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CDK4/6 inhibitors combined with endocrine therapy have demonstrated higher antitumor activity than endocrine therapy alone for the treatment of advanced estrogen receptor-positive breast cancer. Some of these tumors are de novo resistant to CDK4/6 inhibitors and others develop acquired resistance. Here, we show that p16 overexpression is associated with reduced antitumor activity of CDK4/6 inhibitors in patient-derived xenografts ( n  = 37) and estrogen receptor-positive breast cancer cell lines, as well as reduced response of early and advanced breast cancer patients to CDK4/6 inhibitors ( n  = 89). We also identified heterozygous RB1 loss as biomarker of acquired resistance and poor clinical outcome. Combination of the CDK4/6 inhibitor ribociclib with the PI3K inhibitor alpelisib showed antitumor activity in estrogen receptor-positive non-basal-like breast cancer patient-derived xenografts, independently of PIK3CA , ESR1 or RB1 mutation, also in drug de-escalation experiments or omitting endocrine therapy. Our results offer insights into predicting primary/acquired resistance to CDK4/6 inhibitors and post-progression therapeutic strategies. CDK4/6 inhibitor resistance is common in breast cancer. Here, the authors show that p16 overexpression may be linked to reduced efficacy of CDK4/6 inhibition, and show that the combination with PI3K inhibitors may increase anti-tumour effects.

Background Combined targeting of CDK4/6 and ER is now the standard of care for patients with advanced ER+/HER2− breast cancer. However, acquired resistance to these therapies frequently leads to disease progression. As such, it is critical to identify the mechanisms by which resistance to CDK4/6-based therapies is acquired and also identify therapeutic strategies to overcome resistance. Methods In this study, we developed and characterized multiple in vitro and in vivo models of acquired resistance to CDK4/6-based therapies. Resistant models were screened by reverse phase protein array (RPPA) for cell signaling changes that are activated in resistance. Results We show that either a direct loss of Rb or loss of dependence on Rb signaling confers cross-resistance to inhibitors of CDK4/6, while PI3K/mTOR signaling remains activated. Treatment with the p110α-selective PI3K inhibitor, alpelisib (BYL719), completely blocked the progression of acquired CDK4/6 inhibitor-resistant xenografts in the absence of continued CDK4/6 inhibitor treatment in models of both PIK3CA mutant and wild-type ER+/HER2− breast cancer. Triple combination therapy against PI3K:CDK4/6:ER prevented and/or delayed the onset of resistance in treatment-naive ER+/HER2− breast cancer models. Conclusions These data support the clinical investigation of p110α-selective inhibitors of PI3K, such as alpelisib, in patients with ER+/HER2− breast cancer who have progressed on CDK4/6:ER-based therapies. Our data also support the investigation of PI3K:CDK4/6:ER triple combination therapy to prevent the onset of resistance to the combination of endocrine therapy plus CDK4/6 inhibition.

IntroductionProstate-specific membrane antigen positron emission tomography (PSMA-PET) has emerged as valuable imaging to assessing metastatic disease in prostate malignancy. However, there has been limited studies exploring the utility PSMA-PET as primary imaging assessing for index lesions prior to biopsy. The primary objective of this study is to compare the diagnostic accuracy of 18-fluorine PSMA (18F DCFPyL PSMA) PET scans to multiparametric MRI (mpMRI) to detect primary prostate cancer at prostate biopsy.Methods and analysisThe PEDAL trial is a multicentre, prospective, single-arm, paired comparison, non-randomised phase III trial in subjects considered for diagnostic prostate biopsy. Subjects who are eligible for a diagnostic mpMRI prostate will undergo additional same-day 18 F DCFPyl PSMA PET/CT of the chest, abdomen and pelvis. Software coregistration of the mpMRI and PSMA-PET/CT images will be performed. The reporting of the mpMRI prostate, PSMA-PET/CT and PSMA PET/MRI coregistration will be performed blinded. The diagnostic accuracy of PSMA PET/CT alone, and in combination with mpMRI, to detect prostate cancer will be assessed. Histopathology at prostate biopsy will be used as the reference standard. Sample size calculations estimate that 240 subjects will need to be recruited to demonstrate 20% superiority of PSMA-PET/CT. The sensitivity, specificity, positive predictive value and negative predictive value of the combination of mpMRI prostate and PSMA PET/CT compared with targeted and systematic prostate biopsy will be evaluated. It is hypothesised that PSMA PET/CT combined with mpMRI prostate will have improved diagnostic accuracy compared with mpMRI prostate alone for detection of prostate cancer in biopsy-naïve men, resulting in a significant impact on patient management.Ethics and disseminationThis study was approved by the independent Human Research Ethics Committee. Results will be published in peer-reviewed medical journals with eligible investigators will significantly contribute.Trial registration numberACTRN12620000261910.

ObjectivesHigh-grade serous ovarian cancer (HGSOC) represents most epithelial ovarian cancers. Whilst initially responding to platinum-based therapy, ~75% of patients develop resistance, conferring poor prognosis. Homologous recombination repair proficiency is associated with platinum resistance and limited response to PARP inhibitors. PI3K pathway inhibition downregulates BRCA expression, abrogating homologous recombination repair proficiency, and may lead to (re)sensitization to PARP inhibitors. As alpelisib (PI3Kα inhibitor) + olaparib (PARP inhibitor) demonstrated preliminary evidence of synergism in platinum-resistant/refractory, BRCA-wild-type, recurrent HGSOC in a phase 1b study, the EPIK-O study is further evaluating this combination.MethodsEPIK-O/ENGOT-OV61 (NCT04729387) is a phase 3, randomized (1:1), open-label, active-controlled trial evaluating the efficacy and safety of alpelisib + olaparib versus single-agent chemotherapy in patients (N≈358) with no germline BRCA mutation and platinum-resistant/refractory HGSOC. Adult patients with platinum-resistant/refractory, histologically confirmed HGSOC, high-grade endometrioid ovarian, fallopian tube, or primary peritoneal cancer, with no germline BRCA1/2 mutation, are included; patients must have received 1–3 prior systemic therapies. In Arm 1, patients receive alpelisib 200 mg orally OD + olaparib 200 mg orally BID; in Arm 2, patients receive paclitaxel 80 mg/m2 IV weekly or pegylated liposomal doxorubicin 40–50 mg/m2 IV Q28D (investigator’s choice). The primary endpoint is progression-free survival per RECIST 1.1 assessment by a blinded independent review committee. Key secondary endpoint is overall survival. Other secondary endpoints include overall response rate, clinical benefit rate, safety, and quality of life. Enrollment is planned in 26 countries; completion of data collection for the primary endpoint is anticipated in 2023.ResultsNo resultsConclusionsTrial in Progress

Background Neoadjuvant chemotherapy (NAC) plays an important role in the management of locally advanced breast cancer. It allows for downstaging of tumors, potentially allowing for breast conservation. NAC also allows for in-vivo testing of the tumors’ response to chemotherapy and provides important prognostic information. There are currently no clearly defined clinical models that incorporate imaging with clinical data to predict response to NAC. Thus, the aim of this work is to develop a predictive AI model based on routine CT imaging and clinical parameters to predict response to NAC. Methods The CT scans of 324 patients with NAC from multiple centers in Singapore were used in this study. Four different radiomics models were built for predicting pathological complete response (pCR): first two were based on textural features extracted from peri-tumoral and tumoral regions, the third model based on novel space-resolved radiomics which extract feature maps using voxel-based radiomics and the fourth model based on deep learning (DL). Clinical parameters were included to build a final prognostic model. Results The best performing models were based on space-resolved and DL approaches. Space-resolved radiomics improves the clinical AUCs of pCR prediction from 0.743 (0.650 to 0.831) to 0.775 (0.685 to 0.860) and our DL model improved it from 0.743 (0.650 to 0.831) to 0.772 (0.685 to 0.853). The tumoral radiomics model performs the worst with no improvement of the AUC from the clinical model. The peri-tumoral combined model gives moderate performance with an AUC of 0.765 (0.671 to 0.855). Conclusions Radiomics features extracted from diagnostic CT augment the predictive ability of pCR when combined with clinical features. The novel space-resolved radiomics and DL radiomics approaches outperformed conventional radiomics techniques.

Assessing rural habitat suitability and its connection to land response is a vital tool for understanding the socio-economic and environmental challenges in rural areas tailored to local contexts. This study fills existing research gaps by examining the suitability of rural habitats in Anhui Province, opening pathways to reveal how rural sustainability may connect to land. Using the autoregressive distributed lag (ARDL) model, it analyzes the short- and long-term effects of socio-economic and environmental factors on rural suitability across various counties. Additionally, a descriptive analysis explores the pathways linking rural suitability to land use responses. The findings reveal that rural greening, village planning, and housing area per resident positively influence rural habitat suitability in both the short and long term. However, agricultural income growth shows a negative impact, potentially due to structural issues in the sector. Environmental factors like temperature and rainfall have a limited influence on rural suitability. The study underscores the importance of suitable rural infrastructure, namely enhancing rural greening rate, implementing village plans, and improving housing for sustainable rural development. Regional variations in rural habitat suitability across Anhui Province are also evident. While some cities, such as Huaibei and Anqing, demonstrate success in revitalization, others, like Suzhou and Chizhou, face challenges. The results highlight the need for region-specific strategies that account for local environmental, economic, and infrastructural contexts. Tailored approaches are essential to achieving long-term, effective rural development in the province.

The phase-to-height imaging model, as a three-dimensional (3D) measurement technology, has been commonly applied in fringe projection to assist surface profile measurement, where the efficient and accurate calculation of phase plays a critical role in precise imaging. To deal with multiple extra coded patterns and 2π jump error caused to the existing absolute phase demodulation methods, a novel method of phase demodulation is proposed based on dual variable-frequency (VF) coded patterns. In this paper, the frequency of coded fringe is defined as the number of coded fringes within a single sinusoidal fringe period. First, the effective wrapped phase (EWP) as calculated using the four-step phase shifting method was split into the wrapped phase region with complete period and the wrapped phase region without complete period. Second, the fringe orders in wrapped phase region with complete period were decoded according to the frequency of the VF coded fringes and the continuous characteristic of the fringe order. Notably, the sampling frequency of fast Fourier transform (FFT) was determined by the length of the decoding interval and can be adjusted automatically with the variation in height of the object. Third, the fringe orders in wrapped phase region without complete period were decoded depending on the consistency of fringe orders in the connected region of wrapped phase. Last, phase demodulation was performed. The experimental results were obtained to confirm the effectiveness of the proposed method in the phase demodulation of both discontinuous objects and highly abrupt objects.

This study aims to explore how cancer-related risk factors cluster among college students in Guam. Using the 2021–2022 Pacific Islands Cohort of College Students data, we conducted a latent class analysis (LCA) to organize the sample into classes based on clustering cancer risk factors, including tobacco use, binge drinking, low fruit/vegetable intake, physical inactivity, betel nut use, overweight/obesity, depression, and anxiety. Among the 577 college students surveyed, results show a high prevalence of low fruit/vegetable intake, overweight/obesity, depression, and anxiety. The LCA identified three classes, each defined by different clustering cancer risk behaviors. All classes showed high prevalence of low fruit/vegetable intake. Class 1 had the highest rates of tobacco use, betel nut use, and binge drinking. Class 2 had the highest rates of physical inactivity, depression, and anxiety. Class 3 had the lowest rates of betel nut use, overweight/obese, depression, and anxiety when compared with Classes 1 and 2. The clustering of risk behaviors highlights the need for targeted interventions and prevention strategies among Guam’s youth, aiming to address these behaviors and potentially reduce cancer risk in the region.

In order to deal with the problem of composite damage location, an imaging technique based on differential signal and Lamb wave tomography was proposed. Firstly, the feasibility of the technique put forward was verified by simulation. In this process, the composite model was regularly set down by the circular sensor array, with each sensor acting as an actuator in sequence to generate Lamb waves. Apart from that, other sensors were used to collect response signals. With regard to the damage factor, it was mainly determined by the difference between the damage signal and the non-damage signal. The probabilistic imaging algorithm was employed to carry out damage location imaging. Then, experiments were carried out so as to study the selected composite plate. Finally, the tentative outcomes have illustrated that the maximum error of damage imaging position was 7.07 mm. The relative error was 1.6%. In addition, the method has the characteristics of simple calculation and high imaging efficiency. Therefore, it has large technical potential and wide applications in the damage location and damage recognition for composite material.