Design of a 1 × 4 micro-magnetic stimulation device and its targeted, coordinated regulation on LTP of Schaffer-CA1 in the hippocampus of rats.

Magnetic technology has been a hotspot of neuromodulation research in recent years. However, magnetic coil is limited by their size, and it is impossible to realize precise targeted magnetic stimulation to the target area at the cellular scale. To this end, this study designs a 1 × 4 array micro-magnetic stimulation (µMS) device with four sub-millimeter-sized elements, enabling precise magnetic stimulation of the CA1-CA3-DG tri-synaptic positions in the rat hippocampal region. First, it is determined that 70 KHz/2 mT/1 min magnetic stimulation parameter has a modulatory effect on the long-term potentiation (LTP) of Schaffer-CA1 in rat hippocampus. Then, a 1 × 4 array µMS device is used to perform magnetic stimulation at 70 KHz/2 mT/1 min, targeting the CA1, CA3, and DG regions individually with single-point magnetic stimulation; and multi-region magnetic stimulation is applied to the double-point targeting regions of CA1-CA3, CA1-DG, and CA3-DG, as well as the triple-point targeting region of CA1-CA3-DG, so as to investigate the regulation of LTP by single-region magnetic stimulation and multi-region magnetic stimulation. The experimental results indicate that, in the case of single-region magnetic stimulation, the magnitude of the increase in LTP in the CA1 region is the greatest, followed by the CA3 region, while the effect of magnetic stimulation on the DG region is less pronounced. In multi-region magnetic stimulation, synergistic magnetic stimulation of the three-point CA1-CA3-DG results in a greater increase in LTP compared to stimulation of two individual areas, and the enhancement of LTP induction with multi-region magnetic stimulation surpasses that of single-region stimulation. This study has implications for the collaborative targeted magnetic stimulation application of arrayed micro-magnetic devices.

Genomic and transcriptomic characteristics of 12 novel primary cell lines derived from three patients with cholangiocarcinoma.

Cholangiocarcinoma (CCA) is an aggressive bile duct malignancy with poor prognosis. To improve our understanding of the biological characteristics of CCA and develop effective therapies, appropriate preclinical models are required. Here, we established and characterized 12 novel patient-derived primary cancer cell (PDPC) models using multi-region sampling. At the genomic level of PDPCs, we observed not only commonly mutated genes, such as TP53, JAK3, and KMT2C, consistent with the reports in CCA, but also specific mutation patterns in each cell line. In addition, specific expression patterns with distinct biological functions and pathways involved were also observed in the PDPCs at the transcriptomic level. Furthermore, the drug-sensitivity results revealed that the PDPCs exhibited different responses to the six commonly used compounds. Our findings indicate that the established PDPCs can serve as novel in vitro reliable models to provide a crucial molecular basis for improving the understanding of tumorigenesis and its treatment.

Coupled Dynamics of Stimulus-Evoked Gustatory Cortical and Basolateral Amygdalar Activity.

Gustatory cortical (GC) single-neuron taste responses reflect taste quality and palatability in successive epochs. Ensemble analyses reveal epoch-to-epoch firing-rate changes in these responses to be sudden, coherent transitions. Such nonlinear dynamics suggest that GC is part of a recurrent network, producing these dynamics in concert with other structures. Basolateral amygdala (BLA), which is reciprocally connected to GC and central to hedonic processing, is a strong candidate partner for GC, in that BLA taste responses evolve on the same general clock as GC and because inhibition of activity in the BLA→GC pathway degrades the sharpness of GC transitions. These facts motivate, but do not test, our overarching hypothesis that BLA and GC act as a single, comodulated network during taste processing. Here, we provide just this test of simultaneous (BLA and GC) extracellular taste responses in female rats, probing the multiregional dynamics of activity to directly test whether BLA and GC responses contain coupled dynamics. We show that BLA and GC response magnitudes covary across trials and within single responses, and that changes in BLA-GC local field potential phase coherence are epoch specific. Such classic coherence analyses, however, obscure the most salient facet of BLA-GC coupling: sudden transitions in and out of the epoch known to be involved in driving gaping behavior happen near simultaneously in the two regions, despite huge trial-to-trial variability in transition latencies. This novel form of inter-regional coupling, which we show is easily replicated in model networks, suggests collective processing in a distributed neural network.SIGNIFICANCE STATEMENT There has been little investigation into real-time communication between brain regions during taste processing, a fact reflecting the dominant belief that taste circuitry is largely feedforward. Here, we perform an in-depth analysis of real-time interactions between GC and BLA in response to passive taste deliveries, using both conventional coherence metrics and a novel methodology that explicitly considers trial-to-trial variability and fast single-trial dynamics in evoked responses. Our results demonstrate that BLA-GC coherence changes as the taste response unfolds, and that BLA and GC specifically couple for the sudden transition into (and out of) the behaviorally relevant neural response epoch, suggesting (although not proving) that: (1) recurrent interactions subserve the function of the dyad as (2) a putative attractor network.

A multimodal atlas of hepatocellular carcinoma reveals convergent evolutionary paths and 'bad apple' effect on clinical trajectory.

BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a highly fatal cancer characterized by high intra-tumor heterogeneity (ITH). A panoramic understanding of its tumor evolution, in relation to its clinical trajectory, may provide novel prognostic and treatment strategies. METHODS: Through the Asia-Pacific Hepatocellular Carcinoma trials group (NCT03267641), we recruited one of the largest prospective cohorts of patients with HCC, with over 600 whole genome and transcriptome samples from 123 treatment-naïve patients. RESULTS: Using a multi-region sampling approach, we revealed seven convergent genetic evolutionary paths governed by the early driver mutations, late copy number variations and viral integrations, which stratify patient clinical trajectories after surgical resection. Furthermore, such evolutionary paths shaped the molecular profiles, leading to distinct transcriptomic subtypes. Most significantly, although we found the coexistence of multiple transcriptomic subtypes within certain tumors, patient prognosis was best predicted by the most aggressive cell fraction of the tumor, rather than by overall degree of transcriptomic ITH level - a phenomenon we termed the 'bad apple' effect. Finally, we found that characteristics throughout early and late tumor evolution provide significant and complementary prognostic power in predicting patient survival. CONCLUSIONS: Taken together, our study generated a comprehensive landscape of evolutionary history for HCC and provides a rich multi-omics resource for understanding tumor heterogeneity and clinical trajectories. IMPACT AND IMPLICATIONS: This prospective study, utilizing comprehensive multi-sector, multi-omics sequencing and clinical data from surgically resected hepatocellular carcinoma (HCC), reveals critical insights into the role of tumor evolution and intra-tumor heterogeneity (ITH) in determining the prognosis of HCC. These findings are invaluable for oncology researchers and clinicians, as they underscore the influence of distinct evolutionary paths and the 'bad apple' effect, where the most aggressive tumor fraction dictates disease progression. These insights not only enhance prognostic accuracy post-surgical resection but also pave the way for personalized treatment strategies tailored to specific tumor evolutionary and transcriptomic profiles. The coexistence of multiple subtypes within the same tumor prompts a re-appraisal of the utilities of depending on single samples to represent the entire tumor and suggests the need for clinical molecular imaging. This research thus marks a significant step forward in the clinical understanding and management of HCC, underscoring the importance of integrating tumor evolutionary dynamics and multi-omics biomarkers into therapeutic decision-making. CLINICAL TRIAL NUMBER: NCT03267641 (Observational cohort).

Deciphering clonal dynamics and metastatic routines in a rare patient of synchronous triple-primary tumors and multiple metastases with MPTevol.

Multiple primary tumor (MPT) is a special and rare cancer type, defined as more than two primary tumors presenting at the diagnosis in a single patient. The molecular characteristics and tumorigenesis of MPT remain unclear due to insufficient approaches. Here, we present MPTevol, a practical computational framework for comprehensively exploring the MPT from multiregion sequencing (MRS) experiments. To verify the utility of MPTevol, we performed whole-exome MRS for 33 samples of a rare patient with triple-primary tumors and three metastatic sites and systematically investigated clonal dynamics and metastatic routines. MPTevol assists in comparing genomic profiles across samples, detecting clonal evolutionary history and metastatic routines and quantifying the metastatic history. All triple-primary tumors were independent origins and their genomic characteristics were consistent with corresponding sporadic tumors, strongly supporting their independent tumorigenesis. We further showed two independent early monoclonal seeding events for the metastases in the ovary and uterus. We revealed that two ovarian metastases were disseminated from the same subclone of the primary tumor through undergoing whole-genome doubling processes, suggesting metastases-to-metastases seeding occurred when tumors had similar microenvironments. Surprisingly, according to the metastasis timing model of MPTevol, we found that primary tumors of about 0.058-0.124 cm diameter have been disseminating to distant organs, which is much earlier than conventional clinical views. We developed MPT-specialized analysis framework MPTevol and demonstrated its utility in explicitly resolving clonal evolutionary history and metastatic seeding routines with a rare MPT case. MPTevol is implemented in R and is available at https://github.com/qingjian1991/MPTevol under the GPL v3 license.

Multiregion WES of metastatic pancreatic neuroendocrine tumors revealed heterogeneity in genomic alterations, immune microenvironment and evolutionary patterns.

Pancreatic neuroendocrine tumors (PanNETs), though uncommon, have a high likelihood of spreading to other body parts. Previously, the genetic diversity and evolutionary patterns in metastatic PanNETs were not well understood. To investigate this, we performed multiregion sampling whole-exome sequencing (MRS-WES) on samples from 10 patients who had not received prior treatment for metastatic PanNETs. This included 29 primary tumor samples, 31 lymph node metastases, and 15 liver metastases. We used the MSK-MET dataset for survival analysis and validation of our findings. Our research indicates that mutations in the MEN1/DAXX genes might trigger the early stages of PanNET development. We categorized the patients based on the presence (MEN1/DAXXmut, n = 7) or absence (MEN1/DAXXwild, n = 3) of these mutations. Notable differences were observed between the two groups in terms of genetic alterations and clinically relevant mutations, confirmed using the MSK-MET dataset. Notably, patients with mutations in MEN1/DAXX/ATRX genes had a significantly longer median overall survival compared to those without these mutations (median not reached vs. 43.63 months, p = 0.047). Multiplex immunohistochemistry (mIHC) analysis showed a more prominent immunosuppressive environment in metastatic tumors, especially in patients with MEN1/DAXX mutations. These findings imply that MEN1/DAXX mutations lead PanNETs through a unique evolutionary path. The disease's progression pattern indicates that PanNETs can spread early, even before clinical detection, highlighting the importance of identifying biomarkers related to metastasis to guide personalized treatment strategies.

Temporal and structural patterns of hepatitis B virus integrations in hepatocellular carcinoma.

Chronic infection of hepatitis B virus (HBV) is the major cause of hepatocellular carcinoma (HCC). Notably, 90% of HBV-positive HCC cases exhibit detectable HBV integrations, hinting at the potential early entanglement of these viral integrations in tumorigenesis and their subsequent oncogenic implications. Nevertheless, the precise chronology of integration events during HCC tumorigenesis, alongside their sequential structural patterns, has remained elusive thus far. In this study, we applied whole-genome sequencing to multiple biopsies extracted from six HBV-positive HCC cases. Through this approach, we identified point mutations and viral integrations, offering a blueprint for the intricate tumor phylogeny of these samples. The emergent narrative paints a rich tapestry of diverse evolutionary trajectories characterizing the analyzed tumors. We uncovered oncogenic integration events in some samples that appear to happen before and during the initiation stage of tumor development based on their locations in reconstituted trajectories. Furthermore, we conducted additional long-read sequencing of selected samples and unveiled integration-bridged chromosome rearrangements and tandem repeats of the HBV sequence within integrations. In summary, this study revealed premalignant oncogenic and sequential complex integrations and highlighted the contributions of HBV integrations to HCC development and genome instability.

Multi-region sampling with paired sample sequencing analyses reveals sub-groups of patients with novel patient-specific dysregulation in Hepatocellular Carcinoma.

BACKGROUND: Conventional differential expression (DE) testing compares the grouped mean value of tumour samples to the grouped mean value of the normal samples, and may miss out dysregulated genes in small subgroup of patients. This is especially so for highly heterogeneous cancer like Hepatocellular Carcinoma (HCC). METHODS: Using multi-region sampled RNA-seq data of 90 patients, we performed patient-specific differential expression testing, together with the patients' matched adjacent normal samples. RESULTS: Comparing the results from conventional DE analysis and patient-specific DE analyses, we show that the conventional DE analysis omits some genes due to high inter-individual variability present in both tumour and normal tissues. Dysregulated genes shared in small subgroup of patients were useful in stratifying patients, and presented differential prognosis. We also showed that the target genes of some of the current targeted agents used in HCC exhibited highly individualistic dysregulation pattern, which may explain the poor response rate. DISCUSSION/CONCLUSION: Our results highlight the importance of identifying patient-specific DE genes, with its potential to provide clinically valuable insights into patient subgroups for applications in precision medicine.

Towards a low-carbon future for China's power supply chain: Critical sectors identification and scenario analysis.

The power sector is a significant contributor to global carbon emissions and has received widespread attention from scholars; however, the path to achieving supply chain-wide carbon reductions in China from a provincial perspective remains unclear. This study combined multi-regional input-output and betweenness-based methods to identify the critical upstream sectors that indirectly drive large amounts of carbon emissions through power supply chains. The point source data of coal-fired units were collected to ensure the accuracy of the disaggregated input-output table. In addition, a scenario analysis was conducted to examine the effects of different electricity policy combinations on supply chain-wide emissions during the 14th Five-Year Plan (FYP). Our findings indicate that the embodied carbon intensity of the coal-fired power sector in Northwest China is among the highest in the country, ranging from 36.39 to 82.10 tons/10000 CNY. Therefore, the shift of the power sector to Western China during the 14th FYP will partially offset the positive emission reduction effect of the structural transformation of the power system. To achieve a low-carbon power supply chain, it is necessary to improve the production efficiency of critical transmission sectors and the low-carbon technology levels of major emitting sectors. Our results provide valuable insights for provincial governments to plan low-carbon transformation paths for the power sector.

Water-carbon nexus relationship and interaction mechanism analysis within Beijing-Tianjin-Hebei urban agglomeration.

As the total water resources consumption control and carbon mitigation continuous improvement, the weak water-carbon incorporate management is increasingly exposed. In this study, a water-carbon nexus assessment framework is proposed to analyze the nexus relationship between water consumption and carbon emission, and distinguishes the coupled water-carbon transmission intensity and the transfer paths under regional and industrial scales. According to the practical input-output table, water consumption, and carbon emission information, the framework is applied to Beijing-Tianjin-Hebei urban agglomeration (BTHUA), a population, resource, and trade intensive area of China. Inter-regional/intra-regional water consumption and carbon emission transfer fluxes between sectors, the pairwise ecological relationship, and the water-carbon nexus were analyzed. Results indicated that the water-carbon transfer indexes from Hebei to Beijing and Tianjin were 161.85 kg/m3 and 113.88 kg/m3 in the study period, along with the most water consumption and carbon emission, and the worst water-carbon nexus. From the industrial perspective, electricity and gas supplying industry provided 7.8% and 29.1% of the total carbon transfer in Tianjin and Hebei, as the most key node sectors on the water-carbon nexus in the BTHUA. The research provides valuably supporting the adjustment of the existing urban agglomeration water-carbon nexus management schemes.

Model predictive control to mitigate the COVID-19 outbreak in a multi-region scenario.

The COVID-19 outbreak is deeply influencing the global social and economic framework, due to restrictive measures adopted worldwide by governments to counteract the pandemic contagion. In multi-region areas such as Italy, where the contagion peak has been reached, it is crucial to find targeted and coordinated optimal exit and restarting strategies on a regional basis to effectively cope with possible onset of further epidemic waves, while efficiently returning the economic activities to their standard level of intensity. Differently from the related literature, where modeling and controlling the pandemic contagion is typically addressed on a national basis, this paper proposes an optimal control approach that supports governments in defining the most effective strategies to be adopted during post-lockdown mitigation phases in a multi-region scenario. Based on the joint use of a non-linear Model Predictive Control scheme and a modified Susceptible-Infected-Recovered (SIR)-based epidemiological model, the approach is aimed at minimizing the cost of the so-called non-pharmaceutical interventions (that is, mitigation strategies), while ensuring that the capacity of the network of regional healthcare systems is not violated. In addition, the proposed approach supports policy makers in taking targeted intervention decisions on different regions by an integrated and structured model, thus both respecting the specific regional health systems characteristics and improving the system-wide performance by avoiding uncoordinated actions of the regions. The methodology is tested on the COVID-19 outbreak data related to the network of Italian regions, showing its effectiveness in properly supporting the definition of effective regional strategies for managing the COVID-19 diffusion.

Learning mutational graphs of individual tumour evolution from single-cell and multi-region sequencing data.

BACKGROUND: A large number of algorithms is being developed to reconstruct evolutionary models of individual tumours from genome sequencing data. Most methods can analyze multiple samples collected either through bulk multi-region sequencing experiments or the sequencing of individual cancer cells. However, rarely the same method can support both data types. RESULTS: We introduce TRaIT, a computational framework to infer mutational graphs that model the accumulation of multiple types of somatic alterations driving tumour evolution. Compared to other tools, TRaIT supports multi-region and single-cell sequencing data within the same statistical framework, and delivers expressive models that capture many complex evolutionary phenomena. TRaIT improves accuracy, robustness to data-specific errors and computational complexity compared to competing methods. CONCLUSIONS: We show that the application of TRaIT to single-cell and multi-region cancer datasets can produce accurate and reliable models of single-tumour evolution, quantify the extent of intra-tumour heterogeneity and generate new testable experimental hypotheses.

Intratumor heterogeneity comparison among different subtypes of non-small-cell lung cancer through multi-region tissue and matched ctDNA sequencing.

Understanding of intratumor heterogeneity (ITH) among different non-small cell lung cancer (NSCLC) subtypes is necessary. Whether circulating tumor DNA (ctDNA) profile could represent these ITH is still an open question. We performed 181 multi-region tumor tissues sequencing and matched ctDNA sequencing from 32 operative NSCLC to compare ITH among different NSCLC subtypes, including EGFR-mutant lung adenocarcinoma (LUAD), KRAS-mutant LUAD, EGFR&KRAS-wild-type LUAD, and lung squamous cell carcinoma (LUSC), and examine potential value of ctDNA for ITH analysis. ITH is evaluated by ITH index (ITHi). If the somatic genetic alteration is shared by all the tissue regions, it is defined as trunk mutation. Otherwise, it is called branch mutation. The ITHi will be higher, if the tumor has less trunk mutations. We found EGFR-mutant LUAD showed significantly higher ITHi than KRAS-mutant LUAD/wild-type LUAD (P = 0.03) and numerically higher ITH than LUSC. For trunk mutations, driver mutations were identified at a higher proportion than passenger mutations (60% vs. 40%, P = 0.0023) in overall, especially in EGFR-mutant LUAD (86% vs. 14%, P = 0.0004), while it was opposite in KRAS-mutant LUAD (40% vs. 60%, P = 0.18). For branch mutations, the proportions of driver mutations and passenger mutations were similar for each NSCLC subtype. ctDNA analysis showed unsatisfactory detections of tumor-derived trunk and branch mutations (43% vs. 23%, P = 4.53e-6) among all NSCLC subtypes. In summary, EGFR-mutant LUAD has the highest ITH than other NSCLC subtypes, offering further understanding of tumorigenesis mechanisms among different NSCLC subtypes. Besides, ctDNA maybe not an appropriate method to reflect ITH.

Quantifying global CH4 and N2O footprints.

This study aims to quantify global CH4 and N2O footprints in 2012 in terms of 181 economies and 20 world regions based on the official national emission accounts from the UNFCCC database and the global multi-region input-output accounts from the EORA database. Global total CH4 and N2O emissions increased by 15.0% in 2012 compared to 1990, mainly driven by increasing demands of agricultural and energy products. Mainland China, Western Europe, the USA, Southeast Asia and Sub-Saharan Africa were identified as the largest five CH4 footprint contributors (55.6% of the global total), while Mainland China, the USA, Western Europe, Brazil and Sub-Saharan Africa as the largest N2O footprint contributors (59.2% of the global total). In most developed economies, the CH4 and N2O footprints were much higher than their emissions on the production side, but opposite picture is observed in emerging economies. 36.4% and 24.8% of the global CH4 and N2O emissions in 2012 were associated with international trade, respectively. Substantial energy-related CH4 and agricultural CH4 and N2O emissions were transferred from developed countries to developing countries. Several nations within Kyoto targets have reduced their CH4 and N2O emissions significantly between 1990 and 2012, but the generally-believed success is challenged when viewing from the consumption side. Mainland China, Southeast Asia, Sub-Saharan Africa, Brazil, Middle East and India witnessed prominent increase of CH4 and N2O footprints in the same period. The structure and spatial patterns of global CH4 and N2O footprints shed light on the role of consumption-side actions and international cooperation for future non-CO2 GHG emission reduction.

Multidimensional co-segmentation of longitudinal brain MRI ensembles in the presence of a neurodegenerative process.

MRI Segmentation of a pathological brain poses a significant challenge, as the available anatomical priors that provide top-down information to aid segmentation are inadequate in the presence of abnormalities. This problem is further complicated for longitudinal data capturing impaired brain development or neurodegenerative conditions, since the dynamic of brain atrophies has to be considered as well. For these cases, the absence of compatible annotated training examples renders the commonly used multi-atlas or machine-learning approaches impractical. We present a novel segmentation approach that accounts for the lack of labeled data via multi-region multi-subject co-segmentation (MMCoSeg) of longitudinal MRI sequences. The underlying, unknown anatomy is learned throughout an iterative process, in which the segmentation of a region is supported both by the segmentation of the neighboring regions, which share common boundaries, and by the segmentation of corresponding regions, in the other jointly segmented images. A 4D multi-region atlas that models the spatio-temporal deformations and can be adapted to different subjects undergoing similar degeneration processes is reconstructed concurrently. An inducible mouse model of p25 accumulation (the CK-p25 mouse) that displays key pathological hallmarks of Alzheimer disease (AD) is used as a gold-standard to test the proposed algorithm by providing a conditional control of rapid neurodegeneration. Applying the MMCoSeg to a cohort of CK-p25 mice and littermate controls yields promising segmentation results that demonstrate high compatibility with expertise manual annotations. An extensive comparative analysis with respect to current well-established, atlas-based segmentation methods highlights the advantage of the proposed approach, which provides accurate segmentation of longitudinal brain MRIs in pathological conditions, where only very few annotated examples are available.

Understanding intratumor heterogeneity by combining genome analysis and mathematical modeling.

Cancer is composed of multiple cell populations with different genomes. This phenomenon called intratumor heterogeneity (ITH) is supposed to be a fundamental cause of therapeutic failure. Therefore, its principle-level understanding is a clinically important issue. To achieve this goal, an interdisciplinary approach combining genome analysis and mathematical modeling is essential. For example, we have recently performed multiregion sequencing to unveil extensive ITH in colorectal cancer. Moreover, by employing mathematical modeling of cancer evolution, we demonstrated that it is possible that this ITH is generated by neutral evolution. In this review, we introduce recent advances in a research field related to ITH and also discuss strategies for exploiting novel findings on ITH in a clinical setting.

Intraindividual genomic heterogeneity of high-grade serous carcinoma of the ovary and clinical utility of ascitic cancer cells for mutation profiling.

Intraindividual tumoural heterogeneity (ITH) is a hallmark of solid tumours and impedes accurate genomic diagnosis and selection of proper therapy. The aim of this study was to identify ITH of ovarian high-grade serous carcinomas (OSCs) and to determine the utility of ascitic cancer cells as a resource for mutation profiling in spite of ITH. We performed whole-exome sequencing, copy number profiling and DNA methylation profiling of four OSC genomes by using multiregional biopsies from 13 intraovarian lesions, 12 extraovarian tumour lesions (omentum/peritoneum), and ascitic cells. We observed substantial levels of heterogeneity in mutations and copy number alterations (CNAs) of the OSCs. We categorized the mutations into 'common', 'shared' and 'private' according to the regional distribution. Six common, eight shared and 24 private mutations were observed in known cancer-related genes. Common mutations had a higher mutant allele frequency, and included TP53 mutations in all four OSCs. Region-specific chromosomal amplifications and deletions involving BRCA1, PIK3CA and RB1 were also identified. It is of note that the mutations detected in ascitic cancer cells represented 92.3-100% of overall somatic mutations in the given case. Phylogenetic analyses of ascitic genomes predicted a polyseeding origin of somatic mutations in ascitic cells. Our results demonstrate that, despite ITH, somatic mutations, CNAs and DNA methylations in both 'common' category and cancer-related genes were highly conserved in ascitic cells of OSCs, highlighting the clinical relevance of genome analysis of ascitic cells. Ascitic tumour cells may serve as a potential resource for discovering somatic mutations of primary OSC with diagnostic and therapeutic relevance. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The material footprint of nations.

Metrics on resource productivity currently used by governments suggest that some developed countries have increased the use of natural resources at a slower rate than economic growth (relative decoupling) or have even managed to use fewer resources over time (absolute decoupling). Using the material footprint (MF), a consumption-based indicator of resource use, we find the contrary: Achievements in decoupling in advanced economies are smaller than reported or even nonexistent. We present a time series analysis of the MF of 186 countries and identify material flows associated with global production and consumption networks in unprecedented specificity. By calculating raw material equivalents of international trade, we demonstrate that countries' use of nondomestic resources is, on average, about threefold larger than the physical quantity of traded goods. As wealth grows, countries tend to reduce their domestic portion of materials extraction through international trade, whereas the overall mass of material consumption generally increases. With every 10% increase in gross domestic product, the average national MF increases by 6%. Our findings call into question the sole use of current resource productivity indicators in policy making and suggest the necessity of an additional focus on consumption-based accounting for natural resource use.

Multiregion sequencing reveals the intratumor heterogeneity of driver mutations in TP53-driven non-small cell lung cancer.

Intratumor heterogeneity (ITH) in non-small cell lung cancer (NSCLC) may account for resistance after a period of targeted therapies because drugs destroy only a portion of tumor cells. The recognition of ITH helps identify high-risk patients to make effective treatment decisions. However, ITH studies are confounded by interpatient heterogeneity in NSCLC and a large amount of passenger mutations. To address these issues, we recruited NSCLC patients carrying TP53 mutations and selected driver mutations within recurrently mutated genes in NSCLC. A total of 12-paired normal-tumor tissues were subjected to whole-genome/whole-exome sequencing. From these, 367 non-silent mutations were selected as driver mutations and deeply sequenced in 61 intratumoral microdissections. We identified a universal prevalence of heterogeneity in all 12 tumors, indicating branched evolution. Although TP53 mutations were observed in single biopsy of all 12 tumors, most tumors consist of both TP53 mutated and non-mutated cells in separate regions within the same tumor. This suggests the late molecular timing of the acquisition of TP53 mutations; therefore, the detection of TP53 mutations in a single biopsy may simply not reflect the early malignant potential. In addition, we identified regions of loss of heterozygosity surrounding TP53 and CDKN2A mutations in tumor 711, which also exhibited heterogeneity in different regional samples. Because the ITH of driver mutations likely has clinical consequences, further efforts are needed to limit the impact of ITH and to improve therapeutic efficiency, which will benefit NSCLC patients receiving targeted treatments.

Multi-region and single-cell sequencing reveal variable genomic heterogeneity in rectal cancer.

BACKGROUND: Colorectal cancer is a heterogeneous group of malignancies with complex molecular subtypes. While colon cancer has been widely investigated, studies on rectal cancer are very limited. Here, we performed multi-region whole-exome sequencing and single-cell whole-genome sequencing to examine the genomic intratumor heterogeneity (ITH) of rectal tumors. METHODS: We sequenced nine tumor regions and 88 single cells from two rectal cancer patients with tumors of the same molecular classification and characterized their mutation profiles and somatic copy number alterations (SCNAs) at the multi-region and the single-cell levels. RESULTS: A variable extent of genomic heterogeneity was observed between the two patients, and the degree of ITH increased when analyzed on the single-cell level. We found that major SCNAs were early events in cancer development and inherited steadily. Single-cell sequencing revealed mutations and SCNAs which were hidden in bulk sequencing. In summary, we studied the ITH of rectal cancer at regional and single-cell resolution and demonstrated that variable heterogeneity existed in two patients. The mutational scenarios and SCNA profiles of two patients with treatment naïve from the same molecular subtype are quite different. CONCLUSIONS: Our results suggest each tumor possesses its own architecture, which may result in different diagnosis, prognosis, and drug responses. Remarkable ITH exists in the two patients we have studied, providing a preliminary impression of ITH in rectal cancer.