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Neutrophil extracellular traps (NETs), a web-like structure of cytosolic and granule proteins assembled on decondensed chromatin, kill pathogens and cause tissue damage in diseases. Whether NETs can kill cancer cells is unexplored. Here, we report that a combination of glutaminase inhibitor CB-839 and 5-FU inhibited the growth of PIK3CA-mutant colorectal cancers (CRCs) in xenograft, syngeneic, and genetically engineered mouse models in part through NETs. Disruption of NETs by either DNase I treatment or depletion of neutrophils in CRCs attenuated the efficacy of the drug combination. Moreover, NETs were present in tumor biopsies from patients treated with the drug combination in a phase II clinical trial. Increased NET levels in tumors were associated with longer progression-free survival. Mechanistically, the drug combination induced the expression of IL-8 preferentially in PIK3CA-mutant CRCs to attract neutrophils into the tumors. Further, the drug combination increased the levels of ROS in neutrophils, thereby inducing NETs. Cathepsin G (CTSG), a serine protease localized in NETs, entered CRC cells through the RAGE cell surface protein. The internalized CTSG cleaved 14-3-3 proteins, released BAX, and triggered apoptosis in CRC cells. Thus, our studies illuminate a previously unrecognized mechanism by which chemotherapy-induced NETs kill cancer cells.

This paper first proposes a European option pricing method for deposit insurance based on triangular intuitionistic fuzzy numbers. In the proposed method, we take into account the randomness and fuzziness of bank asset value simultaneously, and hence, the method can adequately reflect the high uncertainty of bank asset value. This method fuzzifies the value of bank asset, resubmits it into the original deposit insurance option pricing model as a fuzzy random variable, and then gives an analytic formula of deposit insurance rates using a risk-neutral method. After this, we have also conducted a numerical analysis. In specific, we have obtained the premium interval and presented the static analysis of key parameters. Finally, seven small- and middle-sized banks in Hunan Province in China are used as examples to validate the proposed interval pricing model. The Black-Scholes option pricing model and Yoshida’s triangular fuzzy model are also employed for comparison. The research results show that the interval rates obtained from the proposed European option pricing method for deposit insurance can better reflect the uncertainty of bank asset evaluation than the fixed rates obtained from the Black-Scholes option pricing model. Moreover, the model proposed in this paper is also superior to Yoshida’s model in practice.

This review comprehensively analyzes the current landscape of tumor-agnostic therapies in oncology. Tumor-agnostic therapies are designed to target specific molecular alterations rather than the primary site of the tumor, representing a shift in cancer treatment. We discuss recent approvals by regulatory agencies such as the FDA and EMA, highlighting therapies that have demonstrated efficacy across multiple cancer types sharing common alterations. We delve into the trial methodologies that underpin these approvals, emphasizing innovative designs such as basket trials and umbrella trials. These methodologies present unique advantages, including increased efficiency in patient recruitment and the ability to assess drug efficacy in diverse populations rapidly. However, they also entail certain challenges, including the need for robust biomarkers and the complexities of regulatory requirements. Moreover, we examine the promising prospects for developing therapies for rare cancers that exhibit common molecular targets typically associated with more prevalent malignancies. By synthesizing these insights, this review underscores the transformative potential of tumor-agnostic therapies in oncology. It offers a pathway for personalized cancer treatment that transcends conventional histology-based classification.

Breast cancer is the most diagnosed cancer among women worldwide, with an estimated 2.3 million new cases and 670,000 deaths reported in 2022. Advances in genomic research have heralded a new era in precision medicine, enabling personalized treatment and risk assessment based on molecular profiles. Next-generation sequencing and deep-learning algorithms have transformed breast cancer care by facilitating the analysis of complex and extensive datasets, with the potential to democratize access to omics-informed clinical trials. A comprehensive understanding of the heterogeneity and complexity of breast cancer across diverse populations, along with intricate disease mechanisms, is fueling innovations aimed at personalizing breast cancer care and reducing global disparities in outcomes. Here, Wu et al discuss the convergence of genomic medicine and translational omics in transforming breast cancer patient care.

Hepatocellular carcinoma (HCC) remains one of the most lethal cancers globally, driven by chronic liver disease and a complex tumor microenvironment (TME). Recent advances in spatial omics, single-cell analyses, and AI-driven digital pathology have shed light on the intricate heterogeneity of HCC, highlighting key roles for immune suppression, angiogenesis, and fibrosis in tumor progression. This review synthesizes current epidemiological trends, noting a shift from viral hepatitis to metabolic syndrome as a primary etiology in Western populations, and elucidates how TME components—such as tumor-associated macrophages, cancer-associated fibroblasts, vascular endothelial cells, and immunosuppressive cytokines—contribute to resistance against conventional therapies. We detail the evolution of immunotherapeutic strategies from monotherapy to combination regimens, including dual immune checkpoint blockade and the integration of antiangiogenic agents. Emerging circulating and tissue-based biomarkers offer promise for enhanced patient stratification and real-time monitoring of treatment responses. Collectively, these innovations herald a paradigm shift toward TME-directed precision oncology in HCC, emphasizing the need for multi-targeted approaches to synergistically modulate interacting cellular constituents and ultimately improve clinical outcomes.

Appendiceal neuroendocrine neoplasms (ANENs) usually present as incidental findings at the time of appendectomy for acute appendicitis. They are rare, accounting for only 0.5–1% of intestinal neoplasms; they are found in 0.3–0.9% of all appendectomy specimens. They are usually sporadic tumors. There are several histological types including well-differentiated neuroendocrine tumors (NETs), poorly differentiated neuroendocrine carcinomas (NECs), and mixed neuroendocrine-non-neuroendocrine neoplasms (MiNENs). Histologic differentiation and the grade of well-differentiated NETs correlate with clinical behavior and prognosis. Management varies based on differentiation, aggressiveness, and metastatic potential. There is debate about the optimal surgical management for localized appendiceal NETs that are impacted by many factors including the tumor size, the extent of mesoappendiceal spread, lymphovascular invasion and perineural involvement. In addition, the data to guide therapy in metastatic disease are limited due to the paucity of these tumors. Here, we review the current advances in the management of ANENs within the context of a multidisciplinary approach to these tumors.