Disruptions in antigen processing and presentation machinery on sarcoma.

BACKGROUND: The antigen processing machinery (APM) plays a critical role in generating tumor-specific antigens that can be recognized and targeted by the immune system. Proper functioning of APM components is essential for presenting these antigens on the surface of tumor cells, enabling immune detection and destruction. In many cancers, defects in APM can lead to immune evasion, contributing to tumor progression and poor clinical outcomes. However, the status of the APM in sarcomas is not well characterized, limiting the development of effective immunotherapeutic strategies for these patients. METHODS: We investigated 126 patients with 8 types of bone and soft tissue sarcoma operated between 2001-2021. Tissue microarrays mapped 11 specific areas in each case. The presence/absence of APM protein was determined through immunohistochemistry. Bayesian networks were used. RESULTS: All investigated sarcomas had some defects in APM. The least damaged component was HLA Class I subunit ß2-microglobulin and HLA Class II. The proteasome LMP10 subunit was defective in leiomyosarcoma (LMS), myxoid liposarcoma (MLPS), and dedifferentiated liposarcoma (DDLPS), while MHC I transporting unit TAP2 was altered in undifferentiated pleomorphic sarcoma (UPS), gastrointestinal stromal tumor (GIST), and chordoma (CH). Among different neoplastic areas, high-grade areas showed different patterns of expression compared to high lymphocytic infiltrate areas. Heterogeneity at the patient level was also observed. Loss of any APM component was prognostic of distant metastasis (DM) for LMS and DDLPS and of overall survival (OS) for LMS. CONCLUSION: Sarcomas exhibit a high degree of defects in APM components, with differences among histotypes and tumoral areas. The most commonly altered APM components were HLA Class I subunit ß2-microglobulin, HLA Class I subunit α (HC10), and MHC I transporting unit TAP2. The loss of APM components was prognostic of DM and OS and clinically relevant for LMS and DDLPS. This study explores sarcoma molecular mechanisms, enriching personalized therapeutic approaches.

In Situ Analyses of Placental Inflammatory Response to SARS-CoV-2 Infection in Cases of Mother-Fetus Vertical Transmission.

It has been shown that vertical transmission of the SARS-CoV-2 strain is relatively rare, and there is still limited information on the specific impact of maternal SARS-CoV-2 infection on vertical transmission. The current study focuses on a transcriptomics analysis aimed at examining differences in gene expression between placentas from mother-newborn pairs affected by COVID-19 and those from unaffected controls. Additionally, it investigates the in situ expression of molecules involved in placental inflammation. The Papa Giovanni XXIII Hospital in Bergamo, Italy, has recorded three instances of intrauterine transmission of SARS-CoV-2. The first two cases occurred early in the pandemic and involved pregnant women in their third trimester who were diagnosed with SARS-CoV-2. The third case involved an asymptomatic woman in her second trimester with a twin pregnancy, who unfortunately delivered two stillborn fetuses due to the premature rupture of membranes. Transcriptomic analysis revealed significant differences in gene expression between the placentae of COVID-19-affected mother/newborn pairs and two matched controls. The infected and control placentae were matched for gestational age. According to the Benjamani-Hochberg method, 305 genes met the criterion of an adjusted p-value of less than 0.05, and 219 genes met the criterion of less than 0.01. Up-regulated genes involved in cell signaling (e.g., CCL20, C3, MARCO) and immune response (e.g., LILRA3, CXCL10, CD48, CD86, IL1RN, IL-18R1) suggest their potential role in the inflammatory response to SARS-CoV-2. RNAscope® technology, coupled with image analysis, was utilized to quantify the surface area covered by SARS-CoV-2, ACE2, IL-1ß, IL-6, IL-8, IL-10, and TNF-α on both the maternal and fetal sides of the placenta. A non-statistically significant gradient for SARS-CoV-2 was observed, with a higher surface coverage on the fetal side (2.42 ± 3.71%) compared to the maternal side (0.74 ± 1.19%) of the placenta. Although not statistically significant, the surface area covered by ACE2 mRNA was higher on the maternal side (0.02 ± 0.04%) compared to the fetal side (0.01 ± 0.01%) of the placenta. IL-6 and IL-8 were more prevalent on the fetal side (0.03 ± 0.04% and 0.06 ± 0.08%, respectively) compared to the maternal side (0.02 ± 0.01% and 0.02 ± 0.02%, respectively). The mean surface areas of IL-1ß and IL-10 were found to be equal on both the fetal (0.04 ± 0.04% and 0.01 ± 0.01%, respectively) and maternal sides of the placenta (0.04 ± 0.05% and 0.01 ± 0.01%, respectively). The mean surface area of TNF-α was found to be equal on both the fetal and maternal sides of the placenta (0.02 ± 0.02% and 0.02 ± 0.02%, respectively). On the maternal side, ACE-2 and all examined interleukins, but not TNF-α, exhibited an inverse mRNA amount compared to SARS-CoV-2. On the fetal side, ACE-2, IL-6 and IL-8 were inversely correlated with SARS-CoV-2 (r = -0.3, r = -0.1 and r = -0.4, respectively), while IL-1ß and IL-10 showed positive correlations (r = 0.9, p = 0.005 and r = 0.5, respectively). TNF-α exhibited a positive correlation with SARS-CoV-2 on both maternal (r = 0.4) and fetal sides (r = 0.9) of the placenta. Further research is needed to evaluate the correlation between cell signaling and immune response genes in the placenta and the vertical transmission of SARS-CoV-2. Nonetheless, the current study extends our comprehension of the molecular and immunological factors involved in SARS-CoV-2 placental infection underlying maternal-fetal transmission.

Recapitulating COVID-19 detection methods: RT-PCR, sniffer dogs and electronic nose.

In December 2019, a number of subjects presenting with an unexplained pneumonia-like illness were suspected to have a link to a seafood market in Wuhan, China. Subsequently, this illness was identified as the 2019-novel coronavirus (2019-nCoV) or severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by the World Committee on Virus Classification. Since its initial identification, the virus has rapidly sperad across the globe, posing an extraordinary challenge for the medical community. Currently, the Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) is considered the most reliable method for diagnosing SARS-CoV-2. This procedure involves collecting oro-pharyngeal or nasopharyngeal swabs from individuals. Nevertheless, for the early detection of low viral loads, a more sensitive technique, such as droplet digital PCR (ddPCR), has been suggested. Despite the high effectiveness of RT-PCR, there is increasing interest in utilizing highly trained dogs and electronic noses (eNoses) as alternative methods for screening asymptomatic individuals for SARS-CoV-2. These dogs and eNoses have demonstrated high sensitivity and can detect volatile organic compounds (VOCs), enabling them to distinguish between COVID-19 positive and negative individuals. This manuscript recapitulates the potential, advantages, and limitations of employing trained dogs and eNoses for the screening and control of SARS-CoV-2.

Vitamin D and celiac disease.

Celiac disease (CD) is an immune-mediated condition affecting the small intestine. Its reported global prevalence falls within the range of 0.7% to 1.4%. Notably, historically, higher rates, reaching 1% in Western Ireland, have been documented. Recent research has even revealed prevalence rates as elevated as 2% in northern Europe. These findings underscore the urgency for swift and cost-effective diagnosis, especially in individuals identified through screening efforts. At present, the diagnosis of CD relies on a multifaceted approach involving positive serological markers such as IgA anti-tissue transglutaminase (anti-TTG) and anti-endomysial antibodies (anti-EMA). These serological findings are assessed in conjunction with classical histological alterations, as outlined in the Marsh classification. CD is an inflammatory condition triggered by the consumption of gluten, resulting from intricate interactions between genetic, immunological, and environmental factors. CD is linked to malabsorption, leading to nutritional deficiencies. Individuals with CD are required to adhere to a gluten-free diet, which itself can lead to nutrient deficiencies. One such deficiency includes vitamin D, and there is substantial experimental evidence supporting the notion of a bidirectional relationship between CD and vitamin D status. A low level of vitamin D has a detrimental impact on the clinical course of the disease. Here we summarize the key characteristics of CD and explore the prominent roles of vitamin D in individuals with CD.

Prostate cancer risk stratification via eNose urine odor analysis: a preliminary report.

Introduction: Prostate cancer (PCa) is known for its highly diverse clinical behavior, ranging from low-risk, slow-growing tumors to aggressive and life-threatening forms. To avoid over-treatment of low-risk PCa patients, it would be very important prior to any therapeutic intervention to appropriately classify subjects based on tumor aggressiveness. Unfortunately, there is currently no reliable test available for this purpose. The aim of the present study was to evaluate the ability of risk stratification of PCa subjects using an electronic nose (eNose) detecting PCa-specific volatile organic compounds (VOCs) in urine samples. Methods: The study involved 120 participants who underwent diagnostic prostate biopsy followed by robot assisted radical prostatectomy (RARP). PCa risk was categorized as low, intermediate, or high based on the D'Amico risk classification and the pathological grade (PG) assessed after RARP. The eNose's ability to categorize subjects for PCa risk stratification was evaluated based on accuracy and recall metrics. Results: The study population comprised 120 participants. When comparing eNose predictions with PG an accuracy of 79.2% (95%CI 70.8 - 86%) was found, while an accuracy of 74.2% (95%CI 65.4 - 81.7%) was found when compared to D'Amico risk classification system. Additionally, if compared low- versus -intermediate-/high-risk PCa, the eNose achieved an accuracy of 87.5% (95%CI 80.2-92.8%) based on PG or 90.8% (95%CI 84.2-95.3%) based on D'Amico risk classification. However, when using low-/-intermediate versus -high-risk PCa for PG, the accuracy was found to be 91.7% (95%CI 85.2-95.9%). Finally, an accuracy of 80.8% (95%CI72.6-87.4%) was found when compared with D'Amico risk classification. Discussion: The findings of this study indicate that eNose may represent a valid alternative not only for early and non-invasive diagnosis of PCa, but also to categorize patients based on tumor aggressiveness. Further studies including a wider sample population will be necessary to confirm the potential clinical impact of this new technology.

Investigating the Spatial Distribution of Proliferating Cells in Primary Ovarian Cancers.

BACKGROUND: Ovarian cancer (OC) accounts for about 4% of female cancers globally. While Ki67-immunopositive (Ki67+) cell density is commonly used to assess proliferation in OC, the two-dimensional (2D) distribution pattern of these cells is poorly understood. This study explores the 2D distribution pattern of Ki67+ cells in primary OC tissues and models the proliferation process to improve our understanding of this hallmark of cancer. METHODS: A total of 100 tissue cores, included in a tissue microarray (TMA) representing 5 clear cell carcinomas, 62 serous carcinomas, 10 mucinous adenocarcinomas, 3 endometrioid adenocarcinomas, 10 lymph node metastases from OC, and 10 samples of adjacent normal ovary tissue, were stained using a standardized immunohistochemical protocol. The computer-aided image analysis system assessed the 2D distribution pattern of Ki67+ proliferating cells, providing the cell number and density, patterns of randomness, and cell-to-cell closeness. Three computer models were created to simulate behavior and responses, aiming to gain insights into the variations in the proliferation process. RESULTS: Significant differences in Ki67+ cell density were found between low- and high-grade serous carcinoma/mucinous adenocarcinomas (p = 0.003 and p = 0.01, respectively). The Nearest Neighbor Index of Ki67+ cells differed significantly between high-grade serous carcinomas and endometrioid adenocarcinomas (p = 0.01), indicating distinct 2D Ki67+ distribution patterns. Proxemics analysis revealed significant differences in Ki67+ cell-to-cell closeness between low- and high-grade serous carcinomas (p = 0.002). Computer models showed varied effects on the overall organization of Ki67+ cells and the ability to preserve the original 2D distribution pattern when altering the location and/or density of Ki67+ cells. CONCLUSIONS: Cell proliferation is a hallmark of OCs. This study provides new evidence that investigating the Ki67+ cell density and 2D distribution pattern can assist in understanding the proliferation status of OCs. Moreover, our computer models suggest that changes in Ki67+ cell density and their location are critical for maintaining the 2D distribution pattern.

Is Artificial Intelligence the Key to Revolutionizing Benign Prostatic Hyperplasia Diagnosis and Management?

Benign prostatic hyperplasia (BPH) is a prevalent condition among older men that is characterized by the enlargement of the prostate gland and compression of the urethra, which often results in lower urinary tract symptoms, such as frequent urination, difficulty in starting urination, and incomplete bladder emptying. The development of BPH is thought to be primarily due to an imbalance between cell proliferation and apoptosis, underlying inflammation, epithelial-to-mesenchymal transition, and local paracrine and autocrine growth factors, although the exact molecular mechanisms are not yet fully understood. Anatomical structures considered natural and benign observations can occasionally present multi-parametric magnetic resonance imaging appearances that resemble prostate cancer (PCa), posing a risk of misinterpretation and generating false-positive outcomes and subsequently, unnecessary interventions. To aid in the diagnosis of BPH, distinguish it from PCa, and assist with treatment and outcome prediction, various Artificial Intelligence (AI)-based algorithms have been proposed to assist clinicians in the medical practice. Here, we explore the results of these new technological advances and discuss their potential to enhance clinicians' cognitive abilities and expertise. There is no doubt that AI holds extensive medical potential, but the cornerstone for secure, efficient, and ethical integration into diverse medical fields still remains well-structured clinical trials.