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Cancer is an evolutionary process shaped by selective pressure from the microenvironments. However, recent studies reveal that certain tumors undergo neutral evolution where there is no detectable fitness difference amongst the cells following malignant transformation. Here, through computational modeling, we demonstrate that negative frequency-dependent selection (or NFDS), where the immune response against cancer cells depends on the clonality of neoantigens, can lead to an immunogenic landscape that is highly similar to neutral evolution. Crucially, NFDS promotes high antigenic heterogeneity and early immune evasion in hypermutable tumors, leading to poor responses to immune checkpoint blockade (ICB) therapy. Our model also reveals that NFDS is characterized by a negative association between average clonality and total burden of neoantigens. Indeed, this unique feature of NFDS is common in the whole-exome sequencing (WES) datasets (357 tumor samples from 275 patients) from four melanoma cohorts with ICB therapy and a non-small cell lung cancer (NSCLC) WES dataset (327 tumor samples from 100 patients). Altogether, our study provides quantitative evidence supporting the theory of NFDS in cancer, explaining the high prevalence of neutral-looking tumors. These findings also highlight the critical role of frequency-dependent selection in devising more efficient and predictive immunotherapies. Computational modeling and cancer genomics analysis reveal a new scenario of cancer immune evasion owing to negative frequency-dependent selection (NFDS) of neoantigens, which highlights the role of NFDS in predicting immunotherapy response.

Comprehensive analysis of connections between germline variants and somatic events in cancer offers a resource for investigating the functional significance of genetic mutations and exploring genetic factors contributing to racial disparities. Inherited germline and acquired somatic alterations can both promote human tumor development. Elucidating the cooperation between somatic and germline genetic alterations that drive tumorigenesis could help inform precision cancer prevention and treatment strategies. Here, leveraging genomic genotyping and sequencing data from 9,029 patients with cancer with European, East Asian, and African ancestry, we performed a pan-cancer analysis to evaluate the associations between germline SNPs and somatic alterations, including single-nucleotide variant and small insertion/deletion mutations, copy-number variation, tumor mutational burden, and mutational signatures. Genome-wide significant germline-somatic pairs were abundant, and most of the associations were observed in one cancer type and one ancestry group. A user-friendly interactive Multiethnic Germline-Somatic Association (MGSA) database (http://wanglab-hkust.cn:3838/MGSA/) was developed, which can be used to query, browse, and download the results of the association analyses. Moreover, the MGSA database offers additional survival analysis and functional annotation. Together, this work provides a resource for uncovering the clinical and biological roles of associations between germline variants and somatic alterations in human cancer.Significance: Comprehensive analysis of connections between germline variants and somatic events in cancer offers a resource for investigating the functional significance of genetic mutations and exploring genetic factors contributing to racial disparities.

Background: Intracranial plasmacytomas are rare tumors arising from plasma cells with approximately half of the cases progressing to multiple myeloma (MM). However, there is a lack of comprehensive clinical cohort analysis on the clinical and pathological features, progression, and outcomes of intracranial plasmacytomas. Methods: A retrospective analysis of 190 cases was conducted, combining data from 38 cases in a single institution and 152 cases from the literature. Patient demographics, clinical presentations, tumor locations, imaging features, surgical treatments, and follow-up outcomes were collected and analyzed. Survival analysis and Cox regression analysis were performed to identify prognostic factors. Results: A total of 190 intracranial plasmacytoma patients with an average age of 55.4 years were included in the study. The preoperative misdiagnosis ratio was high at 55.3%, and 59.7% of the tumors affected the calvaria convexity, compared to 40.3% located at the skull base. Resection and biopsy were achieved in 72.4% and 27.6% patients, respectively. Among them, 34.2% (65/190) of patients were initially diagnosed with MM with intracranial plasmacytoma as their first presentation (MM-IPFP), while 63.2% (120/190) of patients were diagnosed with solitary intracranial plasmacytoma (SIP), including 61 extramedullary plasmacytomas and 59 solitary bone plasmacytomas. In the SIP group, 22.4% (24/107) of patients experienced disease progression leading to the development of MM during a median follow-up time of 42.6 months (range 1-230 months). Multivariate analysis unveiled that radiotherapy (HR, 0.05; 95% CI, 0.00-0.87; p = 0.04), not surgery, was a protective prognostic factor for overall survival in MM-IPFP patients. Comparison between the SIP progression group and non-progression group revealed a significant difference of Ki-67 index (non-progression vs. SIP progression, 8.82% +/- 7.03 vs. 16.5% +/- 10.5, p < 0.05). AUC analysis determined that a cutoff value of

Almost all Glioblastoma (GBM) are either intrinsically resistant to the chemotherapeutical drug temozolomide (TMZ) or acquire therapy-induced mutations that cause chemoresistance and recurrence. The genome maintenance mechanisms responsible for GBM chemoresistance and hypermutation are unknown. We show that the E3 ubiquitin ligase RAD18 (a proximal regulator of TLS) is activated in a Mismatch repair (MMR)-dependent manner in TMZ-treated GBM cells, promoting post-replicative gap-filling and survival. An unbiased CRISPR screen provides an aerial map of RAD18-interacting DNA damage response (DDR) pathways deployed by GBM to tolerate TMZ genotoxicity. Analysis of mutation signatures from TMZ-treated GBM reveals a role for RAD18 in error-free bypass of O6mG (the most toxic TMZ-induced lesion), and error-prone bypass of other TMZ-induced lesions. Our analyses of recurrent GBM patient samples establishes a correlation between low RAD18 expression and hypermutation. Taken together we define molecular underpinnings for the hallmark tumorigenic phenotypes of TMZ-treated GBM.

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range of tasks, is advancing healthcare. It promotes the development of healthcare artificial intelligence (AI) models, breaking the contradiction between limited AI models and diverse healthcare practices. Much more widespread healthcare scenarios will benefit from the development of a healthcare foundation model (HFM), improving their advanced intelligent healthcare services. Despite the impending widespread deployment of HFMs, there is currently a lack of clear understanding about how they work in the healthcare field, their current challenges, and where they are headed in the future. To answer these questions, a comprehensive and deep survey of the challenges, opportunities, and future directions of HFMs is presented in this survey. It first conducted a comprehensive overview of the HFM including the methods, data, and applications for a quick grasp of the current progress. Then, it made an in-depth exploration of the challenges present in data, algorithms, and computing infrastructures for constructing and widespread application of foundation models in healthcare. This survey also identifies emerging and promising directions in this field for future development. We believe that this survey will enhance the community's comprehension of the current progress of HFM and serve as a valuable source of guidance for future development in this field. The latest HFM papers and related resources are maintained on our website: this https URL.

Foundation model, which is pre-trained on broad data and is able to adapt to a wide range of tasks, is advancing healthcare. It promotes the development of healthcare artificial intelligence (AI) models, breaking the contradiction between limited AI models and diverse healthcare practices. Much more widespread healthcare scenarios will benefit from the development of a healthcare foundation model (HFM), improving their advanced intelligent healthcare services. Despite the impending widespread deployment of HFMs, there is currently a lack of clear understanding about how they work in the healthcare field, their current challenges, and where they are headed in the future. To answer these questions, a comprehensive and deep survey of the challenges, opportunities, and future directions of HFMs is presented in this survey. It first conducted a comprehensive overview of the HFM including the methods, data, and applications for a quick grasp of the current progress. Then, it made an in-depth exploration of the challenges present in data, algorithms, and computing infrastructures for constructing and widespread application of foundation models in healthcare. This survey also identifies emerging and promising directions in this field for future development. We believe that this survey will enhance the community's comprehension of the current progress of HFM and serve as a valuable source of guidance for future development in this field. The latest HFM papers and related resources are maintained on our website: https://github.com/YutingHe-list/Awesome-Foundation-Models-for-Advancing-Healthcare.

Gastric cancer (GC) is a prevalent malignancy worldwide, ranking as the fifth most common cancer with over 1 million new cases and 700 thousand deaths in 2020. Locally advanced gastric cancer (LAGC) accounts for approximately two-thirds of GC diagnoses, and neoadjuvant chemotherapy (NACT) has emerged as the standard treatment for LAGC. However, the effectiveness of NACT varies significantly among patients, with a considerable subset displaying treatment resistance. Ineffective NACT not only leads to adverse effects but also misses the optimal therapeutic window, resulting in lower survival rate. However, existing multimodal learning methods assume the availability of all modalities for each patient, which does not align with the reality of clinical practice. The limited availability of modalities for each patient would cause information loss, adversely affecting predictive accuracy. In this study, we propose an incomplete multimodal data integration framework for GC (iMD4GC) to address the challenges posed by incomplete multimodal data, enabling precise response prediction and survival analysis. Specifically, iMD4GC incorporates unimodal attention layers for each modality to capture intra-modal information. Subsequently, the cross-modal interaction layers explore potential inter-modal interactions and capture complementary information across modalities, thereby enabling information compensation for missing modalities. To evaluate iMD4GC, we collected three multimodal datasets for GC study: GastricRes (698 cases) for response prediction, GastricSur (801 cases) for survival analysis, and TCGA-STAD (400 cases) for survival analysis. The scale of our datasets is significantly larger than previous studies. The iMD4GC achieved impressive performance with an 80.2% AUC on GastricRes, 71.4% C-index on GastricSur, and 66.1% C-index on TCGA-STAD, significantly surpassing other compared methods., Comment: 27 pages, 9 figures, 3 tables (under review)

Whole-genome sequencing of longitudinal tumor pairs representing transformation of follicular lymphoma to high-grade B cell lymphoma with MYC and BCL2 rearrangements (double-hit lymphoma) identified coding and noncoding genomic alterations acquired during lymphoma progression. Many of these transformation-associated alterations recurrently and focally occur at topologically associating domain resident regulatory DNA elements, including H3K4me3 promoter marks located within H3K27ac super-enhancer clusters in B cell non-Hodgkin lymphoma. One region found to undergo recurrent alteration upon transformation overlaps a super-enhancer affecting the expression of the PAX5 / ZCCHC7 gene pair. ZCCHC7 encodes a subunit of the Trf4/5-Air1/2-Mtr4 polyadenylation-like complex and demonstrated copy number gain, chromosomal translocation and enhancer retargeting-mediated transcriptional upregulation upon lymphoma transformation. Consequently, lymphoma cells demonstrate nucleolar dysregulation via altered noncoding 5.8S ribosomal RNA processing. We find that a noncoding mutation acquired during lymphoma progression affects noncoding rRNA processing, thereby rewiring protein synthesis leading to oncogenic changes in the lymphoma proteome., SCOPUS: ar.j, info:eu-repo/semantics/published

Clonal evolution drives cancer progression and therapeutic resistance. Recent studies have revealed divergent longitudinal trajectories in gliomas, but early molecular features steering posttreatment cancer evolution remain unclear. Here, we collected sequencing and clinical data of initial-recurrent tumor pairs from 544 adult diffuse gliomas and performed multivariate analysis to identify early molecular predictors of tumor evolution in three diffuse glioma subtypes. We found that CDKN2A deletion at initial diagnosis preceded tumor necrosis and microvascular proliferation that occur at later stages of IDH-mutant glioma. Ki67 expression at diagnosis was positively correlated with acquiring hypermutation at recurrence in the IDH-wild-type glioma. In all glioma subtypes, MYC gain or MYC-target activation at diagnosis was associated with treatment-induced hypermutation at recurrence. To predict glioma evolution, we constructed CELLO2 (Cancer EvoLution for LOngitudinal data version 2), a machine learning model integrating features at diagnosis to forecast hypermutation and progression after treatment. CELLO2 successfully stratified patients into subgroups with distinct prognoses and identified a high-risk patient group featured by MYC gain with worse post-progression survival, from the low-grade IDH-mutant-noncodel subtype. We then performed chronic temozolomide-induction experiments in glioma cell lines and isogenic patient-derived gliomaspheres and demonstrated that MYC drives temozolomide resistance by promoting hypermutation. Mechanistically, we demonstrated that, by binding to open chromatin and transcriptionally active genomic regions, c-MYC increases the vulnerability of key mismatch repair genes to treatment-induced mutagenesis, thus triggering hypermutation. This study reveals early predictors of cancer evolution under therapy and provides a resource for precision oncology targeting cancer dynamics in diffuse gliomas.

The role of brain immune compartments in glioma evolution remains elusive. We profile immune cells in glioma microenvironment and the matched peripheral blood from 11 patients. Glioblastoma exhibits specific infiltration of blood-originated monocytes expressing epidermal growth factor receptor (EGFR) ligands EREG and AREG, coined as tumor-associated monocytes (TAMo). TAMo infiltration is mutually exclusive with EGFR alterations (p = 0.019), while co-occurring with mesenchymal subtype (p = 4.7 3 10-7) and marking worse prognosis (p = 0.004 and 0.032 in two cohorts). Evolutionary analysis of initial-recurrent glioma pairs and single-cell study of a multi-centric glioblastoma reveal association between elevated TAMo and glioma mesenchymal transformation. Further analyses identify FOSL2 as a TAMo master regulator and demonstrates that FOSL2-EREG/AREG-EGFR signaling axis promotes glioma invasion in vitro. Collectively, we identify TAMo in tumor microenvironment and reveal its driving role in activating EGFR signaling to shape glioma evolution.

In the published version of Figure 21, an error appeared in Figure 2C on page 1468. In Figure 2C, the Kaplan-Meier estimation of the overall survival of patients with recurrent DG classified according to molecular subtypes was mistakenly covered by the curves of patients with primary DGs during the figure layout process, while the number statistic under the figure is correct. Figure 2C has been updated to correct this mistake. The error does not affect the conclusions of this article. We apologize for the error and for any confusion that it might have caused.

Background: Although temozolomide (TMZ) has been used as a standard adjuvant chemotherapeutic agent for primary glioblastoma (GBM), treating isocitrate dehydrogenase wild-type (IDH-wt) cases remains challenging due to intrinsic and acquired drug resistance. Therefore, elucidation of the molecular mechanisms of TMZ resistance is critical for its precision application. Methods: We stratified 69 primary IDH-wt GBM patients into TMZ-resistant (n = 29) and sensitive (n = 40) groups, using TMZ screening of the corresponding patient-derived glioma stem-like cells (GSCs). Genomic and transcriptomic features were then examined to identify TMZ-associated molecular alterations. Subsequently, we developed a machine learning (ML) model to predict TMZ response from combined signatures. Moreover, TMZ response in multisector samples (52 tumor sectors from 18 cases) was evaluated to validate findings and investigate the impact of intra-tumoral heterogeneity on TMZ efficacy. Results: In vitro TMZ sensitivity of patient-derived GSCs classified patients into groups with different survival outcomes (P = 1.12e−4 for progression-free survival (PFS) and 3.63e−4 for overall survival (OS)). Moreover, we found that elevated gene expression of EGR4, PAPPA, LRRC3, and ANXA3 was associated to intrinsic TMZ resistance. In addition, other features such as 5-aminolevulinic acid negative, mesenchymal/proneural expression subtypes, and hypermutation phenomena were prone to promote TMZ resistance. In contrast, concurrent copy-number-alteration in PTEN, EGFR, and CDKN2A/B was more frequent in TMZ-sensitive samples (Fisher’s exact P = 0.0102), subsequently consolidated by multi-sector sequencing analyses. Integrating all features, we trained a ML tool to segregate TMZ-resistant and sensitive groups. Notably, our method segregated IDH-wt GBM patients from The Cancer Genome Atlas (TCGA) into two groups with divergent survival outcomes (P = 4.58e−4 for PFS and 3.66e−4 for OS). Furthermore, we showed a high

Objective: Extra-axial cavernous hemangiomas (ECHs) are sporadic and rare intracranial occupational lesions that usually occur within the cavernous sinus. The aetiology of ECHs remains unknown. Methods: Whole-exome sequencing was performed on ECH lesions from 12 patients (discovery cohort) and droplet digital polymerase-chain-reaction (ddPCR) was used to confirm the identified mutation in 46 additional cases (validation cohort). Laser capture microdissection (LCM) was carried out to capture and characterise subgroups of tissue cells. Mechanistic and functional investigations were carried out in human umbilical vein endothelial cells and a newly established mouse model. Results: We detected somatic GJA4 mutation (c.121G>T, p.G41C) in 5/12 patients with ECH in the discovery cohort and confirmed the finding in the validation cohort (16/46). LCM followed by ddPCR revealed that the mutation was enriched in lesional endothelium. In vitro experiments in endothelial cells demonstrated that the GJA4 mutation activated SGK-1 signalling that in turn upregulated key genes involved in cell hyperproliferation and the loss of arterial specification. Compared with wild-type littermates, mice overexpressing the GJA4 mutation developed ECH-like pathological morphological characteristics (dilated venous lumen and elevated vascular density) in the retinal superficial vascular plexus at the postnatal 3 weeks, which were reversed by an SGK1 inhibitor, EMD638683. Conclusions: We identified a somatic GJA4 mutation that presents in over one-third of ECH lesions and proposed that ECHs are vascular malformations due to GJA4-induced activation of the SGK1 signalling pathway in brain endothelial cells.

Single-cell multi-omics can provide a unique perspective on tumor cellular heterogeneity. Most previous single-cell whole-genome RNA sequencing (scWGS-RNA-seq) methods demonstrate utility with intact cells from fresh samples. Among them, many are not applicable to frozen samples that cannot produce intact single-cell suspensions. We have developed scONE-seq, a versatile scWGS-RNA-seq method that amplifies single-cell DNA and RNA without separating them from each other and hence is compatible with frozen biobanked samples. We benchmarked scONE-seq against existing methods using fresh and frozen samples to demonstrate its performance in various aspects. We identified a unique transcriptionally normal-like tumor clone by analyzing a 2-year frozen astrocytoma sample, demonstrating that performing single-cell multi-omics interrogation on biobanked tissue by scONE-seq could enable previously unidentified discoveries in tumor biology.

Cerebral cavernous malformations (CCMs) refer to a common vascular abnormality that affects up to 0.5% of the population. A somatic gain-of-function mutation in MAP3K3 (p.I441M) was recently reported in sporadic CCMs, frequently accompanied by somatic activating PIK3CA mutations in diseased endothelium. However, the molecular mechanisms of these driver genes remain elusive. In this study, we performed whole-exome sequencing and droplet digital polymerase chain reaction to analyze CCM lesions and the matched blood from sporadic patients. 44 of 94 cases harbored mutations in KRIT1/CCM2 or MAP3K3, of which 75% were accompanied by PIK3CA mutations (P = 0.006). AAV-BR1-mediated brain endothelial-specific MAP3K3I441M overexpression induced CCM-like lesions throughout the brain and spinal cord in adolescent mice. Interestingly, over half of lesions disappeared at adulthood. Single-cell RNA sequencing found significant enrichment of the apoptosis pathway in a subset of brain endothelial cells in MAP3K3I441M mice compared to controls. We then demonstrated that MAP3K3I441M overexpression activated p38 signaling that is associated with the apoptosis of endothelial cells in vitro and in vivo. In contrast, the mice simultaneously overexpressing PIK3CA and MAP3K3 mutations had an increased number of CCM-like lesions and maintained these lesions for a longer time compared to those with only MAP3K3I441M. Further in vitro and in vivo experiments showed that activating PI3K signaling increased proliferation and alleviated apoptosis of endothelial cells. By using AAV-BR1, we found that MAP3K3I441M mutation can provoke CCM-like lesions in mice and the activation of PI3K signaling significantly enhances and maintains these lesions, providing a preclinical model for the further mechanistic and therapeutic study of CCMs. © 2023, The Author(s), under exclusive licence to Springer Nature B.V.

Many applications, e.g., digital twins, rely on sensing data from Internet of Things (IoT) networks, which is used to infer event(s) and initiate actions to affect an environment. This gives rise to concerns relating to data integrity and provenance. One possible solution to address these concerns is to employ blockchain. However, blockchain has high resource requirements, thereby making it unsuitable for use on resource-constrained IoT devices. To this end, this paper proposes a novel approach, called two-layer directed acyclic graph (2LDAG), whereby IoT devices only store a digital fingerprint of data generated by their neighbors. Further, it proposes a novel proof-of-path (PoP) protocol that allows an operator or digital twin to verify data in an on-demand manner. The simulation results show 2LDAG has storage and communication cost that is respectively two and three orders of magnitude lower than traditional blockchain and also blockchains that use a DAG structure. Moreover, 2LDAG achieves consensus even when 49\% of nodes are malicious.

Drug resistance continues to impede the success of cancer treatments, creating a need for experimental model systems that are broad, yet simple, to allow the identification of mechanisms and novel countermeasures applicable to many cancer types. To address these needs, we investigated a set of engineered mammalian cell lines with synthetic gene circuits integrated into their genome that evolved resistance to Puromycin. We identified DNA amplification as the mechanism underlying drug resistance in 4 out of 6 replicate populations. Triplex-forming oligonucleotide (TFO) treatment combined with Puromycin could efficiently suppress the growth of cell populations with DNA amplification. Similar observations in human cancer cell lines suggest that TFOs could be broadly applicable to mitigate drug resistance, one of the major difficulties in treating cancer. © 2023 the Author(s).

Whole-genome sequencing of longitudinal tumor pairs representing transformation of follicular lymphoma to high-grade B cell lymphoma with MYC and BCL2 rearrangements (double-hit lymphoma) identified coding and noncoding genomic alterations acquired during lymphoma progression. Many of these transformation-associated alterations recurrently and focally occur at topologically associating domain resident regulatory DNA elements, including H3K4me3 promoter marks located within H3K27ac super-enhancer clusters in B cell non-Hodgkin lymphoma. One region found to undergo recurrent alteration upon transformation overlaps a super-enhancer affecting the expression of the PAX5/ZCCHC7 gene pair. ZCCHC7 encodes a subunit of the Trf4/5-Air1/2-Mtr4 polyadenylation-like complex and demonstrated copy number gain, chromosomal translocation and enhancer retargeting-mediated transcriptional upregulation upon lymphoma transformation. Consequently, lymphoma cells demonstrate nucleolar dysregulation via altered noncoding 5.8S ribosomal RNA processing. We find that a noncoding mutation acquired during lymphoma progression affects noncoding rRNA processing, thereby rewiring protein synthesis leading to oncogenic changes in the lymphoma proteome. © 2023, The Author(s).

In the article by Li et al, "De Novo Germline and Somatic Variants Convergently Promote Endothelial-to-Mesenchymal Transition in Simplex Brain Arteriovenous Malformation,"which published in the October 15, 2021 issue of the journal (Circ Res. 2021;129:825-839. doi: 10.1161/CIRCRESAHA.121.319004), a correction was needed. There was an error in the Abstract and Introduction: The definition of AVM was incorrectly displayed as "arteriovenous- malformation-like"when it should have been "arteriovenous-malformation". The journal apologizes for the error. The corrected version of this article is available at www.ahajournals.org/doi/10.1161/CIRCRESAHA.121.319004. © 2021 American Heart Association, Inc.

Arterial stiffness is a progressive aging process that predicts cardiovascular disease. Pulse wave velocity (PWV) has emerged as a noninvasive, valid, and reliable measure of arterial stiffness and an independent risk predictor for adverse outcomes. However, up to now, PWV measurement has mostly been used as a tool for risk prediction and has not been widely used in clinical practice. This consensus paper aims to discuss multiple PWV measurements currently available in Asia and to provide evidence-based assessment together with recommendations on the clinical use of PWV. For the methodology, PWV measurement including the central elastic artery is essential and measurements including both the central elastic and peripheral muscular arteries, such as brachial-ankle PWV and cardio-ankle vascular index, can be a good alternative. As Asian populations are rapidly aging, timely detection and intervention of "early vascular aging" in terms of abnormally high PWV values are recommended. More evidence is needed to determine if a PWV-guided therapeutic approach will be beneficial to the prevention of cardiovascular diseases beyond current strategies. Large-scale randomized controlled intervention studies are needed to guide clinicians.

The advent of multiple rigorous molecular simulation approaches made it possible to unveil molecular mechanisms on atomic level and capture the dynamic features of biomolecules. In this thesis, we will introduce three research projects accomplished using molecular simulations to facilitate drug discovery. Firstly, the COVID-19 pandemic caused by SARS-CoV-2 has resulted in half a billion infections worldwide and effective antivirals are required to curb the pandemic. Nucleotide analogs inhibiting RNA-dependent RNA polymerase (RdRp) represents a well-established strategy to inhibit virus amplification although the inhibitory mechanism was not fully understood. To explain the impact of 2’-modification on inhibition activity against SARS-CoV-2 RdRp, extensive molecular dynamics (MD) simulations and free energy perturbation (FEP) were conducted. We found that small-size modifications such as fluorine had little impact on RNA replication. By contrast, 2’- methyl modification led to immediate RNA chain termination due to intermolecular steric clash, while the instability at 3’-terminal caused by 2’-methyl substitution resulted in partial termination. Secondly, incorporation of two consecutive Favipiravir was found to inhibit RNA replication mediated by influenza A virus RdRp. Yet the detailed mechanism remains elusive. We performed MD simulations and unveiled that the disrupted active site was a consequence of the altered base stacking pattern. The first two projects provide valuable insights into the structural optimization of antivirals on atomic level. Thirdly, cerebral cavernous malformations (CCM) patients have limited options on safe and effective treatments. A recent study discovered the strong association between type II CCM and the somatic mutation of MAP3K3 gene encoding a protein kinase MEKK3. The overactive MEKK3 I441M variant provides a promising target for the type II CCM therapy. Accordingly, we performed a series of molecular docking to repurpose approved/i

Purpose: Our previous study has shown that PTPRZ1-MET (ZM) fusion is a viable target for MET inhibitors in gliomas. However, the diversity and prevalence of somatic MET alterations in difuse gliomas are still elusive and need to be extensively characterized for identifying novel therapeutic targets. Methods: Totally, 1,350 glioma patients and 31 patient-derived cells were collected from the Chinese Glioma Genome Atlas (CGGA) and published data. All kinds of MET fusions and/or splicing variants (MET F/SVs) were identifed by bioinformatical methods. Single-cell RNA sequencing (scRNA-seq) were used for validation. In vitro experiments of drug resistance were conducted for the possibility of MET-targeted treatment. Results: MET F/SVs but not genomic amplifcation, were highly enriched in the secondary glioblastomas (sGBM) and marked worse prognosis. Further molecular and scRNA-seq analysis reveale that MET F/SVs were induced in the course of glioma evolution and highly associated with MET overexpression. Subsequent in vitro and the clinical study showed that cells and patients harboring MET F/SVs have better response to MET inhibitors. Conclusion: Our fndings expanded the percentage of gliomas with abnormal MET alterations and suggested that a subgroup of gliomas harboring MET F/SVs may beneft from MET-targeted therapy.

This paper reviews and highlights how coding schemes have been used to solve various problems in blockchain systems. Specifically, these problems relate to scaling blockchains in terms of their data storage, computation and communication cost, as well as security. To this end, this paper considers the use of coded blocks or shards that allows participants to store only a fraction of the total blockchain, protect against malicious nodes or erasures due to nodes leaving a blockchain system, ensure data availability in order to promote transparency, and scale the security of sharded blockchains. Further, it helps reduce communication cost when disseminating blocks, which is critical to bootstrapping new nodes and helps speed up consensus of blocks. For each category of solutions, we highlight problems and issues that motivated their designs and use of coding. Moreover, we provide a qualitative analysis of their storage, communication and computation cost.

Understanding the racial specificities of diseases-such as adult diffuse glioma, the most common primary malignant tumor of the central nervous system-is a critical step toward precision medicine. Here, we comprehensively review studies of gliomas in East Asian populations and other ancestry groups to clarify the racial differences in terms of epidemiology and genomic characteristics. Overall, we observed a lower glioma incidence in East Asians than in Whites; notably, patients with glioblastoma had significantly younger ages of onset and longer overall survival than the Whites. Multiple genome-wide association studies of various cohorts have revealed single nucleotide polymorphisms associated with overall and subtype-specific glioma susceptibility. Notably, only 3 risk loci-5p15.33, 11q23.3, and 20q13.33-were shared between patients with East Asian and White ancestry, whereas other loci predominated only in particular populations. For instance, risk loci 12p11.23, 15q15-21.1, and 19p13.12 were reported in East Asians, whereas risk loci 8q24.21, 1p31.3, and 1q32.1 were reported in studies in White patients. Although the somatic mutational profiles of gliomas between East Asians and non-East Asians were broadly consistent, a lower incidence of EGFR amplification in glioblastoma and a higher incidence of 1p19q-IDH-TERT triple-negative low-grade glioma were observed in East Asian cohorts. By summarizing large-scale disease surveillance, germline, and somatic genomic studies, this review reveals the unique characteristics of adult diffuse glioma among East Asians, to guide clinical management and policy design focused on patients with East Asian ancestry.

Objective: We aimed to summarize the clinicopathological characteristics and prognostic features of various molecular subtypes of diffuse gliomas (DGs) in the Chinese population.Methods: In total, 1,418 patients diagnosed with DG between 2011 and 2017 were classified into 5 molecular subtypes according to the 2016 WHO classification of central nervous system tumors. The IDH mutation status was determined by immunohistochemistry and/or DNA sequencing, and 1p/19q codeletion was detected with fluorescence in situ hybridization. The median clinical follow-up time was 1,076 days. T-tests and chi-square tests were used to compare clinicopathological characteristics. Kaplan Meier and Cox regression methods were used to evaluate prognostic factors.Results: Our cohort included 15.5% lower-grade gliomas, IDH-mutant and 1p/19q-codeleted (LGG-IDHm-1p/19q); 18.1% lower -grade gliomas, IDH-mutant (LGG-IDHm); 13.1% lower-grade gliomas, IDH-wildtype (LGG-IDHwt); 36.1% glioblastoma, IDH-wildtype (GBM-IDHwt); and 17.2% glioblastoma, IDH-mutant (GBM-IDHm). Approximately 63.3% of the enrolled primary gliomas, and the median overall survival times for LGG-IDHm, LGG-IDHwt, GBM-IDHwt, and GBM-IDHm subtypes were 75.97, 34.47, 11.57, and 15.17 months, respectively. The 5-year survival rate of LGG-IDHm-1p/19q was 76.54%. We observed a significant association between high resection rate and favorable survival outcomes across all subtypes of primary tumors. We also observed a significant role of chemotherapy in prolonging overall survival for GBM-IDHwt and GBM-IDHm, and in prolonging post-relapse survival for the 2 recurrent GBM subtypes.Conclusions: By controlling for molecular subtypes, we found that resection rate and chemotherapy were 2 prognostic factors associated with survival outcomes in a Chinese cohort with DG.

Papillary thyroid carcinoma (PTC) is heterogeneous and its molecular characteristics remain elusive. We integrated transcriptomic sequencing, genomic analysis and clinicopathologic information from 582 tissue samples of 216 PTC and 75 benign thyroid nodule (BTN) patients. We discovered four subtypes of PTC including Immune-enriched Subtype, BRAF-enriched Subtype, Stromal Subtype and CNV-enriched Subtype. Molecular subtypes were validated in an external cohort of 497 PTC cases from the TCGA. Tumors in the Immune-enriched Subtype showed higher immune infiltration and overexpression of immune checkpoints, whilst BRAF-enriched Subtype showed a higher tendency for extrathyroidal extension and more advanced TNM stage. Key oncogenes including LRRK2, SLC34A2, MUC1, FOXQ1 and KRT19 were overexpressed and enriched in oncogenic MAPK and PI3K/AKT signaling pathways in BRAF-enriched subtype. Further analysis of BRAF-enriched Subtype identified three subclasses with different degrees of malignancies. We also uncovered the molecular link of the initiation and progression from BTN to subtypes of PTC using trajectory analysis. Moreover, a 20-gene expression signature was generated for differential diagnosis of PTC from BTN patients. Together, our work identified previously unreported molecular subtypes of PTC, offering opportunities to stratify patients into optimal treatment plans based on molecular subtyping. © 2022, The Author(s).

In the article by Li et al, "De Novo Germline and Somatic Variants Convergently Promote Endothelial-to-Mesenchymal Transition in Simplex Brain Arteriovenous Malformation,"which published in the October 15, 2021 issue of the journal (Circ Res. 2021;129:825-839. doi: 10.1161/CIRCRESAHA.121.319004), a correction was needed. There was an error in the Abstract and Introduction: The definition of AVM was incorrectly displayed as "arteriovenous- malformation-like"when it should have been "arteriovenous-malformation". The journal apologizes for the error. The corrected version of this article is available at www.ahajournals.org/doi/10.1161/CIRCRESAHA.121.319004. © 2021 American Heart Association, Inc.

Background: Resistant hypertension is associated with increased cardiovascular risk. The endothelin pathway has been implicated in the pathogenesis of hypertension, but it is currently not targeted therapeutically, thereby leaving this relevant pathophysiological pathway unopposed with currently available drugs. The aim of the study was to assess the blood pressure lowering efficacy of the dual endothelin antagonist aprocitentan in patients with resistant hypertension. Methods: PRECISION was a multicentre, blinded, randomised, parallel-group, phase 3 study, which was done in hospitals or research centres in Europe, North America, Asia, and Australia. Patients were eligible for randomisation if their sitting systolic blood pressure was 140 mm Hg or higher despite taking standardised background therapy consisting of three antihypertensive drugs, including a diuretic. The study consisted of three sequential parts: part 1 was the 4-week double-blind, randomised, and placebo-controlled part, in which patients received aprocitentan 12·5 mg, aprocitentan 25 mg, or placebo in a 1:1:1 ratio; part 2 was a 32-week single (patient)-blind part, in which all patients received aprocitentan 25 mg; and part 3 was a 12-week double-blind, randomised, and placebo-controlled withdrawal part, in which patients were re-randomised to aprocitentan 25 mg or placebo in a 1:1 ratio. The primary and key secondary endpoints were changes in unattended office systolic blood pressure from baseline to week 4 and from withdrawal baseline to week 40, respectively. Secondary endpoints included 24-h ambulatory blood pressure changes. The study is registered on ClinicalTrials.gov, NCT03541174. Findings: The PRECISION study was done from June 18, 2018, to April 25, 2022. 1965 individuals were screened and 730 were randomly assigned. Of these 730 patients, 704 (96%) completed part 1 of the study; of these, 613 (87%) completed part 2 and, of these, 577 (94%) completed part 3 of the study. The least square m

To follow the revision of the fourth edition of WHO classification and the recent progress on the management of diffuse gliomas, the joint guideline committee of Chinese Glioma Cooperative Group (CGCG), Society for Neuro‐Oncology of China (SNO-China) and Chinese Brain Cancer Association (CBCA) updated the clinical practice guideline. It provides recommendations for diagnostic and management decisions, and for limiting unnecessary treatments and cost. The recommendations focus on molecular and pathological diagnostics, and the main treatment modalities of surgery, radiotherapy, and chemotherapy. In this guideline, we also integrated the results of some clinical trials of immune therapies and target therapies, which we think are ongoing future directions. The guideline should serve as an application for all professionals involved in the management of patients with adult diffuse glioma and also a source of knowledge for insurance companies and other institutions involved in the cost regulation of cancer care in China and other countries. © 2020 Elsevier B.V.

Glioma is the most common lethal tumor of the human brain. The median survival of patients with primary World Health Organization grade IV glioma is only 14.6 months. The World Health Organization classification of tumors of the central nervous system categorized gliomas into lower-grade gliomas and glioblastomas. Unlike primary glioblastoma that usually develop de novo in the elderly, secondary glioblastoma enriched with an isocitrate dehydrogenase mutant typically progresses from lower-grade glioma within 5–10 years from the time of diagnosis. Based on various evolutional trajectories brought on by clonal and subclonal alterations, the evolution patterns of glioma vary according to different theories. Some important features distinguish the normal brain from other tissues, e.g., the composition of the microenvironment around the tumor cells, the presence of the blood-brain barrier, and others. The underlying mechanism of glioma recurrence and evolution patterns of glioma are different from those of other types of cancer. Several studies correlated tumor recurrence with tumor heterogeneity and the immune microenvironment. However, the detailed reasons for the progression and recurrence of glioma remain controversial. In this review, we introduce the different mechanisms involved in glioma progression, including tumor heterogeneity, the tumor microenvironment and drug resistance, and their pre-clinical implements in clinical trials. This review aimed to provide new insights into further clinical strategies for the treatment of patients with recurrent and secondary glioma. © 2021, Higher Education Press.

Cerebral cavernous malformations (CCMs) are vascular disorders that affect up to 0.5% of the total population. About 20% of CCMs are inherited because of familial mutations in CCM genes, including CCM1/KRIT1, CCM2/MGC4607, and CCM3/PDCD10, whereas the etiology of a majority of simplex CCM-affected individuals remains unclear. Here, we report somatic mutations of MAP3K3, PIK3CA, MAP2K7, and CCM genes in CCM lesions. In particular, somatic hotspot mutations of PIK3CA are found in 11 of 38 individuals with CCMs, and a MAP3K3 somatic mutation (c.1323C>G [p.Ile441Met]) is detected in 37.0% (34 of 92) of the simplex CCM-affected individuals. Strikingly, the MAP3K3 c.1323C>G mutation presents in 95.7% (22 of 23) of the popcorn-like lesions but only 2.5% (1 of 40) of the subacute-bleeding or multifocal lesions that are predominantly attributed to mutations in the CCM1/2/3 signaling complex. Leveraging mini-bulk sequencing, we demonstrate the enrichment of MAP3K3 c.1323C>G mutation in CCM endothelium. Mechanistically, beyond the activation of CCM1/2/3-inhibited ERK5 signaling, MEKK3 p.Ile441Met (MAP3K3 encodes MEKK3) also activates ERK1/2, JNK, and p38 pathways because of mutation-induced MEKK3 kinase activity enhancement. Collectively, we identified several somatic activating mutations in CCM endothelium, and the MAP3K3 c.1323C>G mutation defines a primary CCM subtype with distinct characteristics in signaling activation and magnetic resonance imaging appearance.

Effective radiation treatment (RT) for recurrent nasopharyngeal cancers (NPC), featuring an intrinsic hypoxic sub-volume, remains a clinical challenge. Lack of disease-specific in-vitro models of NPC, together with difficulties in establishing patient derived xenograft (PDX) models, have further hindered development of personalized therapeutic options. Herein, we established two NPC organoid lines from recurrent NPC PDX models and further characterized and compared these models with original patient tumors using RNA sequencing analysis. Organoids were cultured in hypoxic conditions to examine the effects of hypoxia and radioresistance. These models were then utilized to determine the radiobiological parameters, such as alpha/beta ratio and oxygen enhancement ratio (OER), characteristic to radiosensitive normoxic and radioresistant hypoxic NPC, using simple dose-survival data analytic tools. The results were further validated in-vitro and in-vivo, to determine the optimal boost dose and fractionation regimen required to achieve effective NPC tumor regression. Despite the differences in tumor microenvironment due to the lack of human stroma, RNA sequencing analysis revealed good correlation of NPC PDX and organoid models with patient tumors. Additionally, the established models also mimicked inter-tumoral heterogeneity. Hypoxic NPC organoids were highly radioresistant and had high alpha/beta ratio compared to its normoxic counterparts. In-vitro and in-vivo fractionation studies showed that hypoxic NPC was less sensitive to RT fractionation scheme and required a large bolus dose or 1.4 times of the fractionated dose that was effective against normoxic cells in order to compensate for oxygen deficiency. This study is the first direct experimental evidence to predict optimal RT boost dose required to cause sufficient damage to recurrent hypoxic NPC tumor cells, which can be further used to develop dose-painting algorithms in clinical practice.

Noncoding RNAs are exquisitely titrated by the cellular RNA surveillance machinery for regulating diverse biological processes. The RNA exosome, the predominant 3′ RNA exoribonuclease in mammalian cells, is composed of nine core and two catalytic subunits. Here, we developed a mouse model with a conditional allele to study the RNA exosome catalytic subunit DIS3. In DIS3-deficient B cells, integrity of the immunoglobulin heavy chain (Igh) locus in its topologically associating domain is affected, with accumulation of DNA-associated RNAs flanking CTCF-binding elements, decreased CTCF binding to CTCF-binding elements and disorganized cohesin localization. DIS3-deficient B cells also accumulate activation-induced cytidine deaminase–mediated asymmetric nicks, altering somatic hypermutation patterns and increasing microhomology-mediated end-joining DNA repair. Altered mutation patterns and Igh architectural defects in DIS3-deficient B cells lead to decreased class-switch recombination but increased chromosomal translocations. Our observations of DIS3-mediated architectural regulation at the Igh locus are reflected genome wide, thus providing evidence that noncoding RNA processing is an important mechanism for controlling genome organization. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.

The mechanotransduction (MT) complex in auditory hair cells converts the mechanical stimulation of sound waves into neural signals. Recently, the MT complex has been suggested to contain at least four distinct integral membrane proteins: protocadherin 15 (PCDH15), transmembrane channel-like protein 1 (TMC1), lipoma HMGIC fusion partner-like 5 (LHFPL5), and transmembrane inner ear protein (TMIE). However, the composition, function, and regulation of the MT-complex proteins remain incompletely investigated. Here, we report previously undescribed splicing isoforms of TMC1, LHFPL5, and TMIE. We identified four alternative splicing events for the genes encoding these three proteins by analyzing RNA-seq libraries of auditory hair cells from adult mice [over postnatal day (P)28], and we then verified the alternative splicing events by using RT-PCR and Sanger sequencing. Moreover, we examined the tissue-specific distribution, developmental expression patterns, and tonotopic gradient of the splicing isoforms by performing semiquantitative and quantitative real-time PCR (qRT-PCR), and we found that the alternative splicing of TMC1 and LHFPL5 is cochlear-specific and occurs in both neonatal and adult mouse cochleae. Our findings not only reveal the potential complexity of the MT-complex composition, but also provide critical insights for guiding future research on the function, regulation, and trafficking of TMC1, LHFPL5, and TMIE and on the clinical diagnosis of hearing loss related to aberrant splicing of these three key genes in hearing.

Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering clinical translation, lacking effective methods for multimodal and multisource data integration is becoming a bottleneck. Here we proposed DeepDRK, a machine learning framework for deciphering drug response through kernel-based data integration. To transfer information among different drugs and cancer types, we trained deep neural networks on more than 20 000 pan-cancer cell line-anticancer drug pairs. These pairs were characterized by kernel-based similarity matrices integrating multisource and multi-omics data including genomics, transcriptomics, epigenomics, chemical properties of compounds and known drug-target interactions. Applied to benchmark cancer cell line datasets, our model surpassed previous approaches with higher accuracy and better robustness. Then we applied our model on newly established patient-derived cancer cell lines and achieved satisfactory performance with AUC of 0.84 and AUPRC of 0.77. Moreover, DeepDRK was used to predict clinical response of cancer patients. Notably, the prediction of DeepDRK correlated well with clinical outcome of patients and revealed multiple drug repurposing candidates. In sum, DeepDRK provided a computational method to predict drug response of cancer cells from integrating pharmacogenomic datasets, offering an alternative way to prioritize repurposing drugs in precision cancer treatment. The DeepDRK is freely available via https://github.com/wangyc82/DeepDRK.

Transcription errors can substantially affect metabolic processes in organisms by altering the epigenome and causing misincorporations in mRNA, which is translated into aberrant mutant proteins. Moreover, within eukaryotic genomes there are specific Transcription Error-Enriched genomic Loci (TEELs) which are transcribed by RNA polymerases with significantly higher error rates and hypothesized to have implications in cancer, aging, and diseases such as Down syndrome and Alzheimer’s. Therefore, research into transcription errors is of growing importance within the field of genetics. Nevertheless, methodological barriers limit the progress in accurately identifying transcription errors. Pro-Seq and NET-Seq can purify nascent RNA and map RNA polymerases along the genome but cannot be used to identify transcriptional mutations. Here we present background Error Model-coupled Precision nuclear run-on Circular-sequencing (EmPC-seq), a method combining a nuclear run-on assay and circular sequencing with a background error model to precisely detect nascent transcription errors and effectively discern TEELs within the genome.

Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and metastatic cancer cases, to assess metastatic risks of primary tumors. MetaNet achieves high accuracy in distinguishing the metastasis from the primary in breast and prostate cancers. From the prediction, we identify Metastasis-Featuring Primary (MFP) tumors, a subset of primary tumors with genomic features enriched in metastasis and demonstrate their higher metastatic risk and shorter disease-free survival. In addition, we identify genomic alterations associated with organ-specific metastases and employ them to stratify patients into various risk groups with propensities toward different metastatic organs. This organotropic stratification method achieves better prognostic value than the standard histological grading system in prostate cancer, especially in the identification of Bone-MFP and Liver-MFP subtypes, with potential in informing organ-specific examinations in follow-ups. © 2021, The Author(s).

Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and metastatic cancer cases, to assess metastatic risks of primary tumors. MetaNet achieves high accuracy in distinguishing the metastasis from the primary in breast and prostate cancers. From the prediction, we identify Metastasis-Featuring Primary (MFP) tumors, a subset of primary tumors with genomic features enriched in metastasis and demonstrate their higher metastatic risk and shorter disease-free survival. In addition, we identify genomic alterations associated with organ-specific metastases and employ them to stratify patients into various risk groups with propensities toward different metastatic organs. This organotropic stratification method achieves better prognostic value than the standard histological grading system in prostate cancer, especially in the identification of Bone-MFP and Liver-MFP subtypes, with potential in informing organ-specific examinations in follow-ups. © 2021, The Author(s).

Transcription errors can substantially affect metabolic processes in organisms by altering the epigenome and causing misincorporations in mRNA, which is translated into aberrant mutant proteins. Moreover, within eukaryotic genomes there are specific Transcription Error-Enriched genomic Loci (TEELs) which are transcribed by RNA polymerases with significantly higher error rates and hypothesized to have implications in cancer, aging, and diseases such as Down syndrome and Alzheimer’s. Therefore, research into transcription errors is of growing importance within the field of genetics. Nevertheless, methodological barriers limit the progress in accurately identifying transcription errors. Pro-Seq and NET-Seq can purify nascent RNA and map RNA polymerases along the genome but cannot be used to identify transcriptional mutations. Here we present background Error Model-coupled Precision nuclear run-on Circular-sequencing (EmPC-seq), a method combining a nuclear run-on assay and circular sequencing with a background error model to precisely detect nascent transcription errors and effectively discern TEELs within the genome.

To follow the revision of the fourth edition of WHO classification and the recent progress on the management of diffuse gliomas, the joint guideline committee of Chinese Glioma Cooperative Group (CGCG), Society for Neuro‐Oncology of China (SNO-China) and Chinese Brain Cancer Association (CBCA) updated the clinical practice guideline. It provides recommendations for diagnostic and management decisions, and for limiting unnecessary treatments and cost. The recommendations focus on molecular and pathological diagnostics, and the main treatment modalities of surgery, radiotherapy, and chemotherapy. In this guideline, we also integrated the results of some clinical trials of immune therapies and target therapies, which we think are ongoing future directions. The guideline should serve as an application for all professionals involved in the management of patients with adult diffuse glioma and also a source of knowledge for insurance companies and other institutions involved in the cost regulation of cancer care in China and other countries. © 2020 Elsevier B.V.

Glioma is the most common lethal tumor of the human brain. The median survival of patients with primary World Health Organization grade IV glioma is only 14.6 months. The World Health Organization classification of tumors of the central nervous system categorized gliomas into lower-grade gliomas and glioblastomas. Unlike primary glioblastoma that usually develop de novo in the elderly, secondary glioblastoma enriched with an isocitrate dehydrogenase mutant typically progresses from lower-grade glioma within 5–10 years from the time of diagnosis. Based on various evolutional trajectories brought on by clonal and subclonal alterations, the evolution patterns of glioma vary according to different theories. Some important features distinguish the normal brain from other tissues, e.g., the composition of the microenvironment around the tumor cells, the presence of the blood-brain barrier, and others. The underlying mechanism of glioma recurrence and evolution patterns of glioma are different from those of other types of cancer. Several studies correlated tumor recurrence with tumor heterogeneity and the immune microenvironment. However, the detailed reasons for the progression and recurrence of glioma remain controversial. In this review, we introduce the different mechanisms involved in glioma progression, including tumor heterogeneity, the tumor microenvironment and drug resistance, and their pre-clinical implements in clinical trials. This review aimed to provide new insights into further clinical strategies for the treatment of patients with recurrent and secondary glioma. © 2021, Higher Education Press.

Noncoding RNAs are exquisitely titrated by the cellular RNA surveillance machinery for regulating diverse biological processes. The RNA exosome, the predominant 3′ RNA exoribonuclease in mammalian cells, is composed of nine core and two catalytic subunits. Here, we developed a mouse model with a conditional allele to study the RNA exosome catalytic subunit DIS3. In DIS3-deficient B cells, integrity of the immunoglobulin heavy chain (Igh) locus in its topologically associating domain is affected, with accumulation of DNA-associated RNAs flanking CTCF-binding elements, decreased CTCF binding to CTCF-binding elements and disorganized cohesin localization. DIS3-deficient B cells also accumulate activation-induced cytidine deaminase–mediated asymmetric nicks, altering somatic hypermutation patterns and increasing microhomology-mediated end-joining DNA repair. Altered mutation patterns and Igh architectural defects in DIS3-deficient B cells lead to decreased class-switch recombination but increased chromosomal translocations. Our observations of DIS3-mediated architectural regulation at the Igh locus are reflected genome wide, thus providing evidence that noncoding RNA processing is an important mechanism for controlling genome organization. © 2021, The Author(s), under exclusive licence to Springer Nature America, Inc.

Effective radiation treatment (RT) for recurrent nasopharyngeal cancers (NPC), featuring an intrinsic hypoxic sub-volume, remains a clinical challenge. Lack of disease-specific in-vitro models of NPC, together with difficulties in establishing patient derived xenograft (PDX) models, have further hindered development of personalized therapeutic options. Herein, we established two NPC organoid lines from recurrent NPC PDX models and further characterized and compared these models with original patient tumors using RNA sequencing analysis. Organoids were cultured in hypoxic conditions to examine the effects of hypoxia and radioresistance. These models were then utilized to determine the radiobiological parameters, such as alpha/beta ratio and oxygen enhancement ratio (OER), characteristic to radiosensitive normoxic and radioresistant hypoxic NPC, using simple dose-survival data analytic tools. The results were further validated in-vitro and in-vivo, to determine the optimal boost dose and fractionation regimen required to achieve effective NPC tumor regression. Despite the differences in tumor microenvironment due to the lack of human stroma, RNA sequencing analysis revealed good correlation of NPC PDX and organoid models with patient tumors. Additionally, the established models also mimicked inter-tumoral heterogeneity. Hypoxic NPC organoids were highly radioresistant and had high alpha/beta ratio compared to its normoxic counterparts. In-vitro and in-vivo fractionation studies showed that hypoxic NPC was less sensitive to RT fractionation scheme and required a large bolus dose or 1.4 times of the fractionated dose that was effective against normoxic cells in order to compensate for oxygen deficiency. This study is the first direct experimental evidence to predict optimal RT boost dose required to cause sufficient damage to recurrent hypoxic NPC tumor cells, which can be further used to develop dose-painting algorithms in clinical practice.

Metastatic cancer is associated with poor patient prognosis but its spatiotemporal behavior remains unpredictable at early stage. Here we develop MetaNet, a computational framework that integrates clinical and sequencing data from 32,176 primary and metastatic cancer cases, to assess metastatic risks of primary tumors. MetaNet achieves high accuracy in distinguishing the metastasis from the primary in breast and prostate cancers. From the prediction, we identify Metastasis-Featuring Primary (MFP) tumors, a subset of primary tumors with genomic features enriched in metastasis and demonstrate their higher metastatic risk and shorter disease-free survival. In addition, we identify genomic alterations associated with organ-specific metastases and employ them to stratify patients into various risk groups with propensities toward different metastatic organs. This organotropic stratification method achieves better prognostic value than the standard histological grading system in prostate cancer, especially in the identification of Bone-MFP and Liver-MFP subtypes, with potential in informing organ-specific examinations in follow-ups. © 2021, The Author(s).

Pediatric germ cell tumors (pGCTs), a group of germ-cell-originated neoplasms, currently lack sufficient study. Although somatic activation of KIT/AKT and RAS/MAPK pathways have been revealed, no driver mutations have been detected in most of GCT cases. To extensively explore germline and somatic mutations, we analyzed genomic and/or transcriptomic sequencing data of 236 pGCTs, including data from not only public datasets but also newly collected whole-genome-sequencing data of tumor samples together with case-unaffected-parents trios collected in Shanghai Xinhua Hospital. A new computational pipeline was developed and carried out to identify functional germline and somatic variants. Overall, > 30,000 germline and > 100,000 somatic mutations were detected and prioritized. Particularly, we found germline trisomy 21 in three cases, germline XXY in five cases, and one germline XO, demonstrating the enrichment of germline chromosomal abnormality in pGCTs (p-value < 0.0001). We identified 196 loss-of-function-like inherited germline mutations involving CBL (4/212), PTEN (3/212), TEX11 (2/212), and ATM (1/212). In addition, we detected 2,160 de novo germline mutations (DNMs), and showed an average of 69.7 DNMs per proband, which is compatible to the previously reported incidence. Moreover, we discovered recurrent somatic mutations in known driver genes such as KIT (27/110), KRAS (10/110), NRAS (4/110), MTOR (5/110), PTEN (3/110), and CBL (2/110). Interestingly, somatic hotspot RRAS2 mutations were detected in seven of 110 cases. Subsequent clinical association analysis showed that patients who harbored RRAS2 mutations were younger than those harboring KRAS mutations (p-value < 0.05). Somatic copy number changes were frequently observed, including chr12p+ (47/110), chr21q+ (47/110), chrX+ (34/110), chr13q- (27/110), and chr20q+ (26/110). Furthermore, we identified chromoplexy in nine out of 62 cases, and this alteration is significantly enriched in yolk sac tumors with the

Detection of DNA copy number alteration in cancer cells is critical to understanding cancer initiation and progression. Widely used methods, such as DNA arrays and genomic DNA sequencing, are relatively expensive and require DNA samples at a microgram level, which are not avaiblable in certain situations like clinical biopsies or single-cell genomes. Here we developed an alternative method-CNAPE to computationally infer copy number alterations from gene expression data. A prior knowledge-aided machine learning model was proposed, trained and tested on 9,740 cancer samples from The Cancer Genome Atlas. We then applied CNAPE to study gliomas, the most common and aggressive brain cancer in adult. Particularly, using RNA sequencing data, CNAPE respectively predicted DNA copy number of chromosomes, chromosomal arms, and 12 commonly altered genes, and achieved >80% accuracy in almost all broad regions and some focal regions. CNAPE was developed as an easy-to-use tool at https://github.com/WangLabHKUST/CNAPE.

Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering clinical translation, lacking effective methods for multimodal and multisource data integration is becoming a bottleneck. Here we proposed DeepDRK, a machine learning framework for deciphering drug response through kernel-based data integration. To transfer information among different drugs and cancer types, we trained deep neural networks on more than 20 000 pan-cancer cell line-anticancer drug pairs. These pairs were characterized by kernel-based similarity matrices integrating multisource and multi-omics data including genomics, transcriptomics, epigenomics, chemical properties of compounds and known drug-target interactions. Applied to benchmark cancer cell line datasets, our model surpassed previous approaches with higher accuracy and better robustness. Then we applied our model on newly established patient-derived cancer cell lines and achieved satisfactory performance with AUC of 0.84 and AUPRC of 0.77. Moreover, DeepDRK was used to predict clinical response of cancer patients. Notably, the prediction of DeepDRK correlated well with clinical outcome of patients and revealed multiple drug repurposing candidates. In sum, DeepDRK provided a computational method to predict drug response of cancer cells from integrating pharmacogenomic datasets, offering an alternative way to prioritize repurposing drugs in precision cancer treatment. The DeepDRK is freely available via https://github.com/wangyc82/DeepDRK.

Effective radiation treatment (RT) for recurrent nasopharyngeal cancers (NPC), featuring an intrinsic hypoxic sub-volume, remains a clinical challenge. Lack of disease-specific in-vitro models of NPC, together with difficulties in establishing patient derived xenograft (PDX) models, have further hindered development of personalized therapeutic options. Herein, we established two NPC organoid lines from recurrent NPC PDX models and further characterized and compared these models with original patient tumors using RNA sequencing analysis. Organoids were cultured in hypoxic conditions to examine the effects of hypoxia and radioresistance. These models were then utilized to determine the radiobiological parameters, such as alpha/beta ratio and oxygen enhancement ratio (OER), characteristic to radiosensitive normoxic and radioresistant hypoxic NPC, using simple dose-survival data analytic tools. The results were further validated in-vitro and in-vivo, to determine the optimal boost dose and fractionation regimen required to achieve effective NPC tumor regression. Despite the differences in tumor microenvironment due to the lack of human stroma, RNA sequencing analysis revealed good correlation of NPC PDX and organoid models with patient tumors. Additionally, the established models also mimicked inter-tumoral heterogeneity. Hypoxic NPC organoids were highly radioresistant and had high alpha/beta ratio compared to its normoxic counterparts. In-vitro and in-vivo fractionation studies showed that hypoxic NPC was less sensitive to RT fractionation scheme and required a large bolus dose or 1.4 times of the fractionated dose that was effective against normoxic cells in order to compensate for oxygen deficiency. This study is the first direct experimental evidence to predict optimal RT boost dose required to cause sufficient damage to recurrent hypoxic NPC tumor cells, which can be further used to develop dose-painting algorithms in clinical practice.