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Patients with non-calcified hamartoma were more susceptible to surgery or needle biopsy for the tough discrimination from lung adenocarcinoma. Radiomics have the ability to quantify the lesion features and potentially improve disease diagnosis. Thus, this study aimed to discriminate non-calcified hamartoma from adenocarcinoma by employing imaging quantification and machine learning.

Forty-two patients with non-calcified hamartoma and 49 patients with adenocarcinoma were retrospentation; Manual lesion segmentation, feature quantification (e.g., texture features), and artificial neural network were performed consecutively. Independent t-test was used to conduct the inter-group comparisons of those imaging features. Receiver operating characteristic curve was performed to investigate the discriminating efficacy.

Significantly higher contrast, cluster prominence, cluster shade, dissimilarity, energy, and entropy in non-calcified hamartoma were observed compared with lung adenocarcinoma. Texture-grey-level co-occurrence matrix showed a well discrimination between non-calcified hamartoma and adenocarcinoma as the detection sensitivity, specificity, accuracy, and the area under the curve were 87.22% ± 9.07%, 82.64% ± 8.07%, 85.11% ± 5.40%, and 0.942, respectively.

Quantifying imaging features is a potentially useful tool for clinical diagnosis. This study demonstrated that non-calcified hamartoma has a heterogeneous distribution of attenuations probably resulting from its complex organizations. Based on this property, imaging quantification could improve discrimination of non-calcified hamartoma from adenocarcinoma.

Quantifying imaging features is a potentially useful tool for clinical diagnosis. This study demonstrated that non-calcified hamartoma has a heterogeneous distribution of attenuations probably resulting from its complex organizations. Based on this property, imaging quantification could improve discrimination of non-calcified hamartoma from adenocarcinoma.Immunotherapy has revolutionized lung cancer treatment in the past decade. By reactivating the host's immune system, immunotherapy significantly prolongs survival in some advanced lung cancer patients. However, resistance to immunotherapy is frequent, which manifests as a lack of initial response or clinical benefit to therapy (primary resistance) or tumor progression after the initial period of response (acquired resistance). Overcoming immunotherapy resistance is challenging owing to the complex and dynamic interplay among malignant cells and the defense system. This review aims to discuss the mechanisms that drive immunotherapy resistance and the innovative strategies implemented to overcome it in lung cancer.The gut microbiota is reported to play an important role in carcinogenesis and the treatment of CRC. SW480 and SW620 colon cancer cells integrated with infrared fluorescent proteins were injected into the rectal submucosa of nude mice. In the subsequent 30 days, we observed tumor growth weekly using an in vivo imaging system. The bacterial solution was infused anally into the mice to perform bacterial transplant. Phosphate-buffered saline, Acinetobacter lwoffii, and Bifidobacterium longum solutions were infused individually. The 16S ribosomal DNA (rDNA) and polymerase chain reaction of murine feces were investigated to confirm the colonization of target bacteria. In the SW620 orthotopic xenograft rectal cancer model, 4 of 5 mice developed rectal cancer by 30 days after submucosal injection. In the SW480 orthotopic xenograft rectal cancer model, 2 of 6 mice developed rectal cancer by 30 days after submucosal injection. For the 16S rDNA analysis, the mice receiving the bacterial solution infusion demonstrated positive findings for A. lwoffii and B. longum. With the successful establishment of a mouse model of orthotopic rectal cancer and transplant of target bacteria, we can further explore the relationship between gut microbiota and CRC. The role of fecal microbiota transplant in the treatment and alleviation of adverse events of chemotherapy in CRC could be clarified in subsequent studies.ATP6V1s participate in the biological process of transporting hydrogen ions and are associated with various cancers in expression and clinicopathological features, while its role in kidney renal clear cell carcinoma is unknown. We aimed to demonstrate the relationship between ATP6V1s and kidney renal clear cell carcinoma. This study investigated the expression and roles of ATP6V1s in KIRC using Oncomine, The Cancer Genome Atlas, UALCAN, Human Protein Atlas, Clinical Proteomics Tumor Analysis Consortium, GeneMANIA, Tumor IMmune Estimation Resource, GEPIA databases. Low mRNA and protein expression of ATP6V1s members were found to be significantly associated with clinical cancer stages, nodal metastasis status, and patient's gender in KIRC patients. Besides, lower mRNA expression of ATP6V1A, ATP6V1B2, ATP6V1C1, ATP6V1C2, ATP6V1D, ATP6V1E1, ATP6V1E2, ATP6V1F, ATP6V1G1, and ATP6V1H have shorter OS. Taken together, these results indicated that ATP6V1s family members could be a potential target in the development of anti-KIRC therapeutics and an efficient marker of the prognostic value of KIRC.Meningiomas are the most common primary tumors of the central nervous system. Given the fact that the majority of meningiomas are benign, the preoperative risk stratification and treatment strategy decision-making highly rely on the conventional subjective radiologic evaluation. However, this traditional diagnostic and treatment modality may not be effective in patients with aggressive-growing tumors or symptomatic patients with potential risk of recurrence after surgical resection or radiotherapy, as this passive "wait and see" strategy could miss the optimal opportunity of intervention. Radiomics, a new rising discipline, translates high-dimensional image information into abundant mathematical data by multiple computational algorithms. It provides an objective and quantitative approach to interpret the imaging data, rather than the subjective and qualitative interpretation from relatively limited human visual observation. In fact, the enormous amount of information generated by radiomics analyses provides radiological to histopathological tumor information, which are visually imperceptible, and offers technological basis to its applications amid diagnosis, treatment, and prognosis. Here, we review the latest advancements of radiomics and its applications in the prediction of the pathological grade, pathological subtype, recurrence possibility, and differential diagnosis of meningiomas, and the potential and challenges in general clinical applications. In this review, we highlight the generalization of shared radiomic features among different studies and compare different performances of popular algorithms. At last, we discuss several possible aspects of challenges and future directions in the development of radiomic applications in meningiomas.Background Recent randomized clinical trials have examined the efficacy of different combinations of systemic and local treatment approaches for metastatic hormone-sensitive prostate cancer (mHSPC). We compared the efficacy of these combined regimens in order to identify the optimal therapy for specific patient subgroups. Methods The treatments were abiraterone (ABI), apalutamide (APA), docetaxel (DOC), enzalutamide (ENZ), and radiotherapy (RT) combined with androgen-deprivation therapy (ADT). Five electronic databases were searched up to May 7, 2020 for relevant trials. The risk of bias in the included trials was evaluated with the Cochrane tool. The hazard ratio (HR) with 95% confidence interval (CI) was determined for the included trials and indirect comparisons were performed using the R software. Results In total, 10 randomized, controlled trials with 11,194 patients were included in the meta-analysis. ADT + RT was superior to ADT monotherapy in terms of overall survival (HR = 0.96, 95% CI 0.85-1.1) and led to superior outcomes in mHSPC patients with low-volume disease. While all combined systemic regimens confer a survival advantage over ADT monotherapy, the optimal treatment approach for certain mHSPC patient subgroups remains to be determined.Background Uveal melanoma (UM) is the most common primary intraocular cancer in adults. Genomic studies have provided insights into molecular subgroups and oncogenic drivers of UM that may lead to novel therapeutic strategies. Methods Dataset TCGA-UVM, download from TCGA portal, were taken as the training cohort, and dataset GSE22138, obtained from GEO database, was set as the validation cohort. In training cohort, Kaplan-Meier analysis and univariate Cox regression model were applied to preliminary screen prognostic genes. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in the validation cohorts through Kaplan-Meier, Cox, and ROC analyses. In addition, the correlation between copy number aberrations and risk score was evaluated by Spearman test. GSEA and immune infiltrating analyses were conducted for understanding function annotation and the role of the signature in the tumor microenvironment. Results A ten-gene signature was built, and rsonalized prognosis prediction and new treatment insights.Medulloblastoma is the most common malignant brain tumor in children. In addition to sporadic cases, medulloblastoma may occur in association with cancer predisposition syndromes. This review aims to provide a complete description of inherited cancer syndromes associated with medulloblastoma. We examine their epidemiological, clinical, genetic, and diagnostic features and therapeutic approaches, including their correlation with medulloblastoma. Furthermore, according to the most recent molecular advances, we describe the association between the various molecular subgroups of medulloblastoma and each cancer predisposition syndrome. Knowledge of the aforementioned conditions can guide pediatric oncologists in performing adequate cancer surveillance. This will allow clinicians to promptly diagnose and treat medulloblastoma in syndromic children, forming a team with all specialists necessary for the correct management of the other various manifestations/symptoms related to the inherited cancer syndromes.Tumor-associated macrophages (TAMs) are major innate immune cells that constitute up to 50% of the cell mass of human tumors. TAMs are highly heterogeneous cells that originate from resident tissue-specific macrophages and from newly recruited monocytes. TAMs' variability strongly depends on cancer type, stage, and intratumor heterogeneity. Majority of TAMs are programmed by tumor microenvironment to support primary tumor growth and metastatic spread. However, TAMs can also restrict tumor growth and metastasis. In this review, we summarized the knowledge about the role of TAMs in tumor growth, metastasis and in the response to cancer therapy in patients with five aggressive types of cancer breast, colorectal, lung, ovarian, and prostate cancers that are frequently metastasize into distant organs resulting in high mortality of the patients. Two major TAM parameters are applied for the evaluation of TAM correlation with the cancer progression total amount of TAMs and specific phenotype of TAMs identified by functional biomarkers.