In Situ Reprogramming of Immune Cells Using Synthetic Nanomaterials.

In the past decade, adoptive cell therapy with chimeric antigen receptor-T (CAR-T) cells has revolutionized cancer treatment. However, the complexity and high costs involved in manufacturing current adoptive cell therapy greatly inhibit its widespread availability and access. To address this, in situ cell therapy, which directly reprograms immune cells inside the body, has recently been developed as a promising alternative. Here, an overview of the recent progress in the development of synthetic nanomaterials is provided to deliver plasmid DNA or mRNA for in situ reprogramming of T cells and macrophages, focusing especially on in situ CAR therapies. Also, the main challenges for in situ immune cell reprogramming are discussed and some approaches to overcome these barriers to fulfill the clinical applications are proposed.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells.

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

A dual deep neural network for auto-delineation in cervical cancer radiotherapy with clinical validation.

BACKGROUND: Artificial intelligence (AI) algorithms are capable of automatically detecting contouring boundaries in medical images. However, the algorithms impact on clinical practice of cervical cancer are unclear. We aimed to develop an AI-assisted system for automatic contouring of the clinical target volume (CTV) and organs-at-risk (OARs) in cervical cancer radiotherapy and conduct clinical-based observations. METHODS: We first retrospectively collected data of 203 patients with cervical cancer from West China Hospital. The proposed method named as SegNet was developed and trained with different data groups. Quantitative metrics and clinical-based grading were used to evaluate differences between several groups of automatic contours. Then, 20 additional cases were conducted to compare the workload and quality of AI-assisted contours with manual delineation from scratch. RESULTS: For automatic CTVs, the dice similarity coefficient (DSC) values of the SegNet trained with incorporating multi-group data achieved 0.85 ± 0.02, which was statistically better than the DSC values of SegNet independently trained with the SegNet(A) (0.82 ± 0.04), SegNet(B) (0.82 ± 0.03) or SegNet(C) (0.81 ± 0.04). Moreover, the DSC values of the SegNet and UNet, respectively, 0.85 and 0.82 for the CTV (P < 0.001), 0.93 and 0.92 for the bladder (P = 0.44), 0.84 and 0.81 for the rectum (P = 0.02), 0.89 and 0.84 for the bowel bag (P < 0.001), 0.93 and 0.92 for the right femoral head (P = 0.17), and 0.92 and 0.91 for the left femoral head (P = 0.25). The clinical-based grading also showed that SegNet trained with multi-group data obtained better performance of 352/360 relative to it trained with the SegNet(A) (334/360), SegNet(B) (333/360) or SegNet(C) (320/360). The manual revision time for automatic CTVs (OARs not yet include) was 9.54 ± 2.42 min relative to fully manual delineation with 30.95 ± 15.24 min. CONCLUSION: The proposed SegNet can improve the performance at automatic delineation for cervical cancer radiotherapy by incorporating multi-group data. It is clinically applicable that the AI-assisted system can shorten manual delineation time at no expense of quality.

Radiomics Based on Nomogram Predict Pelvic Lymphnode Metastasis in Early-Stage Cervical Cancer.

The accurate prediction of the status of PLNM preoperatively plays a key role in treatment strategy decisions in early-stage cervical cancer. The aim of this study was to develop and validate a radiomics-based nomogram for the preoperative prediction of pelvic lymph node metastatic status in early-stage cervical cancer. One hundred fifty patients were enrolled in this study. Radiomics features were extracted from T2-weighted MRI imaging (T2WI). Based on the selected features, a support vector machine (SVM) algorithm was used to build the radiomics signature. The radiomics-based nomogram was developed incorporating radiomics signature and clinical risk factors. In the training cohort (AUC = 0.925, accuracy = 81.6%, sensitivity = 70.3%, and specificity = 92.0%) and the testing cohort (AUC = 0.839, accuracy = 74.2%, sensitivity = 65.7%, and specificity = 82.8%), clinical models that combine stromal invasion depth, FIGO stage, and MTD perform poorly. The combined model had the highest AUC in the training cohort (AUC = 0.988, accuracy = 95.9%, sensitivity = 92.0%, and specificity = 100.0%) and the testing cohort (AUC = 0.922, accuracy = 87.1%, sensitivity = 85.7%, and specificity = 88.6%) when compared to the radiomics and clinical models. The study may provide valuable guidance for clinical physicians regarding the treatment strategies for early-stage cervical cancer patients.

Postoperative radiotherapy for thymus salivary gland carcinoma: A case report.

BACKGROUND: Salivary gland cancer is a rare disease in which cancer cells form in the tissues of the salivary glands. It mostly occurs in the glands that have secretion functions, such as the parotid gland, sublingual gland and submandibular gland. This is very rare when it occurs in other nonsecreting glands. Here, we report one case of salivary gland carcinoma occurring in the thymus and discuss related diagnoses and treatment progress. CASE SUMMARY: One 33-year-old middle-aged man presented with a thymus mass without any clinical symptoms when he underwent regular physical examination. Later, the patient was admitted to the hospital for further examination. Computed tomography (CT) showed that there was a mass of 3 cm × 2.8 cm × 1.5 cm in the thymus area. The patient had no symptom of discomfort or tumor- related medical history before. After completing the preoperative examinations, it was confirmed that the patient had indications for surgery. The surgeon performed a transthoracoscope "thymectomy + pleural mucostomy" for him. During the operation, the tumor tissue was quickly frozen, and the symptomatic section showed a malignant tumor. The final pathological result suggested thymus salivary gland carcinoma- mucoepidermoid carcinoma (MEC). In the second month after surgery, we performed local area radiotherapy for the patient, with a total radiation dose of 50.4 Gy/28Fx. After 12 mo of surgery, the patient underwent positron emission tomography-CT examination, which indicated that there was no sign of tumor recurrence or metastasis. After 16 mo of operation, CT scan re-examination showed that there was no sign of tumor recurrence or metastasis. As of the time of publication, the patient was followed up for one and a half years. He had no sign of tumor recurrence and continued to survive. CONCLUSION: The incidence of MEC in the thymus is low, and its diagnosis needs to be combined with clinical features and imaging methods. Histopathological analysis plays a key role in the diagnosis of the disease. Patients with early-stage disease have a good prognosis and long survival period. In contrast, patients with advanced-stage disease have a poor prognosis and short survival period. Combining radiotherapy and chemotherapy in inoperable patients may prolong survival.

Evaluating the impact of possible interobserver variability in CBCT-based soft-tissue matching using TCP/NTCP models for prostate cancer radiotherapy.

BACKGROUND: Prostate alignment is subject to interobserver variability in cone-beam CT (CBCT)-based soft-tissue matching. This study aims to analyze the impact of possible interobserver variability in CBCT-based soft-tissue matching for prostate cancer radiotherapy. METHODS: Retrospective data, consisting of 156 CBCT images from twelve prostate cancer patients with elective nodal irradiation were analyzed in this study. To simulate possible interobserver variability, couch shifts of 2 mm relative to the resulting patient position of prostate alignment were assumed as potential patient positions (27 possibilities). For each CBCT, the doses of the potential patient positions were re-calculated using deformable image registration-based synthetic CT. The impact of the simulated interobserver variability was evaluated using tumor control probabilities (TCPs) and normal tissue complication probabilities (NTCPs). RESULTS: No significant differences in TCPs were found between prostate alignment and potential patient positions (0.944 ± 0.003 vs 0.945 ± 0.003, P = 0.117). The average NTCPs of the rectum ranged from 5.16 to 7.29 (%) among the potential patient positions and were highly influenced by the couch shift in the anterior-posterior direction. In contrast, the average NTCPs of the bladder ranged from 0.75 to 1.12 (%) among the potential patient positions and were relatively negligible. CONCLUSIONS: The NTCPs of the rectum, rather than the TCPs of the target, were highly influenced by the interobserver variability in CBCT-based soft-tissue matching. This study provides a theoretical explanation for daily CBCT-based image guidance and the prostate-rectum interface matching procedure. TRIAL REGISTRATION: Not applicable.

Automatic delineation of the clinical target volume and organs at risk by deep learning for rectal cancer postoperative radiotherapy.

BACKGROUND AND PURPOSE: Manual delineation of clinical target volumes (CTVs) and organs at risk (OARs) is time-consuming, and automatic contouring tools lack clinical validation. We aimed to construct and validate the use of convolutional neural networks (CNNs) to set better contouring standards for rectal cancer radiotherapy. MATERIALS AND METHODS: We retrospectively collected and evaluated computed tomography (CT) scans of 199 rectal cancer patients treated at our hospital from February 2018 to April 2019. Two CNNs-DeepLabv3+ for extracting high-level semantic information and ResUNet for extracting low-level visual features-were used for the CTV and small intestine contouring, and bladder and femoral head contouring, respectively. Contouring quality was compared using the paired t test. Five-point objective grading was performed independently by two experienced radiation oncologists and verified by a third. The CNN manual correction time was recorded. RESULTS: CTVs calculated using DeepLabv3+ (CTVDeepLabv3+) had significant quantitative parameter advantages over CTVResUNet (volumetric Dice coefficient, 0.88 vs 0.87, P = 0.0005; surface Dice coefficient, 0.79 vs 0.78, P = 0.008). Among 315 graded cases, DeepLabv3+ obtained the highest scores with 284 cases, consistent with the objective criteria, whereas CTVResUNet had the minimum mean manual correction time (7.29 min). DeepLabv3+ performed better than ResUNet for small intestine contouring and ResUNet performed better for bladder and femoral head contouring. The manual correction time for OARs was <4 min for both models. CONCLUSION: CNNs at various feature resolution levels well delineate rectal cancer CTVs and OARs, displaying high quality and requiring shorter computation and manual correction time.

Is stereotactic radiotherapy equivalent to metastasectomy in patients with pulmonary oligometastases?

A best evidence topic in thoracic surgery was written according to a structured protocol. The question addressed was whether stereotactic body radiotherapy (SBRT) was equivalent to metastasectomy in patients with pulmonary oligometastases arising from solid tumours. Altogether, 1612 papers were found using the reported search, of which 5 cohort studies derived from 4 patient populations represented the best evidence to answer the clinical question. The authors, journal, date and country of publication, patient group studied, study type, relevant outcomes and results of these papers are tabulated. All 5 studies demonstrated no significant difference in post-treatment overall survival, disease-free survival or local control between SBRT and metastasectomy for pulmonary oligometastases. One of the 5 studies showed a significantly decreased rate of severe complications among the patients treated with SBRT. The other papers reported higher rates of complications in the SBRT groups, invariably due to radiation, but with uncertain clinical significance. The evidence strength of these findings may be largely attenuated due to the small sample size, heterogeneity of SBRT protocols and incomparable follow-up periods between the 2 treatment groups. The selection criteria for the choice of treatment were not stated. We conclude, based on limited evidence, that SBRT has equivalent outcomes to metastasectomy in the treatment of patients with pulmonary oligometastases.

Biodegradable polymeric micelles coencapsulating paclitaxel and honokiol: a strategy for breast cancer therapy in vitro and in vivo.

The combination of chemotherapy drugs attracts more attention in clinical cancer trials. However, the poor water solubility of chemotherapeutic drugs restricts their anticancer application. In order to improve antitumor efficiency and reduce side effects of free drugs, we prepared paclitaxel (PTX) and honokiol (HK) combination methoxy poly(ethylene glycol)-poly(caprolactone) micelles (P-H/M) by solid dispersion method against breast cancer. The particle size of P-H/M was 28.7±2.5 nm, and transmission electron microscope image confirmed that P-H/M were spherical in shape with small particle size. After being encapsulated in micelles, the release of PTX or HK showed a sustained behavior in vitro. In addition, both the cytotoxicity and the cellular uptake of P-H/M were increased in 4T1 cells, and P-H/M induced more apoptosis than PTX-loaded micelles or HK-loaded micelles, as analyzed by flow cytometry assay and Western blot. Furthermore, the antitumor effect of P-H/M was significantly improved compared with PTX-loaded micelles or HK-loaded micelles in vivo. P-H/M were more effective in inhibiting tumor proliferation, inducing tumor apoptosis, and decreasing the density of microvasculature. Moreover, bioimaging analysis showed that drug-loaded polymeric micelles could accumulate more in tumor tissues compared with the free drug. Our results suggested that P-H/M may have potential applications in breast cancer therapy.

Biodegradable and injectable in situ cross-linking chitosan-hyaluronic acid based hydrogels for postoperative adhesion prevention.

Postsurgical peritoneal adhesions are very common and serious complication after surgery. Biodegradable and injectable hydrogels derived from natural polysaccharides are ideal biomaterials for prevention of postoperative adhesion. In this work, we report a class of injectable, biodegradable, and non-toxic hydrogel derived from N, O-carboxymethyl chitosan (NOCC) and aldehyde hyaluronic acid (A-HA), without requirement of any chemical linkers or radiant light sources. NOCC was prepared by introducing carboxymethyl groups to the N-position and the O-position of chitosan, and A-HA was prepared using periodate oxidation method. The gelation is attributed to the Schiff base between the amino groups of NOCC and aldehyde groups in A-HA, and the hydrogel precursors cross-linked to form a flexible hydrogel. NOCC, A-HA, and NOCC/A-HA hydrogel extract exhibited very low cytotoxicity and hemolysis, and the acute toxicity tests showed that the hydrogel was non-toxic. Besides, the highly porous three-dimensional hydrogel can supported the growth and proliferation of the cells encapsulated in the hydrogels, but was not favorable for the attachment of fibroblasts to the surface, suggesting that the NOCC/A-HA hydrogel can be developed for adhesion prevention. The hydrogel was susceptible to the lysozyme and can be degraded within 2 weeks in vivo. Furthermore, we employed a rat model of sidewall defect-cecum abrasion to investigate the efficacy of NOCC/A-HA hydrogel in preventing post-operative peritoneal adhesions. A significant reduction of peritoneal adhesion formation was found in the NOCC/A-HA-treated group, compared with commercial hyaluronic acid (HA) hydrogel group and normal saline group. In addition, the potential anti-adhesion mechanism of NOCC/A-HA hydrogel was discussed, which may attribute to the combination of barrier function and bioactivity of NOCC and A-HA.

In vitro and in vivo safety evaluation of biodegradable self-assembled monomethyl poly (ethylene glycol)-poly (ε-caprolactone)-poly (trimethylene carbonate) micelles.

Safety evaluation of self-assembled polymeric micelles is important for biomedical involvement in drug delivery systems in the future. In this study, biodegradable monomethyl poly (ethylene glycol)-poly (ε-caprolactone)-poly (trimethylene carbonate) [MPEG-P(CL-co-TMC)] copolymer was synthesized and characterized by Fourier transform infrared spectroscopy, nuclear magnetic resonance analysis, and gel permeation chromatography. MPEG-P(CL-co-TMC) micelles were prepared by self-assembly without any organic solvent. The present study was conducted to assess the safety of blank MPEG-P(CL-co-TMC) micelles both in vitro and in vivo. Particle size (30.09 ± 0.06 nm) and zeta potential (0.067 ± 0.027 mV) of obtained micelles were determined by Malvern laser particle size analyzer. The results of in vitro toxicity evaluation implied that the prepared micelles did not cause hemolysis or severely cell toxicity. Meanwhile, we did not observe any toxic response or histopathological changes in the study of in vivo acute toxicity evaluation and histopathological study of MPEG-P(CL-co-TMC) micelles. In conclusion, the maximal tolerance dose of MPEG-P(CL-co-TMC) micelles (100 mg/mL) by intravenous injection was supposed to be greater than 10 g/kg body weight. Therefore, it might have potential applications in biomedical field.