Lymphoma cell-driven IL-16 is expressed in activated B-cell-like diffuse large Bcell lymphomas and regulates the pro-tumor microenvironment

The activated B-cell–like subtype of diffuse large B-cell lymphoma (ABC-DLBCL) displays a worse outcome than the germinal center B-cell–like subtype (GCB-DLBCL). Currently, targeting tumor microenvironment (TME) is the promising approach to cure DLBCL with profound molecular heterogeneity, however, the factors affecting the tumor-promoting TME of ABCDLBCL are elusive. Here, cytokine interleukin-16 (IL-16) is expressed in tumor cells of ABCDLBCL and secreted by the cleavage of active caspase-3. The serum IL-16 levels are not only a sensitive marker of treatment response but also positively correlated with unfavorable prognosis in DLBCL patients. While IL-16 shows few direct promotional effects on tumor cell growth in vitro, its bioactive form significantly promotes tumor progression in vivo. Mechanically, IL-16 increases the infiltration of macrophages by the chemotaxis of CD4+ monocytes in the TME enhancing angiogenesis, and the expression of cytokine IL-6 and IL-10, as well as decreasing T cell infiltration to accelerate tumor progression. This study demonstrates that IL-16 exerts a novel role in coordinating the bidirectional interactions between tumor progression and the TME. IMM0306, a fusion protein of CD20 mAb with the CD47 binding domain of SIRPα, reverses the tumorpromoting effects of IL-16,which provides new insight into treatment strategy in ABC-DLBCL

Exosomal miR-27a Derived from Gastric Cancer Cells Regulates the Transformation of Fibroblasts into Cancer-Associated Fibroblasts

Background/Aims: The malignant biological behavior of gastric cancer(GC) is not only determined by cancer cells alone, but also closely regulated by the microenvironment. Fibroblasts represent a large proportion of the components in the tumor microenvironment, and they promote the development of disease. Currently, accumulating evidence suggests that exosomes can function as intercellular transport systems to relay their contents, especially microRNAs(miRNAs). Methods: First, we detected the highly-expressed level of miR-27a in exosomes isolated from gastric cancer cells by qRT-PCR. MiR-27a –over-expressed models in vitro and in vivo were established to investigate the transformation of cancer-associated fibroblasts observed by Western blotting, and the malignant behavior of gastric cancer cells using the methods CCK8 and Transwell. Moreover, the downregulation of CSRP2 in fibroblasts was used to evaluate the promotion of malignancy of gastric cancer using the methods CCK8 and Transwell. Results: In this study, we found a marked high level of miR-27a in exosomes derived from GC cells. miR-27a was found to function an oncogene that not only induced the reprogramming of fibroblasts into cancer-associated fibroblasts(CAFs), but also promoted the proliferation, motility and metastasis of cancer cells in vitro and in vivo. Conversely, CAFs with over-expression of miR-27a could pleiotropically increase the malignant behavior of the GC cells. For the first time, we revealed that CSRP2 is a downstream target of miR-27a. CSRP2 downregulation could increase the proliferation and motility of GC cells. Conclusion: Thus, this report indicates that miR-27a in exosomes derived from GC cells has a crucial impact on the microenvironment and may be used as a potential therapeutic target in the treatment of G

Densification Mechanisms and Pore Evolution Analysis of a Tight Reservoir: A Case Study of Shan-1 Member of Upper Paleozoic Shanxi Formation in SW Ordos Basin, China

This comprehensive analysis investigated the causes of formation densification in the Shan-1 Member tight reservoir in the southwestern Ordos Basin. The study aimed to mitigate exploration and development risks by examining petrological characteristics, reservoir performance, pore characteristics, and pore evolution. Various techniques were employed, including thin-section casting, scanning electron microscopy, and analysis of porosity and permeability. By establishing the relationship between visualized reservoir porosity and thin slice porosity, along with employing mechanical compaction correction methods and the principle of “back stripping by inversion,” the recovery of paleophysical properties in tight sandstone reservoirs was conducted. Additionally, the research integrated diagenetic evolution sequences and the recovery of paleophysical properties to analyze the origins of reservoir densification and pore evolution in the Shan-1 Member. The results suggest that compaction is the primary factor contributing to reservoir densification, with burial depth playing a crucial role in determining the intensity of compaction. Cementation, particularly associated with illite, emerged as a significant influence on reservoir densification, while low dissolution also contributed to the densification process. The densification of the Shan-1 reservoir in the study area was estimated to have occurred during the Early Jurassic, approximately 195 Ma. These research findings not only enhance the understanding of the Shan-1 reservoir but also provide valuable insights for predicting tight reservoirs and improving the efficiency of oil and gas production

Abstract LB543: tmHRD: Accurately estimating the homologous recombination deficiency status from clinical panel sequencing data

Abstract Estimating the status of homologous recombination deficiency (HRD) is of clinical interest because the homologous recombination-deficient cells are reported sensitive to poly-ADP ribose polymerase (PARP) inhibitors. As HRD status becomes a critical indicator, many approaches have been proposed to measure the HRD status, among which estimating HRD status from cancer sequencing data is the popular strategy, where the representative methods include HRDetect, SigMA, FoundationFocusCDx, MyChoiceHRD, etc. Although sequencing data is the same input of these bioinformatics tools, algorithms prefer different aspects. Some methods focus on germline variants in BRCA1/2 genes and somatic mutational signatures, while some others capture the genomic scars, including loss of heterozygosity (LOH), telomere allele imbalance (TAI) and large-scale state transition (LST). However, there are two major controversial points when applying these tools on clinical sequencing data. First, panel sequencing is the most popular sequencing plan in clinic, but gene panels usually carry only hundreds to a thousand genes. Thus, the panel sequencing can neither capture a large number of mutations to calculate mutational signatures, nor obtain large genomic scars, such as TAI and LST. Second, the associations between the mutations and HRD status is still unclear. Thus, scoring mutations and genomic scars is not reasonable. To solving these issues, we here proposed a machine learning-based method, called tmHRD, which estimates HRD status according to limited mutations and LOHs captured by clinical panel sequencing data. It consists of a semi-supervised learning (TRI) model and a multi-instance learning (MIL) model. The TRI model filters the false positives from mutation calls. Then, the filtered mutation calls from one patient is defined as a package, where each mutation call is an instance in the package. When training the MIL model, in each iteration, a package with known HRD status (label) is given to MIL model. MIL model calculates the correlations among instances and assigns an adjusted weight for each. Thus, the HRD status is only contributed by those mutations associated with. We tested tmHRD on several datasets obtained by the clinical trials we participated. Compared to the existing methods, tmHRD achieved better performance. The average recognition rate of tmHRD was approaching 90%, while the comparison methods show around 80%. The software package, tmHRD, is freely available at https://github.com/Sherwin-xjtu/TriMILhrd/ for academic usages only. Citation Format: Xuwen Wang, Ying Xu, Yanfang Guan, Xin Yi, Jiayin Wang. tmHRD: Accurately estimating the homologous recombination deficiency status from clinical panel sequencing data [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr LB543.</jats:p

Base-Induced Highly Regioselective Synthesis of <i>N</i>²‑Substituted 1,2,3-Triazoles under Mild Conditions in Air

We developed a highly regioselective base-induced synthesis of N2-substituted 1,2,3-triazoles from N-sulfonyl-1,2,3-triazoles and alkyl bromides/alkyl iodides at room temperature. We propose an SN2-like mechanistic pathway to explain the high N2-regioselectivity. The protocol features a broad substrate scope and generates products in good to excellent yields (72–90%)

Data from: A robust and tunable mitotic oscillator in artificial cells

Single-cell analysis is pivotal to deciphering complex phenomena like heterogeneity, bistability, and asynchronous oscillations, where a population ensemble cannot represent individual behaviors. Bulk cell-free systems, despite having unique advantages of manipulation and characterization of biochemical networks, lack the essential single-cell information to understand a class of out-of-steady-state dynamics including cell cycles. Here, by encapsulating Xenopus egg extracts in water-in-oil microemulsions, we developed artificial cells that are adjustable in sizes and periods, sustain mitotic oscillations for over 30 cycles, and function in forms from the simplest cytoplasmic-only to the more complicated ones involving nuclear dynamics, mimicking real cells. Such innate flexibility and robustness make it key to studying clock properties like tunability and stochasticity. Our results also highlight energy as an important regulator of cell cycles. We demonstrate a simple, powerful, and likely generalizable strategy of integrating strengths of single-cell approaches into conventional in vitro systems to study complex clock functions