Optimal Selection Research Articles

Vaginal microbiota transplantation is a truly opulent and promising edge: fully grasp its potential.

Vaginal microbiota transplantation (VMT) is a cutting-edge treatment modality that has the potential to revolutionize the management of vaginal disorders. The human vagina is a complex and dynamic ecosystem home to a diverse community of microorganisms. These microorganisms play a crucial role in maintaining the health and well-being of the female reproductive system. However, when the balance of this ecosystem is disrupted, it can lead to the development of various vaginal disorders. Conventional treatments, such as antibiotics and antifungal medications, can temporarily relieve the symptoms of vaginal disorders. However, they often fail to address the underlying cause of the problem, which is the disruption of the vaginal microbiota. In recent years, VMT has emerged as a promising therapeutic approach that aims to restore the balance of the vaginal ecosystem. Several studies have demonstrated the safety and efficacy of VMT in treating bacterial vaginosis, recurrent yeast infections, and other vaginal conditions. The procedure has also shown promising results in reducing the risk of sexually transmitted infections and preterm birth in pregnant women. However, more research is needed to establish optimal donor selection, preparation, and screening protocols, as well as long-term safety and efficacy. VMT offers a safe, effective, and minimally invasive treatment option for women with persistent vaginal problems. It could improve the quality of life for millions of women worldwide and become a standard treatment option shortly. With further research and development, it could potentially treat a wide range of other health problems beyond the scope of vaginal disorders.

Abstract 2346: Meningioma molecular classification predict response to surgical resection and adjuvant radiotherapy: An integrated clinicomolecular analysis

Abstract Importance: Meningiomas are the most common primary brain tumor and a heterogeneous disease with a need to study response to surgery and adjuvant RT in the context of contemporary molecular classifications. Objective: The gold standard for treatment of symptomatic meningiomas has been surgical resection including complete removal of tumor and its surrounding dural margin, although the necessity of different degrees of marginal resection is controversial. Adjuvant radiotherapy (RT) is generally reserved for aggressive or subtotally resected (STR) meningiomas. However, uncertainty exists regarding optimal case selection for RT and response to treatment is variable. We aimed to examine the effects of treatment (surgery/RT), molecular, and clinical factors on meningiomas in the context of molecular classifications. Design, Setting, and Participants: In this retrospective analysis, a 20-year cohort of 2490 patients with meningiomas were assembled across 10 institutions. Molecular data (DNA methylation, RNA sequencing) was generated for 1645 cases. Propensity score matching (PSM) was performed for key baseline covariates including WHO grade and molecular classifications, mimicking a randomized, molecular pathology informed clinical trial. Main Outcome and Measures: Progression-free survival (PFS), and overall survival (OS) were assessed based on extent of resection (EOR), Simpson grade, and receipt of adjuvant RT. Results: Gross total resection (GTR) was associated with improved PFS across all molecular groups. The PFS benefit of GTR was lessened in molecularly-defined proliferative meningiomas (HR 0.69, 95%CI 0.50-0.95), but OS benefit was enhanced (HR 0.52, 95%CI 0.30-0.93). Surgically treating the dural margin (Simpson grade 1/2) was associated with improved PFS compared to removal of tumor alone (Simpson grade 3) particularly for immunogenic (HR 0.16, 95%CI 0.03-0.82) and NF2-wildtype meningiomas (HR 0.24, 95%CI 0.11-0.53). Adjuvant RT was associated with improved PFS across all molecular classifications. Molecular groups could reliably predict response to RT, even when controlling for WHO grade and EOR with immunogenic and NF2-wildtype meningiomas benefitting most while proliferative meningiomas are largely RT-resistant (HR 0.96, 95%CI 0.67-1.37). Conclusion: This study is the first to investigate interactions between contemporary molecular classifications and response to both surgical resection and adjuvant RT in a large, multi-institutional cohort of molecularly defined, clinically annotated meningioma cases. Citation Format: Justin Z. Wang, Alexander P. Landry, Vikas Patil, Andrew Ajisebutu, Christopher D. Wilson, Aaron Cohen-Gadol, Ghazaleh Tabatabai, Silky Chotai, Jill Barnholtz-Sloan, Rebecca Yakubov, Mark Wilson, Ramneet Kaloti, Alexander Rebchuk, Damian A. Almiron Bonnin, Eric C. Holland, Stephen Yip, Felix Sahm, Kenneth Aldape, The International Consortium on Meningiomas, Farshad Nassiri, Gelareh Zadeh. Meningioma molecular classification predict response to surgical resection and adjuvant radiotherapy: An integrated clinicomolecular analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2346.

Abstract 5031: Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing

Abstract Background Metastatic castration-resistant prostate cancer (mCRPC) is a heterogeneous disease that is still lacking an optimal patient selection strategy and a validated sequence of therapies. Therefore, there is an urgent need to identify non-invasive biomarkers to guide treatment choice in a perspective of personalized medicine. Plasma cell-free RNA profiling has emerged as a tool to investigate potential liquid biopsy biomarkers. In this study, we aimed to evaluate a method to capture total RNA content deriving from plasma and to identify potential biomarkers for mCRPC. Methods Plasma samples of 41 mCRPC patients treated with first line Abiraterone or Enzalutamide and 7 healthy donors were collected and stored from 2015 to 2022. Plasma cell-free RNA was purified using miRNeasy Serum/Plasma Advanced Kit (Qiagen) with DNase treatment. Bioanalyzer (Agilent) was used for the evaluation of RNA content and integrity profile of the samples. Sequencing libraries were generated using SMARTer Stranded Total RNA-Seq Kit v3 - Pico Input Mammalian (Takara Bio). An average of 80 millions reads pairs were sequenced on Novaseq 6000 (Illumina) using 100 bpx2 approach. After demultiplexing, reads were trimmed and aligned on hg19. Sequencing metrics were evaluated using Picard. Kallisto was used for gene expression analysis. Results A median of 10x109 bases per sample were aligned on hg19, of which a mean of 45% were located on coding or UTR regions. Storage time was investigated as a potential variable for RNA content and sequencing metrics, but no difference related to the year of storage was found. Unsupervised principal component analysis confirmed the absence of batch effects (including storage and sequencing analysis). PC1 seemed to reflect the different tumor RNA content of each sample, in which healthy donors and cancer patients were distinguished. Higher androgen receptor (AR) gene expression was found in mCRPC patients compared to healthy donors. Conclusions Despite enormous interest in extracellular nucleic acids, RNA-sequencing methods for total RNA content outside cells are rare and not standardized. In this study, we found a method to identify plasma non-invasive RNA biomarkers in mCRPC samples, retrieving coding and non-coding RNAs. Case series enlargement and differential gene expression analyses are ongoing. Citation Format: Giorgia Gurioli, Milena Urbini, Alessandra Virga, Chiara Casadei, Emilio Francesco Giunta, Nicole Brighi, Michela Cortesi, Michele Zanoni, Sara Bravaccini, Giovanni Martinelli, Paola Ulivi, Ugo De Giorgi. Identification of predictive/prognostic biomarkers in metastatic castration-resistant prostate cancer patients using plasma cell-free total RNA-sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 5031.

Abstract 2115: Assessing BCL2 protein complex level in peripheral blood mononuclear cells as a surrogate pharmacodynamic biomarker of BCL2 inhibitors in hematological cancers

Abstract In the last decade, cancer therapeutics have adhered to the practice of administering drugs at the maximum tolerated dose (MTD) selected from limited patient cohorts. The emergence of targeted therapies has disrupted this dose selection paradigm, as optimal efficacy may be achievable at lower dose than MTD. Recently, a regulatory agency initiated "OPTIMUS" to redefine the dose selection process, recommending quantitative assessments of drug efficacy in relation to the target protein throughout development and clinical trials. ABT-199 is a protein interaction inhibitor that specifically disrupts the interaction of BCL2 protein. Consequently, the assessment of changes in the level of BCL2 protein complex is necessary to evaluate the ABT-199 efficacy for optimal dose selection. In this study, we adapted the Single-molecule Protein Interaction Detection platform for evaluating pharmacodynamics of BCL2 inhibitors in clinical samples. We assessed the dissociation of two BCL2-related biomarkers, BCL2-BAX and BCL2-BIM, from a model system under various ABT-199 doses. Following one hour treatment with 300 nM of ABT-199, the BCL2-BAX complex dissociated almost by 40%, while 80% of the BCL2-BIM complex remained. The reduction of the BCL2-BIM complex was not changed when extending the treatment for 3 hours, indicating that the BCL2-BAX complex may serve as a more sensitive biomarker for assessing the target engagement of ABT-199. To determine the assay sensitivity, we evaluated the ABT-199 response across different cell numbers and found that 100,000 cells are sufficient for performing the BCL2-BAX assay. Subsequently, we validated the utility of our method in assessing clinical samples, specifically BMMCs and PBMCs. We collected 4 PBMCs and the corresponding BMMCs from hematological cancer patients and treated them with various doses of ABT-199 ex vivo. With 100,000 BMMCs and 1,000,000 PBMCs, we can generate dose-response curves for the BCL2-BAX complex at doses of ABT-199 ranging from 1 to 1,000 nM. To explore the feasibility of employing the BCL2-BAX complex in PBMCs as a surrogate biomarker for assessing ABT-199 engagement with BCL2 in BMMCs, we compared the averaged dose-response curves from 4 PBMCs with that of BMMCs. Remarkably, the two curves showed a coherent dissociation trend, indicating that the biochemical effect of ABT-199 on the BCL2-BAX complex may be conserved across different sample types. Collectively, we have developed a target engagement assay for BCL2 inhibitors by measuring the BCL2-BAX complex. Notably, we observed a consistent dissociation pattern of the BCL2-BAX complex by ABT-199 treatment in both PBMCs and BMMCs. This molecular information offers an alternative way to assess the pharmacodynamics of BCL2 inhibitors, particularly in the case where collecting a series of BMMCs with sufficient amounts may not be feasible. Citation Format: Hongwon Lee, Byungsan Choi, Saem Hong, Yunseo Lee, Tae-Young Yoon, Janghee Woo. Assessing BCL2 protein complex level in peripheral blood mononuclear cells as a surrogate pharmacodynamic biomarker of BCL2 inhibitors in hematological cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2115.

Abstract 4643: A novel epigenomic profiling assay reveals disease biology and therapeutic targets in gastro-esophageal cancer from 1 ml of plasma

Abstract INTRODUCTION: Gastro-esophageal adenocarcinoma (GEA) is an aggressive and heterogeneous disease with a poor prognosis. Targeted therapies have failed largely due to challenges associated with biopsy collection, tumor antigen heterogeneity, and accurately distinguishing transcriptionally distinct esophageal, GE junction or gastric tumor types. We developed a novel, multimodal liquid biopsy assay that profiles genome-wide transcriptional activation. Here, we deploy this assay to define clinically relevant insights in a cohort of GEA patients. METHODS: 1 ml of plasma from whole blood samples was used to assess genome-wide enhancer, promoter and DNA methylation loci in 11 GEA patients (Stage III: 1, Stage IV: 10) and 7 healthy volunteers. 6 patients were confirmed as HER2+ based on standard tissue IHC/ISH methods. ctDNA estimation was performed using the ichorCNA algorithm on low pass whole genome sequencing data. A multimodal HER2 classifier developed previously using genome-wide features including HER2 was used to predict HER2 status of the GEA samples. RESULTS: Epigenomic profiling and comparison of GEA and healthy volunteer plasma samples revealed distinct genome-wide transcriptional activation patterns associated with gastroesophageal adenocarcinoma, including (i) the characteristic upregulation of HER2, FGFR2 and VEGF (ii) SOX2, KLF4, GATA6 transcription factor circuitry, and (iii) DNA methylation at the CHFR and MGMT promoters. We then explored if epigenomic profiling of liquid biopsies could infer the activation status of antibody-drug conjugate (ADC) targets currently under investigation in GEA cancers. Simultaneous examination of multiple target genes including HER2, HER3, TROP2, CLDN18, CEACAM5 and MET demonstrated patient-specific differences and dynamic range in transcriptional activation of a subset of these target genes. Finally, we investigated if HER2 status could be assigned accurately and quantitatively from a liquid biopsy using the multimodal HER2 classifier. HER2 positivity by IHC was predicted accurately in 8/11 samples corresponding to an area under the ROC curve (AUC) greater than 0.85. Discordance between plasma and tissue HER2 calls could be partially attributed to variability associated with tumor site/section used for tissue collection, IHC staining, and time between biopsy collection and blood draw. CONCLUSIONS: We demonstrate the feasibility of comprehensive epigenomic profiling from low input volume of 1ml of plasma to provide a snapshot of the tumor’s transcriptional state to derive clinically actionable insights. The HER2 classifier overcomes several of the challenges with IHC profiling by providing a uniform and quantitative measurement of HER2 activation. This non-invasive assay provides an accurate reflection of tumor transcriptional biology that can inform optimal patient selection strategies. Citation Format: Jonathan Beagan, Aparna Gorthi, Anthony D'Ippolito, Travis Clark, Michael Coyne, Tyrone Tamakloe, Amy Donahue, Baovy Tran, Hyun-Hwan Jeong, Kristian Cibulskis, Hathairat Sawaengsri, Corrie A. Painter, Juliann Chmielecki, J Carl Barrett, Mosammat Faria Afreen, Aditya Pandey, Ilexa Ashley Schechter, Martin S. Taylor, Matthew R. Strickland, Matthew Eaton, Samuel J. Klempner. A novel epigenomic profiling assay reveals disease biology and therapeutic targets in gastro-esophageal cancer from 1 ml of plasma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4643.

Network sum-rate maximization for network-coded clustered uplink NOMA networks with SWIPT-enabled relays

This paper considers network sum-rate maximization for network-coded clustered uplink non-orthogonal multiple-access (NOMA) networks with simultaneous wireless information and power transfer (SWIPT)-enabled relays. Specifically, the aim is to perform joint power allocation, power-splitting, and relay selection (J-PA-PS-RS), subject to quality-of-service (QoS) requirements. The formulated problem is excessively computationally-intensive, as it is a non-convex optimization problem. To efficiently solve it, it is split into two sub-problems: (1) joint power allocation and power-splitting per relay, and (2) relay selection. Particularly, a solution procedure is proposed, where the joint user and relay power allocation, and power-splitting per relay sub-problem is solved via a low-complexity iterative three-layer algorithm, and then followed by optimal relay selection. Simulation results have revealed that the proposed solution procedure can efficiently be used to maximize the network sum-rate, achieve near-optimal solutions, and outperform other benchmark schemes, while satisfying QoS constraints.

Abstract 2542: Real-world validation of the PurIST classifier demonstrates enhanced therapy selection for pancreatic ductal adenocarcinoma (PDAC) patients

Abstract Background: PDAC is a particularly fatal condition lacking established biomarkers for the choice of first-line treatment (1L). The PurIST algorithm is a gene signature (Rashid et al. Clin. Cancer Res., 2020) that categorizes PDAC tumors into basal or classical molecular subtypes and has been previously validated in a patient cohort of advanced PDAC (N=258). In this post-hoc analysis study, we examine whether the PurIST subtypes can distinguish patients likely to respond to FOLFIRINOX (FFX) versus Gemcitabine + nab-paclitaxel (GnP). Methods: A cohort of de-identified PDAC patients was selected from the Tempus Oncology Database following an IRB-approved protocol. Inclusion criteria required no prior systemic treatment, a surgically unresectable/metastatic status, available RNA-sequencing data from primary or metastatic tissue, and the use of FFX or GnP as 1L systemic therapy with documented outcomes. RNA-sequencing was generated by the CAP/CLIA validated Tempus xR assay. The PurIST gene signature was applied to normalized gene expression values to classify samples into basal or classical subtypes. Univariate and multivariate Cox PH analyzes comparing overall survival (OS) with adjustment for delayed entry, between two common 1L treatment regimens, FFX and GnP, were performed for classical patients with an ECOG performance status of 0 or 1. Results: Application of the PurIST model to the PDAC cohort (N=258) resulted in 67% (N=173) labeled as classical, 23% (N=59) as basal, and the remainder as no-call. Amongst classical patients, 35% (N=61) had a known ECOG score of 0 or 1 and were retained for subsequent analysis. Within this subset, 37 were treated with FFX and 24 with GnP as 1L, with an overall median OS of 11.4 months (95% CI: 9.5-16.5) and a 12-month survival rate of 47.2%. A univariate Cox PH analysis showed that classical patients treated with FFX had a significantly longer OS time (HR (95% CI) = 2.32 (1.29-4.17)). This result remained significant in a multivariate Cox PH, adjusting for age and ECOG, (HR=2.5 (1.15-5.44)). Conclusion: In this real-world cohort of advanced PDAC patients, we showed that classical patients with low ECOG scores had superior OS with 1L FFX treatment compared to 1L GnP. These findings demonstrate the potential for PurIST to aid in optimal treatment selection for patients with advanced PDAC. Citation Format: Stephane Wenric, James M. Davison, John Guittar, Gregory M. Mayhew, Kirk Beebe, Alia Zander, Seung Won Hyun, Kyle Beauchamp, Michael V. Milburn, Vincent Chung, Tanios S. Bekaii-Saab, Charles M. Perou. Real-world validation of the PurIST classifier demonstrates enhanced therapy selection for pancreatic ductal adenocarcinoma (PDAC) patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2542.

Abstract 4892: MicroRNA signature and telomere genes in kidney cancer survival

Abstract Introduction: Kidney cancer ranks among the top 10 most prevalent cancers in the United States, clear cell renal cell carcinoma (ccRCC) has the worst disease specific survival histology. MicroRNAs (miRNAs) have emerged as potential prognostic indicators in various cancers, including kidney cancers. Telomerase, a biomarker associated with uncontrolled cancer cell growth, plays a crucial role in the human kidney cortex's telomere shortening over time. However, the link between miRNAs and telomeres in kidney cancer survival remains underexplored. Our study aims to uncover a miRNA signature capable of predicting 5-year survival in ccRCC patients and to investigate the biological relevance of this signature, particularly its shared pathway enrichment mechanisms with telomere genes. Methods: We extracted miRNA expression profiles from The Cancer Genome Atlas database, comprising 166 patients with ccRCC. To identify a robust miRNA signature predicting 5-year survival in ccRCC, we established an Evolutionary Kidney Survival Estimator (EKSE) using an optimal feature selection algorithm and support vector regression. Additionally, we conducted bioinformatics analyses to uncover common biological pathways between miRNAs and telomere genes using Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) categories, encompassing biological processes, molecular functions, and cellular components. Results: EKSE identified a robust signature consisting of 37 miRNAs, achieving a mean correlation coefficient and mean absolute error of 0.82±0.01 and 0.65±0.18, respectively between actual and estimated survival times. The top 10 ranked miRNAs in the signature, including hsa-miR-26a-1-3p, hsa-miR-28-5p, hsa-miR-3913-5p, hsa-miR-3170, hsa-miR-148a-5p, hsa-miR-671-3p, hsa-miR-224-3p, hsa-miR-10a-5p, hsa-miR-29b-1-5p, and hsa-miR-106b-5p, also showed promise in diagnosing ccRCC with AUC values ranging from 0.56 to 0.91. Furthermore, bioinformatics analysis revealed that the miRNA signature targeted well known telomere-associated genes such as TERT, DKC1, CTC1, and RTEL1. Notably, miRNA signature and telomere genes shared several common pathways, including cellular senescence (hsa04218) and proteoglycans in cancer (hsa05205). They also had overlapping GO-Molecular functions, such as DNA-binding transcription factor activity (GO:0003700), histone deacetylase binding (GO:0042826), and promoter-specific chromatin binding (GO:1990841). Conclusions: Our findings suggest an association between microRNAs and telomere genes, potentially playing significant roles in the survival of patients with ccRCC. The identified miRNA signature robustly predicts 5-year survival in ccRCC. The shared biological pathways between these miRNAs and telomere genes offer new insights into the mechanisms driving ccRCC, signaling potential for therapeutic targets and improved prognostic markers in kidney cancer. Citation Format: Srinivasulu Yerukala Sathipati, Rohit Sharma, Scott Hebbring. MicroRNA signature and telomere genes in kidney cancer survival [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4892.

Gas-phase continuous synthesis of metal-organic framework-derived hybrid catalysts for combined CO2 and CO hydrogenation to methanol

Aerosol-based continuous synthesis for metal–organic framework (MOF) derived catalyst materials, in combination with real-time gas-phase electrophoresis for material characterization, is demonstrated for methanol production via combined CO2 and CO hydrogenation. Cu-based and Zn-based MOF colloids were prepared as the templates for the synthesis of Cu-ZnO catalysts supported on either Al2O3 or CeO2. The results showed the incorporation of real-time gas-phase electrophoresis enabled traceability of continuous catalyst production. Optimal selectivity of 90.52 %, and space–time yield of 7.50 mmol gcat−1h−1 were achievable in the methanol production. Interestingly, the space–time yield of methanol was shown to be linearly proportional to metal surface area of the catalyst. This study demonstrated significant advances in the continuous production of MOF-derived hybrid catalysts through aerosol-phase synthesis with real-time characterization. The high catalytic performance of the developed materials in the combined CO2 and CO hydrogenation to methanol bears promise for applications in the field of CO2 utilization.

Definitive results of a prospective non-randomized phase 2 study on stereotactic body radiation therapy (sbrt) for medically inoperable lung and liver oligometastases from breast cancer

Background and purposeTo report mature results for local control and survival in oligometastatic (OM) breast cancer patients treated with stereotactic body radiotherapy (SBRT) on lung and/or liver lesions in a phase II trial. MethodsThis is a prospective non-randomized phase II trial (NCT02581670) which enrolled patients from 2015 to 2021. Eligibility criteria included: age > 18 years, ECOG 0–2, diagnosis of breast cancer, maximum of 4 lung/liver lesions (with a maximum diameter < 5 cm), metastatic disease confined to the lungs and liver or extrapulmonary or extrahepatic disease stable or responding to systemic therapy. The primary end-points were local control (LC) and treatment-related toxicities. The secondary end-points included overall survival (OS), distant metastasis-free survival (DMFS), time to next systemic therapy (TTNS), poly-progression free survival (PPFS). ResultsThe study included 64 patients with a total of 90 lesions treated with SBRT. LC at 1 and 2 years was 94.9 %, 91 % at 3 years. Median local control was not reached.Median OS was 16.5 months, OS at 1, 2 and 3 years was 87.5 %, 60.9 % and 51.9 %, respectively. Median DMFS was 8.3 months, DMFS at 1, 2 and 3 years was 38.1 %, 20.6 % and 16 % respectively. At univariate analysis, local response to SBRT was found to be statistically linked with better OS, DMFS and STFS. ConclusionSBRT is a safe and valid option in oligometastatic breast cancer patients, with very high rates of local control. An optimal selection of patients is likely needed to improve survival outcomes and reduce the rate of distant progression.

Abstract 1977: ACR-2316: A potentially first-in-class, potent, selective WEE1/PKMYT1 inhibitor rationally designed for superior single agent activity through synergistic disruption of cell cycle checkpoints

Abstract WEE1 and PKMYT1 kinases play essential roles in cell cycle checkpoints and DNA damage response. Genetic interaction has been documented between WEE1 and PKMYT1, and clinical trials have reported clinical activity with inhibitors of WEE1 (adavosertib, azenosertib) and PKMYT1 (lunresertib). Here, we report the discovery and characterization of ACR-2316, a dual inhibitor of WEE1 and PKMYT1 specifically designed for optimal selectivity through co-crystallography and superior single agent activity uniquely enabled by Acrivon Predictive Precision Proteomics (AP3). Mass spectrometry-based AP3 profiling was conducted across several novel WEE1 and PKMYT1 inhibitor leads generated through co-crystallography-based rational drug design. Selective leads originating from one series were further optimized using AP3 for biological structure-activity relationship analysis. AP3 profiling revealed WEE1 inhibitor-upregulated phosphorylation sites across a subset of phosphoproteins that were oppositely regulated (quenched) by PKMYT1 inhibitors. Consensus sites for these included CDK1 T14, a direct PKMYT1 phosphorylation site, as well as CHK1 S296. A particular lead compound, ACR-2316, demonstrated a desirable potent, balanced ratio of cellular WEE1 (IC50 = 2 nM, IC90 = 10 nM) and PKMYT1 (IC20 = 44 nM) inhibition resulting in superior activation of the mitotic kinases CDK1, CDK2, and PLK1 compared to adavosertib and lunresertib, based on annotated kinase substrate relationships. ACR-2316 is more selective than adavosertib, azenosertib, and lunresertib based on &amp;gt;200 kinases profiled by AP3 and 468 kinases assessed by KINOMEscan. Cell cycle analyses demonstrated a drastic ACR-2316-induced S-G2/M accumulation qualitatively distinct from adavosertib or lunresertib. In a 19-cancer cell line proliferation assay (CellTiter-Glo), ACR-2316 demonstrated greater potency in all cell lines tested compared to adavosertib and lunresertib (mean IC50 = 70, 252 and 364 nM, respectively). Superior anti-cancer activity of ACR-2316 was observed in 12 ovarian cancer patient-derived xenograft models tested ex vivo (CellTiter-Glo 3D) compared to azenosertib and lunresertib (mean IC50 = 9, 248 and 1620 nM, respectively). Across human tumor xenograft mouse models, oral administration of ACR-2316 demonstrated superior, durable, dose-dependent efficacy compared to azenosertib and lunresertib and was well tolerated at all doses. Complete responses observed with ACR-2316 were associated with strong WEE1 and intermediate PKMYT1 inhibition in tumors. In conclusion, ACR-2316 is a potent, selective dual WEE1/PKMYT1 inhibitor with superior single-agent activity compared to clinical WEE1 or PKMYT1 inhibitors. ACR-2316 is progressing through IND-enabling studies in preparation for clinical monotherapy development. Citation Format: Caroline Wigerup, Helén Nilsson, Lei Shi, Joon Jung, Joelle Baddour-Sousounis, Ruban Cornelius, Nina Lipjankic, Uthira Muralitharan, Valentina Siino, Ignacio Arribas Diez, Zachary Best, Martina Pasetto, William Dahlberg, Shahrzad Rafiei, Portia Lombardo, Magnus E. Jakobsson, Reina Improgo, Christina Scherer, John van Duzer, David A. Proia, Kristina Masson, Peter Blume-Jensen. ACR-2316: A potentially first-in-class, potent, selective WEE1/PKMYT1 inhibitor rationally designed for superior single agent activity through synergistic disruption of cell cycle checkpoints [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1977.

Identification of CREB5 as a prognostic and immunotherapeutic biomarker in glioma through multi-omics pan-cancer analysis

BackgroundThe functional relevance of cyclic adenosine monophosphate (cAMP)-response element-binding protein 5 (CREB5) in cancers remains elusive, despite its significance as a member of the CREB family. The current research aims to explore the role of CREB5 in multiple cancers. MethodsPan-cancer analysis was performed to explore the expression patterns, prognostic value, mutational landscape as well as single-cell omic, immunologic, and drug sensitivity profiles of CREB5. Furthermore, we incorporated five distinct machine learning algorithms and determined that the least absolute shrinkage and selection operator-COX (LASSO-COX) algorithm, which exhibited the highest C index, was the optimal selection. Subsequently, we constructed a prognostic model centered around CREB5-associated genes. To elucidate the biological function of CREB5 in glioma cells, several assays including cell counting kit-8 (CCK-8), wound healing, transwell, flow cytometric were performed. ResultsCREB5 was overexpressed in pan-cancer and was linked to unfavorable prognosis, particularly in glioma. Furthermore, genetic alterations were determined in various types of cancer, and modifications in the CREB5 gene were linked to the prognosis. The single-cell omics and enrichment analyses showed that CREB5 was predominantly expressed in malignant glioma cells and was critically involved in the regulation of various oncogenic processes. Elevated levels of CREB5 were strongly linked with the infiltration of cancer-associated fibroblasts and the Th1 subset of CD4+ T cells. The validated CREB5-associated prognostic model reliably predicted the prognosis and drug response of glioma patients. The in vitro experiments showed that CREB5 promoted glioma cell proliferation, invasion, migration, and gap phase 2/mitotic (G2/M) phase arrest and recruited M2 macrophages into glioma cells. ConclusionCREB5 has the potential to act as an oncogene and a biological marker in multiple cancers, particularly glioma.

Lifetime policy reuse and the importance of task capacity

A long-standing challenge in artificial intelligence is lifelong reinforcement learning, where learners are given many tasks in sequence and must transfer knowledge between tasks while avoiding catastrophic forgetting. Policy reuse and other multi-policy reinforcement learning techniques can learn multiple tasks but may generate many policies. This paper presents two novel contributions, namely 1) Lifetime Policy Reuse, a model-agnostic policy reuse algorithm that avoids generating many policies by optimising a fixed number of near-optimal policies through a combination of policy optimisation and adaptive policy selection; and 2) the task capacity, a measure for the maximal number of tasks that a policy can accurately solve. Comparing two state-of-the-art base-learners, the results demonstrate the importance of Lifetime Policy Reuse and task capacity based pre-selection on an 18-task partially observable Pacman domain and a Cartpole domain of up to 125 tasks.

Clinical Management of Patients with Non-Small Cell Lung Cancer, Brain Metastases, and Actionable Genomic Alterations: A Systematic Literature Review.

Nearly 60% of patients with non-small cell lung cancer (NSCLC) present with metastatic disease, and approximately 20% have brain metastases (BrMs) at diagnosis. During the disease course, 25-50% of patients will develop BrMs. Despite available treatments, survival rates for patients with NSCLC and BrMs remain low, and their overall prognosis is poor. Even with newer agents for NSCLC, options for treating BrMs can be limited by their ineffective transport across the blood-brain barrier (BBB) and the unique brain tumor microenvironment. The presence of actionable genomic alterations (AGAs) is a key determinant of optimal treatment selection, which aims to maximize responses and minimize toxicities. The objective of this systematic literature review (SLR) was to understand the current landscape of the clinical management of patients with NSCLC and BrMs, particularly those with AGAs. A Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)-compliant SLR was conducted to identify studies in patients with BrMs in NSCLC. Searches used the EMBASE and MEDLINE® databases, and articles published between January 1, 2017 and September 26, 2022 were reviewed. Overall, 179 studies were included in the SLR. This subset review focused on 80 studies that included patients with NSCLC, BrMs, and AGAs (19 randomized controlled trials [RCTs], two single-arm studies, and 59 observational studies). Sixty-four of the 80 studies reported on epidermal growth factor receptor (EGFR) mutations, 14 on anaplastic lymphoma kinase (ALK) alterations, and two on both alterations. Ninety-five percent of studies evaluated targeted therapy. All RCTs allowed patients with previously treated, asymptomatic, or neurologically stable BrMs; the percentage of asymptomatic BrMs varied across observational studies. Although targeted therapies demonstrate systemic benefits for patients with NSCLC, BrMs, and AGAs, there remains a continued need for effective therapies to treat and prevent BrMs in this population. Increased BBB permeability of emerging therapies may improve outcomes for this population.

Optimal microphone selection for aero-engine acoustic measurement

Acoustic testing is crucial in the aero-engine design process, providing valuable information about the sound field in terms of acoustic modes. The conventional use of a uniform sampling array limits the achievable resolution for a given number of sensors, necessitating the use of a large number of sensors to achieve high-resolution estimates. This limitation may be overcome using a non-uniform sensing array. In this work, we propose an optimal microphone selection scheme to determine which microphone placements that are preferable given the typically available a priori knowledge of the relevant acoustic modes. Using a weighted A-optimality criterion, we formulate the sensor selection problem as the one minimizing the expected variance of the resulting parameter estimates. Using both numerical and measured data sets, we illustrate how the proposed scheme allows for improved performance as compared to random and uniform sensor placement schemes.

Foamed waste oil-activated rubberized asphalt binder: A sustainable recycling approach for improving foaming effect and performance

This study prepared foamed waste oil-activated rubberized asphalt (ORA) by activating crumb rubber (CR) with waste vegetable oil (WVO) to address the issue of undesirable foaming effect. Optimal foaming parameters for different rubberized asphalt were determined based on foaming characteristic experiments. Furthermore, rheological properties, fatigue resistance, and adhesion performance of various unfoamed or foamed rubberized asphalt were evaluated through dynamic shear rheometer, bending beam rheometer, pull-out tests. Finally, the analytic hierarchy process was utilized to select the optimum foamed rubberized asphalt. The results show that foaming pressure has a great influence on rubberized asphalt foaming effect, and is recommended at 300 kPa. Compared to conventional rubberized asphalt whether foamed or not, with the increase of activation degree, low-temperature performance, and fatigue resistance of ORA are significantly ameliorated, and the adhesion property of ORA first increases and then decreases, but detrimental to high-temperature performance. The foaming process and foaming agent addition are conducive to low-temperature performance but unfavorable to fatigue resistance and high-temperature property, and have little effect on adhesion performance. ORA (mass ratio of WVO to CR is 1:5) with foaming agent is determined as the optimum selection.

Congenital diseases with multi-organ expression as an indication for liver transplantation in children during the first years of life: Integrative approach to improve the outcomes

Pediatric liver transplantation has evolved since the first transplant was performed by Dr. Starzl more than 50 years ago. Innovations in surgical techniques, immunosuppression, and infection control have significantly improved patient outcomes, graft survival, and quality of life. However, further progress depends not only on the discovery of new treatment option but should rely upon the identification of the factors in the perioperative care which contribute to successful outcomes and guide our decision-making process.Indications for pediatric liver transplantation can be divided into three major groups: cholestatic liver conditions, liver based metabolic disorders, and others represented by acute liver failure of different etiologies, tumors, inherited autoimmune diseases, and multiple infectious causes.Many of these conditions manifest themselves with multi organ pathologic expression, requiring earlier interventions to treat acute liver failure or chronic cholestasis leading to failure to thrive. Containment of patient pathology and maintenance of optimal neurologic and extra-hepatic visceral organ function is paramount during the pre - transplant period.Multidisciplinary management of comorbid conditions in complex pediatric liver transplant candidates during the perioperative period with the emphases on optimization and patient selection has never been summarized in the literature. Thant is why this review focuses on a comprehensive, multidisciplinary preoperative evaluation of pediatric patients in whom progressive liver disfunction manifests early in life and eventually requires liver transplantation. We will address multi-organ system involvement, preoperative optimization in anticipation of the complexity of intraoperative care, as well as short- and long-term postoperative management.

Complex biophysical changes and reduced neuronal firing in an SCN8A variant associated with developmental delay and epilepsy

Mutations in the SCN8A gene, encoding the voltage-gated sodium channel NaV1.6, are associated with a range of neurodevelopmental syndromes. The p.(Gly1625Arg) (G1625R) mutation was identified in a patient diagnosed with developmental epileptic encephalopathy (DEE). While most of the characterized DEE-associated SCN8A mutations were shown to cause a gain-of-channel function, we show that the G1625R variant, positioned within the S4 segment of domain IV, results in complex effects. Voltage-clamp analyses of NaV1.6G1625R demonstrated a mixture of gain- and loss-of-function properties, including reduced current amplitudes, increased time constant of fast voltage-dependent inactivation, a depolarizing shift in the voltage dependence of activation and inactivation, and increased channel availability with high-frequency repeated depolarization. Current-clamp analyses in transfected cultured neurons revealed that these biophysical properties caused a marked reduction in the number of action potentials when firing was driven by the transfected mutant NaV1.6. Accordingly, computational modeling of mature cortical neurons demonstrated a mild decrease in neuronal firing when mimicking the patients' heterozygous SCN8A expression. Structural modeling of NaV1.6G1625R suggested the formation of a cation-π interaction between R1625 and F1588 within domain IV. Double-mutant cycle analysis revealed that this interaction affects the voltage dependence of inactivation in NaV1.6G1625R. Together, our studies demonstrate that the G1625R variant leads to a complex combination of gain and loss of function biophysical changes that result in an overall mild reduction in neuronal firing, related to the perturbed interaction network within the voltage sensor domain, necessitating personalized multi-tiered analysis for SCN8A mutations for optimal treatment selection.

PANDAS: Twenty-Five Years Later

Background:: It has been 25 years since the definition of the concept of Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS). The abrupt onset of neuropsychiatric symptoms requires a comprehensive differential diagnosis involving complementary tests and optimal treatment selection. Methods:: This paper describes aspects related to the diagnosis and clinical management of PANDAS. A clinical perspective is developed starting from an example that meets the Swedo's criteria. Discussion:: A comprehensive approach, including interdisciplinary management and urgent evaluation of potential organic causes, is crucial for effective treatment. Treatment decisions should consider severity, symptoms, and available evidence. Collaboration with neuropediatric or neurological services is needed. ASLO/anti-DNase B and 25-OH-Vitamin D tests are valuable for atypical OCD/Tic presentations, always maintaining a broader organic screening.

Combinations of Feature Selection and Machine Learning Models for Object-Oriented “Staple-Crop-Shifting” Monitoring Based on Gaofen-6 Imagery

This paper combines feature selection with machine learning algorithms to achieve object-oriented classification of crops in Gaofen-6 remote sensing images. The study provides technical support and methodological references for research on regional monitoring of food crops and precision agriculture management. “Staple-food-shifting” refers to the planting of other cash crops on cultivated land that should have been planted with staple crops such as wheat, rice, and maize, resulting in a change in the type of arable land cultivated. An accurate grasp of the spatial and temporal patterns of “staple-food-shifting” on arable land is an important basis for rationalizing land use and protecting food security. In this study, the Shihezi Reclamation Area in Xinjiang is selected as the study area, and Gaofen-6 satellite images are used to study the changes in the cultivated area of staple food crops and their regional distribution. Firstly, the images are segmented at multiple scales and four types of features are extracted, totaling sixty-five feature variables. Secondly, six feature selection algorithms are used to optimize the feature variables, and a total of nine feature combinations are designed. Finally, k-Nearest Neighbor (KNN), Random Forest (RF), and Decision Tree (DT) are used as the basic models of image classification to explore the best combination of feature selection method and machine learning model suitable for wheat, maize, and cotton classification. The results show that our proposed optimal feature selection method (OFSM) can significantly improve the classification accuracy by up to 15.02% compared to the Random Forest Feature Importance Selection (RF-FI), Random Forest Recursive Feature Elimination (RF-RFE), and XGBoost Feature Importance Selection (XGBoost-FI) methods. Among them, the OF-RF-RFE model constructed based on KNN performs the best, with the overall accuracy, average user accuracy, average producer accuracy, and kappa coefficient reaching 90.68%, 87.86%, 86.68%, and 0.84, respectively.