs establish an adaptive vascular niche that differentially adjusts and conforms to organoids and tumoroids in a tissue-specific manner. Our Organ-On-VascularNet model will permit metabolic, immunological and physiochemical studies and screens to decipher the crosstalk between organotypic endothelial cells and parenchymal cells for identification of determinants of endothelial cell heterogeneity, and could lead to advances in therapeutic organ repair and tumour targeting.

Precision oncology relies on accurate discovery and interpretation of genomic variants, enabling individualized diagnosis, prognosis and therapy selection. We found that six prominent somatic cancer variant knowledgebases were highly disparate in content, structure and supporting primary literature, impeding consensus when evaluating variants and their relevance in a clinical setting. We developed a framework for harmonizing variant interpretations to produce a meta-knowledgebase of 12,856 aggregate interpretations. We demonstrated large gains in overlap between resources across variants, diseases and drugs as a result of this harmonization. We subsequently demonstrated improved matching between a patient cohort and harmonized interpretations of potential clinical significance, observing an increase from an average of 33% per individual knowledgebase to 57% in aggregate. Our analyses illuminate the need for open, interoperable sharing of variant interpretation data. We also provide a freely available web interface (search.cancervariants.org) for exploring the harmonized interpretations from these six knowledgebases.

The remarkable success of cancer immunotherapies, especially the checkpoint blocking antibodies, in a subset of patients has reinvigorated the study of tumor-immune crosstalk and its role in heterogeneity of response. High-throughput sequencing and imaging technologies can help recapitulate various aspects of the tumor ecosystem. Computational approaches provide an arsenal of tools to efficiently analyze, quantify and integrate multiple parameters of tumor immunity mined from these diverse but complementary high-throughput datasets. This chapter describes numerous such computational approaches in tumor immunology that leverage high-throughput data from diverse sources (genomic, transcriptomics, epigenomics and digitized histopathology images) to systematically interrogate tumor immunity in context of its microenvironment, and to identify mechanisms that confer resistance or sensitivity to cancer therapies, in particular immunotherapy., (© 2020 Elsevier Inc. All rights reserved.)

The expression of antigens that are recognized by self-reactive T cells is essential for immune-mediated tumor rejection by immune checkpoint blockade (ICB) therapy. Growing evidence suggests that mutation-associated neoantigens drive ICB responses in tumors with high mutational burden. In most patients, only a few of the mutations in the cancer exome that are predicted to be immunogenic are recognized by T cells. One factor that limits this recognition is the level of expression of the mutated gene product in cancer cells. Substantial preclinical data show that radiation can convert the irradiated tumor into a site for priming of tumor-specific T cells, that is, an in situ vaccine, and can induce responses in otherwise ICB-resistant tumors. Critical for radiation-elicited T-cell activation is the induction of viral mimicry, which is mediated by the accumulation of cytosolic DNA in the irradiated cells, with consequent activation of the cyclic GMP-AMP synthase (cGAS)/stimulator of interferon (IFN) genes (STING) pathway and downstream production of type I IFN and other pro-inflammatory cytokines. Recent data suggest that radiation can also enhance cancer cell antigenicity by upregulating the expression of a large number of genes that are involved in the response to DNA damage and cellular stress, thus potentially exposing immunogenic mutations to the immune system. Here, we discuss how the principles of antigen presentation favor the presentation of peptides that are derived from newly synthesized proteins in irradiated cells. These concepts support a model that incorporates the presence of immunogenic mutations in genes that are upregulated by radiation to predict which patients might benefit from treatment with combinations of radiotherapy and ICB.

Purpose: Dopamine receptor D2 (DRD2) is a G protein-coupled receptor antagonized by ONC201, an anticancer small molecule in clinical trials for high-grade gliomas and other malignancies. DRD5 is a dopamine receptor family member that opposes DRD2 signaling. We investigated the expression of these dopamine receptors in cancer and their influence on tumor cell sensitivity to ONC201., Experimental Design: The Cancer Genome Atlas was used to determine DRD2/DRD5 expression broadly across human cancers. Cell viability assays were performed with ONC201 in >1,000 Genomic of Drug Sensitivity in Cancer and NCI60 cell lines. IHC staining of DRD2/DRD5 was performed on tissue microarrays and archival tumor tissues of glioblastoma patients treated with ONC201. Whole exome sequencing was performed in RKO cells with and without acquired ONC201 resistance. Wild-type and mutant DRD5 constructs were generated for overexpression studies., Results: DRD2 overexpression broadly occurs across tumor types and is associated with a poor prognosis. Whole exome sequencing of cancer cells with acquired resistance to ONC201 revealed a de novo Q366R mutation in the DRD5 gene. Expression of Q366R DRD5 was sufficient to induce tumor cell apoptosis, consistent with a gain-of-function. DRD5 overexpression in glioblastoma cells enhanced DRD2/DRD5 heterodimers and DRD5 expression was inversely correlated with innate tumor cell sensitivity to ONC201. Investigation of archival tumor samples from patients with recurrent glioblastoma treated with ONC201 revealed that low DRD5 expression was associated with relatively superior clinical outcomes., Conclusions: These results implicate DRD5 as a negative regulator of DRD2 signaling and tumor sensitivity to ONC201 DRD2 antagonism., (©2018 American Association for Cancer Research.)

Suppressing glutaminolysis does not always induce cancer cell death in glutamine dependent tumors because cells may switch to alternative energy sources. To reveal compensatory metabolic pathways, we investigated the metabolome-wide cellular response to inhibited glutaminolysis in cancer cells. Glutaminolysis inhibition with C.968 suppressed cell proliferation but was insufficient to induce cancer cell death. We found that lipid catabolism was activated as a compensation for glutaminolysis inhibition. Accelerated lipid catabolism, together with oxidative stress induced by glutaminolysis inhibition, triggered autophagy. Simultaneously inhibiting glutaminolysis and either beta oxidation with trimetazidine or autophagy with chloroquine both induced cancer cell death. Here we identified metabolic escape mechanisms contributing to cancer cell survival under treatment and we suggest potentially translational strategy for combined cancer therapy, given that chloroquine is an FDA approved drug. Our findings are first to show efficiency of combined inhibition of glutaminolysis and beta oxidation as potential anti-cancer strategy as well as add to the evidence that combined inhibition of glutaminolysis and autophagy may be effective in glutamine-addicted cancers., (Copyright © 2018 The Author(s). Published by Elsevier B.V. All rights reserved.)

Epigenetic modifications play a key role in cellular development and tumorigenesis. Recent large-scale genomic studies have shown that mutations in players of the epigenetic machinery and concomitant perturbation of epigenomic patterning are frequent events in tumors. Among epigenetic marks, DNA methylation is one of the best studied. Hyper- and hypo-methylation events of specific regulatory elements (such as promoters and enhancers) are sometimes thought to be correlated with expression of nearby genes. High-throughput bisulfite converted sequencing is currently the technology of choice for studying DNA methylation in base-pair resolution and on whole-genome scale. Such broad and high-resolution coverage investigations of the epigenome provide unprecedented opportunities to analyze DNA methylation patterns, which are correlated with tumorigenesis, tumor evolution, and tumor progression. However, few computational pipelines are available to the public to perform systematic DNA methylation analysis. Utilizing open source tools, we here describe a comprehensive computational methodology to thoroughly analyze DNA methylation patterns during tumor evolution based on bisulfite converted sequencing data, including intra-tumor methylation heterogeneity.

Pathological evaluation of tumor tissue is pivotal for diagnosis in cancer patients and automated image analysis approaches have great potential to increase precision of diagnosis and help reduce human error. In this study, we utilize several computational methods based on convolutional neural networks (CNN) and build a stand-alone pipeline to effectively classify different histopathology images across different types of cancer. In particular, we demonstrate the utility of our pipeline to discriminate between two subtypes of lung cancer, four biomarkers of bladder cancer, and five biomarkers of breast cancer. In addition, we apply our pipeline to discriminate among four immunohistochemistry (IHC) staining scores of bladder and breast cancers. Our classification pipeline includes a basic CNN architecture, Google's Inceptions with three training strategies, and an ensemble of two state-of-the-art algorithms, Inception and ResNet. Training strategies include training the last layer of Google's Inceptions, training the network from scratch, and fine-tunning the parameters for our data using two pre-trained version of Google's Inception architectures, Inception-V1 and Inception-V3. We demonstrate the power of deep learning approaches for identifying cancer subtypes, and the robustness of Google's Inceptions even in presence of extensive tumor heterogeneity. On average, our pipeline achieved accuracies of 100%, 92%, 95%, and 69% for discrimination of various cancer tissues, subtypes, biomarkers, and scores, respectively. Our pipeline and related documentation is freely available at https://github.com/ih-&#95;lab/CNN&#95;Smoothie., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Targeted cancer therapies that use genetics are successful, but principles for selectively targeting tumor metabolism that is also dependent on the environment remain unknown. We now show that differences in rate-controlling enzymes during the Warburg effect (WE), the most prominent hallmark of cancer cell metabolism, can be used to predict a response to targeting glucose metabolism. We establish a natural product, koningic acid (KA), to be a selective inhibitor of GAPDH, an enzyme we characterize to have differential control properties over metabolism during the WE. With machine learning and integrated pharmacogenomics and metabolomics, we demonstrate that KA efficacy is not determined by the status of individual genes, but by the quantitative extent of the WE, leading to a therapeutic window in vivo. Thus, the basis of targeting the WE can be encoded by molecular principles that extend beyond the status of individual genes., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: This paper describes the Precision Medicine Knowledge Base (PMKB; https://pmkb.weill.cornell.edu ), an interactive online application for collaborative editing, maintenance, and sharing of structured clinical-grade cancer mutation interpretations., Materials and Methods: PMKB was built using the Ruby on Rails Web application framework. Leveraging existing standards such as the Human Genome Variation Society variant description format, we implemented a data model that links variants to tumor-specific and tissue-specific interpretations. Key features of PMKB include support for all major variant types, standardized authentication, distinct user roles including high-level approvers, and detailed activity history. A REpresentational State Transfer (REST) application-programming interface (API) was implemented to query the PMKB programmatically., Results: At the time of writing, PMKB contains 457 variant descriptions with 281 clinical-grade interpretations. The EGFR, BRAF, KRAS, and KIT genes are associated with the largest numbers of interpretable variants. PMKB's interpretations have been used in over 1500 AmpliSeq tests and 750 whole-exome sequencing tests. The interpretations are accessed either directly via the Web interface or programmatically via the existing API., Discussion: An accurate and up-to-date knowledge base of genomic alterations of clinical significance is critical to the success of precision medicine programs. The open-access, programmatically accessible PMKB represents an important attempt at creating such a resource in the field of oncology., Conclusion: The PMKB was designed to help collect and maintain clinical-grade mutation interpretations and facilitate reporting for clinical cancer genomic testing. The PMKB was also designed to enable the creation of clinical cancer genomics automated reporting pipelines via an API., (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association.)

ONC201 is the founding member of a novel class of anti-cancer compounds called imipridones that is currently in Phase II clinical trials in multiple advanced cancers. Since the discovery of ONC201 as a p53-independent inducer of TRAIL gene transcription, preclinical studies have determined that ONC201 has anti-proliferative and pro-apoptotic effects against a broad range of tumor cells but not normal cells. The mechanism of action of ONC201 involves engagement of PERK-independent activation of the integrated stress response, leading to tumor upregulation of DR5 and dual Akt/ERK inactivation, and consequent Foxo3a activation leading to upregulation of the death ligand TRAIL. ONC201 is orally active with infrequent dosing in animals models, causes sustained pharmacodynamic effects, and is not genotoxic. The first-in-human clinical trial of ONC201 in advanced aggressive refractory solid tumors confirmed that ONC201 is exceptionally well-tolerated and established the recommended phase II dose of 625 mg administered orally every three weeks defined by drug exposure comparable to efficacious levels in preclinical models. Clinical trials are evaluating the single agent efficacy of ONC201 in multiple solid tumors and hematological malignancies and exploring alternative dosing regimens. In addition, chemical analogs that have shown promise in other oncology indications are in pre-clinical development. In summary, the imipridone family that comprises ONC201 and its chemical analogs represent a new class of anti-cancer therapy with a unique mechanism of action being translated in ongoing clinical trials.

Importance: Understanding molecular mechanisms of response and resistance to anticancer therapies requires prospective patient follow-up and clinical and functional validation of both common and low-frequency mutations. We describe a whole-exome sequencing (WES) precision medicine trial focused on patients with advanced cancer., Objective: To understand how WES data affect therapeutic decision making in patients with advanced cancer and to identify novel biomarkers of response., Design, Setting, and Patients: Patients with metastatic and treatment-resistant cancer were prospectively enrolled at a single academic center for paired metastatic tumor and normal tissue WES during a 19-month period (February 2013 through September 2014). A comprehensive computational pipeline was used to detect point mutations, indels, and copy number alterations. Mutations were categorized as category 1, 2, or 3 on the basis of actionability; clinical reports were generated and discussed in precision tumor board. Patients were observed for 7 to 25 months for correlation of molecular information with clinical response., Main Outcomes and Measures: Feasibility, use of WES for decision making, and identification of novel biomarkers., Results: A total of 154 tumor-normal pairs from 97 patients with a range of metastatic cancers were sequenced, with a mean coverage of 95X and 16 somatic alterations detected per patient. In total, 16 mutations were category 1 (targeted therapy available), 98 were category 2 (biologically relevant), and 1474 were category 3 (unknown significance). Overall, WES provided informative results in 91 cases (94%), including alterations for which there is an approved drug, there are therapies in clinical or preclinical development, or they are considered drivers and potentially actionable (category 1-2); however, treatment was guided in only 5 patients (5%) on the basis of these recommendations because of access to clinical trials and/or off-label use of drugs. Among unexpected findings, a patient with prostate cancer with exceptional response to treatment was identified who harbored a somatic hemizygous deletion of the DNA repair gene FANCA and putative partial loss of function of the second allele through germline missense variant. Follow-up experiments established that loss of FANCA function was associated with platinum hypersensitivity both in vitro and in patient-derived xenografts, thus providing biologic rationale and functional evidence for his extreme clinical response., Conclusions and Relevance: The majority of advanced, treatment-resistant tumors across tumor types harbor biologically informative alterations. The establishment of a clinical trial for WES of metastatic tumors with prospective follow-up of patients can help identify candidate predictive biomarkers of response.

The transformation of normal cells into cancer cells and maintenance of the malignant state and phenotypes are associated with genetic and epigenetic deregulations, altered cellular signaling responses and aberrant interactions with the microenvironment. These alterations are constantly evolving as tumor cells face changing selective pressures induced by the cells themselves, the microenvironment and drug treatments. Tumors are also complex ecosystems where different, sometime heterogeneous, subclonal tumor populations and a variety of nontumor cells coexist in a constantly evolving manner. The interactions between molecules and between cells that arise as a result of these alterations and ecosystems are even more complex. The cancer research community is increasingly embracing this complexity and adopting a combination of systems biology methods and integrated analyses to understand and predictively model the activity of cancer cells. Systems biology approaches are helping to understand the mechanisms of tumor progression and design more effective cancer therapies. These approaches work in tandem with rapid technological advancements that enable data acquisition on a broader scale, with finer accuracy, higher dimensionality and higher throughput than ever. Using such data, computational and mathematical models help identify key deregulated functions and processes, establish predictive biomarkers and optimize therapeutic strategies. Moving forward, implementing patient-specific computational and mathematical models of cancer will significantly improve the specificity and efficacy of targeted therapy, and will accelerate the adoption of personalized and precision cancer medicine.