Apmis

doi: 10.1111/apm.13144pmid: N/A

Traberg‐Nyborg, Laura; Login, Frédéric H.; Edamana, Sarannya; Tramm, Trine; Borgquist, Signe; Nejsum, Lene N.

doi: 10.1111/apm.13192pmid: 34758159

The canonical function of aquaporin (AQP) water channels is to facilitate passive transport of water across cellular membranes making them essential in the regulation of body water homeostasis. Moreover, AQPs, including AQP1, have been found to be overexpressed in multiple cancer types, including breast cancer, where AQP1 overexpression is associated with poor prognosis. AQPs have been shown to affect cellular processes associated with cancer progression and spread including cell migration, angiogenesis, and proliferation. Moreover, AQPs can regulate levels of adhesion proteins at cell–cell junctions, a regulatory role, which is still largely unexplored in cancer. Understanding the molecular mechanisms of how AQP1 contributes to breast cancer progression and metastatic processes is essential to establish AQP1 as a biomarker and to develop targeted anticancer treatments for breast cancer patients. This mini‐review focuses on the role of AQP1 in breast cancer.

Vesterinen, Tiina; Säilä, Jenni; Blom, Sami; Pennanen, Mirkka; Leijon, Helena; Arola, Johanna

doi: 10.1111/apm.13190pmid: 34741788

The Ki‐67 proliferation index (PI) is a prognostic factor in neuroendocrine tumors (NETs) and defines tumor grade. Analysis of Ki‐67 PI requires calculation of Ki‐67‐positive and Ki‐67‐negative tumor cells, which is highly subjective. To overcome this, we developed a deep learning‐based Ki‐67 PI algorithm (KAI) that objectively calculates Ki‐67 PI. Our study material consisted of NETs divided into training (n = 39), testing (n = 124), and validation (n = 60) series. All slides were digitized and processed in the Aiforia® Create (Aiforia Technologies, Helsinki, Finland) platform. The ICC between the pathologists and the KAI was 0.89. In 46% of the tumors, the Ki‐67 PIs calculated by the pathologists and the KAI were the same. In 12% of the tumors, the Ki‐67 PI calculated by the KAI was 1% lower and in 42% of the tumors on average 3% higher. The DL‐based Ki‐67 PI algorithm yields results similar to human observers. While the algorithm cannot replace the pathologist, it can assist in the laborious Ki‐67 PI assessment of NETs. In the future, this approach could be useful in, for example, multi‐center clinical trials where objective estimation of Ki‐67 PI is crucial.

Li, Lin; Wu, Wei; Zheng, Wanchao; Hui, Qiao; Zhao, Chunna

doi: 10.1111/apm.13193pmid: 34741767

We aimed to explore the correlation between P27 expression and Helicobacter pylori (H. pylori) infection in gastric cancer, so as to provide evidence for understanding the pathogenesis of gastric cancer caused by H. pylori infection. A total of 82 samples of gastric cancer tissues and 56 samples of tumor‐adjacent normal tissues collected from the gastrectomy were enrolled in this study. Then, 14C‐urease breathing test was carried out to evaluate the infection of H. pylori in gastric cancer tissues, the expression of P27 in the tissue samples was detected by the immunohistochemistry staining, and the correlation between the H. pylori infection and P27 expression in gastric cancer was analyzed. Of 82 gastric cancer patients, there were 53 patients with H. pylori infection (64.63%). Among the patients with highly or moderately differentiated gastric cancer, the expression of P27 was much higher than that of patients with poorly differentiated gastric cancer (p < 0.01). Besides, comparison of the P27 expression between males and females, among different age groups, tumor sizes, TNM stages, tumor infiltration degrees, or lymph node metastasis, showed no significant differences (p > 0.05). Analysis of the correlation revealed that P27 expression was negatively correlated with the infection of H. pylori (p < 0.01). Multifactorial logistics regression analysis indicated that tumor differentiation was a risk factor of P27‐positive expression in gastric cancer tissues (p < 0.01). In addition, P27 expression in the gastric cancer tissues was lower than that in the tumor‐adjacent normal tissues (p < 0.01). In gastric cancer patients, expression of P27 is correlated with H. pylori infection which, via downregulating P27, can cause the cancerization of gastric mucosa, and P27, for its role in the development and progression of gastric cancer, is a potential auxiliary indicator for clinical diagnosis whether gastric cancer is complicated with H. pylori infection. So, P27 is a key indicator for diagnosis, treatment, and prognostic evaluation of disease in the advanced stage.

Kristiansen, Glen; Schmid, Matthias

doi: 10.1111/apm.13188pmid: 34748225

This study aimed to clarify whether the pattern recognition involved in scoring proliferation fractions can be trained by abstract computerized images of virtual tissues. Twenty computer‐generated images with randomly distributed blue or red dots were scored by 12 probands (all co‐workers or collaborators of the Institute of Pathology, University of Bonn). Afterward, the probands underwent a training phase during which they received an immediate feedback on the actual rate of positivity after each image. Finally, the initial testing series was rescored. In a second round with 15 different probands, 20 Ki‐67 immunohistochemistry images of tonsil tissue were scored, followed by the same training phase with computer‐generated images, before the immunohistochemistry slides were scored again. Paired t‐tests were used to compare the differences in mean rates pre‐ and post‐training. Concerning computerized images, untrained probands scored the percentages of positive dots with a mean deviation from the true rates of 8.2%. Following training, the same testing series was scored significantly better with a mean deviation of 4.9% (mean improvement 3.3%, p < 0.001). Scoring real immunohistochemistry slides, the training with computerized images also improved correct estimations, albeit to a lesser degree (mean improvement 1%, p = 0.03). Abstract computerized images of virtual tissues may be a useful tool to train and improve the accuracy of pattern recognition involved in semiquantitative scoring of immunohistochemistry slides. As a side results, this study highlights the value of computer‐generated images to verify the performance of image‐analysis software.

Saarentausta, Katariina; Ivarsson, Lovisa; Jacobsson, Susanne; Herrmann, Björn; Sundqvist, Martin; Unemo, Magnus

doi: 10.1111/apm.13191pmid: 34758169

The COVID‐19 pandemic has challenged the societies and health care systems globally, and resulted in many social and physical distancing restrictions to limit the spread of SARS‐CoV‐2. These restrictions have also likely affected the frequency of intimate contacts and the spread of sexually transmitted infections (STIs). Compared to most other countries, Sweden especially in Spring‐Autumn 2020 pursued mainly milder voluntary, that is, not mandatory enforced by laws, recommended restrictions and the impacts of these on society and spread of STIs remain largely unknown. We describe the potential impact of the COVID‐19 pandemic on the national and regional incidence, epidemiology and diagnostic testing of chlamydia and gonorrhoea in Sweden in 2020. Compared to 2019, we found a significant decrease in incidence of chlamydia (−4.5%) and gonorrhoea (−17.5%), and in diagnostic testing (−10.5% for chlamydia, −9.4% for gonorrhoea) in 2020. However, the decrease in chlamydia incidence, which has mainly been decreasing in the last 10 years, was not significant when compared with the average incidence in 2017–2019. The largest decrease in national incidence of both infections was observed among young and heterosexual patients, however, some Swedish regions showed an increased incidence, particularly of chlamydia. Increased “internet‐based self‐sampling” testing approach partly compensated for a decreased attendance at STI clinics. Studies, including sexual behaviour, prevention, reasons for attending STI health care, STIs in different anatomical sites and management of STIs, are required to elucidate the impact of COVID‐19‐associated social and physical distancing restrictions on sexual activity and the incidence and epidemiology of chlamydia and gonorrhoea in Sweden.

Yang, Lei; Shi, You‐Ling; Ma, Yan; Ren, Wei‐Wei; Pang, Guang‐Ming; Liu, Jiao

doi: 10.1111/apm.13194pmid: 34779529

Krüppel‐like factor 16 (KLF16), a member of the Krüppel‐like factor (KLF) family, has been extensively investigated in multiple cancer types. However, the role of KLF16 in oral squamous cell carcinoma (OSCC) remains unknown. Thus, we conducted this study to investigate its related mechanism. KLF16 expression in OSCC cell lines was quantified by western blotting. Then, OECM1 and OC3 cells were divided into Blank, siCtrl, siKLF16#1 and siKLF16#2 groups. Subsequently, cell proliferation was detected using 3‐[4,5‐dimethylthiazol‐2‐yl]‐2,5 diphenyl tetrazolium bromide (MTT) assays, cell migration and invasion were detected with wound healing and Transwell assays, and cell cycle distribution and cell apoptosis were detected via flow cytometry. KLF16, p21, CDK4, Cyclin D1 and p‐Rb expression was detected by western blotting. Finally, xenograft models were established in nude mice to observe the in vivo effects of KLF16 on OSCC. KLF16 protein expression was upregulated in OSCC cells. Compared to the cells in the Blank group, the OECM1 and OC3 cells in the siKLF16#1 group and siKLF16#2 group exhibited a sharp decrease in proliferation but a remarkable increase in apoptosis. Moreover, the proportion of cells in the G0/G1 phase notably increased and that in the S phase decreased, with evident decreases in cell invasion and migration. Moreover, KLF16, cyclin‐dependent kinase 4 (CDK4), Cyclin D1 and p‐Rb protein expression was upregulated, but p21 expression was downregulated. The mice in the siKLF16#1 and siKLF16#2 xenograft model groups exhibited slower tumour growth and smaller tumours with evident downregulation of Ki67 expression compared to the mice in the Blank group. KLF16 expression was upregulated in OSCC cells, and interfering with KLF16 led to cell cycle arrest, inhibited OSCC cell growth and promoted cell apoptosis.

Sjöstedt, Sannia; Schmidt, Ane Yde; Vieira, Filipe Garrett; Woller, Nina Claire; Nielsen, Finn Cilius; Buchwald, Christian

doi: 10.1111/apm.13187pmid: 34741541