Predictive Test Research Articles

Predicting epirubicin response in Danish patients with breast cancer.

539 Background: Anthracyclines are highly effective chemotherapy drugs. However, they are toxic and feared for their cardiotoxicity. There is a need for improved personalized prediction of treatment benefit. For example, state-of-the-art guidelines (NCCN Guidelines Version 1.2024 and meta-analysis PMID: 37061269) mark anthracyclines as optional adjuvant treatment of estrogen receptor (ER) positive, HER2 negative early high-risk breast cancer. A biomarker to predict whether a patient will benefit from anthracycline treatment could potentially lead to increased cure rate and overall reduced toxicity. However, no such test exists. Here we introduce a clinically validated, predictive test based on clinical tumor transcriptome data and the cell line panel NCI60 that can forecast epirubicin response in breast cancer patients with high accuracy. Methods: Microarray gene expression levels and growth inhibition levels (GI50) from the NCI60 cell line panel were acquired from NCBI to build a prediction algorithm. A tumor-specific variance-based filter based on >6.000 patient tumors was applied to select the most relevant genes. AUC (Area Under Curve) was used to evaluate the performance of numerous configurations and combinations of parameters that led to different gene-signature sets. Response scores based on the gene expression level of all genes in each signature were generated for each sample in a published cohort (PMID: 23340299) and a final signature with 141 genes was the best-performing signature (Progressive Disease versus Response AUC 0.81 and ANOVA-test p-value < 0.01). The model was validated on a cohort of Danish breast cancer patients treated with epirubicin in the metastatic setting (n=153), with time-to-progression (TTP) as endpoint (PMID: 31654283, PMID: 30099635). Finally, we used an established method (PMID: 30289602) to test if the gene signature was correlated between microarray- and RNA sequencing-based datasets. Results: The hazard ratio (HR) for the best-performing signature was 0.31 when comparing patients with a difference of at least 50 in response score (two-sided p-value = 0.012, 95% confidence interval 0.12-0.77, endpoint TTP, continuous scoring). This was consistent in a multivariate model including ER and HER2. Using the data and method provided by Pedersen et al (PMID: 30289602), we also saw a high correlation between matching microarray and RNA sequencing datasets for the genes in our model (mean Pearson’s r = 0.87). Conclusions: Here is presented a development and clinical validation of an accurate epirubicin response signature for breast cancer patients. The expression of the genes in the signature is highly correlated between microarray- and RNA sequencing data. Moving forward, we will seek to validate the model independently on RNA sequencing data. Our aim is that these models will be accepted for prospective clinical tests at local hospitals in Denmark in early 2025.

A plasma-based proteomic platform for predicting clinical benefit from immune checkpoint inhibitors in multiple cancers.

2568 Background: Immune checkpoint inhibitor (ICI)-based therapies are preferred treatment options for multiple cancer types. However, there is an unmet need for predictive tests that can identify patients likely to benefit. PROphet-NSCLC is a commercially available pretreatment plasma proteomic test that predicts clinical benefit from first-line PD-(L)1 inhibitor-based therapy in patients with metastatic non-small cell lung cancer (NSCLC), guiding the choice between ICI monotherapy versus ICI-chemotherapy. Here, we evaluate the broader clinical utility of PROphet-NSCLC by testing its predictive capabilities across diverse cancer types. Methods: Pre-treatment plasma samples and clinical data were collected for an observational study from patients with metastatic melanoma (n=68) and HPV-related cancers (n=43; NCT03427411) treated with PD-(L)1 inhibitor-based therapies. HPV-related cancers included anogenital squamous cell carcinoma (n=16), cervical carcinoma (n=18), and head and neck squamous cell carcinoma (n=9). Patients were assigned a PROphet-positive or -negative result based on computational analysis of SomaScan-derived proteomic profiles in pre-treatment plasma samples. Overall survival (OS) and progression-free survival (PFS) in PROphet-positive- and -negative groups was analyzed with the Kaplan-Meier method. Hazard ratios (HR) were calculated from univariate and multivariate Cox proportional hazard models. Results: In the melanoma cohort, PROphet-positive patients (n=51) displayed a significant OS benefit in comparison to PROphet-negative patients (n=17; median OS 92.8 months vs. 9.5 months, HR=0.14, 95% CI: 0.06-0.34, p<0.0001), consistent with the clinically validated predictive performance of the test in patients with NSCLC. OS results remained significant after correcting for sex, age, histology, ECOG performance status, and treatment type (HR=0.05, 95% CI: 0.01-0.25, p<0.001). In PROphet-positive patients, PD-1+CTLA-4 inhibitor combination therapy (n=27) was superior to PD-1 inhibitor monotherapy (n=24; OS: median 118.4 vs. 48.3 months, HR=0.58, p=0.24; PFS: median not reached vs. 10.8 months, HR=0.48, p=0.04). PROphet-negative patients displayed similarly poor outcomes with either treatment, providing a rationale to consider alternative therapies for such patients. In the HPV-related cohort, the median OS in PROphet-positive (n=10) vs PROphet-negative (n=33) groups was 43.6 vs 4.4 months (HR=0.22, 95% CI: 0.08-0.59, p=0.001), with similar trends per sub-cohort. Conclusions: Our findings show that the PROphet-NSCLC test can be applied to PD-(L)1 inhibitor-treated melanoma and HPV-related cancers, suggesting applicability to cancers beyond NSCLC. Analysis of additional patient samples is needed to explore the potential utility of PROphet-NSCLC for informing treatment decisions for a broad range of cancer types.

Risk predictors as companion diagnostics for ER positive, HER2 negative early staged breast cancers from India.

e13049 Background: Gene expression profiling tests can identify women with breast cancer most likely to benefit from chemotherapy providing accurate prognostic information than other non-genetic clinicopathological parameters. These derive specific molecular features of a tumour indicating an increased likelihood of rapid growth, metastasis risk, and response to chemotherapy. The tests are typically performed after surgery, in conjunction with other available information such as tumour size and grade. The objective of the current study was to evaluate the risk prediction as a companion diagnostic assay for women with early staged breast cancers (ER+,HER2-ve). Methods: The risk prediction was done evaluating quantitative gene expression profiling on Nanostring nCounter Flex platform using total RNA extracted from FFPE tissues (n = 81) obtained from trucut biopsy tissues and post MRM specimens after ensuring the tumour representation. The gene quantitations were derived after normalisation and using nSolver and Roselind software based statistical analysis. Results: We found 55.5% (45/81) and 44.5% (36/81) to be of intrinsic subtype Luminal A and Luminal B among our breast tumours respectively. The risk of recurrence score was high for luminal B (36.1% ; 13/36) compared to luminal A (13.4% ; 6/45). There was no difference pertaining to the Tumour Inflammation score (TIS score) among the luminal A and B that depicted good response to immunotherapy with 80% (36/45) among the luminal A and 72.3% (26/36) among the luminal B. We have identified top 38 differentially expressed genes that drive the high breast cancer proliferation score among the breast cancers in Indian women. The top 5 genes influencing the risk of recurrence with high BCP among the luminal A tumours were GNLY, CHRNA5, CDC20, MELK, RRM2 and among luminal B we got FGFR2, AURKA, MYBL2, CCNE2 and UBE2C. The top genes combining both types influencing the genomic risk of recurrence were FGFR2, MYBL2, AURKA, TTK, UBE2c and ORC6. The genomic risk of recurrence is based only on the gene expression unlike the risk of recurrence which includes the tumour size and nodal involvement. The top genes influencing a poor response to immunotherapy among luminal A was CNTFR, HAPLN1, FGF12, COL4A6 and CDH2 and the top genes influencing poor response to immunotherapy among luminal B was FGFR2, MYCN, AURKA and FAM198B. Conclusions: This is the first study from India using risk prediction test as a companion diagnostics assay for ER+ HER2-ve early staged breast cancer. The salient genes important to drive the breast cancer proliferation increasing the risk of recurrence scores in both luminal A and Luminal B intrinsic subtypes have been derived. We can validate these gene signatures as smaller panels of tests that can be low cost and more suitable for LMIC like India. The BCP panel of genes were relevant driving the recurrence.

Asteroid Orbit Determination Using Gaia FPR: Statistical Analysis

The Gaia mission has provided astrometric observations of unprecedented accuracy for more than 156,000 asteroids. The reported astrometric uncertainties are of the order of milliarcseconds, about 2 orders of magnitude smaller than that of traditional ground-based observations. The accuracy of Gaia data requires a high-fidelity orbit determination process, especially in the observation modeling. We present a statistical analysis of Gaia Focused Product Release to test the accuracy of the reported positions and associated uncertainties. We find that center-of-light offsets due to phase variations need to be modeled to properly fit the observational data. Prediction tests show that the uncertainty in the fitted orbits can be optimistic unless the observational uncertainty is inflated to account for errors in finding the center-of-mass of the body. Moreover, errors in the masses of small-body perturbers can cause differences in the orbital solution that exceed formal uncertainties of the best constrained orbits. As an example, we provide an update of the impact hazard analysis of 1950 DA, one of the asteroids observed by Gaia, and find that the impact probability in the year 2880 increases to 3.8 × 10−4.

Linear and Non-Linear Modelling Methods for a Gas Sensor Array Developed for Process Control Applications.

New process developments linked to Power to X (energy storage or energy conversion to another form of energy) require tools to perform process monitoring. The main gases involved in these types of processes are H2, CO, CH4, and CO2. Because of the non-selectivity of the sensors, a multi-sensor matrix has been built in this work based on commercial sensors having very different transduction principles, and, therefore, providing richer information. To treat the data provided by the sensor array and extract gas mixture composition (nature and concentration), linear (Multi Linear Regression-Ordinary Least Square "MLR-OLS" and Multi Linear Regression-Partial Least Square "MLR-PLS") and non-linear (Artificial Neural Network "ANN") models have been built. The MLR-OLS model was disqualified during the training phase since it did not show good results even in the training phase, which could not lead to effective predictions during the validation phase. Then, the performances of MLR-PLS and ANN were evaluated with validation data. Good concentration predictions were obtained in both cases for all the involved analytes. However, in the case of methane, better prediction performances were obtained with ANN, which is consistent with the fact that the MOX sensor's response to CH4 is logarithmic, whereas only linear sensor responses were obtained for the other analytes. Finally, prediction tests performed on one-year aged sensor platforms revealed that PLS model predictions on aged platforms mainly suffered from concentration offsets and that ANN predictions mainly suffered from a drop of sensitivity.

Intelligent prediction of wave loads based on multi-source data-driven methods

ABSTRACT High-fidelity wave-load tests is pivotal in the design and development of modern ship structures. Nonetheless, the prohibitive cost of conducting such tests limits their applicability. A wave-load data fusion method was implemented using the model test data from a typical displacement-type ship to generalise the small sample test, and a multi-source data characterisation and model parameter optimisation method were established to achieve efficient wave-load (wave frequency and slamming superposition) prediction. Using multi-source data, a multi-fidelity wave-load prediction (MFWLP) model was constructed by combining numerical computation, regular wave tests (RWT), and irregular wave test (IWT) data based on transfer learning with a secondary correction wave load prediction under irregular wave conditions. The model was effectively employed in a ship wave-load engineering case. This study reveals that the adopted MFWLP model demonstrates adequate extrapolation and prediction capabilities, even with limited high-fidelity test samples. The discrepancy between the nonlinear wave load prediction and model test was found to be within 15%. Therefore, the proposed method can serve as a foundation for rapidly assessing ship wave loads across various sea conditions, especially under high sea states.

#2120 Impact on CKD classification and comorbidities using GFR estimated by European Kidney Function Consortium equation in kidney transplant recipients

Abstract Background and Aims In 2020, European Kidney Function Consortium (EKFC) proposed a new equation that estimates glomerular filtration rate (GFR) in European population. Few studies have compared EKFC with CKDEPI, particularly in kidney transplant (KT) recipients. Chronic Kidney Disease (CKD) classification by KDIGO is used not only by nephrologists who evaluate more parameters of kidney function, but also by every other specialist who are going to be guided mainly by this stage. Our objective is to compare EKFC equation and CKDEPI in classifying CKD in KT patients and its relationship with associated comorbidities. Method We conduct a retrospective observational study including all KT performed at our centre from 1993 to 2022 with survival greater than one year. We collect creatinine, haemoglobin (Hb), phosphorus (P−), potassium (K+), and bicarbonate (Bic) values at three months and one-year post-transplant. We define anaemia as Hb < 11 g/dl, hyperphosphataemia as serum P− > 4.5 mg/dl, hyperkalaemia as serum K+ > 5 mEq/ml, and acidosis as Bic < 22 mEq/L. We calculate estimated GFR (eGFR) using CKDEPI and EKFC equations, classify CKD stage according to KDIGO, and compare both results in terms of correlation and differences. We use Kappa Coefficient and Chi-Square by contingency tables, and ROC curves with homogeneity test for prediction of these comorbidities. We use SPSS and MedCalc as statistics programs. Results We include 968 KT, with median age at the time of transplant 52.75 year [41.25-61.27]. 294 KT (30.4%) are in women. Comorbidity frequencies are depicted in Table 1. ROC analysis shows no significant differences in predicting acidosis at one year, hyperphosphataemia at any time, hyperkalaemia at 3rd month, anaemia at any time, and composite event at any time. We find significant differences in favour to CKDEPI for acidosis at 3rd month (ΔAUC 0.00575 95% CI [0.00182-0.00969]; p = 0.0042) and for hyperkalaemia at one year (ΔAUC = 0.00853 [0.00161-0.0154]; p = 0.0157). Through contingency tables we compare classification into stages, finding very good agreement based on the Kappa coefficient (κ) but significant differences by Chi-Square. With κ = 0.905, EKFC reclassifies 70 patients, 7.23% overall, but not significantly down nor upstaging (31 vs 39). It reclassifies more men than women: 8.46% vs 4.42%. In 10-year age groups, the largest reclassification occurs in the 70-80 years group, a 17.07% with κ = 0.774, all cases upstaged. At one-year eGFR, contingency tables also show a very good agreement based on κ but significant differences by Chi-Square. EKFC reclassifies 83 KT (κ = 0.887), 8.57% overall. It reclassifies 7.48% women and 9.05% men. In 10-year age groups, the largest reclassification occurs in 20-30 years group with 17.24% (κ = 0.767) and 14.81% in 70-80 years (κ = 0.796). All patients in these groups were upstaged. We resume graphically the reclassification of the groups in Fig. 1, observing how EKFC upstages CKD (worsen CKD stage) in high eGFR stages, and downstages CKD in low eGFR stages. Conclusion Estimation of GFR in KT recipients using the new EKFC equation yields similar results to CKDEPI, showing very good agreement for CKD classification although there is a non-negligible percentage of reclassification, which may be clinically relevant in terms of treatment indications and diagnostic tests. It is to a worse CKD stage in high eGFR and to a better stage in low eGFR, and when EKFC reclassification percentage is greater—in the extreme ages of our cohort—it is always by upstaging. Except for minimal differences which we consider clinically inconsequential, we find no significant differences between both equations in discriminating presence of hyperphosphatemia, hyperkalaemia, anaemia or acidosis.

Predictive value of the HALP score for pre-eclampsia with severe features

ABSTRACT Introduction Predictive tests are needed to ensure the development and subsequent follow-up of pre-eclampsia, which is responsible for significant rates of morbidity and mortality during pregnancy. This study aimed to evaluate the predictive value of the Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) score for the severity of preeclampsia. Methods We retrospectively analyzed the data of women diagnosed with pre-eclampsia at our clinic from January 2019 to January 2023. The control group consisted of normotensive, healthy pregnant women. Women diagnosed with preeclampsia were further evaluated in two groups: those with severe features and those without severe features. The clinical and demographic data of the cases were evaluated. The HALP score was calculated using the first trimester blood parameters of the cases and compared between groups. Results The study included 229 patients with preeclampsia and 142 normotensive healthy controls. Of the patients with preeclampsia, 104 (28.1%) had severe features of the disease. The HALP score was significantly higher in the preeclampsia group with severe features than in the control group (6.18 ± 2.66 vs. 3.75 ± 1.86; p = 0.006). In multivariate logistic regression analysis, the HALP score (odds ratio: 2.02, 95% confidence interval: 1.10–3.32, p = 0.017) was found to be an independent indicator for preeclampsia with severe features. A HALP score of > 4.61 predicted the development of preeclampsia with severe features with a sensitivity of 74.5% and a specificity of 81.3%. Conclusion We found a significant correlation between the HALP score and preeclampsia with severe features. The HALP score may be useful in predicting the severity of preeclampsia.

Salivary metabolites are promising noninvasive biomarkers of drug-induced liver injury.

Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.

ATHLETES’ SATISFACTION TOWARDS SPORT TRAINING: AN INITIAL INVESTIGATION AND DEVELOPMENT OF QUESTIONNAIRE

<p>This study aims to investigate and develop a questionnaire to measure athletes’ satisfaction towards sports training. This quantitative research used a structural equating modeling (SEM) approach with the help of Smart-PLS. The population of this study consisted of athletes from Yogyakarta Province, Riau Province, and South Kalimantan Province. The sample was 806 athletes from 27 sports (Table 1) who will compete at the National Sports Week (PON) 2024. PON is a multi-event tournament held every four years in Indonesia, so athletes who will compete have high experience and performance. Athletes who participated in this research were aged 22.6±8.3 years, and they had 10.3±4.7 years of training experience. Instrument preparation is done by reviewing the literature and focus group discussions (FGD) involving sports coaching lecturers and nationally licensed coaches. The results of this study are that the outer loading value is >0.7, and the discriminant validity value (Fornell-Larcker Criteria) is >0.7. Cronbach Alpha Reliability and Composite Reliability also showed > 0.7. Goodness of Fit (GoF) shows an SRMR value of 0.076<0.10 or <0.08, so the model fits the data. The predictive relevance test or Q Square is 0.9>0, so this study has a good observation value. Based on the results, the questionnaire consisted of 16 items divided into four dimensions (Appendix 1), namely the dimensions of training quality, mental and emotional health, competitive performance, and competitive experience. In conclusion, a questionnaire can measure athletes’ satisfaction towards sports training. From the results of this study, it is recommended that athletes’ sports training satisfaction variable be tested on indirect influences as mediating or intervening variables. It can also be used as a variable that strengthens or weakens (moderator). Then, it is combined with other independent and dependent variables in management, psychology, society, education, and sports. So that in the future, it can produce more comprehensive research.</p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/soc/0711/a.php" alt="Hit counter" /></p>

Assessment the Role of Erythrocyte Sedimentation Rate and C-Reactive Protein Tests For Prediction Of Rheumatoid Arthritis Activity In Misan Province

Rheumatoid Arthritis (RA) activity was assessed based on erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) tests. The ESR and CRP tests were monitored in 25 Rheumatoid Arthritis diagnosed patients and 25 healthy approved cases of suspected patients from Missan Province. The sample comprised of 25 male and 25 females with ages varied from 21-68 years and body weights from 45 – 112 kg. ESR readings in RA diagnosed patients varied between 22 – 116 averaged 46.8 mm/h in patients case while those recorded in the healthy approvrd cases ranged between 4-18 averaged 8.4 mm/h. Differences between patients and control cases were statistically significant (P < 0.05). This approved that measuring ESR is a valid tool to predict RA among Missan population. CRP test showed only 2 negative results among RA patients compared with 15 negative results in healthy approved cases. CRP values in patients sample ranged between 10 mg/dl in 11 cases and 24 – 48 mg/dl in another 11 cases with only one highly extreme value of 96 mg/dl. In he healthy approved cases, CRP values ranging from 6-12 mg/dl were recorded in 10 cases and negative results in the rest 15 cases. differences were highly significant (p< 0.01) indicating the validity of CRP test to predict RA cases. Both parameters varied among various age groups, gender and body weight classes. Apparantly both ESR and CRP tests may help to find or monitor inflammation in acute or chronic conditions of rheumatoid arthritis.

The analysis of transcriptomic signature of TNBC—searching for the potential RNA-based predictive biomarkers to determine the chemotherapy sensitivity

AbstractNeoadjuvant chemotherapy is the foundation treatment for triple-negative breast cancer (TNBC) and frequently results in pathological complete response (pCR). However, there are large differences in clinical response and survival after neoadjuvant chemotherapy of TNBC patients. The aim was to identify genes whose expression significantly associates with the efficacy of neoadjuvant chemotherapy in patients with TNBC. Transcriptomes of 46 formalin-fixed paraffin-embedded (FFPE) tumor samples from TNBC patients were analyzed by RNA-seq by comparing 26 TNBCs with pCR versus 20 TNBCs with pathological partial remission (pPR). Subsequently, we narrowed down the list of genes to those that strongly correlated with drug sensitivity of 63 breast cancer cell lines based on Dependency Map Consortium data re-analysis. Furthermore, the list of genes was limited to those presenting specific expression in breast tumor cells as revealed in three large published single-cell RNA-seq breast cancer datasets. Finally, we analyzed which of the selected genes were significantly associated with overall survival (OS) in TNBC TCGA dataset. A total of 105 genes were significantly differentially expressed in comparison between pPR versus pCR. As revealed by PLSR analysis in breast cancer cell lines, out of 105 deregulated genes, 42 were associated with sensitivity to docetaxel, doxorubicin, paclitaxel, and/or cyclophosphamide. We found that 24 out of 42 sensitivity-associated genes displayed intermediate or strong expression in breast malignant cells using single-cell RNAseq re-analysis. Finally, 10 out of 24 genes were significantly associated with overall survival in TNBC TCGA dataset. Our RNA-seq-based findings suggest that there might be transcriptomic signature consisted of 24 genes specifically expressed in tumor malignant cells for predicting neoadjuvant response in FFPE samples from TNBC patients prior to treatment initiation. Additionally, nine out of 24 genes were potential survival predictors in TNBC. This group of 24 genes should be further investigated for its potential to be translated into a predictive test(s).

Insights of potential trypanocidal effect of the synthetic derivative (2E)-1-(4-aminophenyl)-3-(2,4-dichlorophenyl)prop-2-en-1-one: in vitro assay, MEV analysis, quantum study, molecular docking, molecular dynamics, MPO analysis, and predictive ADMET.

This study aims to evaluate the antitrypanosomiasis activity of a synthetic dichloro-substituted aminochalcone via in vitro assays against infected cell cultures, as well as a theoretical characterization of pharmacokinetics and pharmacodynamics against the protein targets of the evolutionary cycle of T. cruzi. The in vitro evaluation of parasite proliferation inhibition was performed via cytotoxicity analysis on mammalian host cells, effect on epimastigote and trypomastigote forms, and cell death analysis, while computer simulations characterized the electronic structure of (2E)-1-(4-aminophenyl)-3-(2,4-dichlorophenyl)prop-2-en-1-one (DCl), the mechanism of action against the proteins of the evolutionary cycle of T. cruzi: Cruzain, Trypanothione reductase, TcGAPDH, and CYP51 by molecular docking and dynamics and predictive pharmacokinetics by MPO-based ADMET. The in vitro tests showed that the DCl LC50 in order of 178.9 ± 23.9 was similar to the BZN, evidencing the effectiveness of chalcone against Trypomastigotes. Molecular docking and dynamics simulations suggest that DCl acts on the active site of the CYP51 receptor, with hydrogen interactions that showed a high degree of occupation, establishing a stable complex with the target. MPO analysis and ADMET prediction tests suggest that the compound presents an alignment between permeability and hepatic clearance, although it presents low metabolic stability. Chalcone showed stable pharmacodynamics against the CYP51 target, but can form reactive metabolites from N-conjugation and C = C epoxidation, as an indication of controlled oral dose, although the estimated LD50 rate > 500mg/kg is a indicative of low incidence of lethality by ingestion, constituting a promising therapeutic strategy.

Association Between Systemic Immune Inflammation Indexes and DVT in Patients With Malignancy Requiring PICC Insertion.

Background: In order to reduce the risk of leakage of cytotoxic agents, peripherally inserted central catheters (PICC) are widely used in patients diagnosed with malignancy before chemotherapy. While inflammation has been demonstrated to be associated with deep vein thrombosis (DVT), the connection between systemic immune inflammation indexes and the formation of PICC-DVT remains unclear. Purpose: This study aims to evaluate the association between PICC-DVT and systemic immune inflammation indexes including platelet-to-lymphocyte ratio (PLR), systemic immune-inflammatory index (SII), and systemic inflammatory response index (SIRI). Methods: From August 2018 to October 2021, we enrolled consecutive patients diagnosed with malignancy who underwent PICC implantation before chemotherapy. DVT was assessed using color Doppler ultrasonography. Results: Among the 513 patients, 57 patients (11.1%) developed PICC-DVT. The optimal cutoff values for PLR, SII and SIRI were 260.1, 1318.7, and 2.7, respectively. Based on the multiple logistic regression analysis, correlations were found between PICC-DVT and elevated PLR (p = .014), SII (p = .012), and SIRI (p = .022). Patients with malignancy having higher values of PLR, SII or SIRI tended to be more likely to develop PICC-DVT. Conclusions: The systemic immune inflammation indexes increases the risk of PICC-DVT and could be used as auxiliary predictive tests for PICC-DVT.

Abstract PS09-07: SPAG5 as a companion prognostic and predictive test for management of early stage HER2 positive breast cancer (BCs)

Abstract Background: SPAG5 is a novel oncogene that is amplified in 40% of HER2+BC. Herein, we evaluated the prognostic and predictive significance of SPAG5 in HER2+ BC Methods: This retrospective cohort study included 2454 patients with HER2+BC derived from 6 cohorts in adjuvant (Adj) and neoadjuvant (NACT) settings. Adj cohorts: The association between SPAG5 and survivals were evaluated in 1354 HER2+ BC who received Adj therapy: 1) HER2+ Adj transcript cohort (n=448): 31% (137/448) did not receive Anthracycline (AC), Taxane (TX), Trastuzumab (TZ) or Pertuzuman (PZ) whereas 20% (89/448) had received AC alone and 35% (155/448) received TZ + AC +/- TX (Median follow- up (MFU): 60 months (m). 2) HER2+ Adj Molecular Taxonomy of BC International Consortium cohort (n=240): patients with ER- and lymph node (LN) + received Adj chemotherapy but none received TZ (MFU: 109 m). 3) HER2+ Adj Historical cohort (n=206): no TZ, AC or TX was received (MFU: 143 m). 4) HER2+/ER- cohort (n=101): AC alone was received; MFU: 62 m. 5) HER+ Adj TZ cohort (n=359): patients received TZ +TX+/-AC (MFU: 90 m). Neo-Adjuvant cohort: the associations of SPAG5 protein expression with pathological complete response (pCR) was evaluated in 1100 BCs (MFUT: 67 m) including 200 local cases participated in ROSCO trial. In this cohort; 73% (803/1100) received AC+TX. AC alone was given to 187/1100 (17%) whereas 88/1100 (8%) received TX alone. Of HER2+ BC, 14% (54/399) received AC +/- TX and 63% received TZ + TX +/-AC and 23% (92/399) received TZ + PZ + TX +/- AC. Sections were IHC profiled for HER2, ER, PR, Ki67 and SPAG5 and stained for Fluorescent in situ hybridisation (FISH) using a novel triple colour probe (HER2/SPAG5/Ch17). ASCO guidelines recommendations were followed. Results: In univariate survival analysis, High SPAG5 (+) transcript was associated with shorter 5- year distant metastases free survival (5-y DRFS); p< 0.0001, compared to SPAG5 low (-) in HER2+ patients who did not receive TZ or AC whereas in those who received AC alone, SPAG5+ was associated with lower risk of 5-y DRFS than SPAG5- (p < 0.001). Multivariable Cox regression analysis showed that SPAG5+ transcript ; as well as LN status, was independently associated with poor prognosis (HR (95% CI): 4.9 (2.0-12.0), p< 0.001). The interaction term between SPAG5 and AC was significantly associated with lower risk of DR. Multivariable Cox regression analysis for 10-year relapse free survival (10y-RFS) in HER2+ patients who did not receive AC or TZ confirmed that SPAG5+ protein expression ; as well as LN status and tumour size, were independently associated with poor prognosis (HR (95% CI): 2.1 (1.3, 3.5), p=0.002). SPAG5+ predicted response for NACT +/- HER2 targeting agents. For instance; None of HER2 IHC 2+ with SPAG5- expression/(0/191) either with HER2 FISH- (0/121) or HER2 FISH+ (0/70) achieved pCR whereas 51% (48/95) of those of HER2 IHC 2+/SPAG5+ achieved pCR (p < 0.0001). Similarly patients with HER2+ IHC 3+/SPAG5+ achieved higher pCR rate compared to those with SPAG5- expression [73% (107/146) vs., 10% (14/135); respectively]; p< 0.0001. Noteworthy, after receiving TZ+ PZ +Texans +/- AC, patients with SPAG5+ achieved higher pCR rate compared to those with SPAG5- expression [85% (50/59) vs., 0% (0/51); respectively, p< 0.001]. Similarly in HER2 + BC patients who received TZ + TX +/- AC, SPAG5+ expression was associated with higher pCR [67% (67/101)] compared to those with SPAG5- [10% (11/107)]; p< 0.001. In HER2+ who received AC alone, SPAG5+ cases achieved higher pCR compared to those with SPAG5- [56% (20/36) vs., 6% (3/47); p< 0.001; respectively]. Multivariable logistic regression analysis showed that SPAG5+ expression as well as ER, HER2 IHC, grade, clinical TNM and HER2 targeting agents were independent predictors for pCR (OR (95% CI: 13.74 (5.76-32.79; p< 0.001). Conclusions SPAG5 is an independent poor prognostic factor in HER2+ BC and could help in distinguishing those who would and would not benefit from NACT and HER2 targeting agents. Citation Format: TAREK ABDEL-Fatah, Graham Ball, Daniel Yeo, Graham Hickman, Arlene Chan, Ian Ellis, Stephen Chan. SPAG5 as a companion prognostic and predictive test for management of early stage HER2 positive breast cancer (BCs) [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS09-07.

Abstract PO5-02-02: LyKi1: a highly predictive immune-based score of pathological response to chemotherapy in luminal breast cancer

Abstract Background: Identifying which luminal breast cancer (BC) patients will benefit from (neo)adjuvant chemotherapy still remains a challenge. Efficient predictive tests and genomic signatures are still lacking. Because neoadjuvant chemotherapy (NACT) constitutes an in vivo chemotherapy-sensitivity test, we used the pre-treatment core biopsies to identify predictive factors of pathological response in luminal HR+/Her2- BC. Analyses on sTILS and TIL subtypes (CD3, CD4, CD8, CD20) are rare in luminal BC while a predictive value has been reported in TNBC and Her-2 positive BC. Patients and Methods: We performed a retrospective analysis of 211 patients treated with NACT followed by surgery for a T0-T4 luminal (HR+/Her-2-) breast cancer. Association of anthracyclin and taxane was used in 99% of cases. Median age was 48.4 yo (28 – 76). Initial clinical stage was: I: 0.5%, II: 67%; III: 33%. Biopsy analyses were the followings: NST carcinomas: 90%; luminal B: 82%; E&E grade I/II/III: 10%/57%/32%; KI-67 > 20%: 74%. After NACT, RCB 0-1 was observed in 32 cases (15.2%) and pCR in 19 (9.0 %) cases. All pre-therapeutic biopsies were reviewed for pathological factors, blinded to the patients’ outcomes. Clinico-pathological analyses were performed using standard methods. sTILs were estimated on H&E slides. Intratumoral CD3, CD4, CD8 and CD20 infiltrates were carried out by an independent laboratory using a machine learning model for automated and quantitative evaluation based on digital IHC stains. Correlation between sTILs and TIL subtypes were assessed by Spearman’s coefficient. Predictive factors of RCB 0/1 were explored using unconditional logistic regression analysis. After selection on univariate analysis (p< 0.05), multivariate prognostic models were developed using stepwise backward variable elimination process and compared using area under the curve (AUC). Results: sTILs levels ≥ 10% were observed in 15.2% of biopsies. 42 % of tumors had ≥ 10 % CD3-positive cells, 46% for CD4, 38% for CD8, and 8% for CD20. A high level of correlation was observed between these different markers (Spearman’s coefficient ≥ 0.73 for each comparison). By univariate analysis, significant factors (p< 0.05) associated with RCB 0-1 were: age, mitotic index (1 vs 2 vs 3), aneuploidy (1-2 vs 3), differentiation (1-2 vs 3), E&E grade (1-2 vs 3), mitotic count, Ki-67, Magee equation 3, phenotypic group (luminal A vs B), ER, sTILs and each TIL subtype. Age, E&E grade, Ki-67, Magee equation 3, sTILs and all TIL subtypes were selected for multivariate analysis. As TIL subtypes were highly correlated, different predictive models could be performed. The model we selected (called LyKi1) was constructed based on CD8 [OR 2.24 (95%CI 1.55-3.25; p< 10-4)], E&E grade [OR 3.00 (95%CI 1.22-7.42; p=0.017)] and Ki-67 [OR 1.74 (95%CI 1.09-2.76; p=0.019)]. It was highly significantly associated with RCB 0-1, with an AUC value of 0.856 (95%CI 0.756-0.916). For instance, LyKi1 could isolate a group of 30% of patients that achieved RCB 0-1 in 39.7% of cases vs 4.7% for the 70% of patients with lowest LyKi1 scores. pCR rates were 25% and 2%, respectively. Importantly, prediction value of LyKi1 remained very high if restricted to luminal B tumors (AUC 0.817; 95% CI: 0.741-0.894). Ability to predict pCR was also very high (AUC 0.837 (95%CI: 0.750-0.924) in this phenotype). Conclusion: This retrospective analysis clearly highlights the important predictive role of sTILs and TIL subpopulations for the response to an anthracyclin-taxane based regimen in a neoadjuvant setting for luminal breast cancer. Within this cohort, LyKi1 score (combining CD8, grade and Ki-67) has a very high value to predict pathological response to NACT in luminal breast cancer. Importantly, such score has to be validated in a multicentric prospective cohort and investigated in adjuvant setting. Citation Format: Marc Debled, Hugo Deboissy, Coralie Cantarel, Chloé Delfour, Léonie Alran, Marion Fournier, Nathalie Quenel-Tueux, Valérie Velasco, Foucault Chammings, Véronique Brouste, Monica Arnedos, Gaétan MacGrogan. LyKi1: a highly predictive immune-based score of pathological response to chemotherapy in luminal breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-02-02.

The effect of maleic anhydride grafted polypropylene addition on the degradation in the mechanical properties of the PP/wood composites

This work focuses on studying the influence of coupling agents on the degradation in the mechanical properties of Polypropylene (PP)/wood composites. Maleic anhydride polypropylene (MAPP) was used as a coupling agent between the wood flour and PP matrix. As the coupling agent plays an important role in the stability of the WPC, a 10 wt% wood flour was mixed with PP granules along with a UV stabilizer and varying percentages (1, 3, 5 wt%) of MAPP in a twin-screw extruder to obtain PWC granules. The composite granules were injection molded to produce tensile samples for the mechanical characterization of the composites. To test the environmental degradation of the PWCs, the tensile samples were exposed to the environmental conditions for 0, 336 h (14 days), and 672 h (28 days) prior to testing. After the specified exposure time, the samples were mechanically characterized using tensile testing. The degradation characteristics of the WPCs were quantified in terms of the failure strains of the composite with exposure time. The experiments were designed, and various analyses, including ANOVA, regression equation, and prediction tests, were carried out to investigate the impact of parameters on the failure strain of the PWCs. Moreover, the study aimed to examine the effect of parameters such as MAPP and time, on the failure strain of the composites. From the experimental results, it is concluded that the composites containing 1 wt% of MAPP showed superior retention in the degradation of composites when compared with 3 and 5 wt% MAPP content.

Dutch multicenter study: Point-of-care test for CT lesion prediction in mild traumatic brain injury using GFAP and UCH-L1

Dutch multicenter study: Point-of-care test for CT lesion prediction in mild traumatic brain injury using GFAP and UCH-L1

Remaining useful life prediction and cycle life test optimization for multiple-formula battery: A method based on multi-source transfer learning

Achieving highly accurate predictions based on less data with multiple formulations has become a significant challenge. Unlike the traditional prediction model that ignores the similarities and differences between multi-formula batteries, the proposed multi-source transfer RUL prediction is an effective way to jointly transfer several samples and merge degradation information from multi-source domains, thereby taking full advantage of the information. Aiming at the problem of negative transfer and insufficient transfer when multi-source domains are available, dynamic time warping is employed to adaptively select transferable samples, ignoring the local individual differences. The least absolute shrinkage and selection operator are utilized to generate an optimal subset and allocate personalized weights. Then, an optimization strategy for the cycle life tests is proposed by automatically giving a reasonable threshold of stopping the test. The proposed method is verified based on an actual dataset with multiple formulations collected under different test conditions from a battery manufacturer. Experimental results show that the proposed method has high accuracy based on even a small amount of data. The systematic optimization strategy can significantly reduce the time and cost of the test.

Cyclooxygenase-2 inhibitors alleviated depressive and anxious-like behaviors in mice exposed to lipopolysaccharide: Involvement of oxidative stress and neuroinflammation

Depression and anxiety disorders have their pathophysiologies linked to inflammation and oxidative stress. In this context, celecoxib (CLX) and etoricoxib (ETR) inhibit cyclooxygenase 2 (COX-2), an enzyme expressed by cells involved in the inflammatory process and found in the brain. Studies have been using CLX as a possible drug in the treatment of depression, although its mechanisms at the central nervous system level are not fully elucidated. In this study, the effects of CLX and ETR on behavioral, oxidative, and inflammatory changes induced by systemic exposure to Escherichia coli lipopolysaccharide (LPS) were evaluated in adult male swiss mice. For ten days, the animals received intraperitoneal injections of LPS at 0.5 mg/kg. From the sixth to the tenth day, one hour after LPS exposure, they were treated orally with CLX (15 mg/kg), ETR (10 mg/kg), or fluoxetine (FLU) (20 mg/kg). Twenty-four hours after the last oral administration, the animals underwent evaluation of locomotor activity (open field test), predictive tests for depressive-like behavior (forced swim and tail suspension tests), and anxiolytic-like effect (elevated plus maze and hole board tests). Subsequently, the hippocampus, prefrontal cortex and striatum were dissected for the measurement of oxidative and nitrosative parameters (malondialdehyde, nitrite, and glutathione) and quantification of pro-inflammatory cytokines (IL-1β and IL-6). LPS induced depressive and anxious-like behavior, and treatment with CLX or ETR was able to reverse most of the behavioral changes. It was evidenced that nitrosative stress and the degree of lipid peroxidation induced by LPS were reduced in different brain areas after treatment with the drugs, as well as the endogenous defense system against free radicals was strengthened. CLX and ETR also significantly reduced LPS-induced cytokine levels. These data are expected to expand information on the role of inflammation in depression and anxiety and provide insights into possible mechanisms of COX-2 inhibitors in psychiatric disorders with a neurobiological basis in inflammation and oxidative stress.