Scalable and Effective Temporal Graph Representation Learning With Hyperbolic Geometry.

Real-life graphs often exhibit intricate dynamics that evolve continuously over time. To effectively represent continuous-time dynamic graphs (CTDGs), various temporal graph neural networks (TGNNs) have been developed to model their dynamics and topological structures in Euclidean space. Despite their notable achievements, the performance of Euclidean-based TGNNs is limited and bounded by the representation capabilities of Euclidean geometry, particularly for complex graphs with hierarchical and power-law structures. This is because Euclidean space does not have enough room (its volume grows polynomially with respect to radius) to learn hierarchical structures that expand exponentially. As a result, this leads to high-distortion embeddings and suboptimal temporal graph representations. To break the limitations and enhance the representation capabilities of TGNNs, in this article, we propose a scalable and effective TGNN with hyperbolic geometries for CTDG representation (called STGNh ). It captures evolving behaviors and stores hierarchical structures simultaneously by integrating a memory-based module and a structure-based module into a unified framework, which can scale to billion-scale graphs. Concretely, a simple hyperbolic update gate (HuG) is designed as the memory-based module to store temporal dynamics efficiently; for the structure-based module, we propose an effective hyperbolic temporal Transformer (HyT) model to capture complex graph structures and generate up-to-date node embeddings. Extensive experimental results on a variety of medium-scale and billion-scale graphs demonstrate the superiority of the proposed STGNh for CTDG representation, as it significantly outperforms baselines in various downstream tasks.

Peripheral Soluble Immune Checkpoint-Related Proteins Were Associated with Survival and Treatment Efficacy of Osteosarcoma Patients, a Cohort Study.

BACKGROUND: The immune checkpoint blockade remains obscure in osteosarcoma (OS). We aim to explore the clinical significance of soluble immune checkpoint (ICK)-related proteins in OS. METHODS: We profiled 14 soluble ICK-related proteins (BTLA, GITR, HVEM, IDO, LAG-3, PD-1, PD-L1, PD-L2, TIM-3, CD28, CD80, CD137, CD27, and CTLA-4) in the plasma of 76 OS patients and matched controls. We evaluated the associations between the biomarkers and the risk of OS using unconditional multivariate logistic regression. The multivariate Cox model was utilized to develop the prediction model of OS. Immune subtypes were established from the identified biomarkers. Transcriptional data from GEO were analyzed to elucidate potential mechanisms. RESULTS: We found that sTIM3, sCD137, sIDO, and sCTLA4 were significantly correlated with OS risk (all p < 0.05). sBTLA, sPDL2, and sCD27 were significantly associated with the risk of lung metastasis, whereas sBTLA and sTIM3 were associated with the risk of disease progression. We also established an immune subtype based on sBTLA, sPD1, sTIM3, and sPDL2. Patients in the sICK-type2 subtype had significantly decreased progression-free survival (PFS) and lung metastasis-free survival (LMFS) than those in the sICK-type1 subtype (log-rank p = 2.8 × 10-2, 1.7 × 10-2, respectively). Interestingly, we found that the trend of LMFS and PFS in the subtypes of corresponding ICK genes' expression was opposite to the results in the blood (log-rank p = 2.6 × 10-4, 9.5 × 10-4, respectively). CONCLUSION: Four soluble ICK-related proteins were associated with the survival of OS patients. Soluble ICK-related proteins could be promising biomarkers for the outcomes and immunotherapy of OS patients, though more research is warranted.

First-Line Anlotinib Treatment for Soft Tissue Sarcoma in Chemotherapy-Ineligible Patients: An Open-label, Single-arm, Phase 2 Clinical Trial.

PURPOSE: Standard treatment for patients with unresectable locally advanced or metastatic soft-tissue sarcoma (LA/M STS) is chemotherapy based on anthracyclines, but patient tolerance of chemotherapy is limited. The present trial (NCT03792542) investigated the use of anlotinib as first-line treatment for patients with advanced STS, in particular liposarcoma (LPS). PATIENTS AND METHODS: Eligible patients were previously untreated, pathologically confirmed, unresectable LA/M STS cases. Anlotinib was given orally at a dose of 12 mg once daily from day 1 to day 14 every 3 weeks until disease progression or intolerable adverse events (AEs) occurred. The primary endpoint was progression-free survival (PFS) and the secondary endpoints overall survival (OS), the objective response rate and the disease control rate (DCR). The safety profile was also evaluated. RESULTS: Forty patients were enrolled from April 2019 to Jun 2022 and are included in the intention-to-treat analysis. The median PFS was 6.83 months [95% confidence interval (CI): 4.17-8.71] and the median OS 27.40 months (95% CI: 16.43-not evaluable); 1 patient reached partial response and 26 attained stable disease, with a DCR of 67.5% (27/40). Median PFS and OS times for LPS patients were 8.71 and 16.23 months, respectively. Ten (25.0%) patients had treatment-related AEs ≥ grade 3, with in particular a higher incidence of hypertension (15.0%) and proteinuria (7.5%). CONCLUSIONS: The findings suggest a potential benefit in employing front-line anlotinib to treat patients with STS, who are not eligible for cytotoxic chemotherapy. Of note, the clinical outcomes for the LPS subgroup of patients were encouraging.

Multiple influence of immune cells in the bone metastatic cancer microenvironment on tumors.

Bone is a common organ for solid tumor metastasis. Malignant bone tumor becomes insensitive to systemic therapy after colonization, followed by poor prognosis and high relapse rate. Immune and bone cells in situ constitute a unique immune microenvironment, which plays a crucial role in the context of bone metastasis. This review firstly focuses on lymphatic cells in bone metastatic cancer, including their function in tumor dissemination, invasion, growth and possible cytotoxicity-induced eradication. Subsequently, we examine myeloid cells, namely macrophages, myeloid-derived suppressor cells, dendritic cells, and megakaryocytes, evaluating their interaction with cytotoxic T lymphocytes and contribution to bone metastasis. As important components of skeletal tissue, osteoclasts and osteoblasts derived from bone marrow stromal cells, engaging in 'vicious cycle' accelerate osteolytic bone metastasis. We also explain the concept tumor dormancy and investigate underlying role of immune microenvironment on it. Additionally, a thorough review of emerging treatments for bone metastatic malignancy in clinical research, especially immunotherapy, is presented, indicating current challenges and opportunities in research and development of bone metastasis therapies.

Osteocyte mitochondria inhibit tumor development via STING-dependent antitumor immunity.

Bone is one of the most common sites of tumor metastases. During the last step of bone metastasis, cancer cells colonize and disrupt the bone matrix, which is maintained mainly by osteocytes, the most abundant cells in the bone microenvironment. However, the role of osteocytes in bone metastasis is still unclear. Here, we demonstrated that osteocytes transfer mitochondria to metastatic cancer cells and trigger the cGAS/STING-mediated antitumor response. Blocking the transfer of mitochondria by specifically knocking out mitochondrial Rho GTPase 1 (Rhot1) or mitochondrial mitofusin 2 (Mfn2) in osteocytes impaired tumor immunogenicity and consequently resulted in the progression of metastatic cancer toward the bone matrix. These findings reveal the protective role of osteocytes against cancer metastasis by transferring mitochondria to cancer cells and potentially offer a valuable therapeutic strategy for preventing bone metastasis.

Cancer cells reprogram to metastatic state through the acquisition of platelet mitochondria.

Metastasis is the major cause of cancer deaths, and cancer cells evolve to adapt to various tumor microenvironments, which hinders the treatment of tumor metastasis. Platelets play critical roles in tumor development, especially during metastasis. Here, we elucidate the role of platelet mitochondria in tumor metastasis. Cancer cells are reprogrammed to a metastatic state through the acquisition of platelet mitochondria via the PINK1/Parkin-Mfn2 pathway. Furthermore, platelet mitochondria regulate the GSH/GSSG ratio and reactive oxygen species (ROS) in cancer cells to promote lung metastasis of osteosarcoma. Impairing platelet mitochondrial function has proven to be an efficient approach to impair metastasis, providing a direction for osteosarcoma therapy. Our findings demonstrate mitochondrial transfer between platelets and cancer cells and suggest a role for platelet mitochondria in tumor metastasis.

Learning Accurate Label-Specific Features From Partially Multilabeled Data.

Feature selection is an effective dimensionality reduction technique, which can speed up an algorithm and improve model performance such as predictive accuracy and result comprehensibility. The study of selecting label-specific features for each class label has attracted considerable attention since each class label might be determined by some inherent characteristics, where precise label information is required to guide label-specific feature selection. However, obtaining noise-free labels is quite difficult and impractical. In reality, each instance is often annotated by a candidate label set that comprises multiple ground-truth labels and other false-positive labels, termed partial multilabel (PML) learning scenario. Here, false-positive labels concealed in a candidate label set might induce the selection of false label-specific features while masking the intrinsic label correlations, which misleads the selection of relevant features and compromises the selection performance. To address this issue, a novel two-stage partial multilabel feature selection (PMLFS) approach is proposed, which elicits credible labels to guide accurate label-specific feature selection. First, the label confidence matrix is learned to help elicit ground-truth labels from the candidate label set via the label structure reconstruction strategy, each element of which indicates how likely a class label is ground truth. After that, based on distilled credible labels, a joint selection model, including label-specific feature learner and common feature learner, is designed to learn accurate label-specific features to each class label and common features for all class labels. Besides, label correlations are fused into the features selection process to facilitate the generation of an optimal feature subset. Extensive experimental results clearly validate the superiority of the proposed approach.

Survey on Exact kNN Queries over High-Dimensional Data Space.

k nearest neighbours (kNN) queries are fundamental in many applications, ranging from data mining, recommendation system and Internet of Things, to Industry 4.0 framework applications. In mining, specifically, it can be used for the classification of human activities, iterative closest point registration and pattern recognition and has also been helpful for intrusion detection systems and fault detection. Due to the importance of kNN queries, many algorithms have been proposed in the literature, for both static and dynamic data. In this paper, we focus on exact kNN queries and present a comprehensive survey of exact kNN queries. In particular, we study two fundamental types of exact kNN queries: the kNN Search queries and the kNN Join queries. Our survey focuses on exact approaches over high-dimensional data space, which covers 20 kNN Search methods and 9 kNN Join methods. To the best of our knowledge, this is the first work of a comprehensive survey of exact kNN queries over high-dimensional datasets. We specifically categorise the algorithms based on indexing strategies, data and space partitioning strategies, clustering techniques and the computing paradigm. We provide useful insights for the evolution of approaches based on the various categorisation factors, as well as the possibility of further expansion. Lastly, we discuss some open challenges and future research directions.

Human γδ T cells induce CD8+ T cell antitumor responses via antigen-presenting effect through HSP90-MyD88-mediated activation of JNK.

Human Vγ9Vδ2 T cells have attracted considerable attention as novel alternative antigen-presenting cells (APCs) with the potential to replace dendritic cells in antitumor immunotherapy owing to their high proliferative capacity and low cost. However, the utility of γδ T cells as APCs to induce CD8+ T cell-mediated antitumor immune response, as well as the mechanism by which they perform APC functions, remains unexplored. In this study, we found that activated Vγ9Vδ2 T cells were capable of inducing robust CD8+ T cell responses in osteosarcoma cells. Activated γδ T cells also effectively suppressed osteosarcoma growth by priming CD8+ T cells in xenograft animal models. Mechanistically, we further revealed that activated γδ T cells exhibited increased HSP90 production, which fed back to upregulate MyD88, followed by JNK activation and a subsequent improvement in CCL5 secretion, leading to enhanced CD8+ T cell cross-priming. Thus, our study suggests that Vγ9Vδ2 T cells represent a promising alternative APC for the development of γδ T cell-based tumor immunotherapy.

Enhancement of T cell infiltration via tumor-targeted Th9 cell delivery improves the efficacy of antitumor immunotherapy of solid tumors.

Insufficient infiltration of T cells severely compromises the antitumor efficacy of adoptive cell therapy (ACT) against solid tumors. Here, we present a facile immune cell surface engineering strategy aiming to substantially enhance the anti-tumor efficacy of Th9-mediated ACT by rapidly identifying tumor-specific binding ligands and improving the infiltration of infused cells into solid tumors. Non-genetic decoration of Th9 cells with tumor-targeting peptide screened from phage display not only allowed precise targeted ACT against highly heterogeneous solid tumors but also substantially enhanced infiltration of CD8+ T cells, which led to improved antitumor outcomes. Mechanistically, infusion of Th9 cells modified with tumor-specific binding ligands facilitated the enhanced distribution of tumor-killing cells and remodeled the immunosuppressive microenvironment of solid tumors via IL-9 mediated immunomodulation. Overall, we presented a simple, cost-effective, and cell-friendly strategy to enhance the efficacy of ACT against solid tumors with the potential to complement the current ACT.

Survey of Collision Avoidance Systems for Underground Mines: Sensing Protocols.

With the growing number of unintentional interactions occurring in underground mines, Collision Avoidance System (CAS) establishment and maintenance has become an urgent need for mining industries to enhance their risk profile and improve construction safety. Usually, most collision accidents can be divided into three different categories in line with the involved participants and infrastructure condition. The accidents pose a great risk of financial cost to mining companies and even cause casualties. In detail, this paper presents an intensive study survey of positioning techniques, including ranging algorithms, to accommodate the demands of various proximity sensors and improve the capability of situational awareness. Then, we exploit the importance of the communication system, prevalent low-power wide-area technologies and related communication protocols. The effectiveness of communication systems decides and facilitates the success of the final integrated system that can be used to fundamentally address the problem of collision avoidance. For the purpose of collaboration between communication systems and other executive departments, a series of systematic comparisons of pertinent technologies and algorithms is given near the end, followed by a brief discussion on the best choice among these options. In the proposed solution, the overall end-to-end delay can be minimised to a few nanoseconds and the localisation accuracy can achieve centimetre level when operating in the range of 100 m.

Metabolic control of CD47 expression through LAT2-mediated amino acid uptake promotes tumor immune evasion.

Chemotherapy elicits tumor immune evasion with poorly characterized mechanisms. Here, we demonstrate that chemotherapy markedly enhances the expression levels of CD47 in osteosarcoma tissues, which are positively associated with patient mortality. We reveal that macrophages in response to chemotherapy secrete interleukin-18, which in turn upregulates expression of L-amino acid transporter 2 (LAT2) in tumor cells for substantially enhanced uptakes of leucine and glutamine, two potent stimulators of mTORC1. The increased levels of leucine and enhanced glutaminolysis activate mTORC1 and subsequent c-Myc-mediated transcription of CD47. Depletion of LAT2 or treatment of tumor cells with a LAT inhibitor downregulates CD47 with enhanced macrophage infiltration and phagocytosis of tumor cells, and sensitizes osteosarcoma to doxorubicin treatment in mice. These findings unveil a mutual regulation between macrophage and tumor cells that plays a critical role in tumor immune evasion and underscore the potential to intervene with the LAT2-mediated amino acid uptake for improving cancer therapies.

[Application of three-dimensional printed total scapula for reverse shoulder arthroplasty in treatment of scapular tumors].

Objective: To investigate the effectiveness of three-dimensional (3D) printed total scapula for reverse shoulder arthroplasty in the treatment of scapular tumors. Methods: Between November 2017 and December 2021, 5 patients with scapular tumors were treated by reverse shoulder arthroplasty with 3D printed total scapula. There was 1 male and 4 females. The age ranged from 44 to 59 years, with an average of 50.4 years. There were 2 cases of chondro sarcoma, 1 case of high-grade osteosarcoma, 1 case of lung cancer with scapular metastasis, and 1 case of ligamentoid fibromatosis recurrence. The disease duration was 4-8 months, with an average of 5.8 months. According to the Musculoskeletal Tumor Society (MSTS) scapular girdle classification criteria, 4 cases of tumors involved both S1 and S2 zones, and 1 case involved S2 zone. The tumor diameters ranged from 4.2 to 11.2 cm, with an average of 6.1 cm. The operation time, intraoperative blood loss, and blood transfusion were recorded. During follow-up, the MSTS score was used to evaluate the recovery of limb function of the patients. The sink depth of the affected shoulder, complications, and oncological outcomes were observed. The position of the prosthesis was reviewed by imaging. Results: The operation time ranged from 155 to 230 minutes, with an average of 189 minutes. The intraoperative blood loss was 100-1 500 mL, with a median of 600 mL. Two patients were received blood transfusion of 800 mL and 1 850 mL respectively during operation. All incisions healed by first intention, and no complications such as infection occurred. All patients were followed up 4-22 months, with an average of 13 months. Two patients died at 8 and 15 months after operation respectively due to multiple metastases and organ failure. At last follow-up, the MSTS score of all patients was 73%-83%, with an average of 77.4%. The affected shoulder was 2-4 cm lower than the contralateral side, with an average of 3 cm. Imaging examinations showed that no prosthesis loosening, dislocation, or fracture occurred during follow-up. Conclusion: Reverse shoulder arthroplasty with 3D printed total scapula can obtain good shoulder function and appearance. Patients have high acceptance and satisfaction with this surgical method.

Can "domino" therapy effectively treat the infection around the prosthesis after the limb salvage surgery of bone tumor? - A study of sequential therapy.

BACKGROUND: Tumor resection and prosthetic replacement have become the treatments of choice for malignant bone tumors. Infections are the leading cause of failure of limb salvage surgeries. Therefore, treating infections around prostheses after limb salvage is essential and challenging. Our research team designed a "domino" sequential treatment plan to treat postoperative infections around tumor prostheses and evaluated its efficacy. PURPOSE: To introduce the new domino sequential treatment plan for postoperative infections of tumor prostheses, and evaluate the technical points of the plan and prognosis in medium- and long-term follow-ups. METHODS: Between January 2015 and August 2021, 14 patients were treated with prosthesis-preserving domino sequential therapy for peripheral prosthesis infections after bone-tumor limb salvage. The sample included eight cases of distal femur tumor, two of proximal tibia tumor, three of pelvic tumor, and one of middle femur tumor. We evaluated routine blood test results, C-reactive protein level, the erythrocyte sedimentation rate, and other indicators. X-rays and CT scans of the surgical site were obtained and the Musculoskeletal Tumor Society (MSTS) score was calculated. Treatment involved debridement and lavage of the prosthesis, and systemic and local antibiotics. RESULTS: The positivity rate of microbial culture was 78.6%. There were three cases of Staphylococcus aureus, one of Staphylococcus epidermidis, two of methicillin-resistant Staphylococcus epidermidis, one of methicillin-resistant Staphylococcus aureus, two of Acinetobacter baumannii, one of Streptococcus lactis (group C), one of Streptococcus mitis, and three with negative cultures. In three cases, sequential treatment failed to control the infection. The operation success rate was 78.6% (11/14). One case eventually required amputation, and another required long-term wound dressings. To control the infection, a third had to be treated using antibiotic bone cement combined with the "intramedullary nail reverse double insertion" technique. The MSTS scores of patients before infection debridement and at the last follow-up showed statistically significant differences (t = 5.312, p = 0.02). CONCLUSIONS: The prosthesis-preserving domino sequential method has certain advantages for treating bone-tumor limb salvage infections around the prosthesis. LEVEL OF EVIDENCE: Level IV, therapeutic.

Predictive and Prognostic Biomarkers for Lung Cancer Bone Metastasis and Their Therapeutic Value.

Lung cancer is the leading cause of cancer-related death worldwide. Bone metastasis, which usually accompanies severe skeletal-related events, is the most common site for tumor distant dissemination and detected in more than one-third of patients with advanced lung cancer. Biopsy and imaging play critical roles in the diagnosis of bone metastasis; however, these approaches are characterized by evident limitations. Recently, studies regarding potential biomarkers in the serum, urine, and tumor tissue, were performed to predict the bone metastases and prognosis in patients with lung cancer. In this review, we summarize the findings of recent clinical research studies on biomarkers detected in samples obtained from patients with lung cancer bone metastasis. These markers include the following: (1) bone resorption-associated markers, such as N-terminal telopeptide (NTx)/C-terminal telopeptide (CTx), C-terminal telopeptide of type I collagen (CTx-I), tartrate-resistant acid phosphatase isoform 5b (TRACP-5b), pyridinoline (PYD), and parathyroid hormone related peptide (PTHrP); (2) bone formation-associated markers, including total serum alkaline phosphatase (ALP)/bone specific alkaline phosphatase(BAP), osteopontin (OP), osteocalcin (OS), amino-terminal extension propeptide of type I procollagen/carboxy-terminal extension propeptide of type I procollagen (PICP/PINP); (3) signaling markers, including epidermal growth factor receptor/Kirsten rat sarcoma/anaplastic lymphoma kinase (EGFR/KRAS/ALK), receptor activator of nuclear factor κB ligand/receptor activator of nuclear factor κB/osteoprotegerin (RANKL/RANK/OPG), C-X-C motif chemokine ligand 12/C-X-C motif chemokine receptor 4 (CXCL12/CXCR4), complement component 5a receptor (C5AR); and (4) other potential markers, such as calcium sensing receptor (CASR), bone sialoprotein (BSP), bone morphogenetic protein 2 (BMP2), cytokeratin 19 fragment/carcinoembryonic antigen (CYFRA/CEA), tissue factor, cell-free DNA, long non-coding RNA, and microRNA. The prognostic value of these markers is also investigated. Furthermore, we listed some clinical trials targeting hotspot biomarkers in advanced lung cancer referring for their therapeutic effects.

Clinical Features and Serological Markers Risk Model Predicts Overall Survival in Patients Undergoing Breast Cancer and Bone Metastasis Surgeries.

BACKGROUND: Surgical therapy of breast cancer and bone metastasis can effectively improve the prognosis of breast cancer. However, after the first operation, the relationship between preoperative indicators and outcomes in patients who underwent metastatic bone surgery remained to be studied. Purpose 1. Recognize clinical and laboratory prognosis factors available to clinical doctors before the operation for bone metastatic breast cancer patients. 2. Develop a risk prediction model for 3-year postoperative survival in patients with breast cancer bone metastasis. METHODS: From 2014 to 2020, patients who suffered from breast cancer bone metastasis and received therapeutic procedures in our institution were included for analyses (n=145). For patients who underwent both breast cancer radical surgery and bone metastasis surgery, comprehensive datasets of the parameters of interest (clinical features, laboratory factors, and patient prognoses) were collected (n=69). We performed Multivariate Cox regression to identify factors that were associated with postoperative outcome. 3-year survival prediction model and nomograms were established by 100 bootstrapping. Its benefit was evaluated by calibration plot, C-index, and decision curve analysis. The Surveillance, Epidemiology, and End Results database was also used for external validation. RESULTS: Radiotherapy for primary cancer, pathological type of metastatic breast cancer, lymph node metastasis, elevated serum alkaline phosphatase, lactate dehydrogenase were associated with postoperative prognosis. Pathological types of metastatic breast cancer, multiple bone metastasis, organ metastases, and elevated serum lactate dehydrogenase were associated with 3-year survival. Then those significant variables and serum alkaline phosphatase counts were integrated to construct nomograms for 3-year survival. The C-statistic of the established predictive model was 0.83. The calibration plot presents a graphical representation of calibration. In the decision curve analysis, the benefits are higher than those of the extreme curve. The receiver operating characteristic of the external validation of the model was 0.82, indicating a favored fitting degree of the two models. CONCLUSION: Our study suggests that several clinical features and serological markers can predict the overall survival among the patients who are about to receive bone metastasis surgery after breast cancer surgery. The model can guide the preoperative evaluation and clinical decision-making for patients. Level of evidence Level III, prognostic study.

Mutational characteristics of bone metastasis of lung cancer.

BACKGROUND: Roughly 30-40% of lung cancer (LC) patients develop bone metastasis during the course of disease. The genetic differences between primary LC and matched bone metastasis are not yet fully understood. METHODS: A total of 40 LC patients with bone metastasis were collected and 450 targeted cancer-related genes were sequenced for genomic-alteration (GA) identification. RESULTS: Among the 40 LC patients, 33 had adenocarcinomas and 7 had squamous cell carcinomas. The metastatic sites of the 33 lung adenocarcinomas (LUADs) were the pelvis (6 patients), spine (16 patients), and limbs (11 patients). A total of 425 and 422 GAs were detected in the primary and metastatic lesions, respectively. The most common GAs were epidermal growth factor receptor (EGFR) mutations, which had mutation rates of 85.0% and 72.5% in the primary and metastatic lesions, respectively, and tumor protein 53 (TP53) mutations, which had mutation rates of 52.5% and 67.5% in the primary and metastatic lesions, respectively. Metastases to the pelvis and spine were most commonly accompanied by factor receptor substrate 2 (FRS2), cyclin-dependent kinase 4 (CDK4), and murine double minute 2 (MDM2) amplification, and cyclin-dependent kinase inhibitor 2A (CDKN2A) deletion. The concordance between primary lung squamous cell carcinoma (LUSC) and corresponding metastasis was significantly higher than that of primary LUAD and corresponding metastasis (P=0.033). Compared to limb and pelvis metastases, the shared mutation in spine metastasis was significantly lower (P=0.016 and P=0.023, respectively). In matched primary LUSCs and bone metastasis lesions, there was no significant difference in the distribution of the tumor mutational burden (TMB) (P=0.9). Conversely, a significant difference of the TMB distribution was detected in pairs of primary LUAD and corresponding bone metastasis lesions (P=0.021). CONCLUSIONS: The consistency of mutation patterns between primary LC lesions and matched bone metastases may vary in terms of metastatic sites, but is very high in general. There was a significant difference in the TMB between primary LUAD and matched bone metastatic lesions. Our findings contribute to molecular understandings of primary LC and matched bone metastatic lesions.

Genomic characterization and outcome evaluation of kinome fusions in lung cancer revealed novel druggable fusions.

Kinase fusions represent an important type of somatic alterations that promote oncogenesis and serve as diagnostic markers in lung cancer. We aimed to identify the landscape of clinically relevant kinase fusions in Chinese lung cancer and to explore rare kinase rearrangements; thus, providing valuable evidence for therapeutic decision making. We performed genomic profiling of 425 cancer-relevant genes from tumor/plasma biopsies from a total of 17,442 Chinese lung cancer patients using next generation sequencing (NGS). Patients' clinical characteristics and treatment histories were retrospectively studied. A total of 1162 patients (6.66%; 1162/17,442) were identified as having kinase fusions, including 906 adenocarcinomas (ADCs) and 35 squamous cell carcinomas (SCCs). In ADC, 170 unique gene fusion pairs were observed, including rare kinase fusions, SLC12A2-ROS1, NCOA4-RET, and ANK3-RET. As for SCC, 15 unique gene fusions were identified, among which the most frequent were EML4-ALK and FGFR3-TACC3. Analyses of oncogenic mutations revealed a dual role for the gene fusions, CCDC6-RET and FGFR3-TACC3, in driving oncogenesis or serving as acquired resistance mechanisms to kinase inhibitors. In addition, our real-world evidence showed that patients with recurrent kinase fusions with low frequency (two occurrences) could benefit from treatment with kinase inhibitors' off-label use. Notably, patients with stage IV ADC who had novel RORB-ALK or AFF2-RET fusions, but no other known oncogenic driver mutations, demonstrated favorable clinical outcomes on tyrosine kinase inhibitors. Our data provide a comprehensive overview of the landscape of oncogenic kinase fusions in lung cancer, which assist in recognizing potentially druggable fusions that can be translated into therapeutic applications.