Mitopherogenesis, a form of mitochondria-specific ectocytosis, regulates sperm mitochondrial quantity and fertility.

Mitochondrial export into the extracellular space is emerging as a fundamental cellular process implicated in diverse physiological activities. Although a few studies have shed light on the process of discarding damaged mitochondria, how mitochondria are exported and the functions of mitochondrial release remain largely unclear. Here we describe mitopherogenesis, a formerly unknown process that specifically secretes mitochondria through a unique extracellular vesicle termed a 'mitopher'. We observed that during sperm development in male Caenorhabditis elegans, healthy mitochondria are exported out of the spermatids through mitopherogenesis and each of the generated mitophers harbours only one mitochondrion. In mitopherogenesis, the plasma membrane first forms mitochondrion-embedding outward buds, which then promptly bud off and thereby result in the generation of mitophers. Mechanistically, extracellular protease signalling in the testis triggers mitopher formation from spermatids, which is partially mediated by the tyrosine kinase SPE-8. Moreover, mitopherogenesis requires normal microfilament dynamics, whereas myosin VI antagonizes mitopher generation. Strikingly, our three-dimensional electron microscopy analyses indicate that mitochondrial quantity requires precise modulation during sperm development, which is critically mediated by mitopherogenesis. Inhibition of mitopherogenesis causes accumulation of mitochondria in sperm, which may lead to sperm motility and fertility defects. Our findings identify mitopherogenesis as a previously undescribed process for mitochondria-specific ectocytosis, which may represent a fundamental branch of mechanisms underlying mitochondrial quantity control to regulate cell functions during development.

Artificial intelligence in breast imaging: potentials and challenges.

Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, including neoadjuvant chemotherapy, surgery, postoperative chemotherapy, targeted therapy, endocrine therapy, and radiotherapy, are tailored for individual patients. Such personalized therapies have tremendously reduced the threat of breast cancer in females. Furthermore, early imaging screening plays an important role in reducing the treatment cycle and improving breast cancer prognosis. The recent innovative revolution in artificial intelligence (AI) has aided radiologists in the early and accurate diagnosis of breast cancer. In this review, we introduce the necessity of incorporating AI into breast imaging and the applications of AI in mammography, ultrasonography, magnetic resonance imaging, and positron emission tomography/computed tomography based on published articles since 1994. Moreover, the challenges of AI in breast imaging are discussed.

Differentiation between Phyllodes Tumors and Fibroadenomas through Breast Ultrasound: Deep-Learning Model Outperforms Ultrasound Physicians.

The preoperative differentiation of breast phyllodes tumors (PTs) from fibroadenomas (FAs) plays a critical role in identifying an appropriate surgical treatment. Although several imaging modalities are available, reliable differentiation between PT and FA remains a great challenge for radiologists in clinical work. Artificial intelligence (AI)-assisted diagnosis has shown promise in distinguishing PT from FA. However, a very small sample size was adopted in previous studies. In this work, we retrospectively enrolled 656 breast tumors (372 FAs and 284 PTs) with 1945 ultrasound images in total. Two experienced ultrasound physicians independently evaluated the ultrasound images. Meanwhile, three deep-learning models (i.e., ResNet, VGG, and GoogLeNet) were applied to classify FAs and PTs. The robustness of the models was evaluated by fivefold cross validation. The performance of each model was assessed by using the receiver operating characteristic (ROC) curve. The area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were also calculated. Among the three models, the ResNet model yielded the highest AUC value, of 0.91, with an accuracy value of 95.3%, a sensitivity value of 96.2%, and a specificity value of 94.7% in the testing data set. In contrast, the two physicians yielded an average AUC value of 0.69, an accuracy value of 70.7%, a sensitivity value of 54.4%, and a specificity value of 53.2%. Our findings indicate that the diagnostic performance of deep learning is better than that of physicians in the distinction of PTs from FAs. This further suggests that AI is a valuable tool for aiding clinical diagnosis, thereby advancing precision therapy.

Deep Learning-Based Recognition of Cervical Squamous Interepithelial Lesions.

Cervical squamous intraepithelial lesions (SILs) are precursor lesions of cervical cancer, and their accurate diagnosis enables patients to be treated before malignancy manifests. However, the identification of SILs is usually laborious and has low diagnostic consistency due to the high similarity of pathological SIL images. Although artificial intelligence (AI), especially deep learning algorithms, has drawn a lot of attention for its good performance in cervical cytology tasks, the use of AI for cervical histology is still in its early stages. The feature extraction, representation capabilities, and use of p16 immunohistochemistry (IHC) among existing models are inadequate. Therefore, in this study, we first designed a squamous epithelium segmentation algorithm and assigned the corresponding labels. Second, p16-positive area of IHC slides were extracted with Whole Image Net (WI-Net), followed by mapping the p16-positive area back to the H&E slides and generating a p16-positive mask for training. Finally, the p16-positive areas were inputted into Swin-B and ResNet-50 to classify the SILs. The dataset comprised 6171 patches from 111 patients; patches from 80% of the 90 patients were used for the training set. The accuracy of the Swin-B method for high-grade squamous intraepithelial lesion (HSIL) that we propose was 0.914 [0.889-0.928]. The ResNet-50 model for HSIL achieved an area under the receiver operating characteristic curve (AUC) of 0.935 [0.921-0.946] at the patch level, and the accuracy, sensitivity, and specificity were 0.845, 0.922, and 0.829, respectively. Therefore, our model can accurately identify HSIL, assisting the pathologist in solving actual diagnostic issues and even directing the follow-up treatment of patients.

An Ultrasound-based Prediction Model for Occult Contralateral Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: To investigate the occult contralateral papillary thyroid carcinoma (PTC)-associated ultrasound (US) and clinical characteristics and establish a US-based model for the prediction of occult contralateral carcinoma in adolescents and young adults (AYAs) who were diagnosed with unilateral thyroid carcinoma preoperatively. MATERIALS AND METHODS: From January 2015 to December 2020, patients who were diagnosed with unilateral thyroid carcinoma by preoperative US examination and underwent total thyroidectomy or thyroid lobectomy with more than 60 months of US follow-up at our hospital were retrospectively collected. Univariate and multivariate analyses were applied to identify the independent risk factors associated with occult contralateral PTC in AYAs, on which a prediction model was developed. The performance of the model was evaluated with accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve. RESULTS: Occult contralateral PTC was found in 91 of 365 (24.9%) PTC patients with a median age at diagnosis of 26 years (interquartile range, 24-29 years). The multivariate analysis indicated that the presence of contralateral benign nodule, intra-tumoral calcification, and intraglandular dissemination were significantly associated with occult contralateral PTC in AYAs. The prediction model, which incorporated all independent predictors, yielded an area under the receiver operating characteristic curve of .661 (95% CI: .602-.719). The accuracy, sensitivity and specificity were 67.9%, 54.9%, and 72.3%, respectively. CONCLUSION: The US-based prediction model proposed here exhibited a favorable performance for predicting occult contralateral PTC, which might be used to determine the appropriate extent of surgery for AYAs who had a preoperative diagnosis of unilateral thyroid carcinoma.

Retraction: A near-infrared laser and H2O2 activated bio-nanoreactor for enhanced photodynamic therapy of hypoxic tumors.

Retraction of 'A near-infrared laser and H2O2 activated bio-nanoreactor for enhanced photodynamic therapy of hypoxic tumors' by Liming Deng et al., Biomater. Sci., 2020, 8, 858-870, https://doi.org/10.1039/C9BM01126A.

Application of Deep Learning to Reduce the Rate of Malignancy Among BI-RADS 4A Breast Lesions Based on Ultrasonography.

The aim of the work described here was to develop an ultrasound (US) image-based deep learning model to reduce the rate of malignancy among breast lesions diagnosed as category 4A of the Breast Imaging-Reporting and Data System (BI-RADS) during the pre-operative US examination. A total of 479 breast lesions diagnosed as BI-RADS 4A in pre-operative US examination were enrolled. There were 362 benign lesions and 117 malignant lesions confirmed by postoperative pathology with a malignancy rate of 24.4%. US images were collected from the database server. They were then randomly divided into training and testing cohorts at a ratio of 4:1. To correctly classify malignant and benign tumors diagnosed as BI-RADS 4A in US, four deep learning models, including MobileNet, DenseNet121, Xception and Inception V3, were developed. The performance of deep learning models was compared using the area under the receiver operating characteristic curve (AUROC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Meanwhile, the robustness of the models was evaluated by five-fold cross-validation. Among the four models, the MobileNet model turned to be the optimal model with the best performance in classifying benign and malignant lesions among BI-RADS 4A breast lesions. The AUROC, accuracy, sensitivity, specificity, PPV and NPV of the optimal model in the testing cohort were 0.897, 0.913, 0.926, 0.899, 0.958 and 0.784, respectively. About 14.4% of patients were expected to be upgraded to BI-RADS 4B in US with the assistance of the MobileNet model. The deep learning model MobileNet can help to reduce the rate of malignancy among BI-RADS 4A breast lesions in pre-operative US examinations, which is valuable to clinicians in tailoring treatment for suspicious breast lesions identified on US.

Analysis of the Factors Related to Intracranial Infection after Brain Tumor Surgery.

In order to explore the factors related to intracranial infection after brain tumor surgery, a retrospective analysis is conducted in this study. According to the patients with intracranial infection after brain tumor surgery in our hospital from January 2020 to October 2020, clinical data are divided into different groups and some indicators are put into the multiple regression model for multivariate analysis. The factors related to intracranial infection after brain tumor surgery are analyzed, and the clinical effect of a detailed management plan based on the abovementioned risk factors to prevent intracranial infection in patients after brain tumor surgery is observed. Multiple regression models demonstrate that complicated underlying diseases, operation time, and intraoperative blood loss are independent risk factors for postoperative intracranial infection.

Survival outcome assessment for triple-negative breast cancer: a nomogram analysis based on integrated clinicopathological, sonographic, and mammographic characteristics.

OBJECTIVE: This study aimed to incorporate clinicopathological, sonographic, and mammographic characteristics to construct and validate a nomogram model for predicting disease-free survival (DFS) in patients with triple-negative breast cancer (TNBC). METHODS: Patients diagnosed with TNBC at our institution between 2011 and 2015 were retrospectively evaluated. A nomogram model was generated based on clinicopathological, sonographic, and mammographic variables that were associated with 1-, 3-, and 5-year DFS determined by multivariate logistic regression analysis in the training set. The nomogram model was validated according to the concordance index (C-index) and calibration curves in the validation set. RESULTS: A total of 636 TNBC patients were enrolled and divided into training cohort (n = 446) and validation cohort (n = 190). Clinical factors including tumor size > 2 cm, axillary dissection, presence of LVI, and sonographic features such as angular/spiculated margins, posterior acoustic shadows, and presence of suspicious lymph nodes on preoperative US showed a tendency towards worse DFS. The multivariate analysis showed that no adjuvant chemotherapy (HR = 6.7, 95% CI: 2.6, 17.5, p < 0.0005), higher axillary tumor burden (HR = 2.7, 95% CI: 1.0, 7.1, p = 0.045), and ≥ 3 malignant features on ultrasound (HR = 2.4, CI: 1.1, 5.0, p = 0.021) were identified as independent prognostic factors associated with poorer DFS outcomes. In the nomogram, the C-index was 0.693 for the training cohort and 0.694 for the validation cohort. The calibration plots also exhibited excellent consistency between the nomogram-predicted and actual survival probabilities in both the training and validation cohorts. CONCLUSIONS: Clinical variables and sonographic features were correlated with the prognosis of TNBCs. The nomogram model based on three variables including no adjuvant chemotherapy, higher axillary tumor load, and more malignant sonographic features showed good predictive performance for poor survival outcomes of TNBC. KEY POINTS: • The absence of adjuvant chemotherapy, heavy axillary tumor load, and malignant-like sonographic features can predict DFS in patients with TNBC. • Mammographic features of TNBC could not predict the survival outcomes of patients with TNBC. • The nomogram integrating clinicopathological and sonographic characteristics is a reliable predictive model for the prognostic outcome of TNBC.

BRAF V600E mutation and the Bethesda System for Reporting Thyroid Cytopathology of fine-needle aspiration biopsy for distinguishing benign from malignant thyroid nodules.

BACKGROUND: The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) predicts the risk of malignancy for the different categories of the ultrasound-guided fine-needle aspiration biopsy (FNAB). The objective of this study is to investigate the efficiencies of the v-raf murine sarcoma viral oncogene homolog B1 (BRAF) V600E mutation test and the TBSRTC categories in distinguishing between benign and malignant thyroid nodules. METHODS: In this study, 362 ultrasound-guided fine-needle aspiration (FNA) samples from 344 patients aged from 17 to 76 years old were retrospectively reviewed. The patients were classified into six groups (I-VI) according to the TBSRTC system. The amplification refractory mutation system-polymerase chain reaction (ARMS-PCR) was used to evaluate the BRAF V600E mutation level in total 362 samples. Among of the 344 patients, 128 patients (131 thyroid nodules) who underwent surgeries were followed by histopathological examination. The predictive values of the BRAF V600E mutation test and TBSRTC categories were evaluated in these 131 thyroid nodules. RESULTS: The median ages of the patients in the TBSRTC IV-VI group were smaller than those in the TBSRTC I-III groups. The proportion of nodules over 1 cm was larger than it in the TBSRTC IV group compared to the other groups. Significant differences in BRAF V600E mutation were observed (P < .001) among these six groups. The sensitivity (89.57%) for the detection of malignant thyroid nodules, negative predictive value (NPV; 45.45%) for the detection of benign nodules, and accuracy (86.26%) for distinguishing between benign and malignant thyroid nodules increased by combining the BRAF V600E mutation test and TBSRTC system when compared with the BRAF V600E mutation test and TBSRTC system respectively. The BRAF V600E mutation test alone demonstrated the increased positive predictive value (PPV; 98.91%) and specificity (93.75%) for the detection of malignant thyroid nodules compared to the TBSRTC method (alone or in combination with the BRAF V600E method). CONCLUSION: In summary, significant differences in age, nodule diameter, and BRAF V600E mutation were noted among the six categories of the TBSRTC system. The combination of the BRAF V600E mutation test and TBSRTC system demonstrated increases in the NPV, sensitivity, and accuracy, while the BRAF V600E method proved superiority to the TBSRTC system with regard to the PPV and specificity.

Identifying GNG4 might play an important role in colorectal cancer TMB.

BACKGROUND: Colorectal carcinoma (CRC) is one of the most leading cause of cancer death all over the world. The tumor immune microenvironment is illustrated to be necessary for the progress of CRC. And the accumulating evidence indicated that tumor mutation burden (TMB) is effective in differentiating responding population of immune checkpoint inhibitor (ICI) therapies in various cancers. In this study, we aimed to evaluated the potential relationship between TMB and the recurrence risk of CRC. METHODS: The transcriptomic and clinical data of CRC patients were collected from The Cancer Genome Atlas (TCGA) database (n= 382). Then the genomic analysis of tumor mutation burden and tumor purity were conducted by a computational method based on transcriptomic data. RESULTS: Firstly, we accessed the distribution of TMB and preferences at the gene and mutation level using somatic mutation data from TCGA data about CRC. We identified that high TMB predicted better prognosis of CRC patients. Secondly, the differentially expressed genes (DEGs) between the low TMB and high TMB group was clarified. Then the protein-protein interaction (PPI) analysis was performed, and the results confirmed ten hub genes among the DEGs. Utilizing the GEPIA web-tool, we discovered that GNG4 was up-regulated in tumor tissues, and GNG4 was related to the overall survival (OS) and tumor free survival (TFS) of CRC patients. Therefore, we considered GNG4 was essential for the tumor immune microenvironment of CRC. Furthermore, we also accessed the protein level of GNG4 in CRC and liver metastases from CRC. CONCLUSIONS: In this study, GNG4 was demonstrated to be the key element of the CRC TMB, which will be essential for the ICI therapy of CRC. Besides, GNG4 was up-regulated in CRC and liver metastases from CRC tissues. Thus, we thought that GNG4 might play an important role in colorectal cancer TMB and induce its metastasis in liver.

Low-intensity focused ultrasound-augmented Cascade chemodynamic therapy via boosting ROS generation.

Fenton reaction-mediated chemodynamic therapy (CDT), which destroys tumor cells by converting H2O2 into cytotoxic hydroxyl radical (OH) and singlet oxygen (1O2) species, is a promising field. However, Fenton-based CDT is severely impaired by the inappropriate tumor environment associated with undesirable intratumoral acidity and insufficient H2O2 supply in tumor microenvironment (TME). Therefore, a strategy that can address these concerns is highly desired and beneficial for boosting such treatment. Herein, a magnetic nanoreactor system (denoted as poly (lactic-co-glycolic acid) (PLGA)-superparamagnetic iron oxide (SPIO)&vitamin C (Vc) was constructed with Vc in the core, SPIO on the shell, and PLGA as the building carrier. Upon low-intensity focused ultrasound irradiation, on-demand Vc release can locally decompose into H2O2, which can generate a favorable condition for facilitating SPIO-based Fenton-like reaction and result in continuous O2 and OH/1O2 generation. The TME modulation-augmented CDT by this nanoreactor based on the reinforced Fenton reaction tremendously improved the antitumor outcomes, especially under increased accumulation contributed by magnetic targeting combined with enhanced permeability and retention effect. Moreover, the explosive production of oxygen can be monitored by real-time photoacoustic imaging, offering a noninvasive means to forecast the treatment efficacy. Therefore, this established microenvironment modulation strategy for augmenting Fenton reaction-based CDT paves a new avenue to realize highly efficient cancer theranostics.

Perfluorocarbon Nanodroplets with Deep Tumor Penetration and Controlled Drug Delivery for Ultrasound/Fluorescence Imaging Guided Breast Cancer Therapy.

Some impediments, including insufficient drug release, poor tumor penetration, and lack of real-time imaging guidance, still limited the therapeutic efficiency of nanotechnology-based drug delivery systems. Here, light-responsive perfluoropentane (PFP) based nanodroplets as doxorubicin (DOX) nanocarriers that could achieve deep tumor delivery under multimodal imaging guidance were developed. Triggered by laser irradiation, the liquid PFP with low boiling point could go through small-to-big size change and liquid-to-gas phase transformation. At the same time, the accompanied cavitation effect led to not only the disruption of dense extracellular matrix for deep penetration but also the disruption of endo-/lysosome for nucleus delivery of released DOX. Furthermore, different from many imaging approaches which were always "on", only upon laser stimulation could the nanodroplets act as ultrasound/fluorescence probes due to the echogenic PFP bubbles and the recovered fluorescence of DOX itself after released from nanodroplets, which was highly desirable to indicate the DOX state in real time. Therefore, such PFP nanodroplets with phase/size tunable properties enable site-specific drug delivery efficiently and exhibit their potent in cancer theranostics.

A self-activating nanovesicle with oxygen-depleting capability for efficient hypoxia-responsive chemo-thermo cancer therapy.

Hypoxia-activated prodrugs (HAPs) promise to mitigate side effects of conventional chemotherapy and to enable precise medication treatment. One challenge facing HAPs-based chemotherapy is prodrug failure in normoxic tumor region. However, current strategies to enhance tumor hypoxia rely on delivery of oxygen-consuming agents and external stimulation, which can impede the optimal application of HAPs. Herein, a novel self-activating nanovesicle, TH-302@BR-Chitosan NPs, is constructed by assembling bilirubin-chitosan conjugate (named as BR-Chitosan) with a HAP, TH-302. It is interesting to find that the BR-Chitosan shows the inherent oxygen-depleting performance, especially in the presence of over expressed H2O2 in tumor area, during which the BR-Chitosan can facily transform into biliverdin-chitosan (BV-Chitosan) and subsequently result in the disassembly of nanovesicles to release and activate the prodrug. Thus, this in situ strengthening hypoxia level of tumor can greatly promote the chemotherapy efficacy of HAPs. Moreover, as the oxidation derivatives of BR-Chitosan, BV-Chitosan exhibits intense absorbance at the range from long wavelength of visible region to near-infrared region, which can be acted as an effective photothermal agent for photothermal therapy (PTT). This biodegradable and self-activating nanovesicle with concise formulation demonstrates greatly enhanced synergistic therapeutic outcome in the activatable chemo-thermo combined therapy, showing much promising in future clinical transformation.

A New Model Incorporating Axillary Ultrasound After Neoadjuvant Chemotherapy to Predict Non-Sentinel Lymph Node Metastasis in Invasive Breast Cancer.

PURPOSE: Few models with good discriminative power have been introduced to predict the risk of non-sentinel lymph node (non-SLN) metastasis in breast cancer after neoadjuvant chemotherapy (NAC). We aimed to develop a new and simple model for predicting the probability of non-SLN metastasis in breast cancer and facilitate the selection of patients who could avoid unnecessary axillary lymph node dissection following NAC. PATIENTS AND METHODS: A total of 298 patients diagnosed with invasive breast cancer, who underwent SLN biopsy after completing NAC and subsequently breast surgery, were included and classified into the training set (n=228) and testing set (n=70). Univariate and multivariate analyses were used to select factors that could be determined prior to breast surgery and significantly correlated with non-SLN metastasis in the training set. A logistic regression model was developed based on these factors and validated in the testing set. RESULTS: Nodal status before NAC, post-NAC axillary ultrasound status, SLN number, and SLN metastasis number were independent predictors of non-SLN metastases in breast cancer after NAC. A predictive model based on these factors yielded an area under the curve of 0.838 (95% confidence interval: 0.774-0.902, p< 0.001) in the training set. When applied to the testing set, this model yielded an area under the curve of 0.808 (95% confidence interval: 0.609-1.000, p= 0.003). CONCLUSION: A new and simple model, which incorporated factors that could be determined prior to breast surgery, was developed to predict non-SLN metastasis in invasive breast cancer following NAC. Although this model performed excellently in internal validation, it requires external validation before it can be widely utilized in the clinical setting.

A near-infrared laser and H2O2 activated bio-nanoreactor for enhanced photodynamic therapy of hypoxic tumors.

Hypoxic resistance, photosensitizer toxicity, and target deficiency are major challenges strongly inhibiting the efficacy of clinical photodynamic therapy (PDT) in tumor treatment. To overcome these challenges, we synthesized IR780 and catalase co-loaded liposomes to form a tumor-targeted bio-nanoreactor (LIP-IR-CAT). The efficient strategy can solve the physicochemical problems including strong hydrophobicity, poor light stability, poor tolerance, and high toxicity in vivo of IR780 as a photosensitizer and promote the clinical application of IR780. Taking advantage of the high catalytic efficiency of catalase when it meets hydrogen peroxide (H2O2), continuous oxygen can be generated due to the abnormally elevated level of H2O2 within the tumor, thus remarkably promoting tumor oxygenation. With the conjunction of photosensitivity and specific mitochondria-targeting ability of IR780, the intratumoral reactive oxygen species (ROS) are strongly enhanced, and adenosine triphosphate (ATP) is reduced under near-infrared (NIR) laser irradiation. Following a single-dose intravenous injection of LIP-IR-CAT, tumor hypoxia can be seriously attenuated, at the same time creating an opportunity to enhance the efficacy of PDT on the tumor. Our in vivo data show that the nanoreactor LIP-IR-CAT, in combination with just two short time NIR laser irradiation sessions, can effectively inhibit the growth of solid tumors without systemic toxicity.

Furin substrate as a novel cell-penetrating peptide: combining a delivery vector and an inducer of cargo release.

We have developed a new cell-penetrating peptide (CPP) using a repeated protease (furin) substrate. This CPP can not only deliver cargo into cells but can also be cleaved by furin in cells and release the cargo. Cell-impermeable antitumor pro-apoptotic peptide KLAKLAKKLAKLAK (KLA) and chemotherapy drug chlorambucil were chosen to be delivered by the CPP into live cancer cells and their cytotoxicity was greatly enhanced for in vivo cancer treatment.

Photothermal therapy mediated by phase-transformation nanoparticles facilitates delivery of anti-PD1 antibody and synergizes with antitumor immunotherapy for melanoma.

Melanoma remains one of the most challenging malignant tumor related deaths worldwide and alternative approaches to efficiently treat melanoma are eagerly needed. Anti-PD1 antibody (aPD1) immunotherapy is the most significant and impactful therapy for melanoma by immune checkpoint inhibition and T cell stimulation to mediate tumor killing. But the clinical remission rate of aPD1 immunotherapy is limited in melanoma. Here we show a potent combination of aPD1 and photothermal therapy (PTT) by effective delivery of a multifunctional phase-transformation nanocarrier to melanoma tumor. We successfully synthesized multifunctional nanoparticles (NPs) encapsulated with aPD1, iron oxide and perfluoropentane (PFP) in lactic-co-glycolic acid (PLGA) shell modified with poly ethylene glycol (PEG) and Gly-Arg-Gly-Asp-Ser (GRGDS) peptides (GOP@aPD1). In vitro, GOP@aPD1 NPs were characterized for particle size and drug-loading efficiency. The NPs were also tested for photothermal property, optical droplet vaporization (ODV) capacity and the ability of aPD1 release profile. In vivo, GOP@aPD1 NPs were systemically administered to melanoma-bearing mice demonstrated no toxicity and accumulation at tumor site. When mediated with PTT, this synergistic treatment achieved enhanced antitumor efficacy, due to combination of the effective aPD1 release and increased CD8+ T cell infiltration in tumor site. In conclusion, GOP@aPD1 NPs combined with PTT could potentiate the efficacy of aPD1 not only by tumor-targeted delivery of aPD1 but also by activating the immune system in the tumor microenvironment, which is a highly effective approach to treat melanoma.

Mitochondria-Targeted Artificial "Nano-RBCs" for Amplified Synergistic Cancer Phototherapy by a Single NIR Irradiation.

Phototherapy has emerged as a novel therapeutic modality for cancer treatment, but its low therapeutic efficacy severely hinders further extensive clinical translation and application. This study reports amplifying the phototherapeutic efficacy by constructing a near-infrared (NIR)-responsive multifunctional nanoplatform for synergistic cancer phototherapy by a single NIR irradiation, which can concurrently achieve mitochondria-targeting phototherapy, synergistic photothermal therapy (PTT)/photodynamic therapy (PDT), self-sufficient oxygen-augmented PDT, and multiple-imaging guidance/monitoring. Perfluorooctyl bromide based nanoliposomes are constructed for oxygen delivery into tumors, performing the functions of red blood cells (RBCs) for oxygen delivery ("Nano-RBC" nanosystem), which can alleviate the tumor hypoxia and enhance the PDT efficacy. The mitochondria-targeting performance for enhanced and synergistic PDT/PTT is demonstrated as assisted by nanoliposomes. In particular, these "Nano-RBCs" can also act as the contrast agents for concurrent computed tomography, photoacoustic, and fluorescence multiple imaging, providing the potential imaging capability for phototherapeutic guidance and monitoring. This provides a novel strategy to achieve high therapeutic efficacy of phototherapy by the rational design of multifunctional nanoplatforms with the unique performances of mitochondria targeting, synergistic PDT/PTT by a single NIR irradiation (808 nm), self-sufficient oxygen-augmented PDT, and multiple-imaging guidance/monitoring.

Bioinspired Multifunctional Melanin-Based Nanoliposome for Photoacoustic/Magnetic Resonance Imaging-Guided Efficient Photothermal Ablation of Cancer.

Background: The construction of theranostic nanosystems with concurrently high biosafety and therapeutic performance is a challenge but has great significance for the clinical translation of nanomedicine for combating cancer. Methods: Bio-inspired melanin-based nanoliposomes (Lip-Mel) as theranostic agents were constructed for simultaneous photoacoustic (PA) imaging- and T1-weighted magnetic resonance (MR) imaging-guided photothermal ablation of tumors, which was demonstrated both in vitro and in vivo. The high biosafety of Lip-Mel was also systematically evaluated. Results: The achieved Lip-Mel nanoliposomes demonstrated their imaging capability for both PA and T1-weighted MR imaging (r1 = 0.25 mM-1·s-1) both in vitro and in vivo, providing the potential for therapeutic guidance and monitoring. Importantly, the desirable photothermal-conversion efficiency of the as-prepared Lip-Mel achieved complete eradication of tumors in breast cancer-bearing mice, exhibiting remarkable photothermal-based therapeutic performance. In particular, the efficient encapsulation of melanin into the PEGylated liposome mitigated the potential toxicity of melanin and improved the photothermal performance of the loaded melanin. Systematic in vivo biosafety evaluations demonstrated the high biocompatibility of Lip-Mel at a high dose of 100 mg/kg. Conclusion: In this work, we reported a bioinspired strategy where melanin, a natural product in the human body, is encapsulated into PEGylated nanoliposomes for efficient theranostics with high biocompatibility. This work provides a new strategy for creating desirable theranostic agents with concurrent high biocompatibility and satisfactory theranostic performance through the use of materials that totally originate from biosystems.