Automated Screening of Precancerous Cervical Cells Through Contrastive Self-Supervised Learning.

Cervical cancer is a significant health challenge, yet it can be effectively prevented through early detection. Cytology-based screening is critical for identifying cancerous and precancerous lesions; however, the process is labor-intensive and reliant on trained experts to scan through hundreds of thousands of mostly normal cells. To address these challenges, we propose a novel distribution-augmented approach using contrastive self-supervised learning for detecting abnormal squamous cervical cells from cytological images.

Feasibility of an indocyanine green-hyaluronic acid mixture (LuminoMark™) for targeting suspicious axillary lymph nodes in patients with breast cancer.

Purpose: During breast cancer surgery, the use of dyes such as indigo carmine, methylene blue, or indocyanine green (ICG) for targeting axillary lymph nodes (ALNs) under ultrasound guidance can result in rapid diffusion, complicated tissue differentiation, and disruption of staining. LuminoMark™, a novel ICG-hyaluronic acid mixture, can provide real-time visualization and minimize dye spread, thereby ensuring a clear surgical field. The aim of our study was to evaluate the efficacy of LuminoMark™ for targeting ALNs in patients with breast cancer.

Association of human papillomavirus 16 and 18 with ovarian cancer risk: Insights from a meta‑analysis.

Ovarian cancer (OC) presents a global health challenge, with well-documented genetic aspects. However, to the best of our knowledge, the role of human papillomavirus (HPV) types 16 and 18 in OC remains unclear. The present meta-analysis assessed the prevalence of HPV in OC across 43 studies and included a comparative meta-analysis of 19 case-control studies to determine the association of HPV with OC risk.

The Mclust Analysis of Tumor Budding Unveils the Role of the Collagen Family in Cervical Cancer Progression.

In RNA-seq data analysis, condensing the gene count matrix size is pivotal for downstream investigations, particularly pathway analysis. For this purpose, harnessing machine learning attracts increasing interest, while conventional methodologies depend on -value comparisons. In this study, 20 tissue samples from real-world cervical cancers were subjected to sequencing, followed by the application of the Mclust algorithm to delineate an optimal cluster.

Toward Interpretable Cell Image Representation and Abnormality Scoring for Cervical Cancer Screening Using Pap Smears.

Screening is critical for prevention and early detection of cervical cancer but it is time-consuming and laborious. Supervised deep convolutional neural networks have been developed to automate pap smear screening and the results are promising. However, the interest in using only normal samples to train deep neural networks has increased owing to the class imbalance problems and high-labeling costs that are both prevalent in healthcare.

Role of Tumor-Associated Macrophages in Cervical Cancer: Integrating Classical Perspectives with Recent Technological Advances.

Tumor-associated macrophages (TAMs) play a pivotal role in the tumor microenvironment, influencing cancer progression and contributing to poor prognosis. However, in cervical cancer (CC), their significance and involvement are relatively less studied than in other gynecological cancers such as ovarian and endometrial cancer. This review aims to provide an overview of TAMs, covering their origins and phenotypes and their impact on CC progression, along with major TAM-targeted therapeutic approaches.

Long non-coding RNA SOX2OT in tamoxifen-resistant breast cancer.

Hormone receptor (HR)-positive breast cancer can become aggressive after developing hormone-treatment resistance. This study elucidated the role of long non-coding RNA (lncRNA) SOX2OT in tamoxifen-resistant (TAMR) breast cancer and its potential interplay with the tumor microenvironment (TME). TAMR breast cancer cell lines TAMR-V and TAMR-H were compared with the luminal type A cell line (MCF-7).

Exploration of MELK as a downstream of Del-1 and druggable targets in triple-negative breast cancer.

Purpose: In our previous study, Developmental endothelial locus-1 (Del-1) was a promising predictive marker for breast cancer. However, the downstream targets of Del-1 remain unknown. Here, we sought to discover a druggable target downstream of Del-1 and investigate the mechanism by which it regulates the course of breast cancer.

Improving Tumor-Infiltrating Lymphocytes Score Prediction in Breast Cancer with Self-Supervised Learning.

Tumor microenvironment (TME) plays a pivotal role in immuno-oncology, which investigates the intricate interactions between tumors and the human immune system. Specifically, tumor-infiltrating lymphocytes (TILs) are crucial biomarkers for evaluating the prognosis of breast cancer patients and have the potential to refine immunotherapy precision and accurately identify tumor cells in specific cancer types. In this study, we conducted tissue segmentation and lymphocyte detection tasks to predict TIL scores by employing self-supervised learning (SSL) model-based approaches capable of addressing limited labeling data issues.

Heterogeneity of gut microbiome compositions in the third decade of life in Japanese women: insights from a comparative analysis.

The reasons for sex-associated gut microbiota differences have not been determined, and although sex hormones, diet, and other factors are considered to contribute to them, many of these factors are age related. To shed light on this complex interplay, our study aimed to investigate and compare the gut microbial compositions of males and females across a broad range of ages, aiming to identify sex-associated disparities and potential causal factors. Our study encompassed a comprehensive analysis of gut microbiota data obtained from 444 Japanese individuals, ranging from newborns to centenarians, sourced from the DNA Data Bank of Japan.

Profiling of Lymphovascular Space Invasion in Cervical Cancer Revealed PI3K/Akt Signaling Pathway Overactivation and Heterogenic Tumor-Immune Microenvironments.

Lymphovascular space invasion (LVSI) is the presence of tumor emboli in the endothelial-lined space at the tumor body's invasive edge. LVSI is one of three Sedlis criteria components-a prognostic tool for early cervical cancer (CC)-essential for indicating poor prognosis, such as lymph node metastasis, distant metastasis, or shorter survival rate. Despite its clinical significance, an in-depth comprehension of the molecular mechanisms or immune dynamics underlying LVSI in CC remains elusive.

Comparison of immunohistochemistry and next-generation sequencing results in oncogenic PTEN missense mutations.

Background: Phosphatase and tensin homolog (PTEN) is one of the most frequently mutated tumor suppressor genes in malignant tumors. Oncogenic PTEN mutations have diagnostic, prognostic, and therapeutic implications. Similar to TP53 mutations, oncogenic PTEN mutations can result from nonsynonymous missense mutations.

Relationship between Human Papillomavirus Status and the Cervicovaginal Microbiome in Cervical Cancer.

Uterine cervical cancer (CC) is a complex, multistep disease primarily linked to persistent infection with high-risk human papillomavirus (HR-HPV). However, it is widely acknowledged that HR-HPV infection alone cannot account for the formation and progression of CC. Emerging evidence suggests that the cervicovaginal microbiome (CVM) also plays a significant role in HPV-related CC.

Pellino-1 expression is associated with epidermal proliferation and enhanced Th17 cell infiltration in psoriatic lesions.

Pellino-1 plays a crucial role in cellular proliferation and regulates inflammatory processes. This study investigated Pellino-1 expression patterns and their relationship with CD4 T-cell subsets in psoriasis patients. Group 1 comprised primarily biopsied psoriasis lesions from 378 patients, multiplex-immunostained for Pellino-1, CD4 and representative T helper (Th) cells (T-bet [Th1], GATA3 [Th2], and RORγt [Th17] and regulatory T cell [FoxP3] markers).

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with aggressive biologic behavior. Predicting promoter mutation is thus necessary for the prognostic stratification of thyroid cancer patients. In this study, we evaluate promoter mutation status in thyroid cancer through the deep learning approach using histologic images.

Mutations as a Prognostic Factor in Patients With Residual Rectal Cancer After Neoadjuvant Chemoradiotherapy.

Background/aim: PIK3CA mediates various cellular processes, such as transformation, tumor initiation and proliferation, and resistance to apoptosis. This study was conducted to identify the clinical significance and prognostic effect of PIK3CA mutations in patients with residual rectal cancer who underwent surgery after neoadjuvant chemoradiotherapy (NACRT).

Patients And Methods: Formalin-fixed and paraffin-embedded surgical specimens were collected from 128 patients between January 2006 and December 2011 and analyzed using real-time polymerase chain reaction for hotspot mutations in exons 9 and 20 of the PIK3CA gene.

Ten-Year Oncologic Outcomes in T1-3N1 Breast Cancer After Targeted Axillary Sampling: A Retrospective Study.

Background: Targeted axillary sampling (TAS) is a new surgical concept for the assessment of axillary lymph node status in breast cancer that is hypothesized to be more effective at minimizing postoperative morbidities than axillary lymph node dissection (ALND), provided the metastatic axillary lymph node can be accurately detected without missing data; however, the oncologic outcomes over long-term follow-up have not been sufficiently investigated. This was a retrospective analysis to evaluate the 10-year oncologic outcomes in T1-3N1 breast cancer after TAS.

Methods: Between 2008 and 2013, 230 female patients with cT1-3N1 breast cancer underwent breast and axillary surgery (ALND, n = 171; TAS, n = 59) at our institute.

Transcriptomic Network Analysis Using Exfoliative Cervical Cells Could Discriminate a Potential Risk of Progression to Cancer in HPV-related Cervical Lesions: A Pilot Study.

Background/aim: Cervical cancer is the fourth most common type of cancer in women worldwide and it is a major cause of cancer-related deaths in developing countries. Despite the marked reduction observed in the rates of the disease as a result of screening programs, it is necessary to develop robust biomarkers that can detect the neoplastic progression early in HPV-related cervical lesions.

Materials And Methods: We performed comparative mRNA sequencing from exfoliative cervical cytology samples from nine Korean women using the Illumina NovaSeq6000 platform.

Oncologic necessity for the complete removal of residual microcalcifications after neoadjuvant chemotherapy for breast cancer.

The surgical range of breast cancer that shows pathologic complete response (pCR) without change in microcalcifications after neoadjuvant chemotherapy (NAC) is controversial. This study examined whole breast specimens to evaluate the necessity of mastectomy in those cases. The viability of cancer cells around the residual microcalcification was assessed using prospectively collected breast samples to confirm the presence or absence of cancer cells.

Validation and Clinical Application of ONCOaccuPanel for Targeted Next-Generation Sequencing of Solid Tumors.

Purpose: Targeted next-generation sequencing (NGS) is widely used for simultaneously detecting clinically informative genetic alterations in a single assay. Its application in clinical settings requires the validation of NGS gene panels. In this study, we aimed to validate a targeted hybridization capture-based DNA panel (ONCOaccuPanel) using the Illumina MiSeq sequencing platform.

Immune Pathway and Gene Database (IMPAGT) Revealed the Immune Dysregulation Dynamics and Overactivation of the PI3K/Akt Pathway in Tumor Buddings of Cervical Cancer.

Tumor budding (TB) is a small cluster of malignant cells at the invasive front of a tumor. Despite being an adverse prognosis marker, little research has been conducted on the tumor immune microenvironment of tumor buddings, especially in cervical cancer. Therefore, RNA sequencing was performed using 21 formalin-fixed, paraffin-embedded slides of cervical tissues, and differentially expressed genes (DEGs) were analyzed.

Simple Electric Device to Isolate Nucleic Acids from Whole Blood Optimized for Point of Care Testing of Brain Damage.

Background: Detection or monitoring of brain damage is a clinically crucial issue. Nucleic acids in the whole blood can be used as biomarkers for brain injury. Polymerase chain reaction (PCR) which is one of the most commonly used molecular diagnostic assays requires isolated nucleic acids to initiate amplification.

Transcriptomic Immune Profiles Can Represent the Tumor Immune Microenvironment Related to the Tumor Budding Histology in Uterine Cervical Cancer.

Tumor budding (TB) histology has become a critical biomarker for several solid cancers. Despite the accumulating evidence for the association of TB histology with poor prognosis, the biological characteristics of TB are little known about in the context related to the tumor immune microenvironment (TIME) in uterine cervical cancer (CC). Therefore, this study aimed to identify the transcriptomic immune profiles related to TB status and further provide robust medical evidence for clinical application.