Pathology, research and practice最新文献

Here, we explored the role of Prolyl 4-Hydroxylase Subunit Alpha 3 (P4HA3), the most recently identified member of the prolyl-4-hydroxylase (P4H) family, in head and neck squamous cell carcinoma (HNSCC) progression. P4HA3 is upregulated during cancer progression; however, its specific role in HNSCC progression remains elusive. Thus, this study aimed to elucidate the regulatory function of P4HA3 in HNSCC development and progression and to describe the underlying mechanisms. Initially, we analyzed the correlation between the expression of P4HA3 and the WNT pathway genes and clinicopathologic features in HNSCC based on microarray data from The Cancer Genome Atlas (TCGA). Next, we used Gene Oncology (GO) functional data to describe several potentially associated pathways in HNSCC. Then, we knocked down P4HA3 in SCC15 and SCC25 cells, two classic HNSCC cell lines, and assessed the resulting changes using RT-qPCR. Furthermore, we used Western blot to evaluate the regulatory role of P4HA3 in the epithelial-to-mesenchymal transition (EMT) and the WNT/β-catenin signaling pathway. To explore the effect of P4HA3 knockdown on tumor progression, in vivo experiments were conducted using a murine model. Immunohistochemistry assays were then employed to identify proteins associated with EMT and the WNT/β-catenin signaling pathway in tumor tissues. Upregulated P4HA3 in HNSCC patient tumor tissues was positively correlated with poor prognosis. Notably, P4HA3 knockdown significantly inhibited the proliferative and invasive abilities of HNSCC. The levels of genes and proteins associated with EMT and the WNT/β-catenin signaling pathway were also markedly reduced by P4HA3 knockdown. Importantly, the in vivo experiments demonstrated that P4HA3 can promote subcutaneous tumorigenesis in nude mice and knockdown of P4HA3 induce a significant ihibitation of EMT and WNT/β-catenin pathway detected by immunohistochemistry assay in tumor tissues. In summary, we demonstrated that P4HA3 is a promising diagnostic and therapeutic biomarker for HNSCC. As an oncogene, P4HA3 increases HNSCC proliferation by inducing the EMT and activating the WNT/β-catenin signaling pathway.

Yin yang 1 (YY1), a transcription factor, plays crucial roles in cell fate specification, differentiation, and pluripotency during embryonic development. It is also involved in tumorigenesis, drug resistance, metastasis, and relapse caused by cancer stem cells (CSCs), particularly in prostate cancer (PCa). Targeting YY1 could potentially eliminate prostate CSCs (PCSCs) and provide novel therapeutic approaches. PCa tissues often exhibit elevated YY1 expression levels, especially in high-grade cases. Notably, high-grade PCa tissues from 58 PCa patients and CD133^high/CD44^high PCSCs isolated from DU145 PCa cell line by FACS both showed significantly increased YY1 expression as observed through immunofluorescence staining, respectively. To investigate the embryonic microenvironment impact on YY1 expression in CSC populations, firstly PCSCs were microinjected into the inner cell mass of blastocysts and then PCSCs were co-cultured with blastocysts. Next Generation Sequencing was used to analyze alterations in YY1 and related gene expressions. Interestingly, exposure to the embryonic microenvironment significantly reduced the expressions of YY1, YY2, and other relevant genes in PCSCs. These findings emphasize the tumor-suppressing effects of the embryonic environment by downregulating YY1 and YY1-related genes in PCSCs, thus providing promising strategies for PCa therapy. Through elucidating the mechanisms involved in embryonic reprogramming and its effects on YY1 expression, this research offers opportunities for further investigation into focused therapies directed against PCSCs, therefore enhancing the outcomes of PCa therapy. As a result, PCa tumors may benefit from YY1 and associated genes as a novel therapeutic target.

Accurate assessment of HER2 expression in tumor tissue is crucial for determining HER2-targeted treatment options. Nevertheless, pathologists' assessments of HER2 status are less objective than automated, computer-based evaluations. Artificial Intelligence (AI) promises enhanced accuracy and reproducibility in HER2 interpretation. This study aimed to systematically evaluate current AI algorithms for HER2 immunohistochemical diagnosis, offering insights to guide the development of more adaptable algorithms in response to evolving HER2 assessment practices. A comprehensive data search of the PubMed, Embase, Cochrane, and Web of Science databases was conducted using a combination of subject terms and free text. A total of 4994 computational pathology articles published from inception to September 2023 identifying HER2 expression in breast cancer were retrieved. After applying predefined inclusion and exclusion criteria, seven studies were selected. These seven studies comprised 6867 HER2 identification tasks, with two studies employing the HER2-CONNECT algorithm, two using the CNN algorithm, one with the multi-class logistic regression algorithm, and two using the HER2 4B5 algorithm. AI's sensitivity and specificity for distinguishing HER2 0/1+ were 0.98 [0.92–0.99] and 0.92 [0.80–0.97] respectively. For distinguishing HER2 2+, the sensitivity and specificity were 0.78 [0.50–0.92] and 0.98 [0.93–0.99], respectively. For HER2 3+ distinction, AI exhibited a sensitivity of 0.99 [0.98–1.00] and specificity of 0.99 [0.97–1.00]. Furthermore, due to the lack of HER2-targeted therapies for HER2-negative patients in the past, pathologists may have neglected to distinguish between HER2 0 and 1+, leaving room for improvement in the performance of artificial intelligence (AI) in this differentiation. AI excels in automating the assessment of HER2 immunohistochemistry, showing promising results despite slight variations in performance across different HER2 status. While incorporating AI algorithms into the pathology workflow for HER2 assessment poses challenges in standardization, application patterns, and ethical considerations, ongoing advancements suggest its potential as a widely effective tool for pathologists in clinical practice in the near future.

The human microbiome is a complex network of microorganisms that includes viruses, bacteria, and fungi. The gut virome is an essential component of the immune system, which is responsible for regulating the growth and responses of the host's immune system. The virome maintains a crucial role in the development of numerous diseases, including inflammatory bowel disease (IBD), Crohn's disease, and neurodegenerative disorders. The human virome has emerged as a promising biomarker and therapeutic target. This comprehensive review summarizes the present understanding of the virome and its implications in matters of health and disease, with a focus on the Human Microbiome Project.

Lipoleiomyomas are rare variants of uterine leiomyomas rarely studied in the literature. We retrospectively studied 20 cases of uterine lipoleiomyomas showing that these lesions represent 0.7 % of all uterine leiomyomas diagnosed histologically. The patients did not experience any recurrence, and the tumors showed no morphological criteria of malignancy. They did not show significant p16, p53 or MiB1 expression. They showed diffuse and strong expression or estrogen and progesterone receptors by the smooth muscle component but without accompanying expression by the adipocytic component in one third of the cases. Androgen receptors were rarely expressed. They expressed in their majority HMGA2 in both components, while RB1 was usually not found. Fumarate hydratase (FH) is expressed by lipoleiomyomas, while they are negative for HMB45. In conclusion, uterine lipoleiomyomas are rare, benign tumors, characterized by HMGA2 expression, while they show no elements suspicious of malignancy, PEComas or FH deficiency. The role of RB1 in these tumors should be further explored.

Gliomas are among the most common cancers in the central nervous system, arising through various signaling pathways. One significant pathway is Wnt signaling, a tightly regulated process that plays a crucial role in gliomagenesis and development. The current study aims to explore the relationship between circular RNAs (circRNAs) and the Wnt/β-catenin signaling pathway in gliomas, considering the growing recognition of circRNAs in disease pathogenesis. A comprehensive review of recent research was conducted to investigate the roles of circRNAs in gliomas, focusing on their expression patterns and interactions with the Wnt signaling pathway. The analysis included studies examining circRNAs' function as microRNA sponges and their impact on glioma biology. The findings reveal that circRNAs are differentially expressed in gliomas and significantly influence the occurrence, growth, and metastasis of these tumors. Specifically, circRNAs interact with the Wnt signaling pathway, affecting glioma development and progression. This interaction highlights the importance of circRNAs in glioma pathophysiology. Understanding the regulatory network involving circRNAs and Wnt signaling offers valuable insights into glioma pathophysiology. CircRNAs hold promise as diagnostic and prognostic biomarkers and may serve as targets for novel therapeutic strategies in glioma treatment.

Objective

Human epidermal growth factor receptor 2 (HER2)–positive breast cancer exhibits an aggressive phenotype and poor prognosis. The application of neoadjuvant therapy (NAT) in patients with breast cancer can significantly reduce the risks of disease recurrence and improve survival. By integrating different clinicopathological factors, nomograms are valuable tools for prognosis prediction. This study aimed to assess the prognostic value of clinicopathological factors in patients with HER2-positive breast cancer and construct a nomogram for outcome prediction.

Methods

We retrospectively analyzed the clinicopathological data from 374 patients with breast cancer admitted to the Fourth Hospital of Hebei Medical University between January 2009 and December 2017, who were diagnosed with invasive breast cancer through preoperative core needle biopsy pathology, underwent surgical resection after NAT, and were HER2-positive. Patients were randomly divided into a training and validation set at a ratio of 7:3. Univariate and multivariate survival analyses were performed using Kaplan-Meier and Cox proportional hazards regression models. Results of the multivariate analysis were used to create nomograms predicting 3-, 5-, and 8-year overall survival (OS) rates. Calibration curves were plotted to test concordance between the predicted and actual risks. Harrell C-index and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discriminability of the nomogram prediction model.

Results

All included patients were women, with a mean age of 50 ± 10.4 years (range: 26–72 years). In the training set, both univariate and multivariate analyses identified residual cancer burden (RCB) class, tumor-infiltrating lymphocytes(TILs), and clinical stage as independent prognostic factors for OS, and these factors were combined to construct a nomogram. The calibration curves demonstrated good concordance between the predicted and actual risks, and the C-index of the nomogram was 0.882 (95 % CI 0.863–0.901). The 3-, 5-, and 8-year areas under the ROC curve (AUCs) were 0.909, 0.893, and 0.918, respectively, indicating good accuracy of the nomogram. The calibration curves also demonstrated good concordance in the validation set, with a C-index of 0.850 (95 % CI 0.804–0.896) and 3-, 5-, and 8-year AUCs of 0.909, 0.815, and 0.834, respectively, which also indicated good accuracy.

Conclusion

The nomogram prediction model accurately predicted the prognostic status of post-NAT patients with breast cancer and was more accurate than clinical stage and RCB class. Therefore, it can serve as a reliable guide for selecting clinical treatment measures for breast cancer.

MicroRNAs (miRNAs) are a class of small non-coding RNAs that act as important regulators of gene expression, involved in various biological pathways. Aberrant miRNAs expression is associated with the onset and progression of colorectal cancer (CRC). The aim of this study was to investigate the correlation between five miRNAs (miR-29a, miR-101, miR-125b, miR-146a, and miR-155), found to be deregulated in tissue samples of CRC patients, and clinicopathological characteristics and histological markers. Analysis of histological markers was performed by immunohistochemical staining of tumour tissues with Ki-67, p53, CD34, and Bcl-2. Our findings revealed a significant negative correlation between miR-29a expression and Bcl-2 levels. Furthermore, high miR-29a expression was associated with a lower incidence of distant metastasis in CRC patients. We observed negative correlations between miR-101 expression and the number of lymph nodes with metastasis, as well as the size of the largest metastasis; miR-125b expression and lymphovascular invasion; and miR-155 expression and mucus presence. Our survival analysis demonstrated that high miR-29a expression correlated with better progression-free survival of CRC patients, underscoring its potential as a prognostic marker. Our study unveiled intricate relationships between specific miRNA expressions and clinicopathological features in CRC, highlighting the potential utility of miR-29a as a valuable prognostic biomarker.

Gastric cancer (GC), a globally prevalent and lethal malignancy, continues to be a key research focus. However, due to its considerable heterogeneity and complex pathogenesis, the treatment and diagnosis of gastric cancer still face significant challenges. With the rapid development of spatial omics technology, which provides insights into the spatial information within tumor tissues, it has emerged as a significant tool in gastric cancer research. This technology affords new insights into the pathology and molecular biology of gastric cancer for scientists. This review discusses recent advances in spatial omics technology for gastric cancer research, highlighting its applications in the tumor microenvironment (TME), tumor heterogeneity, tumor genesis and development mechanisms, and the identification of potential biomarkers and therapeutic targets. Moreover, this article highlights spatial omics' potential in precision medicine and summarizes existing challenges and future directions. It anticipates spatial omics' continuing impact on gastric cancer research, aiming to improve diagnostic and therapeutic approaches for patients. With this review, we aim to offer a comprehensive overview to scientists and clinicians in gastric cancer research, motivating further exploration and utilization of spatial omics technology. Our goal is to improve patient outcomes, including survival rates and quality of life.

Cancer is the main contributor for mortality in the world. Conventional therapy that available as the treatment options are chemotherapy, radiotherapy and surgery. However, these treatments are hardly cell-specific most of the time. Nowadays, extensive research and investigations are made to develop cell-specific approaches prior to cancer treatment. Some of them are photodynamic therapy, hyperthermia, immunotherapy, stem cell transplantation and targeted therapy. This review article will be focusing on the development of gene therapy in cancer. The objective of gene therapy is to correct specific mutant genes causing the excessive proliferation of the cell that leads to cancer. There are lots of explorations in the approach to modify the gene. The delivery of this therapy plays a big role in its success. If the inserted gene does not find its way to the target, the therapy is considered a failure. Hence, vectors are needed and the common vectors used are viral, non viral or synthetic, polymer based and lipid based vectors. The advancement of gene therapy in cancer treatment will be focussing on the top three cancer cases in the world which are breast, lung and colon cancer. In breast cancer, the discussed therapy are CRISPR/Cas9, siRNA and gene silencing whereas in colon cancer miRNA and suicide gene therapy and in lung cancer, replacement of tumor suppressor gene, CRISPR/Cas9 and miRNA.