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ARID1A (the AT-rich interaction domain 1A, also known as BAF250a ) is one of the most commonly mutated genes in cancer 1 , 2 . The majority of ARID1A mutations are inactivating mutations and lead to loss of ARID1A expression 3 , which makes ARID1A a poor therapeutic target. Therefore, it is of clinical importance to identify molecular consequences of ARID1A deficiency that create therapeutic vulnerabilities in ARID1A -mutant tumors. In a proteomic screen, we found that ARID1A interacts with mismatch repair (MMR) protein MSH2. ARID1A recruited MSH2 to chromatin during DNA replication and promoted MMR. Conversely, ARID1A inactivation compromised MMR and increased mutagenesis. ARID1A deficiency correlated with microsatellite instability genomic signature and a predominant C>T mutation pattern and increased mutation load across multiple human cancer types. Tumors formed by an ARID1A-deficient ovarian cancer cell line in syngeneic mice displayed increased mutation load, elevated numbers of tumor-infiltrating lymphocytes, and PD-L1 expression. Notably, treatment with anti-PD-L1 antibody reduced tumor burden and prolonged survival of mice bearing ARID1A -deficient but not ARID1A -wild-type ovarian tumors. Together, these results suggest ARID1A deficiency contributes to impaired MMR and mutator phenotype in cancer, and may cooperate with immune checkpoint blockade therapy. Loss of mismatch-repair protein ARID1A in cancer correlates with high mutation load & checkpoint blockade response, complementing MSI-based prognosis.

Background Endometrial cancer is one of the major gynecological cancers, with increasing incidence and mortality in the past decades. Emerging preclinical and clinical data have indicated its close association with obesity and dyslipidemia. Metabolism reprogramming has been considered as the hallmark of cancer, to satisfy the extensive need of nutrients and energy for survival and growth. Particularly, lipid metabolism reprogramming has aroused the researchers’ interest in the field of cancer, including tumorigenesis, invasiveness, metastasis, therapeutic resistance and immunity modulation, etc. But the roles of lipid metabolism reprogramming in endometrial cancer have not been fully understood. This review has summarized how lipid metabolism reprogramming induces oncogenesis and progression of endometrial cancer, including the biological functions of aberrant lipid metabolism pathway and altered transcription regulation of lipid metabolism pathway. Besides, we proposed novel therapeutic strategies of targeting lipid metabolism pathway and concentrated on its potential of sensitizing immunotherapy and hormonal therapy, to further optimize the existing treatment modalities of patients with advanced/metastatic endometrial cancer. Moreover, we expect that targeting lipid metabolism plus hormone therapy may block the endometrial malignant transformation and enrich the preventative approaches of endometrial cancer. Conclusion Lipid metabolism reprogramming plays an important role in tumor initiation and cancer progression of endometrial cancer. Targeting the core enzymes and transcriptional factors of lipid metabolism pathway alone or in combination with immunotherapy/hormone treatment is expected to decrease the tumor burden and provide promising treatment opportunity for patients with advanced/metastatic endometrial cancer.

Ding Ma, Hui Wang, Xun Xu and colleagues report a genome-wide map of HPV integration sites in cervical cancer samples and cell lines. In addition to discovering new integration hot spots, the authors identify microhomology-mediated DNA repair as a likely mechanism by which HPV integrates into the human genome. Human papillomavirus (HPV) integration is a key genetic event in cervical carcinogenesis 1 . By conducting whole-genome sequencing and high-throughput viral integration detection, we identified 3,667 HPV integration breakpoints in 26 cervical intraepithelial neoplasias, 104 cervical carcinomas and five cell lines. Beyond recalculating frequencies for the previously reported frequent integration sites POU5F1B (9.7%), FHIT (8.7%), KLF12 (7.8%), KLF5 (6.8%), LRP1B (5.8%) and LEPREL1 (4.9%), we discovered new hot spots HMGA2 (7.8%), DLG2 (4.9%) and SEMA3D (4.9%). Protein expression from FHIT and LRP1B was downregulated when HPV integrated in their introns. Protein expression from MYC and HMGA2 was elevated when HPV integrated into flanking regions. Moreover, microhomologous sequence between the human and HPV genomes was significantly enriched near integration breakpoints, indicating that fusion between viral and human DNA may have occurred by microhomology-mediated DNA repair pathways 2 . Our data provide insights into HPV integration-driven cervical carcinogenesis.

Recurrence is the main cause of death in patients with endometrial cancer (EC). This study aimed to construct and validate a nomogram to predict the recurrence-free survival of patients with EC. This was a multicenter retrospective study. A total of 812 patients from Wuhan Tongji Hospital were divided into training and validation cohorts, and 347 and 580 patients from People’s Hospital of Peking University and Qilu Hospital of Shandong, respectively, were used for validation. Univariate and multivariate Cox regression analyses were used to construct a nomogram for predicting recurrence-free survival of EC. Calibration curves, receiver operating characteristic (ROC) curves, and consistency indexes (C-indexes) were used to estimate the performance of the model. Decision curve analysis (DCA) curves were used to assess the clinical utility of the model. Age ( P  = 0.013), cancer antigen 125 level ( P  = 0.014), lymphovascular space invasion ( P  = 0.004), International Federation of Gynecology and Obstetrics stage ( P  = 0.034), and P53 ( P  < 0.001) were independently associated with recurrence, and we constructed a nomogram based on these variables. The C-indexes of the validation cohorts were 0.880, 0.835, and 0.875, respectively. The calibration, ROC, and DCA curves revealed that this model had excellent performance and clinical utility. Combining clinical data, clinicopathological factors, serological indicators, and immunohistochemical marks, a multicenter externally verified nomogram with robust performance was constructed to predict the recurrence of patients with EC.

Human cancers results in large part from the accumulation of multiple mutations. The progression of premalignant cells is an evolutionary process in which mutations provide the fundamental driving force for genetic diversity. The increased mutation rate in premalignant cells allows selection for increased proliferation and survival and ultimately leads to invasion, metastasis, recurrence, and therapeutic resistance. Therefore, it is important to understand the molecular determinants of the mutational processes. Recent genome-wide sequencing data showed that apolipoprotein B mRNA editing catalytic polypeptide-like 3B (APOBEC3B) is a key molecular driver inducing mutations in multiple human cancers. APOBEC3B, a DNA cytosine deaminase, is overexpressed in a wide spectrum of human cancers. Its overexpression and aberrant activation lead to unexpected clusters of mutations in the majority of cancers. This phenomenon of clustered mutations, termed kataegis (from the Greek word for showers), forms unique mutation signatures. In this review, we will discuss the biological function of APOBEC3B, its tumorigenic role in promoting mutational processes in cancer development and the clinical potential to develop novel therapeutics by targeting APOBEC3B.

Objective: This study was intended to investigate the relationship between COVID-19 disease and ovarian function in reproductive-aged women. Methods: Female COVID-19 patients of reproductive age were recruited between January 28 and March 8, 2020 from Tongji Hospital in Wuhan. Their baseline and clinical characteristics, as well as menstrual conditions, were recorded. Differentials in ovarian reserve markers and sex hormones (including anti-Müllerian hormone [AMH], follicle-stimulating hormone [FSH], the ratio of FSH to luteinizing hormone [LH], estradiol [E2], progesterone [P], testosterone [T], and prolactin [PRL] were compared to those of healthy women who were randomly selected and individually matched for age, region, and menstrual status. Uni- and multi-variable hierarchical linear regression analyses were performed to identify risk factors associated with ovarian function in COVID-19 women. Results: Seventy eight patients agreed to be tested for serum hormone, of whom 17 (21.79%) were diagnosed as the severe group and 39 (50%) were in the basal level group. Menstrual status ( P = 0.55), menstrual volumes ( P = 0.066), phase of menstrual cycle ( P = 0.58), and dysmenorrhea history ( P = 0.12) were similar without significant differences between non-severe and severe COVID-19 women. Significant lower serum AMH level/proportion (0.19/0.28 vs. 1.12 ng/ml, P = 0.003/0.027; AMH ≤ 1.1 ng/ml: 75/70.4 vs. 49.7%, P = 0.009/0.004), higher serum T (0.38/0.39 vs. 0.22 ng/ml, P < 0.001/0.001) and PRL (25.43/24.10 vs. 12.12 ng/ml, P < 0.001/0.001) levels were observed in basal level and the all-COVID-19 group compared with healthy age-matched control. When adjusted for age, menstrual status and parity variations in multivariate hierarchical linear regression analysis, COVID-19 disease was significantly associated with serum AMH (β = −0.191; 95% CI: −1.177–0.327; P = 0.001), T (β = 0.411; 95% CI: 11.154–22.709; P < 0.001), and PRL (β = 0.497; 95% CI: 10.787–20.266; P < 0.001), suggesting an independent risk factor for ovarian function, which accounted for 3.2% of the decline in AMH, 14.3% of the increase in T, and 20.7% of the increase in PRL. Conclusion: Ovarian injury, including declined ovarian reserve and reproductive endocrine disorder, can be observed in women with COVID-19. More attention should be paid to their ovarian function under this pandemic, especially regarding reproductive-aged women. Clinical Trial Number: ChiCTR2000030015.

High-mobility group AT-hook1 (HMGA1, formerly HMG-I/Y), an architectural transcription factor, participates in a number of tumor biological processes. However, its effect on cervical cancer remains largely indistinct. In this study, we found that HMGA1 was generally overexpressed in cervical cancer tissues and was positively correlated with lymph node metastasis and advanced clinical stage. Via exogenously increasing or decreasing the expression of HMGA1, we showed that HMGA1 affected the proliferation, colony formation, migration and invasion of cervical cancer cells in vitro. Rescue experiments suggested that miR-221/222 could partly reverse HMGA1-mediated migration and invasion processes. Mechanistically, we discovered that HMGA1 accelerated the G1/S phase transition by regulating the expression of cyclin D1 and cyclin E1, which was consistent with the results of the in vivo experiment. Furthermore, we found that HMGA1 regulated the expression of the miR-221/222 cluster at the transcriptional level and that miR-221/222 targeted the 3'UTR of tissue inhibitor of metalloproteinases 3(TIMP3). We propose a fresh perspective that HMGA1 participates in the migration and invasion process via the miR-221/222-TIMP3-MMP2/MMP9 axis in cervical cancer. In summary, our study identified a critical role played by HMGA1 in the progression of cervical cancer and the potential mechanisms by which exerts its effects, suggesting that targeting HMGA1-related pathways could be conducive to the therapies for cervical cancer.

This paper proposes a fusion algorithm based on state-tracking collision detection and the simulated annealing potential field (SCD-SAPF) to address the challenges of obstacle avoidance for autonomous underwater vehicles (AUVs) in dynamic environments. Navigating AUVs in complex underwater environments requires robust autonomous obstacle avoidance capabilities. The SCD-SAPF algorithm aims to accurately assess collision risks and efficiently plan avoidance trajectories. The algorithm introduces an SCD model for proactive collision risk assessment, predicting collision risks between AUVs and dynamic obstacles. Additionally, it proposes a simulated annealing (SA) algorithm to optimize trajectory planning in a simulated annealing potential field (SAPF), integrating the SCD model with the SAPF algorithm to guide AUVs in obstacle avoidance by generating optimal heading and velocity outputs. Extensive simulation experiments demonstrate the effectiveness and robustness of the algorithm in various dynamic scenarios, enabling the early avoidance of dynamic obstacles and outperforming traditional methods. This research provides an accurate collision risk assessment and efficient obstacle avoidance trajectory planning, offering an innovative approach to the field of underwater robotics and supporting the enhancement of AUV autonomy and reliability in practical applications.

While advances in behavioural and neuroimaging methods suitable for use with infants have greatly increased our understanding of infant brain function, cognition and behaviour in recent years, relatively little is known about the rapid period of development during the last trimester of pregnancy and first weeks and months after birth, as well as the roles that the social environment and stress play in shaping this development. This protocol paper outlines The UK Perinatal Imaging in Partnership with Families (PIPKIN) Study, a unique, multi-method, longitudinal cohort study investigating the early development of fetal and infant neurocognitive function and behaviour, and how the infant’s social and family environment shapes this development. The study follows families from a range of socio-economic backgrounds who participate at ten timepoints, from the third trimester of pregnancy until their infant is nine months old, with three visits taking place during the infant’s first postnatal month. The study harnesses recent methodological advances coupled with the drive for more ecologically valid data collection by undertaking many of these visits in families’ homes. Methods include measures of fetal behaviour using 4D ultrasound scanning; infant brain imaging using fNIRS and EEG; a full-day video recording of the home environment from the infant’s perspective, with physiological measures; measures of recent stress in both infant and mother; questionnaires relating to the home environment as well as parents’ feelings, attitudes, health and parenting routines; and standardised measures of infant behaviour and development. Specific aims are to investigate: i) individual differences in basic sensory, behavioural and motor processing between late prenatal and early postnatal periods; ii) rapid change in cortical functions over the first month, particularly for brain networks that support social behaviour; iii) effects of social interaction on developing brain function; and iv) individual differences in developmental trajectories associated with poverty-related contextual factors.