Tumor Cell Morphology Research Articles

Cytologic features of gastric-type endocervical adenocarcinoma: Three cases report and literature review.

Cervical gastric-type adenocarcinoma shows gastric differentiation, and the tumor cell morphology appears benign and unrelated to human papillomavirus, which makes cervical gastric-type adenocarcinoma highly susceptible to misdiagnosis as normal glandular epithelium in cytologic diagnosis. We present 3 cases of gastric-type adenocarcinoma, with the first being a 57-year-old female with abnormal uterine bleeding and fluid drainage. The second patient was a 63-year-old female, and the third was a 59-year-old female with irregular vaginal bleeding after menopause. The 3 patients were diagnosed with cervical gastric-type adenocarcinoma by combining their history, clinical data, cytopathology, histopathology, and immunohistochemistry. Patient 1 underwent total hysterectomy and adnexectomy, but refused radiotherapy and chemotherapy. Patient 2 received a chemotherapeutic regimen, and patient 3 was treated with traditional Chinese medicine. Patient 1 was followed-up for 9 months and is currently in good general condition, while patients 2 and 3 were not followed-up. The "drunken honeycomb" cell arrangement is diagnostically important in liquid-based cytology, especially when three-dimensional spheroids are present, and may be a characteristic cytological finding of well-differentiated cervical gastric-type adenocarcinoma.

Experimental Study on Biomimetic Curcumin-Mediated Sonodynamic Therapy of Melanoma

To study the role of curcumin-mediated sonodynamic therapy in the treatment of malignant melanoma, and to provide a new strategy for the treatment of malignant melanoma. The ultrasonic sound and vibration method was applied to coat curcumin with mouse melanoma cell membrane, thereby forming biomimetic curcumin. The morphology of biomimetic curcumin was observed by transmission electron microscope. Flow cytometry was used to analyze the effect of biomimetic curcumin in terms of in vitro targeting, apoptosis, and intracellular reactive oxygen species (ROS) production. The in vivo experiment was divided into control group, US group, turmeric group, imitation turmeric group, and imitation turmeric+US group, with 3 mice in each group. The in vivo safety of biomimetic curcumin was evaluated by HE staining. In addition, HE, CD31, Ki67, and TUNEL stainings were performed to evaluate the in vivo anti-melanoma therapeutic effect of ultrasound combined with biomimetic curcumin. The biomimetic curcumin had a generally uniform morphology and possessed a core-shell structure. Flow cytometry analysis performed with FlowJo showed that the biomimetic curcumin could be effectively taken up by melanoma cells. The apoptosis rate was (10.30±0.61)% in the control group, (10.41±3.13)% in the ultrasound group, (24.97±1.38)% in the curcumin group, (31.39±3.84)% in the biomimetic curcumin group, and (40.89±0.79)% in the biomimetic curcumin and ultrasound combination group. The apoptosis rate in the biomimetic curcumin and ultrasound combination group was higher than those in the other groups (P<0.05). The results of ROS flow cytometry showed that, compared with the control group, the ultrasound group demonstrated almost no increase in the fluorescence intensity, while the other groups showed an increase in the fluorescence intensity to varying degrees. There was no significant difference in the fluorescence intensity between the biomimetic curcumin group ([1.10±0.38]%) and the curcumin group ([0.73±0.26]%) (P>0.05). The fluorescence intensity of the biomimetic curcumin and ultrasound combination group ([3.35±0.04]%) was higher than those of the other groups (P<0.05). HE staining showed no obvious abnormalities in the morphology of heart, liver, spleen, lung, and kidney tissues in any of the treatment groups. HE staining showed the most significant changes in cell morphology in the biomimetic curcumin and ultrasound combination group, followed by the biomimetic curcumin group and the curcumin group. No obvious abnormalities in tumor cell morphology were observed in the ultrasound group. According to the respective results of CD31 staining, Ki67 staining, and TUNEL staining, the biomimetic curcumin and ultrasound combination group had the largest brown area, the highest number of red fluorescence, and the highest number of green fluorescence, followed by the biomimetic curcumin group and the curcumin group. The biomimetic curcumin displays uniform morphology, a core-shell structure, and good targeting properties. When it is used in combination with ultrasound, biomimetic curcumin demonstrates a good anti-tumor therapeutic effect both in vivo and in vitro.

A novel computational pathology approach for identifying gene signatures prognostic of disease-free survival for papillary thyroid carcinomas

IntroductionPapillary thyroid carcinoma (PTC) is the most prevalent form of thyroid cancer, with the classical and follicular variants representing most cases. Despite generally favorable prognoses, approximately 10% of patients experience recurrence post-surgery and radioactive iodine therapy. Attempts to stratify risk of recurrence have relied on gene expression-based prognostic and predictive signatures with a focus on mutations of well-known driver genes, while hallmarks of tumor morphology have been ignored. ObjectivesWe introduce a new computational pathology approach to develop prognostic gene signatures for PTC that is informed by quantitative features of tumor and immune cell morphology. MethodsWe quantified nuclear and immune-related features of tumor morphology to develop a pathomic signature, which was then used to inform an RNA-expression signature model provides a notable advancement in risk stratification compared to both standalone and pathology-informed gene-expression signatures. ResultsThere was a 17.8% improvement in the C-index (from 0.605 to 0.783) for 123 cPTCs and 15% (from 0.576 to 0.726) for 38 fvPTCs compared to the standalone gene-expression signature. Hazard ratios also improved for cPTCs from 0.89 (0.67,0.99) to 4.43 (3.65,6.68) and fvPTC from 0.98 (0.76,1.32) to 2.28 (1.87,3.64). We validated the image-based risk model on an independent cohort of 32 cPTCs with hazard ratio 1.8 (1.534,2.167).

Effect of Selol on Tumor Morphology and Biochemical Parameters Associated with Oxidative Stress in a Prostate Tumor-Bearing Mice Model.

Prostate cancer is the leading cause of cancer death in men. Some studies suggest that selenium Se (+4) may help prevent prostate cancer. Certain forms of Se (+4), such as Selol, have shown anticancer activity with demonstrated pro-oxidative effects, which can lead to cellular damage and cell death, making them potential candidates for cancer therapy. Our recent study in healthy mice found that Selol changes the oxidative-antioxidative status in blood and tissue. However, there are no data on the effect of Selol in mice with tumors, considering that the tumor itself influences this balance. This research investigated the impact of Selol on tumor morphology and oxidative-antioxidative status in blood and tumors, which may be crucial for the formulation's effectiveness. Our study was conducted on healthy and tumor-bearing animal models, which were either administered Selol or not. We determined antioxidant enzyme activities (Se-GPx, GPx, GST, and TrxR) spectrophotometrically in blood and the tumor. Furthermore, we measured plasma prostate-specific antigen (PSA) levels, plasma and tumor malondialdehyde (MDA) concentration as a biomarker of oxidative stress, selenium (Se) concentrations and the tumor ORAC value. Additionally, we assessed the impact of Selol on tumor morphology and the expression of p53, BCL2, and Ki-67. The results indicate that treatment with Selol influences the morphology of tumor cells, indicating a potential role in inducing cell death through necrosis. Long-term supplementation with Selol increased antioxidant enzyme activity in healthy animals and triggered oxidative stress in cancer cells, activating their antioxidant defense mechanisms. This research pathway shows promise in understanding the anticancer effects of Selol. Selol appears to increase the breakdown of cancer cells more effectively in small tumors than in larger ones. In advanced tumors, it may accelerate tumor growth if used as monotherapy. Therefore, further studies are necessary to evaluate its efficacy either in combination therapy or for the prevention of recurrence.

Clinicopathological features of metastatic melanoma in effusion cytology of serosal cavity

Objective: To investigate the clinical, cytomorphology, immunocytochemical and molecular features of metastatic melanoma in serosal cavity effusion. Methods: Cytological specimens of 14 patients with melanoma in the chest and abdomen were collected from 2017 to 2023, at the Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. SOX10, S-100 protein, PRAME, BRAF V600E, HMB45, and Melan A were detected by immunocytochemical methods. Fourteen cases were tested for routine antibody combinations, including Claudin4, HEG1, Calretinin, CD68, etc. Four of the patients had biopsy or surgical samples of metastatic solid lesions of primary sites, and further next-generation sequencing (NGS) or amplification refractory mutation system (ARMS)-PCR molecular test was performed. In addition, 30 cases of serosal effusion samples were collected as control groups (10 cases of benign mesothelial cell reactive hyperplasia, 10 cases of mesothelioma, and 10 cases of metastatic lung adenocarcinoma). Results: Among the 14 cases of melanoma, there were 7 males and 7 females, with ages ranging from 35 to 86 years, and an average age of 57 years, there 10 cases aged ≥50 years. The tumor cells in the serosal effusion varied in morphology and degree of atypia. SOX10 was positive in all 14 cases (14/14), S-100 protein was positive in 10 cases (10/14), PRAME was positive in 12 cases (12/14), BRAF V600E was positive in 10 cases (10/14), HMB45 was positive in 12 cases (12/14), and Melan A was positive in 13 cases (13/14). In 4 patients with histological correlation, the cytological and histological expression of SOX10, BRAF V600E, and PRAME was positive in all 4 cases (4/4); S-100 protein was positive in 2 cases (2/4); and HMB45 and Melan A were positive in 3 cases (3/4). Using NGS or ARMS-PCR, missense mutations of BRAF V600E were detected in all 4 patients; TERT promoter mutations was detected in 1 case; and CDKN2A terminating mutations and MSI1 deletion mutations were detected in the other case. SOX10, S-100, HMB45, Melan A, PRAME and BRAF V600E were all negative in 30 control samples of serosal cavity effusion. Conclusion: By observing the morphology of tumor cells, immunocytochemical test of several combination markers, especially the expression of SOX10, BRAF V600E and PRAME, can help to improve the positive diagnosis rate of melanoma in serous cavity effusion.

Breast Tumor Cell Survival and Morphology in a Brain-like Extracellular Matrix Depends on Matrix Composition and Mechanical Properties.

Triple-negative breast cancer (TNBC) is the most invasive type of breast cancer with high risk of brain metastasis. To better understand interactions between breast tumors with the brain extracellular matrix (ECM), a 3D cell culture model is implemented using a thiolated hyaluronic acid (HA-SH) based hydrogel. The latter is used as HA represents a major component of brain ECM. Melt-electrowritten (MEW) scaffolds of box- and triangular-shaped polycaprolactone (PCL) micro-fibers for hydrogel reinforcement are utilized. Two different molecular weight HA-SH materials (230 and 420kDa) are used with elastic moduli of 148 ± 34Pa (soft) and 1274 ± 440Pa (stiff). Both hydrogels demonstrate similar porosities. The different molecular weight of HA-SH, however, significantly changes mechanical properties, e.g., stiffness, nonlinearity, and hysteresis. The breast tumor cell line MDA-MB-231 forms mainly multicellular aggregates in both HA-SH hydrogels but sustains high viability (75%). Supplementation of HA-SH hydrogels with ECM components does not affect gene expression but improves cell viability and impacts cellular distribution and morphology. The presence of other brain cell types further support numerous cell-cell interactions with tumor cells. In summary, the present 3D cell culture model represents a novel tool establishing a disease cell culture model in a systematic way.

Pathological Changes Following Neoadjuvant Endocrine Therapy (NAET): A Multicentre Study of 391 Breast Cancers.

Oestrogen receptor (ER)-positive breast cancer (BC) is generally well responsive to endocrine therapy. Neoadjuvant endocrine therapy (NAET) is increasingly being used for downstaging ER-positive tumours. This study aims to analyse the effect of NAET on a well-characterised cohort of ER-positive BC with particular emphasis on receptor expression. This is a retrospective United Kingdom (UK) multicentre study of 391 patients who received NAET between October 2012 and October 2020. Detailed analyses of the paired pre- and post-NAET morphological changes and hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression were performed. The median duration of NAET was 86 days, with median survival and overall survival rates of 380 days and 93.4%, respectively. A total of 90.3% of cases achieved a pathological partial response, with a significantly higher rate of response in the HER2-low cancers. Following NAET, BC displayed some pathological changes involving the tumour stroma including central scarring and an increase in tumour infiltrating lymphocytes (TILs) and tumour cell morphology. Significant changes associated with the duration of NAET were observed in tumour grade (30.6% of cases), with downgrading identified in 19.3% of tumours (p < 0.001). The conversion of ER status from positive to low or negative was insignificant. The conversion of progesterone receptor (PR) and HER2 status to negative status was observed in 31.3% and 38.1% of cases, respectively (p < 0.001). HER2-low breast cancer decreased from 63% to 37% following NAET in the paired samples. Significant morphological and biomarker changes involving PR and HER2 expression occurred following NAET. The findings support biomarker testing on pre-treatment core biopsies and post-treatment residual carcinoma.

Reciprocal Interactions of Human Monocytes and Cancer Cells in Co-Cultures In Vitro.

The tumor microenvironment (TME) includes immune and stromal cells and noncellular extracellular matrix (ECM) components. Tumor-associated macrophages (TAMs) are the most important immune cells in TME and are crucial for carcinomas' progression. The purpose was to analyze direct and indirect interactions in co-culture of tumor cells with monocytes/macrophages and, additionally, to indicate which interactions are more important for cancer development. Cytokines, reactive oxygen species, nitric oxide level, tumor cell cycle and changes in tumor cell morphology after human tumor cells (Hep-2 and RK33 cell lines) with human monocyte/macrophage (THP-1 cell line) interactions were tested. Morphology and cytoskeleton organization of tumor cells did not change after co-culture with macrophages. In co-culture of tumor cells with human monocyte, changes in the percentage of tumor cells in cell cycle phases was observed. No significant changes in reactive oxygen species (ROS) were found in the co-culture as compared to the tumor cell mono-culture. Monocytes produced about three times higher ROS than tumor cells. In co-cultures, a lower nitric oxide (NOx) level was found as compared to the sum of the production by both mono-cultures. Co-culture conditions limited the production of cytokines (IL-4, IL-10 and IL-13) as compared to the sum of their level in mono-cultures. In conclusion, macrophages influence tumor cell growth and functions. Mutual (direct and paracrine) interactions between tumor cells and macrophages changed cytokine production and tumor cell cycle profile. The data obtained may allow us to initially indicate which kind of interactions may have a greater impact on cancer development processes.

Acute promyelocytic leukemia presenting with basophilia: diagnostic features and clinical observation

Acute promyelocytic leukemia (APL) is a blood tumor characterized by aggressive clinical progression with characteristic clinical and laboratory signs (typical tumor cell morphology, severe hemorrhagic syndrome, hemorrhages with hematoma formation, excessive fibrinolysis, disseminated intravascular coagulation syndrome) but modern approaches to therapy potentially make this disease fully curable. APL is considered one of the most studied subtypes of acute leukemia and is characterized by abnormal proliferation of promyelocytes in the bone marrow. The morphologic picture of APL is quite diverse, but an increased basophil count represents a rare manifestation that requires further study and understanding of its significance. Currently, there are limited scientific data on the clinical course and response to standard therapy in patients with APL presenting with basophilia.

Assessment of silver nanoparticles' antitumor effects: Insights into cell number, viability, and morphology of glioblastoma and prostate cancer cells

Silver nanoparticles (AgNPs) hold promise for cancer therapy. This study aimed to evaluate their impact on tumor and non-tumor cell number, viability, and morphology. Antitumor activity was tested on U-87MG (glioblastoma) and DU-145 (prostate cancer) cell lines. Treatment with AgNPs notably reached a reduction of U-87MG and DU-145 cell growth by 89.30% and 79.74%, respectively, resulting in slower growth rates. AgNPs induced DNA damage, evidenced by reduced nuclear area and DNA content via fluorescent image-based analyses. Conversely, HFF-1 non-tumor cells displayed no significant changes post-AgNPs exposure. Viability assays revealed substantial reductions in U-87MG and DU-145 cells (79% and 63% in MTT assays, 30% and 52.2% in high-content analyses), while HFF-1 cells exhibited lower sensitivity. Tumor cells had notably lower IC50 values than non-tumor cells, indicating selective susceptibility. Transmission electron microscopy (TEM) showed morphological changes post-AgNPs administration, including increased vacuoles, myelin figures, membrane ghosts, cellular extravasation, and membrane projections. The findings suggest the potential of AgNPs against glioblastoma and prostate cancer, necessitating further exploration across other cancer cell lines.

Machine Learning and Deep Learning Approach for Medical Image Analysis Summary Generator

Colorectal cancer, which is frequent, recognized tumours in both genders around the globe. As per the report generated by WHO in 2018, colon cancer placed in the third position, whereas 1.80 million individuals are affected. Precisely, it is the succeeding leading cancer, which is the second most common cause of cancer in females, and the third for males. The loss of control over the integrity of epidermal cells in bowel or malignancy can be the cause of colorectal cancer. An effective way to recognize colon cancer at an early stage and substantial treatment can reduce the ensuing death rates to a great extent. To perform Screening of Morphology of Malignant Tumor Cells in the colon, a Gastroenterologist may refer to cancer diagnosis tests for pathological images. In any Histology method, the process takes a significant duration of time due to infinite numbers of glands in the gastrointestinal system, which may lead to irreconcilable outcomes. By diagnosing through computer algorithms, can give practical and contributory results. Hence, accurate gland segmentation is one crucial prerequisite stage to get reliable and informative morphological image data. In recent times, the scholars applied machine learning algorithms to pathological image analysis for the diagnosis of cancer disease. We propose that features extracted from the diagnostic tests, given as input to a machine learning architecture used along with semantic segmentation algorithm, provide results that are accurate than the existing image segmentation algorithms. This work is the extensive review of machine learning architectures used for semantic segmentation on the histological images of the colon.In our project we will be using the following algorithms such as Adaboost as existing and Convolution Neural Network (CNN) as proposed and its accuracy is been calculated and well compared to other algorithms. It is found that CNN performs less than other algorithms

Abstract 4913: Morphological feature discrepancies in wild-type vs. BRCA1/BRCA2 mutated high-grade serous ovarian cancer

Abstract Introduction: The understanding of morphological heterogeneity at the cellular level in High-Grade Serous Ovarian Cancer (HGSOC), particularly in relation to BRCA1 and BRCA2 mutations, is still an ongoing area of research. This study aims to elucidate the morphological features that distinguish wild-type (WT) tumors from those with BRCA1/BRCA2 mutations using deep learning models. Methods: A total of 300 H&amp;E stained HGSOC slides were collected in a patient-wise manner and tumor areas were annotated by an expert pathologist. We used a convolutional neural network model with spatial attention pre-trained on pathological images to extract features from slides, and the features were clustered into 96 groups. Subsequently, a nuclei segmentation model was employed for precise cell segmentation, followed by measurement of cellular features including cell shape (area, eccentricity) and cell texture (dissimilarity, correlation). The assessment of cell texture evaluates the variation and uniformity in gray-level intensity across the cell. We performed independent t-tests on samples of 100 patches from each cluster, comparing cells of selected patches from the top-N clusters representing the highest proportion of each label. Results: H&amp;E slides (n=300) include 69 (23%) BRCA1 mutants and 50 (16.7%) BRCA2 mutants. In Table1, negative t-statistics suggest that WT carcinoma cancer cells exhibit lower values for the measured features compared to BRCA mutants, whereas positive values denote higher values in WT. BRCA1 and BRCA2 mutant carcinoma cancer cells showed significantly larger areas and higher eccentricity than WT carcinoma cancer cells in all top-N clusters settings (N=3, 5, 10, 30). Furthermore, WT carcinoma cancer cells showed higher dissimilarity and reduced correlation compared to BRCA1 mutant carcinoma cells in four settings. Conclusions: Our observations in BRCA-mutated HGSOC cells enrich our understanding of tumor cell morphology with BRCA mutations. Table 1. Comparison of cell features between WT and BRCA mutants cell feature comparison top-3 clusters (t-statistics, p-value) top-5 clusters (t-statistics, p-value) top-10 clusters (t-statistics, p-value) top-30 clusters (t-statistics, p-value) area WT vs BRCA1 -37.41, &amp;lt;0.001 -50.2, &amp;lt;0.001 -37.53, &amp;lt;0.001 -85.95, &amp;lt;0.001 WT vs BRCA2 -42.14, &amp;lt;0.001 -50.61, &amp;lt;0.001 -16.57, &amp;lt;0.001 -51.98, &amp;lt;0.001 eccentricity WT vs BRCA1 -24.40, &amp;lt;0.001 -34.14, &amp;lt;0.001 -38.02, &amp;lt;0.001 -37.40, &amp;lt;0.001 WT vs BRCA2 -26.77, &amp;lt;0.001 -30.46, &amp;lt;0.001 -29.47, &amp;lt;0.001 -47.64, &amp;lt;0.001 dissimilarity WT vs BRCA1 55.17, &amp;lt;0.001 52.73, &amp;lt;0.001 103.57, &amp;lt;0.001 166.78, &amp;lt;0.001 WT vs BRCA2 -38.15, &amp;lt;0.001 -24.75, &amp;lt;0.001 0.2, &amp;lt;0.001 107.73, &amp;lt;0.001 correlation WT vs BRCA1 1.94, &amp;lt;0.001 -2.46, &amp;lt;0.001 -50.24, &amp;lt;0.001 -65.96, &amp;lt;0.001 WT vs BRCA2 87.62, &amp;lt;0.001 90.83, &amp;lt;0.001 52.6, &amp;lt;0.001 -48.90, &amp;lt;0.001 Citation Format: JaeHeon Lee, Hyunil Kim, Yongeun Lee, Yoon-La Choi, Kyungsoo Jung, Tae-Yeong Kwak, Sun Woo Kim, Hyeyoon Chang. Morphological feature discrepancies in wild-type vs. BRCA1/BRCA2 mutated high-grade serous ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4913.

Flow Cytometry in Mature T- and NK-cell Neoplasms: A Retrospective Descriptive Study from a Tertiary Care Cancer Centre in Kerala, India

Introduction: Mature T- and NK-cell Neoplasms (MTNKN) constitute around 12% of all non-Hodgkin lymphomas. They have a variable clinical course, ranging from indolent to highly aggressive tumours. Flow cytometry immunophenotyping is crucial for the diagnosis, staging, and classification of MTNKN. Aim: To determine the frequency, morphologic, and immunophenotypic profile of various subtypes of MTNKN diagnosed by flow cytometry. Materials and Methods: This was a retrospective descriptive study conducted at the Department of Pathology, Regional Cancer Centre, Thiruvananthapuram, Kerala, India. All cases of MTNKN diagnosed by flow cytometry in peripheral blood, bone marrow aspirates, or body fluids from January 1, 2010 to June 30, 2020 (10.5 years duration) at the cancer centre were studied. The morphology of tumour cells and immunophenotype by flow cytometry were analysed. Clinical parameters (lymphadenopathy, hepatosplenomegaly, skin lesions, effusions, B symptoms) and follow-up details, including Progression-free Survival (PFS) and Overall Survival (OS), were also noted. Descriptive statistics for continuous variables and frequencies and percentages for categorical variables were obtained. The Kaplan-Meier method for survival plots was used. Results: Mature T- and NK-cell neoplasms constituted 83 cases. The median age of patients was 56 years. The majority of patients were males (n=49). Adult T-cell Leukaemia/Lymphoma (ATLL) (n=50) constituted the most common subtype, followed by Mycosis fungoides/Sezary syndrome (MF/SS) (n=14), T-cell Large Granular Lymphocytic Leukaemia (T-LGLL) (n=7), T-cell Prolymphocytic Leukaemia (T-PLL) (n=4), Aggressive NK-cell Leukaemia (ANKL) (n=3), Hepatosplenic T-cell Lymphoma (HSTL) (n=3), and Anaplastic Large Cell Lymphoma (ALCL) (n=2). OS and PFS at three years were 22.3% and 16.6%, respectively. Conclusion: Mature T- and NK-cell neoplasms presenting as leukaemia is rare. ATLL was the most common subtype of MTNKN. Flower cells, Sezary cells, and prolymphocytes are useful morphological clues for diagnosis. Immunophenotyping by flow cytometry, along with clinicopathologic correlation, is crucial for the diagnosis and subclassification of MTNKN. All subtypes except T-LGLL show inferior PFS and OS.

Photo-Driven InSitu Solidification of Whole Cells through Inhibition of Trogocytosis for Immunotherapy.

Achieving antitumor immunotherapy based on hybridization of multiple types of inactivated cells has attracted a lot of attention. However, the hybridized cells of disordered structure could result in the shedding of antigens and their transfer to immune cells, which suppresses tumor immunity through trogocytosis. Here, we report a strategy for in situ solidification of tumor whole cell by biomineralization for sustained stimulation of antitumor immunity. The near-infrared light was used to accelerate the breaking of Au=P bonds in auranofin, and the exposed Au atoms biomineralize at the secondary structure (β-corner) of the protein to form Au nanocrystals with insitu protein coronas in tumor cells. Au nanocrystals are anchored to the tumor cells through protein coronas, which fixes the morphology and antigens of whole tumor cells, rendering them physiologically inactive. Interestingly, this solidified tumor cell prevents immune cells from undergoing trogocytosis, which inhibits proximal and distal tumor growth. Thus, this study presents the strategy of solidified cells and its potential application in tumor immunotherapy.

Development of a Machine Learning Model to Evaluate Changes during Radiotherapy in Cervical Cancer Tumor Cells.

Radiotherapy is considered the standard treatment for advanced cervical cancer. It is known that irradiation changes the morphology of tumor cells during the treatment, though its clinical significance is unknown. Recently, the usefulness of machine learning using medical images has been reported, as also as pathological images. The purpose of this study is to create a classification model for cervical tumor biopsy treated with radiotherapy, visualized on whole slide images using machine learning, in an attempt to explore the clinical significance of morphology changes during radiotherapy. Cervical cancer patients who underwent radical irradiation with both pre- and mid-treatment biopsy from April 1, 2013, to December 1, 2020, were retrospectively analyzed. Tumor biopsies were Hematoxylin and eosin stained and digitized to whole slide images (WSIs). WSI s were divided into tiles of 224 × 224 pixels and converted into feature vectors using a pre-trained convolutional neural network (densenet121). A training and test dataset were divided 1:1 on a patient basis, and the model was trained to classify "pre-treatment" and "mid-treatment", and its accuracy was evaluated. The probability obtained from the classification model was defined as the radiation change index (RCI), and its color map was projected on the WSI for visualization. Survival analysis was performed to examine the clinical significance of the RCI values. A total of eighty-four patients were analyzed, and the median observation period was 3.2 years. 184 WSIs were obtained, and 2203407 tiles were generated. The classification model was trained using 2500 tiles for each "pre-treatment" and "mid-treatment". The accuracy of the classification model was 70.8 %, with an AUC of 0.77 for the ROC curve. The probability obtained from the classification model was defined as RCI, with 0 being "pre-treatment" and 1 being "mid-treatment", and the mean RCI of "pre-treatment" and "mid-treatment" were 0.38 and 0.61, respectively. When the RCIs were visualized with a color map, the areas considered to be "pre-treatment" were consistent with a viable tumor component, and the areas considered to be "mid-treatment" were consistent with fibrosis supposed to cause by irradiation. To evaluate the clinical significance of RCI, we divide the clinical cohort into two groups with a threshold mean RCI of 0.4 in the pre-treatment biopsy. The disease-free survival was 91 months and 47 months in the RCI<0.4 and RCI≥0.4 groups, respectively. We created a model to classify tissues before and during radiotherapy and successfully visualized it on slide images. The low RCI group before treatment had a better prognosis than the high RCI group, suggesting that the tumor morphologic features obtained by machine learning may be useful for prognosis prediction. Further studies are planned to develop a model that can accurately predict prognosis.

Participance in time of the different stages of medical help is the necessary factor for the success of realization of practical medical activity (with the description of own observations of ovarian cancer clinical case and its using at classes in State l

Ovarian cancer is a second by the rate gynecological malignant disorder in developed countries and has one of the worst prognosis and mortality rate. In comparison to other gynecological malignant disorders (cervical, uterіne, vaginal, vulvar), patients with ovarian cancer suffer from the biggest mortality rate. Because of the absence of the early detection methods patients most common are identified at developed stage (III or IV by FIGO), thus with limited possibilities for treatment. Epithelial ovarian cancer is the most common type of ovarian cancer with 90 % of all reported cases. This cancer is divided in five histotypes: highgrade serous, low-grade serous, mucinous, endometrioid and clear-cell. Histotypes are different in morphology of tumor cells, clinical manifestations intensity, systemic effect and response to treatment. General clinical hardship of ovarian cancer detection on early stages due to the lack of definite semiotic picture produces the big role of primary care specialists for the systemic evaluation of the female health state with consideration of the “small signs” of the disorder, which progress constantly and with time will be transformed to obvious morphological oncomanifestations. Article contains the results of own clinical observations of the features of ovarian cancer. We consider this description as demonstrative for the analysis at practical classes in State language and in English.

Paclitaxel nanocrystals carrying miR-200c inhibit prostate cancer in rats by regulating forkhead box protein O (FOXO) activity

Prostate cancer is a malignant tumor in the male reproductive organs. Its incidence is increasing year by year, and therefore, this study investigated regulatory effect of paclitaxel nanocrystals on forkhead box protein O (FOXO) activity in rats with prostate cancer. Firstly, paclitaxel nanocrystals carrying miRNA-200c were synthesized. Nine rats in the model control group were used to establish a tumor-bearing model. The rats were intervened with miRNA-200c in the miRNA-200c group on the basis of model group, and treated with paclitaxel nanosuspension in the paclitaxel nano group. The rats were intervened with paclitaxel nano and miRNA-200c in the paclitaxel nano+miRNA-200c group. Tumor inhibition rates were measured, and tumor cell morphology was assessed by hematoxylin-eosin (HE) staining, while cell behaviors were detected by CCK-8, 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide (MTT), AnnexinV-Fluorescein isothiocyanate (FITC), and Transwell methods, which were used to analyze miRNA-200c and FOXO levels. Paclitaxel nanocrystals carrying miR-200c (PN-miR-200c) significantly slowed down the growth rate of prostate cancer. In addition, it also reduced the viability, proliferation and invasion of rat PC3 cells, and increased cell apoptosis. On the other hand, PN-miR-200c further increased FoxO mRNA expression by activating FoxO pathway. The bioinformatics software RegRNA 2.0 predicted that, the specific target gene that may be regulated by miR-200c is FoxO, which confirmed that, the miR-200c has a targeting relationship with FoxO. PN-miR-200c can activate FOXO pathway, up-regulate FoxO, reduce the biological behaviors of rat PC3 cells, increase apoptosis, and ameliorate histopathological damage, providing new ideas for clinical treatment of prostate cancer.

Cordycepin, a metabolite of Cordyceps militaris, inhibits xenograft tumor growth of tongue squamous cell carcinoma in nude mice

To evaluate the inhibitory effect of cordycepin on oral cancer xenograft in nude mice and explore the underlying mechanisms. Sixteen BALB/c mice bearing subcutaneous human tongue squamous cell carcinoma (TSCC) TCA-8113 cell xenografts were randomized into model group and cordycepin treatment group for daily treatment with saline and cordycepin for 4 weeks. After the treatment, the tumor xenografts were dissected and weighed to assess the tumor inhibition rate. Histological changes in the heart, spleen, liver, kidney, and lung of the mice were evaluated with HE staining, and tumor cell apoptosis was examined using TUNEL staining; The expressions of Bax, Bcl-2, GRP78, CHOP, and caspase-12 in the xenografts were detected using RT-qPCR and Western blotting. Cordycepin treatment resulted in a tumor inhibition rate of 56.09% in the nude mouse models, induced obvious changes in tumor cell morphology and significantly enhanced apoptotic death of the tumor cells without causing pathological changes in the vital organs. Cordycepin treatment also significantly reduced Bcl-2 expression (P < 0.05) and increased Bax, GRP78, CHOP, and caspase-12 expressions at both the RNA and protein levels in the tumor tissues. Cordycepin treatment can induce apoptotic death of TCA-8113 cell xenografts in nude mice via the endogenous mitochondrial pathway and endoplasmic reticulum stress pathways.

Scars Run Deep: Problematic Morphology and Immunoprofile of Scars in Renal Oncocytomas.

In some instances, the central scar of renal oncocytoma can demonstrate entrapped cells with unusual morphology and aberrant immunoprofile creating potential diagnostic confusion. Herein, 100 renal oncocytomas containing scars with embedded epithelial cells were identified from 6 institutions, including nephrectomies (64% partial, 36% radical) of similar laterality (left = 51%) and sex distribution (male = 56%), with patient ages ranging from 38 to 86 years (mean = 64.3years) and tumor sizes ranging from 2 to 16 cm (mean = 5.3 cm). Immunohistochemistry was performed on all tumors for KRT7, KIT, vimentin, and CA9 with staining intensity and extensity separately analyzed. Of 4 architectural patterns of cells within the scar, 60% showed tubular pattern. Of 4 cytologies within the scar, flat/elongated (49%) and cuboidal cells (40%) predominated. Within the scar, 62% showed eosinophilic cytoplasm, with 38% showing both cleared and eosinophilic cytoplasm; notably, 79% showed higher grade nuclei than typical oncocytes. A subset of scar cells showed mucinous-like basophilic secretions (19%). Compared to background renal oncocytoma, tumor cells within the scar were more often positive for vimentin, KRT7, and CA9 and more frequently negativity for KIT. Specifically, of the notable "aberrant" immunoprofiles, 79% showed KRT7 positivity/KIT negativity/vimentin positive, 84% showed vimentin positivity/CA9 positivity, and 78% showed KIT negativity/vimentin positivity/CA9 positivity. While encountering scars within renal oncocytomas is not uncommon, what is not well appreciated is the unique morphology and immunohistochemistry of tumor cells within the scar. Comparing tumor morphology and immunoprofile of the scar to the background oncocytoma is helpful to avoid interpretative confusion.

Automated screening of primary cell-based aptamers for targeting and therapy of pancreatic cancer

Although it has been developed for many years, nucleic acid aptamer screening technology still fails to be widely used, a considerable part of it is due to the variability of tumor cell morphology, which leads to the use of immortalized cell lines in the laboratory to screen nucleic acid aptamers for recognition ability of tumor cells in the diseased body. To address this, primary cells that can be stably passaged were isolated and extracted from spontaneous tumors of genetically engineered pancreatic ductal adenocarcinoma model mice in this study. Next, an automated screening instrument for nucleic acid aptamers developed autonomously by our group was used to perform efficient aptamer screening using a limited number of cells, and the obtained nucleic acid aptamers were affinity verified at the cellular level. Finally, to answer the question of the cell growth environment difference on the recognition ability of nucleic acid aptamers, we verified its targeting ability to tumors in vivo on a nude mice xenograft tumor model, and further used a common antitumor drug doxorubicin combined with nucleic acid aptamers to verify the drug loading ability of this aptamer combined with the targeting therapeutic ability.