The global landscape of approved antibody therapies

Antibody therapies have become an important class of therapeutics in recent years as they have exhibited outstanding efficacy and safety in the treatment of several major diseases including cancers, immune-related diseases, infectious disease and hematological disease. There has been significant progress in the global research and development landscape of antibody therapies in the past decade. In this review, we have collected available data from the Umabs Antibody Therapies Database (Umabs-DB, https://umabs.com) as of 30 June 2022. The Umabs-DB shows that 162 antibody therapies have been approved by at least one regulatory agency in the world, including 122 approvals in the US, followed by 114 in Europe, 82 in Japan and 73 in China, whereas biosimilar, diagnostic and veterinary antibodies are not included in our statistics. Although the US and Europe have been at the leading position for decades, rapid advancement has been witnessed in Japan and China in the past decade. The approved antibody therapies include 115 canonical antibodies, 14 antibody-drug conjugates, 7 bispecific antibodies, 8 antibody fragments, 3 radiolabeled antibodies, 1 antibody-conjugate immunotoxin, 2 immunoconjugates and 12 Fc-Fusion proteins. They have been developed against 91 drug targets, of which PD-1 is the most popular, with 14 approved antibody-based blockades for cancer treatment in the world. This review outlined the global landscape of the approved antibody therapies with respect to the regulation agencies, therapeutic targets and indications, aiming to provide an insight into the trends of the global development of antibody therapies

The presence of autoantibodies is associated with improved overall survival in lung cancer patients

ObjectiveAutoantibodies have been reported to be associated with cancers. As a biomarker, autoantibodies have been widely used in the early screening of lung cancer. However, the correlation between autoantibodies and the prognosis of lung cancer patients is poorly understood, especially in the Asian population. This retrospective study investigated the association between the presence of autoantibodies and outcomes in patients with lung cancer.MethodsA total of 264 patients diagnosed with lung cancer were tested for autoantibodies in Henan Provincial People’s Hospital from January 2017 to June 2022. The general clinical data of these patients were collected, and after screening out those who met the exclusion criteria, 151 patients were finally included in the study. The Cox proportional hazards model was used to analyze the effect of autoantibodies on the outcomes of patients with lung cancer. The Kaplan-Meier curve was used to analyze the relationship between autoantibodies and the overall survival of patients with lung cancer.ResultsCompared to lung cancer patients without autoantibodies, those with autoantibodies had an associated reduced risk of death (HRs: 0.45, 95% CIs 0.27~0.77), independent of gender, age, smoking history, pathological type, and pathological stage of lung cancer. Additionally, the association was found to be more significant by subgroup analysis in male patients, younger patients, and patients with small cell lung cancer. Furthermore, lung cancer patients with autoantibodies had significantly longer survival time than those without autoantibodies.ConclusionThe presence of autoantibodies is an independent indicator of good prognosis in patients with lung cancer, providing a new biomarker for prognostic evaluation in patients with lung cancer

Single-cell analysis reveals the COL11A1+ fibroblasts are cancer-specific fibroblasts that promote tumor progression

Background: Cancer-associated fibroblasts (CAFs) promote tumor progression through extracellular matrix (ECM) remodeling and extensive communication with other cells in tumor microenvironment. However, most CAF-targeting strategies failed in clinical trials due to the heterogeneity of CAFs. Hence, we aimed to identify the cluster of tumor-promoting CAFs, elucidate their function and determine their specific membrane markers to ensure precise targeting.Methods: We integrated multiple single-cell RNA sequencing (scRNA-seq) datasets across different tumors and adjacent normal tissues to identify the tumor-promoting CAF cluster. We analyzed the origin of these CAFs by pseudotime analysis, and tried to elucidate the function of these CAFs by gene regulatory network analysis and cell-cell communication analysis. We also performed cell-type deconvolution analysis to examine the association between the proportion of these CAFs and patients’ prognosis in TCGA cancer cohorts, and validated that through IHC staining in clinical tumor tissues. In addition, we analyzed the membrane molecules in different fibroblast clusters, trying to identify the membrane molecules that were specifically expressed on these CAFs.Results: We found that COL11A1+ fibroblasts specifically exist in tumor tissues but not in normal tissues and named them cancer-specific fibroblasts (CSFs). We revealed that these CSFs were transformed from normal fibroblasts. CSFs represented a more activated CAF cluster and may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. High CSF proportion was associated with poor prognosis in bladder cancer (BCa) and lung adenocarcinoma (LUAD), and IHC staining of COL11A1 confirmed their specific expression in tumor stroma in clinical BCa samples. We also identified that CSFs specifically express the membrane molecules LRRC15, ITGA11, SPHK1 and FAP, which could distinguish CSFs from other fibroblasts.Conclusion: We identified that CSFs is a tumor specific cluster of fibroblasts, which are in active state, may promote tumor progression through the regulation on ECM remodeling and antitumor immune responses. Membrane molecules LRRC15, ITGA11, SPHK1 and FAP could be used as therapeutic targets for CSF-targeting cancer treatment

Global Value Network Transformations: Exploring interactions between value chains and organisations

Multinational corporations can be seen as the significant components of the contemporary business structure that are responsible for a considerable portion of the world’s economic, productive and investment activities. As the epitome of modern capitalism, the changes that happen in their operational and managerial methods are vital for both the academic community and practitioners. Also, the emerging new globalisation diagrams indicate that it is necessary to explore deeply the increasing internationalisation trends. Recent academic work has focused on and discussed the changing business environment of MNCs and further opened the black box of the global value network concept. However, it is relatively less known about the relationships and interactions of the two major systems- the supply chain systems and the organisational and administrative systems within MNCs, especially during their GVN transformations. Hence, this research is aiming at the specific question: *How could MNCs reconfigure their global value networks during strategic transformations?* To comprehensively understand the complex connections of the mentioned systems, this dissertation adopts a networked and processing model to investigate how MNCs strategically adapt their global value networks- an interconnected intra-firm network structure that contains two coordinated systems for its global management. The GVN model contains and equally focuses on both organisational systems and global functional systems in MNCs. By linking the two concepts- global operations management and organisational theory together within a single model, this dissertation provides a novel perspective to investigate global value networks. A generic framework was developed to analyse the GVN model using a 4C model, which contains four analysing dimensions- contexts, configurations, capabilities and changes. Also, a three-step process is adopted to disassemble the complicated transformation into a more straightforward logic that can be summarised as the preparation phase, the adaptation phase and the outcome phase. To understand a new phenomenon embedded in the context, this research follows an interpretivism approach to build theory through case studies. Six multinational companies from Europe and Asia - Faurecia, Geely, Haier, Huawei, Yanmar and Daimler - in manufacturing industries have been selected and aligned with the theoretical sampling rationales. A case study has been conducted in each MNC, and their internationalisation processes as well as key GVN transformations have been captured for analysis. Primary data is collected mainly from semi-structured interviews with medium to high-level managers and decision-makers who are familiar with the growth history of the firms they worked for. The primary data was complemented and triangulated with the secondary data collected from documentation, archives, academic papers and other reliable resources, as well as the biographies of MNCs and their main founders, etc. Inductive coding and process study method were adopted to understand the changing factors, the adapting processes, and the outcomes of each GVN. There are five findings that explain GVN changes from multiple dimensions. Firstly, the research finds out existing contextual factors and internal triggers that interpret why MNCs need to adapt their operational patterns. Secondly, a GVN transformational typology was developed to explain the configuration of GVNs, and three specific types of changes were identified accordingly, namely VCDTs (value chain dominance transformations), ODTs (organisation dominance transformations) and IDTs (integrated dominance transformations). This dissertation also sheds light on how to configure a new GVN by puzzling out the interactions of the two systems during changing processes. The fourth finding mainly contributes to the outcomes of GVN transformations by investigating capability changes of each type of GVN. With these dimensions, an integrated and processed GVN transformation model was finally developed. And it argues that GVNs should be carefully restructured and reconfigured under certain considerations step-by-step strategically. This dissertation seeks to contribute to both operations management literature and international business literature with a dynamic view to capture practices and changes of MNCs’ global value networks. The findings bridge the gaps between two organic systems within one globally dispersed entity and explain how they function interactionally. The process model of GVN transformations contributes to the process study of MNCs in the IB field. It also provides implications and strategic guidance to practitioners such as managers, directors and decision-makers in large multinationals to better operate MNCs both short-term and long-term

Classification method of shale gas analytic stages and its application

Article highlights 1. According to the inflection point of the curvature of shale desorption efficiency curve, the curvature curve can be divided into four stages: sensitive desorption, rapid desorption, slow desorption and inefficient desorption. 2. The Upper Paleozoic shale in Yulin area of Ordos Basin is mainly in the stage of inefficient desorption and slow desorption. 3. When shale gas is open, according to the desorption stage and pressure node of shale exploitation, the formation pressure can be properly reduced to improve shale gas recovery

More on Three-Dimensional Systems of Rational Difference Equations

We are concerned with a kind of three-dimensional system of rational difference equations, given by Kurbanli (2011). A new expression of solution of the system is presented, and the asymptotical behavior is described. At the same time, we also consider a different system and obtain some results, which expand the study of such a kind of difference equations and the method can be applied to other systems

Laser Based Navigation in Asymmetry and Complex Environment

For collision-free navigation in unstructured and cluttered environments, deep reinforcement learning (DRL) has gained extensive successes for being capable of adapting to new environments without much human effort. However, due to its asymmetry, the problems related to its lack of data efficiency and robustness remain as challenges. In this paper, we present a new laser-based navigation system for mobile robots, which combines a global planner with reinforcement learning-based local trajectory re-planning. The proposed method uses Proximal Policy Optimization to learn an efficient and robust local planning policy with asynchronous data generation and training. Extensive experiments have been presented, showing that the proposed system achieves better performance than previous methods including end-to-end DRL, and it can improve the asymmetrical performance. Our analysis show that the proposed method can efficiently avoid deadlock points and achieves a higher success rate. Moreover, we show that our system can generalize to unseen environments and obstacles with only a few shots. The model enables the warehouse to realize automatic management through intelligent sorting and handling, and it is suitable for various customized application scenarios

Cost-effectiveness analysis of sorafenib, lenvatinib, atezolizumab plus bevacizumab and sintilimab plus bevacizumab for the treatment of advanced hepatocellular carcinoma in China

Key points With the approval of new first-and second-line drugs and the establishment of treatment based on immune checkpoint inhibitors as standard treatment, treatment options for advanced hepatocellular carcinoma are more diverse than ever before. Therefore, clinical decision-making requires a multidisciplinary team to develop individualized treatment strategies according to the patients' disease and financial ability to pay. Here, we point out that lenvatinib, sintilimab plus bevacizumab and atezolizumab plus bevacizumab are more effective in the treatment of advanced hepatocellular carcinoma, but the cost of treatment is beyond the affordability of the patient. We outlined better drug purchase prices and health insurance reimbursement policies to enable patients to get the optimal treatment