Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the USs. Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), 3 adenosarcomas, 2 carcinosarcomas, and 1 uterine tumor resembling an ovarian sex-cord tumor (UTROSCT). ESS (including high-grade ESS and low-grade ESS) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A - PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uDEGs were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named MMN-MIL showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion: USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors.

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

CuET overcomes regorafenib resistance by inhibiting epithelial-mesenchymal transition through suppression of the ERK pathway in hepatocellular carcinoma.

BACKGROUND AND PURPOSE: Regorafenib was approved by the US Food and Drug Administration (FDA) for hepatocellular carcinoma (HCC) patients showing progress on sorafenib treatment. However, there is an inevitably high rate of drug resistance associated with regorafenib, which reduces its effectiveness in clinical treatment. Thus, there is an urgent need to find a potential way to solve the problem of regorafenib resistance. The metabolite of disulfiram complexed with copper, the Diethyldithiocarbamate-copper complex (CuET), has been found to be an effective anticancer drug candidate. In the present study, we aimed to evaluate the effect of CuET on regorafenib resistance in HCC and uncover the associated mechanism. EXPERIMENTAL APPROACH: Regorafenib-resistant HCC strains were constructed by applying an increasing concentration gradient. This study employed a comprehensive range of methodologies, including the cell counting kit-8 (CCK-8) assay, colony formation assay, cell cycle analysis, wound healing assay, Transwell assay, tumor xenograft model, and immunohistochemical analysis. These methods were utilized to investigate the antitumor activity of CuET, assess the combined effect of regorafenib and CuET, and elucidate the molecular mechanism underlying CuET-mediated regorafenib resistance. KEY RESULTS: The inhibitory effect of regorafenib on cell survival, proliferation and migration was decreased in regorafenib-resistant MHCC-97H (MHCC-97H/REGO) cells compared with parental cells. CuET demonstrated significant inhibitory effects on cell survival, proliferation, and migration of various HCC cell lines. CuET restored the sensitivity of MHCC-97H/REGO HCC cells to regorafenib in vitro and in vivo. Mechanistically, CuET reverses regorafenib resistance in HCC by suppressing epithelial-mesenchymal transition (EMT) through inhibition of the ERK signaling pathway. CONCLUSION AND IMPLICATIONS: Taken together, the results of this study demonstrated that CuET inhibited the activation of the ERK signaling pathway, leading to the suppression of the epithelial-mesenchymal transition (EMT) and subsequently reversing regorafenib resistance in HCC both in vivo and in vitro. This study provides a new idea and potential strategy to improve the treatment of regorafenib-resistant HCC.

Stabilized ε-Fe2C catalyst with Mn tuning to suppress C1 byproduct selectivity for high-temperature olefin synthesis.

Accurately controlling the product selectivity in syngas conversion, especially increasing the olefin selectivity while minimizing C1 byproducts, remains a significant challenge. Epsilon Fe2C is deemed a promising candidate catalyst due to its inherently low CO2 selectivity, but its use is hindered by its poor high-temperature stability. Herein, we report the successful synthesis of highly stable ε-Fe2C through a N-induced strategy utilizing pyrolysis of Prussian blue analogs (PBAs). This catalyst, with precisely controlled Mn promoter, not only achieved an olefin selectivity of up to 70.2% but also minimized the selectivity of C1 byproducts to 19.0%, including 11.9% CO2 and 7.1% CH4. The superior performance of our ε-Fe2C-xMn catalysts, particularly in minimizing CO2 formation, is largely attributed to the interface of dispersed MnO cluster and ε-Fe2C, which crucially limits CO to CO2 conversion. Here, we enhance the carbon efficiency and economic viability of the olefin production process while maintaining high catalytic activity.

Pulsed laser induced plasma and thermal effects on molybdenum carbide for dry reforming of methane.

Dry reforming of methane (DRM) is a highly endothermic process, with its development hindered by the harsh thermocatalytic conditions required. We propose an innovative DRM approach utilizing a 16 W pulsed laser in combination with a cost-effective Mo2C catalyst, enabling DRM under milder conditions. The pulsed laser serves a dual function by inducing localized high temperatures and generating *CH plasma on the Mo2C surface. This activates CH4 and CO2, significantly accelerating the DRM reaction. Notably, the laser directly generates *CH plasma from CH4 through thermionic emission and cascade ionization, bypassing the traditional step-by-step dehydrogenation process and eliminating the rate-limiting step of methane cracking. This method maintains a carbon-oxygen balanced environment, thus preventing the deactivation of the Mo2C catalyst due to CO2 oxidation. The laser-catalytic DRM achieves high yields of H2 (14300.8 mmol h-1 g-1) and CO (14949.9 mmol h-1 g-1) with satisfactory energy efficiency (0.98 mmol kJ-1), providing a promising alternative for high-energy-consuming catalytic systems.

Fully exposed Pt clusters for efficient catalysis of multi-step hydrogenation reactions.

For di-nitroaromatics hydrogenation, it is a challenge to achieve the multi-step hydrogenation with high activity and selectivity due to the complexity of the process involving two nitro groups. Consequently, many precious metal catalysts suffer from low activity for this multi-step hydrogenation reaction. Herein, we employ a fully exposed Pt clusters catalyst consisting of an average of four Pt atoms on nanodiamond@graphene (Ptn/ND@G), demonstrating excellent catalytic performance for the multi-step hydrogenation of 2,4-dinitrotoluene. The TOF (40647 h-1) of Ptn/ND@G is significantly superior to that of single Pt atoms catalyst, Pt nanoparticles catalyst, and even all the known catalysts. Density functional theory calculations and absorption experiments reveal that the synergetic interaction between the multiple active sites of Ptn/ND@G facilitate the co-adsorption/activation of reactants and H2, as well as the desorption of intermediates/products, which is the key for the higher catalytic activity than single Pt atoms catalyst and Pt nanoparticles catalyst.

Deep learning framework for comprehensive molecular and prognostic stratifications of triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is the most challenging breast cancer subtype. Molecular stratification and target therapy bring clinical benefit for TNBC patients, but it is difficult to implement comprehensive molecular testing in clinical practice. Here, using our multi-omics TNBC cohort (N = 425), a deep learning-based framework was devised and validated for comprehensive predictions of molecular features, subtypes and prognosis from pathological whole slide images. The framework first incorporated a neural network to decompose the tissue on WSIs, followed by a second one which was trained based on certain tissue types for predicting different targets. Multi-omics molecular features were analyzed including somatic mutations, copy number alterations, germline mutations, biological pathway activities, metabolomics features and immunotherapy biomarkers. It was shown that the molecular features with therapeutic implications can be predicted including the somatic PIK3CA mutation, germline BRCA2 mutation and PD-L1 protein expression (area under the curve [AUC]: 0.78, 0.79 and 0.74 respectively). The molecular subtypes of TNBC can be identified (AUC: 0.84, 0.85, 0.93 and 0.73 for the basal-like immune-suppressed, immunomodulatory, luminal androgen receptor, and mesenchymal-like subtypes respectively) and their distinctive morphological patterns were revealed, which provided novel insights into the heterogeneity of TNBC. A neural network integrating image features and clinical covariates stratified patients into groups with different survival outcomes (log-rank P < 0.001). Our prediction framework and neural network models were externally validated on the TNBC cases from TCGA (N = 143) and appeared robust to the changes in patient population. For potential clinical translation, we built a novel online platform, where we modularized and deployed our framework along with the validated models. It can realize real-time one-stop prediction for new cases. In summary, using only pathological WSIs, our proposed framework can enable comprehensive stratifications of TNBC patients and provide valuable information for therapeutic decision-making. It had the potential to be clinically implemented and promote the personalized management of TNBC.

TMVP1448, a novel peptide improves detection of primary tumors and metastases by specifically targeting VEGFR-3.

Lymphangiogenesis at primary tumor and draining lymph nodes plays a pivotal role in tumor metastasis, which has been demonstrated to be regulated by the vascular endothelial growth factor receptor 3 (VEGFR-3) pathway. However, the effect of molecular imaging peptides, which specifically bind VEGFR-3, in tracing tumors remains unclear. We prepared a novel peptide, TMVP1448, with high-affinity to VEGFR-3. The dissociation constant (KD) of TMVP1448 with VEGFR-3 was 7.07 ×10-7 M. In vitro cellular assay showed that TMVP1448 could bind specifically with VEGFR-3. Near infrared imaging results showed that Cy7-TMVP1448 was able to accurately trace primary and metastatic cancers, and PET/CT results showed that [68Ga]Ga-DOTA-TMVP1448 was superior to commonly used radiotracers 18F-FDG. Additionally, no significant negative effect of TMVP1448 was found in mice. Our results suggested that TMVP1448 had great potential for future clinical applications in fluorescence imaging and nuclear imaging of tumors.

A High-Throughput Circular Tumor Cell Sorting Chip with Trapezoidal Cross Section.

Circulating tumor cells are typically found in the peripheral blood of patients, offering a crucial pathway for the early diagnosis and prediction of cancer. Traditional methods for early cancer diagnosis are inefficient and inaccurate, making it difficult to isolate tumor cells from a large number of cells. In this paper, a new spiral microfluidic chip with asymmetric cross-section is proposed for rapid, high-throughput, label-free enrichment of CTCs in peripheral blood. A mold of the desired flow channel structure was prepared and inverted to make a trapezoidal cross-section using a micro-nanotechnology process of 3D printing. After a systematic study of how flow rate, channel width, and particle concentration affect the performance of the device, we utilized the device to simulate cell sorting of 6 µm, 15 µm, and 25 µm PS (Polystyrene) particles, and the separation efficiency and separation purity of 25 µm PS particles reached 98.3% and 96.4%. On this basis, we realize the enrichment of a large number of CTCs in diluted whole blood (5 mL). The results show that the separation efficiency of A549 was 88.9% and the separation purity was 96.4% at a high throughput of 1400 µL/min. In conclusion, we believe that the developed method is relevant for efficient recovery from whole blood and beneficial for future automated clinical analysis.

Exploratory biomarker analysis in the phase III L-MOCA study of olaparib maintenance therapy in patients with platinum-sensitive relapsed ovarian cancer.

BACKGROUND: The prospective phase III multi-centre L-MOCA trial (NCT03534453) has demonstrated the encouraging efficacy and manageable safety profile of olaparib maintenance therapy in the Asian (mainly Chinese) patients with platinum-sensitive relapsed ovarian cancer (PSROC). In this study, we report the preplanned exploratory biomarker analysis of the L-MOCA trial, which investigated the effects of homologous recombination deficiency (HRD) and programmed cell death ligand 1 (PD-L1) expression on olaparib efficacy. METHODS: HRD status was determined using the ACTHRD assay, an enrichment-based targeted next-generation sequencing assay. PD-L1 expression was assessed by SP263 immunohistochemistry assay. PD-L1 expression positivity was defined by the PD-L1 expression on ≥ 1% of immune cells. Kaplan-Meier method was utilised to analyse progression-free survival (PFS). RESULTS: This exploratory biomarker analysis included 225 patients and tested HRD status [N = 190; positive, N = 125 (65.8%)], PD-L1 expression [N = 196; positive, N = 56 (28.6%)], and BRCA1/2 mutation status (N = 219). The HRD-positive patients displayed greater median PFS than the HRD-negative patients [17.9 months (95% CI: 14.5-22.1) versus 9.2 months (95% CI: 7.5-13.8)]. PD-L1 was predominantly expressed on immune cells. Positive PD-L1 expression on immune cells was associated with shortened median PFS in the patients with germline BRCA1/2 mutations [14.5 months (95% CI: 7.4-18.2) versus 22.2 months (95% CI: 18.3-NA)]. Conversely, positive PD-L1 expression on immune cells was associated with prolonged median PFS in the patients with wild-type BRCA1/2 [20.9 months (95% CI: 13.9-NA) versus 8.3 months (95% CI: 6.7-13.8)]. CONCLUSIONS: HRD remained an effective biomarker for enhanced olaparib efficacy in the Asian patients with PSROC. Positive PD-L1 expression was associated with decreased olaparib efficacy in the patients with germline BRCA1/2 mutations but associated with improved olaparib efficacy in the patients with wild-type BRCA1/2. TRIAL REGISTRATION: NCT03534453. Registered at May 23, 2018.

Improvement of Performance of CZTSSe Solar Cells by the Synergistic Effect of Back Contact Modification and Ag Doping.

To improve the performance of Cu2ZnSn(S,Se)4 solar cells, a strategy is proposed to improve the quality of absorber and back interface simultaneously by substituting V-doped Mo (Mo:V) for a conventional Mo back electrode and incorporating Ag into the Cu2ZnSn(S,Se)4 (ACZTSSe) absorber in this work. Since p+-type V-doped MoSe2 (MoSe2:V) is formed in the site between the absorber and Mo:V during selenization, the conventional Mo/n-MoSe2 back contact is modified to Mo:V/p+-MoSe2:V, a back surface passivation field (BSPF) is established at the back interface, the band bending of MoSe2:V is downward and that of bottom of the absorber is upward. Further investigation reveals that the back contact modification and Ag doping have a synergistic effect on inhibiting carrier recombination, decreasing series resistance and increasing shunt resistance, thereby leading to the PCE of device without antireflection coating increased from 8.61 to 10.98%, which is larger than the sum of increase in PCE induced by Ag doping alone (8.61 to 9.66%) and back contact modification alone (8.61 to 9.63%). It is demonstrated that the synergistic effect stems mainly from the strengthened BSPF and the further reduced back contact barrier height. The former is due to the increased difference in work function (WF) between MoSe2:V and absorber induced by the reduced WF of the absorber after Ag doping and the raised WF of MoSe2:V after V doping. The latter is due to the downshifted valence band maximum of absorber after Ag doping. This work highlights the synergistic effect of back contact modification and Ag doping on improving the performance of CZTSSe solar cells and also provides an effective way to suppress carrier recombination.

FOXS1 acts as an oncogene and induces EMT through FAK/PI3K/AKT pathway by upregulating HILPDA in prostate cancer.

Prostate cancer (PCa) is a widespread global health concern characterized by elevated rates of occurrence, and there is a need for novel therapeutic targets to enhance patient outcomes. FOXS1 is closely linked to different cancers, but its function in PCa is still unknown. The expression of FOXS1, its prognostic role, clinical significance in PCa, and the potential mechanism by which FOXS1 affects PCa progression were investigated through bioinformatics analysis utilizing public data. The levels of FOXS1 and HILPDA were evaluated in clinical PCa samples using various methods, such as western blotting, immunohistochemistry, and qRT-PCR. To examine the function and molecular mechanisms of FOXS1 in PCa, a combination of experimental techniques including CCK-8 assay, flow cytometry, wound-healing assay, Transwell assay, and Co-IP assay were employed. The FOXS1 expression levels were significantly raised in PCa, correlating strongly with tumor aggressiveness and an unfavorable prognosis. Regulating FOXS1 expression, whether upregulating or downregulating it, correspondingly enhanced or inhibited the growth, migration, and invasion capabilities of PCa cells. Mechanistically, we detected a direct interaction between FOXS1 and HILPDA, resulting in the pathway activation of FAK/PI3K/AKT and facilitation EMT in PCa cells. FOXS1 collaborates with HILPDA to initiate EMT, thereby facilitating the PCa progression through the FAK/PI3K/AKT pathway activation.

Constructing Metal(II)-Sulfate Site Catalysts toward Low Overpotential Carbon Dioxide Electroreduction to Fuel Chemicals.

Precise regulation of the active site structure is an important means to enhance the activity and selectivity of catalysts in CO2 electroreduction. Here, we creatively introduce anionic groups, which can not only stabilize metal sites with strong coordination ability but also have rich interactions with protons at active sites to modify the electronic structure and proton transfer process of catalysts. This strategy helps to convert CO2 into fuel chemicals at low overpotentials. As a typical example, a composite catalyst, CuO/Cu-NSO4/CN, with highly dispersed Cu(II)-SO4 sites has been reported, in which CO2 electroreduction to formate occurs at a low overpotential with a high Faradaic efficiency (-0.5 V vs. RHE, FEformate=87.4 %). Pure HCOOH is produced with an energy conversion efficiency of 44.3 % at a cell voltage of 2.8 V. Theoretical modeling demonstrates that sulfate promotes CO2 transformation into a carboxyl intermediate followed by HCOOH generation, whose mechanism is significantly different from that of the traditional process via a formate intermediate for HCOOH production.

Calcification-associated molecular traits and therapeutic strategies in hormone receptor-positive HER2-negative breast cancer.

OBJECTIVE: Mammographic calcifications are a common feature of breast cancer, but their molecular characteristics and treatment implications in hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer remain unclear. METHODS: We retrospectively collected mammography records of an HR+/HER2- breast cancer cohort (n = 316) with matched clinicopathological, genomic, transcriptomic, and metabolomic data. On the basis of mammographic images, we grouped tumors by calcification status into calcification-negative tumors, tumors with probably benign calcifications, tumors with calcification of low-moderate suspicion for maligancy and tumors with calcification of high suspicion for maligancy. We then explored the molecular characteristics associated with each calcification status across multiple dimensions. RESULTS: Among the different statuses, tumors with probably benign calcifications exhibited elevated hormone receptor immunohistochemical staining scores, estrogen receptor (ER) pathway activation, lipid metabolism, and sensitivity to endocrine therapy. Tumors with calcifications of high suspicion for malignancy had relatively larger tumor sizes, elevated lymph node metastasis incidence, Ki-67 staining scores, genomic instability, cell cycle pathway activation, and may benefit from cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors. CONCLUSIONS: Our research established links between tumor calcifications and molecular features, thus proposing potential precision treatment strategies for HR+/HER2- breast cancer.

Asynchronous characteristics of Feammox and iron reduction from paddy soils in Southern China.

Recently, the newly discovered anaerobic ammonium oxidation coupled with iron reduction (i.e., Feammox) has been proven to be a widespread nitrogen (N) loss pathway in ecosystems and has an essential contribution to gaseous N loss in paddy soil. However, the mechanism of iron-nitrogen coupling transformation and the role of iron-reducing bacteria (IRB) in Feammox were poorly understood. This study investigated the Feammox and iron reduction changes and microbial community evolution in a long-term anaerobic incubation by 15N isotope labeling combined with molecular biological techniques. The average rates of Feammox and iron reduction during the whole incubation were 0.25 ± 0.04 µg N g-1 d-1 and 40.58 ± 3.28 µg Fe g-1 d-1, respectively. High iron oxide content increased the Feammox rate, but decreased the proportion of Feammox-N2 in three Feammox pathways. RBG-13-54-9, Brevundimonas, and Pelomonas played a vital role in the evolution of microbial communities. The characteristics of asynchronous changes between Feammox and iron reduction were found through long-term incubation. IRB might not be the key species directly driving Feammox, and it is necessary to reevaluate the role of IRB in Feammox process.

Degradation of thiocyanate by Fe/Cu/C microelectrolysis: Role of pre-magnetization and enhancement mechanism.

Thiocyanate (SCN-), a non-volatile inorganic pollutant, is commonly found in various types of industrial wastewater, which is resistant to hydrolysis and has the potential to be toxic to organisms. Premagnetized iron-copper-carbon ternary micro-electrolytic filler (pre-Fe/Cu/C) was prepared to degrade SCN-. Pre-Fe/Cu/C exhibited the most significant enhancement effect on SCN- removal when magnetized for 5 min with an intensity of 100 mT, and the SCN- removal rate was the highest at an initial pH of 3.0 and an aeration rate of 1.6 L/min. The electrochemical corrosion and electron transfer in the pre-Fe/Cu/C system were confirmed through SEM, XPS, FTIR, XRD, and electrochemical tests. This resulted in the formation of more corrosion products and multiple cycles of Fe2+/Fe3+ and Cu0/Cu+/Cu2+. Additionally, density functional theory (DFT) calculations and electron paramagnetic resonance (EPR) were utilized to illustrate the oxygen adsorption properties of the materials and the participation of reactive oxygen species (1O2, ·O2-, and ·OH) in SCN- removal. The degradation products of SCN- were identified as SO42-, HCO3-, NH4+, and N2. This study introduced the use of permanent magnets for the first time to enhance Fe/Cu/C ternary micro-electrolytic fillers, offering a cost-effective, versatile, and stable approach that effectively effectively enhanced the degradation of SCN-.

Proteogenomic insights into early-onset endometrioid endometrial carcinoma: predictors for fertility-sparing therapy response.

Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10Q144K mutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.

Genetic interactions reveal distinct biological and therapeutic implications in breast cancer.

Co-occurrence and mutual exclusivity of genomic alterations may reflect the existence of genetic interactions, potentially shaping distinct biological phenotypes and impacting therapeutic response in breast cancer. However, our understanding of them remains limited. Herein, we investigate a large-scale multi-omics cohort (n = 873) and a real-world clinical sequencing cohort (n = 4,405) including several clinical trials with detailed treatment outcomes and perform functional validation in patient-derived organoids, tumor fragments, and in vivo models. Through this comprehensive approach, we construct a network comprising co-alterations and mutually exclusive events and characterize their therapeutic potential and underlying biological basis. Notably, we identify associations between TP53mut-AURKAamp and endocrine therapy resistance, germline BRCA1mut-MYCamp and improved sensitivity to PARP inhibitors, and TP53mut-MYBamp and immunotherapy resistance. Furthermore, we reveal that precision treatment strategies informed by co-alterations hold promise to improve patient outcomes. Our study highlights the significance of genetic interactions in guiding genome-informed treatment decisions beyond single driver alterations.

The impact of low-velocity shock waves on the dynamic behaviour characteristics of nanobubbles.

Low-velocity shock wave-induced contraction and expansion of nanobubbles can be applied to biocarriers and microfluidic systems. Although experiments have been conducted to study the application effects, the dynamic behavior characteristics of nanobubbles remain unexplored. In this work, we utilize molecular dynamics (MD) simulations to investigate the dynamic behavior characteristics of nanobubbles influenced by low-velocity shock waves in a liquid argon system. The DBSCAN (Density-Based Spatial Clustering of Applications with Noise) machine learning method is used to calculate the equivalent radius of nanobubbles. Two statistical methods are then utilized to predict the time series changes in the equivalent radius of nanobubbles without rebound shock waves. The piston velocity is analyzed using the bisection method to obtain the critical impact states of the nanobubble. The results show that at the low velocity shock wave (piston velocity of 0.1 km s-1), the shock wave pressure is small, the non-vacuum nanobubbles contract and expand in a circular shape, and the gas particles inside the bubble are not dispersed. In contrast, the vacuum nanobubbles collapse directly. As the shock wave rebounds upon impact, it triggers periodic contraction and expansion of the nanobubbles. The predictions indicate that the equivalent radius will vary within a small range according to the pre-predicted values in the absence of the rebound shock wave. Nanobubbles are present in four critical impact states: dispersed gaps, multiple smaller bubbles, two split bubbles, and a concave bubble.

Characterization of the Dynamic Behavior of Multinanobubble System under Shock Wave Influence.

Shockwave-induced changes in nanobubbles cause cavitation erosion and membrane damage but can also be applied to biocarrier transport. Currently, research focuses on single nanobubbles; however, in reality, nanobubbles usually appear as a multibubble system. Therefore, this study proposes a method based on cutting and replicating to construct a multibubble model. This method can be widely applied to molecular dynamics (MD) models and enhance the customization capabilities of MD models. The dynamic behavior of a multinanobubble system with different numbers and arrangements of nanobubbles is investigated with the MD method under the influence of shock waves in a liquid argon system. The study also explores the range of influence between nanobubbles. The results show that in the case of two nanobubbles, when the distance between the bubbles is constant, the smaller the angle between the direction of the shock wave and the line connecting the bubbles, the greater is the influence between nanobubbles, and the moment of collapse of the nanobubbles farther away from the shock wave is slower. When three nanobubbles are arranged with a right offset, after the first bubble collapses, the effect on the other two bubbles is similar to the changes in bubbles when the angle of arrangement is 30° or 60°. Under a different arrangement, the change of shock wave velocity on the nanobubble size only affects its collapse time and contraction collapse rate. When the shock wave with a radian of about 2.87 or greater than 2.87 touches the bubbles, the collapse of the second nanobubble will not be affected.