Combined deep learning and radiomics in pretreatment radiation esophagitis prediction for patients with esophageal cancer underwent volumetric modulated arc therapy.

PURPOSE: To develop a combined radiomics and deep learning (DL) model in predicting radiation esophagitis (RE) of a grade ≥ 2 for patients with esophageal cancer (EC) underwent volumetric modulated arc therapy (VMAT) based on computed tomography (CT) and radiation dose (RD) distribution images. MATERIALS AND METHODS: A total of 273 EC patients underwent VMAT were retrospectively reviewed and enrolled from two centers and divided into training (n = 152), internal validation (n = 66), and external validation (n = 55) cohorts, respectively. Radiomic and dosiomic features along with DL features using convolutional neural networks were extracted and screened from CT and RD images to predict RE. The performance of these models was evaluated and compared using the area under curve (AUC) of the receiver operating characteristic curves (ROC). RESULTS: There were 5 and 10 radiomic and dosiomic features were screened, respectively. XGBoost achieved a best AUC of 0.703, 0.694 and 0.801, 0.729 with radiomic and dosiomic features in the internal and external validation cohorts, respectively. ResNet34 achieved a best prediction AUC of 0.642, 0.657 and 0.762, 0.737 for radiomics based DL model (DLR) and RD based DL model (DLD) in the internal and external validation cohorts, respectively. Combined model of DLD + Dosiomics + clinical factors achieved a best AUC of 0.913, 0.821 and 0.805 in the training, internal, and external validation cohorts, respectively. CONCLUSION: Although the dose was not responsible for the prediction accuracy, the combination of various feature extraction methods was a factor in improving the RE prediction accuracy. Combining DLD with dosiomic features was promising in the pretreatment prediction of RE for EC patients underwent VMAT.

Multi-omics deep learning for radiation pneumonitis prediction in lung cancer patients underwent volumetric modulated arc therapy.

BACKGROUND AND OBJECTIVE: To evaluate the feasibility and accuracy of radiomics, dosiomics, and deep learning (DL) in predicting Radiation Pneumonitis (RP) in lung cancer patients underwent volumetric modulated arc therapy (VMAT) to improve radiotherapy safety and management. METHODS: Total of 318 and 31 lung cancer patients underwent VMAT from First Affiliated Hospital of Wenzhou Medical University (WMU) and Quzhou Affiliated Hospital of WMU were enrolled for training and external validation, respectively. Models based on radiomics (R), dosiomics (D), and combined radiomics and dosiomics features (R+D) were constructed and validated using three machine learning (ML) methods. DL models trained with CT (DLR), dose distribution (DLD), and combined CT and dose distribution (DL(R+D)) images were constructed. DL features were then extracted from the fully connected layers of the best-performing DL model to combine with features of the ML model with the best performance to construct models of R+DLR, D+DLD, R+D+DL(R+D)) for RP prediction. RESULTS: The R+D model achieved a best area under curve (AUC) of 0.84, 0.73, and 0.73 in the internal validation cohorts with Support Vector Machine (SVM), XGBoost, and Logistic Regression (LR), respectively. The DL(R+D) model achieved a best AUC of 0.89 and 0.86 using ResNet-34 in training and internal validation cohorts, respectively. The R+D+DL(R+D) model achieved a best performance in the external validation cohorts with an AUC, accuracy, sensitivity, and specificity of 0.81(0.62-0.99), 0.81, 0.84, and 0.67, respectively. CONCLUSIONS: The integration of radiomics, dosiomics, and DL features is feasible and accurate for the RP prediction to improve the management of lung cancer patients underwent VMAT.

Radiation pneumonitis prediction with dual-radiomics for esophageal cancer underwent radiotherapy.

BACKGROUND: To integrate radiomics and dosiomics features from multiple regions in the radiation pneumonia (RP grade ≥ 2) prediction for esophageal cancer (EC) patients underwent radiotherapy (RT). METHODS: Total of 143 EC patients in the authors' hospital (training and internal validation: 70%:30%) and 32 EC patients from another hospital (external validation) underwent RT from 2015 to 2022 were retrospectively reviewed and analyzed. Patients were dichotomized as positive (RP+) or negative (RP-) according to CTCAE V5.0. Models with radiomics and dosiomics features extracted from single region of interest (ROI), multiple ROIs and combined models were constructed and evaluated. A nomogram integrating radiomics score (Rad_score), dosiomics score (Dos_score), clinical factors, dose-volume histogram (DVH) factors, and mean lung dose (MLD) was also constructed and validated. RESULTS: Models with Rad_score_Lung&Overlap and Dos_score_Lung&Overlap achieved a better area under curve (AUC) of 0.818 and 0.844 in the external validation in comparison with radiomics and dosiomics models with features extracted from single ROI. Combining four radiomics and dosiomics models using support vector machine (SVM) improved the AUC to 0.854 in the external validation. Nomogram integrating Rad_score, and Dos_score with clinical factors, DVH factors, and MLD further improved the RP prediction AUC to 0.937 and 0.912 in the internal and external validation, respectively. CONCLUSION: CT-based RP prediction model integrating radiomics and dosiomics features from multiple ROIs outperformed those with features from a single ROI with increased reliability for EC patients who underwent RT.

Depletion of SASP senescent cardiomyocytes with senolytic drugs confers therapeutic effects in doxorubicin-related cardiotoxicity.

Doxorubicin (Dox), an anthracycline antibiotic, is widely used in cancer treatment. Although its antitumor efficacy appears significant, its clinical use is greatly restricted by its induction of cardiotoxicity. Cardiac senescence drives the Dox-induced cardiotoxicity, but whether diminishing these senescent cardiomyocytes could alleviate the cardiotoxicity remains unclear. Here, we assessed whether senescent cardiomyocytes have a senescence-associated secretory phenotype (SASP) that affects healthy non-senescent cardiomyocytes, rendering them senescent via the delivery of exosomes. Additionally, we explored whether targeting SASP senescent cardiomyocytes using a Bcl-2 inhibitor could alleviate cardiotoxicity. Cardiac damage was induced in a mouse model of continuous Dox treatment in vivo, and cardiomyocytes in vitro. Immunofluorescence of the senescence markers of Cdkn2a, Cdkn1a and γ-H2A.X was used to assess the SASP in the Dox-treated heart. To explore the molecular mechanisms involved, the Bcl-2 inhibitor ABT-199 was employed to eliminate SASP senescent cardiomyocytes. We show that the cardiomyocytes acquire a SASP during Dox treatment. The senescent cardiomyocytes upregulated Bcl-2, although treatment of mice with ABT-199 selectively eliminated SASP senescent cardiomyocytes involved in Dox-induced cardiotoxicity, thus leading to partial alleviation of Dox-induced cardiotoxicity. Moreover, we concluded that SASP factors secreted by senescent cardiomyocytes induced by Dox renders otherwise healthy cardiomyocytes senescent through exosome delivery. Our findings suggest that SASP senescent cardiomyocytes are a significant component of the pathogenesis of Dox-dependent cardiotoxicity and indicate that targeting the clearance of SASP senescent cardiomyocytes could be a new therapeutic approach for Dox-induced cardiac injury.

Mitochondria-Targeted Nanoadjuvants Induced Multi-Functional Immune-Microenvironment Remodeling to Sensitize Tumor Radio-Immunotherapy.

It is newly revealed that collagen works as a physical barrier to tumor immune infiltration, oxygen perfusion, and immune depressor in solid tumors. Meanwhile, after radiotherapy (RT), the programmed death ligand-1 (PD-L1) overexpression and transforming growth factor-ß (TGF-ß) excessive secretion would accelerate DNA damage repair and trigger T cell exclusion to limit RT efficacy. However, existing drugs or nanoparticles can hardly address these obstacles of highly effective RT simultaneously, effectively, and easily. In this study, it is revealed that inducing mitochondria dysfunction by using oxidative phosphorylation inhibitors like Lonidamine (LND) can serve as a highly effective multi-immune pathway regulation strategy through PD-L1, collagen, and TGF-ß co-depression. Then, IR-LND is prepared by combining the mitochondria-targeted molecule IR-68 with LND, which then is loaded with liposomes (Lip) to create IR-LND@Lip nanoadjuvants. By doing this, IR-LND@Lip more effectively sensitizes RT by generating more DNA damage and transforming cold tumors into hot ones through immune activation by PD-L1, collagen, and TGF-ß co-inhibition. In conclusion, the combined treatment of RT and IR-LND@Lip ultimately almost completely suppressed the growth of bladder tumors and breast tumors.

MRI radiomics nomogram integrating postoperative adjuvant treatments in recurrence risk prediction for patients with early-stage cervical cancer.

BACKGROUND AND PURPOSE: Adjuvant treatments are valuable to decrease the recurrence rate and improve survival for early-stage cervical cancer patients (ESCC), Therefore, recurrence risk evaluation is critical for the choice of postoperative treatment. A magnetic resonance imaging (MRI) based radiomics nomogram integrating postoperative adjuvant treatments was constructed and validated externally to improve the recurrence risk prediction for ESCC. MATERIAL AND METHODS: 212 ESCC patients underwent surgery and adjuvant treatments from three centers were enrolled and divided into the training, internal validation, and external validation cohorts. Their clinical data, pretreatment T2-weighted images (T2WI) were retrieved and analyzed. Radiomics models were constructed using machine learning methods with features extracted and screen from sagittal and axial T2WI. A nomogram for recurrence prediction was build and evaluated using multivariable logistic regression analysis integrating radiomic signature and adjuvant treatments. RESULTS: A total of 8 radiomic features were screened out of 1020 extracted features. The extreme gradient boosting (XGboost) model based on MRI radiomic features performed best in recurrence prediction with an area under curve (AUC) of 0.833, 0.822 in the internal and external validation cohorts, respectively. The nomogram integrating radiomic signature and clinical factors achieved an AUC of 0.806, 0.718 in the internal and external validation cohorts, respectively, for recurrence risk prediction for ESCC. CONCLUSION: In this study, the nomogram integrating T2WI radiomic signature and clinical factors is valuable to predict the recurrence risk, thereby allowing timely planning for effective treatments for ESCC with high risk of recurrence.

Multifunctional iron-apigenin nanocomplex conducting photothermal therapy and triggering augmented immune response for triple negative breast cancer.

Triple negative breast cancer (TNBC) presents a formidable challenge due to its low sensitivity to many chemotherapeutic drugs and a relatively low overall survival rate in clinical practice. Photothermal therapy has recently garnered substantial interest in cancer treatment, owing to its swift therapeutic effectiveness and minimal impact on normal cells. Metal-polyphenol nanostructures have recently garnered significant attention as photothermal transduction agents due to their facile preparation and favorable photothermal properties. In this study, we employed a coordinated approach involving Fe3+ and apigenin, a polyphenol compound, to construct the nanostructure (nFeAPG), with the assistance of ß-CD and DSPE-PEG facilitating the formation of the complex nanostructure. In vitro research demonstrated that the formed nFeAPG could induce cell death by elevating intracellular oxidative stress, inhibiting antioxidative system, and promoting apoptosis and ferroptosis, and near infrared spectrum irradiation further strengthen the therapeutic outcome. In 4T1 tumor bearing mice, nFeAPG could effectively accumulate into tumor site and exhibit commendable control over tumor growth. Futher analysis demonstrated that nFeAPG ameliorated the suppressed immune microenvironment by augmenting the response of DC cells and T cells. This study underscores that nFeAPG encompasses a multifaceted capacity to combat TNBC, holding promise as a compelling therapeutic strategy for TNBC treatment.

A T-Cell Inspired Sonoporation System Enhances Low-Dose X-Ray-Mediated Pyroptosis and Radioimmunotherapy Efficacy by Restoring Gasdermin-E Expression.

Genome editing has the potential to improve the unsatisfactory therapeutic effect of antitumor immunotherapy. However, the cell plasma membrane prevents the entry of almost all free genome-manipulation agents. Therefore, a system can be spatiotemporally controlled and can instantly open the cellular membrane to allow the entry of genome-editing agents into target cells is needed. Here, inspired by the ability of T cells to deliver cytotoxins to cancer cells by perforation, an ultrasound (US)-controlled perforation system (UPS) is established to enhance the delivery of free genome-manipulating agents. The UPS can perforate the tumor cell membrane while maintaining cell viability via a controllable lipid peroxidation reaction. In vitro, transmembrane-incapable plasmids can enter cells and perform genome editing with the assistance of UPS, achieving an efficiency of up to 90%. In vivo, the UPS is biodegradable, nonimmunogenic, and tumor-targeting, enabling the puncturing of tumor cells under US. With the application of UPS-assisted genome editing, gasdermin-E expression in 4T1 tumor-bearing mice is successfully restored, which leads to pyroptosis-mediated antitumor immunotherapy via low-dose X-ray irradiation. This study provides new insights for designing a sonoporation system for genome editing. Moreover, the results demonstrate that restoring gasdermin expression by genome editing significantly improves the efficacy of radioimmunotherapy.

A CTL-Inspired Killing System Using Ultralow-Dose Chemical-Drugs to Induce a Pyroptosis-Mediated Antitumor Immune Function.

A Cytotoxic T lymphocyte-inspired system capable of using ultralow-dose chemical drugs to manipulate cell death is needed to investigate the antitumor immunotherapy. Recent studies reveal pyroptosis promotes antitumor immune function. However, high-dose chemotherapy leads to cytokine release syndrome by pyroptosis. Therefore, pyroptosis-inducing ultralow-dose chemotherapy is potential in preclinical and clinical research, but its efficacy, safety, and the antitumor immune responses are not clear. Here, a near-infrared light controllable killing system (BIK system) is established by which ultralow-dose doxorubicin can be spatiotemporally transported to tumor cells and mediate efficient pyroptosis. This BIK system reduces total drug consumption to less than one-thirtieth the common dose in vitro. Moreover, this BIK system exhibited good tumor targeting and tumor penetration. This system is applied for pyroptosis-induced antitumor therapies, which shows less than ≈25 µg kg-1 doxorubicin is sufficient for tumor regression with negligible injuries to major organs. The antitumor immune function are proven to correlate with the impressive efficacy of pyroptosis-inducing ultralow-dose chemotherapy. This study provides new insights into the design of nanoassisted systems for activating the antitumor immunity by microstimulation; the application of the BIK system suggests that ultralow-dose chemotherapy is sufficient for inducing a robust pyroptosis-mediated antitumor immunity.

Proteome-wide analysis reveals potential therapeutic targets for Colorectal cancer: a two-sample mendelian randomization study.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, highlighting an unmet clinical need for more effective therapies. This study aims to evaluate the causal relationship between 4,489 plasma proteins and CRC to identify potential therapeutic targets for CRC. METHODS: We conducted two-sample Mendelian randomization (MR) analysis to examine the causal effects of plasma proteins on CRC. Mediation analysis was performed to assess the indirect effects of plasma proteins on CRC through associated risk factors. In addition, we conducted a phenome-wide association study using the UK Biobank dataset to examine associations between these plasma proteins and other phenotypes. RESULTS: Out of 4,489 plasma proteins, MR analysis revealed causal associations with CRC for 23 proteins, including VIMP, MICB, TNFRSF11B, C5orf38 and SLC5A8. Our findings also confirm the associations between reported risk factors and CRC. Mediation analysis identified mediating effects of proteins on CRC outcomes through risk factors. Furthermore, MR analysis identified 154 plasma proteins are causally linked to at least one CRC risk factor. CONCLUSIONS: Our study evaluated the causal relationships between plasma proteins and CRC, providing a more complete understanding of potential therapeutic targets for CRC.

Mutual communication between radiosensitive and radioresistant esophageal cancer cells modulates their radiosensitivity.

Radiotherapy is an important treatment modality for patients with esophageal cancer; however, the response to radiation varies among different tumor subpopulations due to tumor heterogeneity. Cancer cells that survive radiotherapy (i.e., radioresistant) may proliferate, ultimately resulting in cancer relapse. However, the interaction between radiosensitive and radioresistant cancer cells remains to be elucidated. In this study, we found that the mutual communication between radiosensitive and radioresistant esophageal cancer cells modulated their radiosensitivity. Radiosensitive cells secreted more exosomal let-7a and less interleukin-6 (IL-6) than radioresistant cells. Exosomal let-7a secreted by radiosensitive cells increased the radiosensitivity of radioresistant cells, whereas IL-6 secreted by radioresistant cells decreased the radiosensitivity of radiosensitive cells. Although the serum levels of let-7a and IL-6 before radiotherapy did not vary significantly between patients with radioresistant and radiosensitive diseases, radiotherapy induced a more pronounced decrease in serum let-7a levels and a greater increase in serum IL-6 levels in patients with radioresistant cancer compared to those with radiosensitive cancer. The percentage decrease in serum let-7a and the percentage increase in serum IL-6 levels at the early stage of radiotherapy were inversely associated with tumor regression after radiotherapy. Our findings suggest that early changes in serum let-7a and IL-6 levels may be used as a biomarker to predict the response to radiotherapy in patients with esophageal cancer and provide new insights into subsequent treatments.

Preoperative prediction of clinical and pathological stages for patients with esophageal cancer using PET/CT radiomics.

BACKGROUND: Preoperative stratification is critical for the management of patients with esophageal cancer (EC). To investigate the feasibility and accuracy of PET-CT-based radiomics in preoperative prediction of clinical and pathological stages for patients with EC. METHODS: Histologically confirmed 100 EC patients with preoperative PET-CT images were enrolled retrospectively and randomly divided into training and validation cohorts at a ratio of 7:3. The maximum relevance minimum redundancy (mRMR) was applied to select optimal radiomics features from PET, CT, and fused PET-CT images, respectively. Logistic regression (LR) was applied to classify the T stage (T1,2 vs. T3,4), lymph node metastasis (LNM) (LNM(-) vs. LNM(+)), and pathological state (pstage) (I-II vs. III-IV) with features from CT (CT_LR_Score), PET (PET_LR_Score), fused PET/CT (Fused_LR_Score), and combined CT and PET features (CT + PET_LR_Score), respectively. RESULTS: Seven, 10, and 7 CT features; 7, 8, and 7 PET features; and 3, 6, and 3 fused PET/CT features were selected using mRMR for the prediction of T stage, LNM, and pstage, respectively. The area under curves (AUCs) for T stage, LNM, and pstage prediction in the validation cohorts were 0.846, 0.756, 0.665, and 0.815; 0.769, 0.760, 0.665, and 0.824; and 0.727, 0.785, 0.689, and 0.837 for models of CT_LR_Score, PET_ LR_Score, Fused_ LR_Score, and CT + PET_ LR_Score, respectively. CONCLUSIONS: Accurate prediction ability was observed with combined PET and CT radiomics in the prediction of T stage, LNM, and pstage for EC patients. CRITICAL RELEVANCE STATEMENT: PET/CT radiomics is feasible and promising to stratify stages for esophageal cancer preoperatively. KEY POINTS: • PET-CT radiomics achieved the best performance for Node and pathological stage prediction. • CT radiomics achieved the best AUC for T stage prediction. • PET-CT radiomics is feasible and promising to stratify stages for EC preoperatively.

A cytotoxic T cell inspired oncolytic nanosystem promotes lytic cell death by lipid peroxidation and elicits antitumor immune responses.

Lytic cell death triggers an antitumour immune response. However, cancer cells evade lytic cell death by several mechanisms. Moreover, a prolonged and uncontrolled immune response conversely leads to T-cell exhaustion. Therefore, an oncolytic system capable of eliciting an immune response by killing cancer cells in a controlled manner is needed. Here, we establish a micro-scale cytotoxic T-cell-inspired oncolytic system (TIOs) to precisely lyse cancer cells by NIR-light-controlled lipid peroxidation. Our TIOs present antigen-based cell recognition, tumour-targeting and catalytic cell-lysis ability; thus, the TIOs induce oncolysis in vivo. We apply TIOs to preclinical cancer models, showing anti-tumor activity with negligible side-effects. Tumour regression is correlated with a T-cell based anti-tumour immune response and TIOs also improve responses to anti-PD-1 therapy or STING activation. Our study provides insights to design oncolytic systems for antitumour immunity. Moreover, activation of STING can reverse T-cell exhaustion in oncolysis.

Regorafenib activates oxidative stress by inhibiting SELENOS and potentiates oxaliplatin-induced cell death in colon cancer cells.

Colorectal cancer (CRC) is the third most common cancer, and is one of the leading causes of cancer-related death worldwide. At the time of diagnosis, about 20% of patients with CRC present metastatic disease. Regorafenib, an oral multi-kinase inhibitor, has been demonstrated the efficacy and tolerability in patients with metastatic CRC. Oxaliplatin is a frontline treatment regimen for CRC, and combination treatments with oxaliplatin and other chemotherapeutic agents exert superior therapeutic effects. However, side effects and drug resistance limited their further clinical application. Here, we found that combined treatment with regorafenib and oxaliplatin synergistically enhanced anti-tumor activities in CRC by activating reactive oxygen species (ROS) mediated endoplasmic reticulum (ER) stress, C-Jun-amino-terminal kinase (JNK) and p38 signaling pathways. Regorafenib promoted ROS production by suppressing the expression of selenoprotein S (SELENOS). Knocking down SELENOS sensitized ROS-mediated anti-tumor effects of regorafenib in CRC cells. Furthermore, mouse xenograft models demonstrated that synergistic anti-tumor effects of combined treatment with regorafenib and oxaliplatin. This study provided solid experimental evidences for the combined treatment with regorafenib and oxaliplatin in CRC.

Integrating plan complexity and dosiomics features with deep learning in patient-specific quality assurance for volumetric modulated arc therapy.

PURPOSE: To investigate the feasibility and performance of deep learning (DL) models combined with plan complexity (PC) and dosiomics features in the patient-specific quality assurance (PSQA) for patients underwent volumetric modulated arc therapy (VMAT). METHODS: Total of 201 VMAT plans with measured PSQA results were retrospectively enrolled and divided into training and testing sets randomly at 7:3. PC metrics were calculated using house-built algorithm based on Matlab. Dosiomics features were extracted and selected using Random Forest (RF) from planning target volume (PTV) and overlap regions with 3D dose distributions. The top 50 dosiomics and 5 PC features were selected based on feature importance screening. A DL DenseNet was adapted and trained for the PSQA prediction. RESULTS: The measured average gamma passing rate (GPR) of these VMAT plans was 97.94% ± 1.87%, 94.33% ± 3.22%, and 87.27% ± 4.81% at the criteria of 3%/3 mm, 3%/2 mm, and 2%/2 mm, respectively. Models with PC features alone demonstrated the lowest area under curve (AUC). The AUC and sensitivity of PC and dosiomics (D) combined model at 2%/2 mm were 0.915 and 0.833, respectively. The AUCs of DL models were improved from 0.943, 0.849, 0.841 to 0.948, 0.890, 0.942 in the combined models (PC + D + DL) at 3%/3 mm, 3%/2 mm and 2%/2 mm, respectively. A best AUC of 0.942 with a sensitivity, specificity and accuracy of 100%, 81.8%, and 83.6% was achieved with combined model (PC + D + DL) at 2%/2 mm. CONCLUSIONS: Integrating DL with dosiomics and PC metrics is promising in the prediction of GPRs in PSQA for patients underwent VMAT.

Efficacy of apatinib+radiotherapy vs radiotherapy alone in patients with advanced multiline therapy failure for non small cell lung cancer with brain metastasis.

OBJECTIVE: Lung cancer is the leading cause of cancer-associated mortality worldwide. Central nervous system (CNS) metastasis is a prevalent and serious complication. The most common treatment for brain metastasis (BM) is still radiation therapy (RT). An increasing number of drugs have been shown to have intracranial activity or to sensitize tumours to radiotherapy. METHODS: Consecutive advanced multiline therapy failure in patients with non-small-cell lung cancer (NSCLC) with BM at the authors' hospital were retrospectively reviewed. Eligible patients were divided into two groups: Apatinib+RT group and RT group. Intracranial progression-free survival (PFS) and overall survival (OS) were analysed using the Kaplan-Meier method. RESULTS: The median intracranial PFS for the RT group and Apatinib+RT group was 5.83 months and 11.81 months (p = 0.034). The median OS for the RT group and Apatinib+RT group was 9.02 months and 13.62 months (p = 0.311). The Apatinib+RT group had a better intracranial PFS, but there were no significant differences between the two arms in OS. The Apatinib+RT group had significantly reduced symptoms caused by BM. CONCLUSION: RT combined with apatinib could help to control intracranial metastases. The Apatinib+RT group had significantly reduced symptoms caused by BM and improved quality of life for patients, the safety of the two treatments was similar. ADVANCES IN KNOWLEDGE: Here, we propose that RT combined with apatinib can significantly relieve brain symptoms and tolerate side-effects without affecting OS in patients with BM following failure of multiline therapy for NSCLC. Of course, this paper is a retrospective origin study, and more powerful evidence is needed to demonstrate.

Central nervous system efficacy of rezivertinib (BPI-7711) in advanced NSCLC patients with EGFR T790M mutation: A pooled analysis of two clinical studies.

BACKGROUND: Rezivertinib (BPI-7711) is a novel third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor (TKI) which revealed the systematic and central nervous system (CNS) antitumor activities for EGFR T790M-mutated advanced NSCLC in previous clinical studies and is further analyzed here. METHODS: Eligible patients from the previous phase I and phase IIb studies of rezivertinib were included for pooled analysis. Post-progressive patients who received a prescribed dosage (≥180 mg) of rezivertinib orally once daily were included in full analysis set (FAS), while those with stable, asymptomatic CNS lesions, including measurable and non-measurable ones at baseline were included in CNS full analysis set (cFAS). Patients with measurable CNS lesions were included in CNS evaluable for response set (cEFR). BICR-assessed CNS objective response rate (CNS-ORR), CNS disease control rate (CNS-DCR), CNS duration of response (CNS-DoR), CNS progression-free survival (CNS-PFS), and CNS depth of response (CNS-DepOR) were evaluated. RESULTS: 355 patients were included in FAS, among whom 150 and 45 patients were included in cFAS and cEFR. This pooled analysis showed the CNS-ORR was 32.0% (48/150; 95% CI: 24.6-40.1%) and the CNS-DCR was 42.0% (63/150; 95% CI: 34.0-50.3%) in cFAS, while that in cEFR were 68.9% (31/45; 95% CI: 53.4-81.8%) and 100% (45/45; 95% CI: 92.1-100.0%). In cEFR, the median CNS-DepOR and the mean of CNS-DepOR were -52.0% (range: -100.0 to 16.1%) and -46.8% (95% CI: -55.5 to -38.1%). In cFAS, the median CNS-DoR and CNS-PFS were 13.8 (95% CI: 9.6-not calculable [NC]) and 16.5 (95% CI: 13.7-NC) months. CONCLUSIONS: Rezivertinib demonstrated encouraging clinical CNS efficacy among advanced NSCLC patients with EGFR T790M mutation and CNS metastases.

ATB0,+-targeted nanoparticles initiate autophagy suppression to overcome chemoresistance for enhanced colorectal cancer therapy.

Oxaliplatin (OXA) resistance remains the major obstacle to the successful chemotherapy of colorectal cancer (CRC). As a self-protection mechanism, autophagy may contribute to tumor drug resistance, therefore autophagy suppression could be regarded as a possible treatment option in chemotherapy. Cancer cells, especially drug-resistant tumor cells, increase their demand for specific amino acids by expanding exogenous supply and up-regulating de novo synthesis, to meet the needs for excessive proliferation. Therefore, it is possible to inhibit cancer cell proliferation through pharmacologically blocking the entry of amino acid into cancer cells. SLC6A14 (ATB0,+) is an essential amino acid transporter, that is often abnormally up-regulated in most cancer cells. Herein, in this study, we designed oxaliplatin/berbamine-coloaded, ATB0,+-targeted nanoparticles ((O + B)@Trp-NPs) to therapeutically target SLC6A14 (ATB0,+) and inhibit cancer proliferation. The (O + B)@Trp-NPs utilize the surface-modified tryptophan to achieve SLC6A14-targeted delivery of Berbamine (BBM), a compound that is found in a number of plants used in traditional Chinese medicine, which could suppress autolysosome formation though impairing autophagosome-lysosome fusion. We verified the feasibility of this strategy to overcome the OXA resistance during colorectal cancer treatment. The (O + B)@Trp-NPs significantly inhibited the proliferation and decreased the drug resistance of resistant colorectal cancer cells. In vivo, (O + B)@Trp-NPs greatly suppressed the tumor growth in tumor-bearing mice, which is consistent with the in vitro data. This research offers a unique and promising chemotherapeutic treatment for colorectal cancer.

Metabolic Intervention Liposome Boosted Lung Cancer Radio-Immunotherapy via Hypoxia Amelioration and PD-L1 Restraint.

At present, radiotherapy (RT) still acquires limited success in clinical due to the lessened DNA damage under hypoxia and acquired immune tolerance owing to the amplified programmed death ligand-1 (PD-L1) expression. Incredibly, intracellular PD-L1 expression depression is proven to better sensitize RT by inhibiting DNA damage repair. However, the disability of the clinically used antibodies in disrupting the extracellular PD-L1function still limits the effectiveness of radio-immunotherapy. Therefore, better PD-L1 regulation strategies are still urgently needed to better sensitize radio-immunotherapy. Hence, for this purpose, TPP-LND is synthesized by linking mitochondrial-targeted triphenylphosphine cations (TPP+ ) to the antineoplastic agent lonidamine (LND), which significantly reduces the dose needed for LND to induce effective oxidative phosphorylation inhibition (2 vs 300 µM). Then, TPP-LND is wrapped with liposomes to form TPP-LND@Lip nanoparticles. By doing this, TPP-LND@Lip nanoparticles can sensitize RT by reversing the hypoxic microenvironment of tumors to generate more DNA damage and reducing the expression of PD-L1 via enhancing the adenosine 5'-monophosphate-activated protein kinase activation. As expected, these well-designed economical TPP-LND@Lip nanoparticles are more effective than conventional anti-PD-L1 antibodies to some extent.

Intra- and peri-tumoral MRI radiomics features for preoperative lymph node metastasis prediction in early-stage cervical cancer.

BACKGROUND: Noninvasive and accurate prediction of lymph node metastasis (LNM) is very important for patients with early-stage cervical cancer (ECC). Our study aimed to investigate the accuracy and sensitivity of radiomics models with features extracted from both intra- and peritumoral regions in magnetic resonance imaging (MRI) with T2 weighted imaging (T2WI) and diffusion weighted imaging (DWI) for predicting LNM. METHODS: A total of 247 ECC patients with confirmed lymph node status were enrolled retrospectively and randomly divided into training (n = 172) and testing sets (n = 75). Radiomics features were extracted from both intra- and peritumoral regions with different expansion dimensions (3, 5, and 7 mm) in T2WI and DWI. Radiomics signature and combined radiomics models were constructed with selected features. A nomogram was also constructed by combining radiomics model with clinical factors for predicting LNM. RESULTS: The area under curves (AUCs) of radiomics signature with features from tumors in T2WI and DWI were 0.841 vs. 0.791 and 0.820 vs. 0.771 in the training and testing sets, respectively. Combining radiomics features from tumors in the T2WI, DWI and peritumoral 3 mm expansion in T2WI achieved the best performance with an AUC of 0.868 and 0.846 in the training and testing sets, respectively. A nomogram combining age and maximum tumor diameter (MTD) with radiomics signature achieved a C-index of 0.884 in the prediction of LNM for ECC. CONCLUSIONS:  Radiomics features extracted from both intra- and peritumoral regions in T2WI and DWI are feasible and promising for the preoperative prediction of LNM for patients with ECC.