Tetraspanin-29 activates Notch signaling by interacting with ADAM10 to enhance its activity in colorectal cancer.

ADAM10 acts upstream of Notch signaling and plays oncogenic roles in various cancers. Tetraspanin family proteins regulate ADAM10 trafficking and activity. Here, we aimed to investigate whether and how tetraspanin-29 modulates ADAM10 in colorectal cancer (CRC). We found that ADAM10 expression was upregulated in CRC tissues and this was cross-validated in the TCGA COAD data set. The ADAM10 protein level and its α-secretase activity were enhanced in CRC cell lines compared with control cell lines. Co-immunoprecipitation showed ADAM10 interacted with tetraspanin-29 in the LoVo cell line. Tetraspanin-29 knockdown reduced the cell surface trafficking and α-secretase activity of ADAM10. In addition, tetraspanin-29 knockdown inhibited Notch activity in a luciferase reporter assay and reduced the levels of cleaved Notch1 and Notch target genes such as HES2, c-MYC, and cyclin D3. Consistently, tetraspanin-29 overexpression increased cleaved Notch1 and this effect was blocked by ADAM10 inhibitors. The TCGA COAD data set confirmed the positive correlations of tetraspanin-29 with HES2, c-MYC, and cyclin D3. Thus, the tetraspanin-29/ADAM10/Notch pathway plays an important role in CRC.

Long-term consumption of recycled cooking oil induces cell death and tissue damage.

Recycled cooking oil (RCO) is widely used in many small restaurants. However, the health risk posed by long-term consumption of RCO is unclear. In this study, C57 mice were treated with RCO for 34 weeks. Organ coefficients of the liver, stomach, and kidney were found to be decreased. H&E staining revealed overt lesions in the pancreas, liver, kidney, esophagus, duodenum, and ileum of RCO-treated mice. Immunohistochemistry showed significant DNA damage in the duodenum and ileum and apoptosis in the lungs of the RCO-treated mice. Immunoblotting showed elevated levels of γ-H2AX, Bcl-2/Bax, TNFα, cleaved Caspase-3 and poly ADP-ribose polymerase (PARP). Increased levels of lactate dehydrogenase (LDH) and decreased levels of succinate dehydrogenase (SDH) were also detected. These findings suggest that long-term consumption of RCO produces various toxicities in mice with important implications for humans. DNA damage followed by mitochondria-associated apoptosis, and necrosis is likely to contribute to the toxicities.

Skip participates in formation and lipid metabolism of beige adipose and might mediate the effects of SIRT1 activator BTM-0512 on beige remodeling.

Dissipating energy by activating thermogenic adipose to combating obesity attracts many interests. Ski-interacting protein (Skip) has been known to play an important role in cell proliferation and differentiation, but whether it participates in energy metabolism is not known. Our previous study revealed that BTM-0512 could induce beige adipose formation, accompanying with up-regulation of Skip, but the role of Skip in metabolism was unknown. In this study, we mainly investigated whether Skip was involved in beige remodeling of subcutaneous white preadipocytes as well as in lipid metabolism of differentiated beige adipocytes. The results showed that in high fat diet-induced obesity mice, the protein levels of Skip in subcutaneous and visceral white adipose as well as in brown adipose were all down-regulated, especially in subcutaneous white adipose. Then we cultured subcutaneous adipose derived-stem cells (ADSCs) and found knock-down of Skip (siSkip) inhibited the expressions of thermogenic adipose specific genes including PRDM16 and UCP1 in both undifferentiated ADSCs and differentiated beige adipocytes, which could abolish the effects of BTM-0512 on beige remodeling. We further observed that siSkip affected multiple rate-limiting enzymes in lipid metabolism. The expressions of ACC, GPAT-1, HSL and ATGL were down-regulated, while CPT1α expression was up-regulated by siSkip. The expression of AMPK was also decreased by siSkip. In conclusion, our study demonstrated that Skip might play an important role in the beige remodeling of white adipocytes as well as lipid metabolism of beige adipose.

Alpha-glucosidase inhibitor 1-Deoxynojirimycin promotes beige remodeling of 3T3-L1 preadipocytes via activating AMPK.

Obesity is a serious health challenge in the world, and searching effective drugs to cure obesity is of great importance. 1-Deoxynojirimycin (DNJ) is extracted from mulberry leaves and acts as an α-glucosidase inhibitor to lower blood glucose. Recent studies demonstrated that it also has anti-obesity effect, but the mechanisms remain unknown. In our present study, we mainly examined the effects of DNJ on beige remodeling of 3T3-L1 preadipocytes. We observed that DNJ didn't affect the mRNA levels of fatty acid binding protein 4 (aP2), peroxisome proliferator-activated receptor γ (PPARγ), preadipocyte factor-1 (Pref-1) as well as the mitochondrial uncoupling protein 1 (UCP1), PR domain containing protein 16 (PRDM16), transmembrane protein 26 (TMEM26) in undifferentiated preadipocytes. But after inducing 3T3-L1 preadipocytes to differentiation with white or beige adipogenic medium, DNJ significantly reduced aP2, PPARγ and Pref-1 expressions, while up-regulated the expressions of UCP1, PRDM16 and TMEM26, accompanying with decreased lipid deposition. The ratio of p-AMPK/AMPK was up-regulated by DNJ (10 µM) treatment for 10 days, and the effects of DNJ on p-AMPK/AMPK, UCP1 and PRDM16 could be blocked by AMPK inhibitor Compound C. These results demonstrated that hypoglycemic agent DNJ could suppress the adipogenesis during the differentiation of white preadipocytes, and promote the switch of white preadipocytes to beige adipocytes via activating AMPK, which provided new mechanisms for explaining the benefits of DNJ on obesity-related disorders.

Resveratrol derivative BTM-0512 mitigates obesity by promoting beige remodeling of subcutaneous preadipocytes.

Recent studies revealed that sirtuin 1 (SIRT1) is involved in the regulation of energy metabolism and its agonist resveratrol showed anti-obesity effect. This study aims to determine whether BTM-0512, a novel derivative of resveratrol, acts as an antagonist of obesity and to explore its possible mechanisms. High-fat diet (HFD)-induced obese mice were intragastrically administered with BTM-0512 (5, 10, and 20 mg/kg/day) or resveratrol (10 mg/kg/day). It was found that the body weight, Lee's index, ratio of visceral adipose tissue (VAT) to body weight, and blood glucose were significantly reduced in BTM-0512-treated mice when compared with those in mice treated with resveratrol. BTM-0512 up-regulated the expressions of SIRT1, full length PRDM16 (fPRDM16), total PRDM16 (tPRDM16, including fPPRDM16 and other PRDM16 isoforms), and uncoupling protein 1 (UCP1) in both brown and subcutaneous adipose tissues. Although BTM-0512 and resveratrol also up-regulated SIRT1 and tPRDM16 levels in VAT of HFD-induced obese mice, the expressions of fPRDM16, UCP1, and TMEM26 were down-regulated. In mouse primary subcutaneous preadipocytes cultured with or without adipogenic medium, BTM-0512 up-regulated fPRDM16, tPRDM16, and UCP1 expressions, which was reversed by SIRT1 antagonists. But in cultured brown and visceral adipocytes, the UCP1 protein level showed no significant change after treatment with 1 µM of BTM-0512. Moreover, transfection with human SIRT1 plasmid reduced lipid deposit, as well as the mRNA levels of fPRDM16, UCP1, and TMEM26, in cultured human visceral adipose-derived stem cells. In conclusion, BTM-0512 has stronger anti-obesity effect than resveratrol, which might be associated with activation of beige remodeling in subcutaneous adipose tissue.

Eurochevalierines A-I, Sesquiterpene Alkaloid Hybrids with Anti-Triple Negative Breast Cancer Activity from Penicillium sp. HZ-5.

Nine new sesquiterpene alkaloids, eurochevalierines A-I (1-9), were separated from the rice cultures of the endophytic fungus Penicillium sp. HZ-5 originated from the fresh leaf of Hypericum wilsonii N. Robson. The structures' illumination was conducted by single-crystal X-ray diffraction, extensive spectroscopic analysis, alkaline hydrolysis reaction, and Snatzke's method. Importantly, the antitumor activities screen of these isolates indicated that 1 could suppress triple negative breast cancer (TNBC) cell proliferation and induce apoptosis, with an IC50 value of 5.4 µM, which is comparable to the positive control docetaxel (DXT). Flow cytometry experiments mentioned that compound 1 significantly reduced mitochondrial membrane potential (MMP) of TNBC cells. In addition, 1 could activate caspase-3 and elevated the levels of reactive oxygen species (ROS) and expressions of suppressive cytokines and chemokines. Further Western blot analysis showed that 1 could selectively induce mitochondria-dependent apoptosis in TNBC cells via the BAX/BCL-2 pathway. Remarkably, these finding provide a new natural product skeleton for the treatment of TNBC.

The association of adipose-derived dimethylarginine dimethylaminohydrolase-2 with insulin sensitivity in experimental type 2 diabetes mellitus.

Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of nitric oxide synthase (NOS), which can be hydrolyzed by dimethylarginine-dimethylaminohydrolase (DDAH). It has been reported that adipocytes can produce DDAH/ADMA, but its role remains unknown. In the present study, we examined the effects of adipocyte-derived DDAH/ADMA on insulin sensitivity using animal and cell models. Results showed that in adipose tissue of high fat diet-fed diabetic rats, as well as in high glucose (25 mM) plus insulin (100 nM)-treated 3T3-L1 adipocytes, expression levels of insulin receptor substance-1 (IRS-1), glucose transporter-4 (GLUT-4), and DDAH isoform-2 (DDAH-2) were down-regulated compared with control, although DDAH-1 expression showed no significant changes. We also observed that nitric oxide bioavailability, DDAH and NOS activities were subsequently decreased, while the local ADMA content was elevated in diabetic adipose tissue. Transfection of human DDAH-2 gene into high glucose- and insulin-treated 3T3-L1 adipocytes significantly ameliorated DDAH activity, reduced ADMA contents, and up-regulated the mRNA expression levels of IRS-1 and GLUT-4. These findings suggested that in the development of type 2 diabetes mellitus, local DDAH-2 in adipocytes might play an important role in regulating insulin sensitivity.

TGF-ß1 alters microRNA profile in human gastric cancer cells.

OBJECTIVE: MicroRNAs (miRNAs) are important regulators that play a key role in tumorigenesis and tumor progression. Transforming growth factor-ß1 (TGF-ß1) is involved in invasion and metastasis in many tumors. In this study, we investigated the microRNAs (miRNA) profiles altered by TGF-ß1 in gastric cancer (GC) cells. METHODS: We detected the expression profiles of miRNA by miRNA microarray and quantitative real-time polymerase chain reaction. Migration and invasion, wound-healing assay, prediction of miRNA targets, Western blot and qRT-PCR analysis were carried out to determine the role of one selected miRNA, namely miR-193b, in affecting the biological behaviors of GC BGC823 cells. RESULTS: Among 847 human miRNAs in the microarray, three miRNAs (miR-27a, miR-29b-1 and miR-194) were up-regulated and three (miR-574-3p, miR-193b and miR-130b) were down-regulated in BGC823 cells treated with TGF-ß1 compared with control. miR-193b suppressed the invasion and metastasis of GC cells in vivo and in vitro, and down-regulated urokinase-type plasminogen activator (uPA) protein in GC cells. CONCLUSIONS: TGF-ß1 altered miRNA expression profile in BGC823 cells. Among the altered miRNAs, TGF-ß1 induced the down-regulation of miR-193b, which inhibited cell invasion and metastasis in vivo and in vitro, and down-regulated uPA protein in GC cells.

Neoadjuvant chemotherapy for breast cancer: an evaluation of its efficacy and research progress.

Neoadjuvant chemotherapy (NAC) for breast cancer is widely used in the clinical setting to improve the chance of surgery, breast conservation and quality of life for patients with advanced breast cancer. A more accurate efficacy evaluation system is important for the decision of surgery timing and chemotherapy regimen implementation. However, current methods, encompassing imaging techniques such as ultrasound and MRI, along with non-imaging approaches like pathological evaluations, often fall short in accurately depicting the therapeutic effects of NAC. Imaging techniques are subjective and only reflect macroscopic morphological changes, while pathological evaluation is the gold standard for efficacy assessment but has the disadvantage of delayed results. In an effort to identify assessment methods that align more closely with real-world clinical demands, this paper provides an in-depth exploration of the principles and clinical applications of various assessment approaches in the neoadjuvant chemotherapy process.

Treatment strategies for clear cell renal cell carcinoma: Past, present and future.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent histological subtype of kidney cancer, which is prone to metastasis, recurrence, and resistance to radiotherapy and chemotherapy. The burden it places on human health due to its refractory nature and rising incidence rate is substantial. Researchers have recently determined the ccRCC risk factors and optimized the clinical therapy based on the disease's underlying molecular mechanisms. In this paper, we review the established clinical therapies and novel potential therapeutic approaches for ccRCC, and we support the importance of investigating novel therapeutic options in the context of combining established therapies as a research hotspot, with the goal of providing diversified therapeutic options that promise to address the issue of drug resistance, with a view to the early realization of precision medicine and individualized treatment.

Corrigendum: HER-2 positive primary neuroendocrine neoplasms of the breast with signet ring feature: A case report and review of literature.

[This corrects the article DOI: 10.3389/fonc.2022.1029007.].

Preparing Data for Artificial Intelligence in Pathology with Clinical-Grade Performance.

The pathology is decisive for disease diagnosis but relies heavily on experienced pathologists. In recent years, there has been growing interest in the use of artificial intelligence in pathology (AIP) to enhance diagnostic accuracy and efficiency. However, the impressive performance of deep learning-based AIP in laboratory settings often proves challenging to replicate in clinical practice. As the data preparation is important for AIP, the paper has reviewed AIP-related studies in the PubMed database published from January 2017 to February 2022, and 118 studies were included. An in-depth analysis of data preparation methods is conducted, encompassing the acquisition of pathological tissue slides, data cleaning, screening, and subsequent digitization. Expert review, image annotation, dataset division for model training and validation are also discussed. Furthermore, we delve into the reasons behind the challenges in reproducing the high performance of AIP in clinical settings and present effective strategies to enhance AIP's clinical performance. The robustness of AIP depends on a randomized collection of representative disease slides, incorporating rigorous quality control and screening, correction of digital discrepancies, reasonable annotation, and sufficient data volume. Digital pathology is fundamental in clinical-grade AIP, and the techniques of data standardization and weakly supervised learning methods based on whole slide image (WSI) are effective ways to overcome obstacles of performance reproduction. The key to performance reproducibility lies in having representative data, an adequate amount of labeling, and ensuring consistency across multiple centers. Digital pathology for clinical diagnosis, data standardization and the technique of WSI-based weakly supervised learning will hopefully build clinical-grade AIP.

Preclinical and Basic Research Strategies for Overcoming Resistance to Targeted Therapies in HER2-Positive Breast Cancer.

The amplification of epidermal growth factor receptor 2 (HER2) is associated with a poor prognosis and HER2 gene is overexpressed in approximately 15-30% of breast cancers. In HER2-positive breast cancer patients, HER2-targeted therapies improved clinical outcomes and survival rates. However, drug resistance to anti-HER2 drugs is almost unavoidable, leaving some patients with an unmet need for better prognoses. Therefore, exploring strategies to delay or revert drug resistance is urgent. In recent years, new targets and regimens have emerged continuously. This review discusses the fundamental mechanisms of drug resistance in the targeted therapies of HER2-positive breast cancer and summarizes recent research progress in this field, including preclinical and basic research studies.

Incorporating ultrasound-based lymph node staging significantly improves the performance of a clinical nomogram for predicting preoperative axillary lymph node metastasis in breast cancer.

Models for predicting axillary lymph node metastasis (ALNM) in breast cancer patients are lacking. We aimed to develop an efficient model to accurately predict ALNM. Three hundred fifty-five breast cancer patients were recruited and randomly divided into the training and validation sets. Univariate and multivariate logistic regressions were applied to identify predictors of ALNM. We developed nomograms based on these variables to predict ALNM. The performance of the nomograms was tested using the receiver operating characteristic curve and calibration curve, and a decision curve analysis was performed to assess the clinical utility of the prediction models. The nomograms that included clinical N stage (cN), pathological grade (pathGrade), and hemoglobin accurately predicted ALNM in the training and validation sets (area under the curve [AUC] 0.80 and 0.80, respectively). We then explored the importance of the cN and pathGradesignatures used in the integrated model and developed new nomograms by removing the two variables. The results suggested that the combine-pathGrade nomogram also accurately predicted ALNM in the training and validation sets (AUC 0.78 and 0.78, respectively), but the combine-cN nomogram did not (AUC 0.64 and 0.60, in training and validation sets, respectively). We described a cN-based ALNM prediction model in breast cancer patients, presenting a novel efficient clinical decision nomogram for predicting ALNM.

[Corrigendum] CXCR1 promotes malignant behavior of gastric cancer cells in vitro and in vivo in AKT and ERK1/2 phosphorylation.

Subsequently to the publication of the above article, the authors contacted the Editorial Office to explain that they had inadvertently included data from the same original source in the first row of data panels in Fig. 4B on p. 2191 (showing the results of cell migration assay experiments) to represent two differently performed experiments. Specifically, these images (second and third data panels) containing partially overlapping data corresponded to the 'Vacant­BGC823' in the empty plasmid transfection group and the background 'BGC823 cell' groups, respectively. However, the authors had retained their original data, which they presented to the office for our inspection, and were able to reassemble the data correctly in the figure. The revised version of Fig. 4, showing the replacement data for the 'Vacant­BGC823' and 'BGC823' Migration panels in Fig. 4B, is shown on the next page. The authors are grateful to the Editor of International Journal of Oncology for allowing them this opportunity to publish a Corrigendum, and all the authors agree with its publication. Furthermore, the authors apologize to the readership for any inconvenience caused. [International Journal of Oncology 48: 2184­2196, 2016; DOI: 10.3892/ijo.2016.3428].

HER-2-positive primary neuroendocrine neoplasms of the breast with signet ring feature: A case report and review of literature.

Background: Primary neuroendocrine neoplasm of the breast (BNEN) is an uncommon breast neoplasm, and in most cases, it presents as hormone receptors positive and HER-2 negative. Moreover, in neuroendocrine neoplasms (NENs), the signet ring feature is a rare morphological subtype, and only a few cases have been reported. Here, we report the case of a primary breast neuroendocrine neoplasm with an unusual signet ring cell appearance in this paper. The documentation of this case, combined with a review of the literature, may add to existing knowledge about the outcome and management of this rare tumor. Methods: In the present review, we describe a unique case of HER-2-positive primary BNEN with a signet ring feature that has not been reported in English. Additionally, we performed a literature search of the PubMed and Web of Science databases and calculated statistics for clinical data and follow-up. Results: Our literature search, excluding non-English literature, identified 15 articles with data from 24 cases, including ours. The mean age was 51.25 years (range, 30-79 years), and there were 13 male patients (54%) and 11 female patients (46%). Of the 24 cases, some cases (11/24) were associated with lymph node metastases, a few cases (6/24) had distant metastasis, and the vast majority of cases (23/24) occurred in the digestive system. Primary hepatic signet ring cell neuroendocrine tumor showed slow progression and good prognosis. Lymph node involvement was identified in one of eight (12.5%) documented cases, and one of eight (12.5%) reported cases presented with distant metastatic disease. However, the prognosis of neuroendocrine tumors with signet ring cells in the pancreas and stomach was poor. Lymph node involvement was identified in 9 of 15 (60%) documented cases, and 5 of 15 (33.3%) reported cases presented with distant metastatic disease. Conclusion: NENs with a signet ring feature is uncommon, and this is the first case report of its occurrence in the breast. Current knowledge is limited to anecdotal experience based on case reports and small case series. We provide a literature review to summarize knowledge about this rare entity.

A low-cost pathological image digitalization method based on 5 times magnification scanning.

Background: Digital pathology has aroused widespread interest in modern pathology. The key to digitalization is to scan the whole slide image (WSI) at high magnification. The file size of each WSI at 40 times magnification (40×) may range from 1 gigabyte (GB) to 5 GB depending on the size of the specimen, which leads to huge storage capacity, very slow scanning and network exchange, seriously increasing time and storage costs for digital pathology. Methods: We design a strategy to scan slides with low resolution (LR) (5×), and a superresolution (SR) method is proposed to restore the image details during diagnosis. The method is based on a multiscale generative adversarial network, which can sequentially generate three high-resolution (HR) images: 10×, 20×, and 40×. A dataset consisting of 100,000 pathological images from 10 types of human body systems is used for training and testing. The differences between the generated images and the real images have been extensively evaluated using quantitative evaluation, visual inspection, medical scoring, and diagnosis. Results: The file size of each 5× WSI is approximately 15 Megabytes. The peak-signal-to-noise ratios (PSNRs) of 10× to 40× generated images are 24.167±3.734 dB, 22.272±4.272 dB, and 20.436±3.845 dB, and the structural similarity (SSIM) index values are 0.845±0.089, 0.680±0.150, and 0.559±0.179, which are better than those of other SR networks and conventional digital zoom methods. Visual inspections show that the generated images have details similar to the real images. Visual scoring average with 0.95 confidence interval from three pathologists are 3.630±1.024, 3.700±1.126, and 3.740±1.095, respectively, and the P value of analysis of variance is 0.367, indicating the pathologists confirm that generated images include sufficient information for diagnosis. The average value of the Kappa test of the diagnoses of paired generated and real images is 0.990, meaning the diagnosis of generated images is highly consistent with that of the real images. Conclusions: The proposed method can generate high-quality 10×, 20×, 40× images from 5× images, which can effectively reduce the time and storage costs of digitalization up to 1/64 of the previous costs, which shows the potential for clinical applications and is expected to be an alternative digitalization method after large-scale evaluation.

eEF2K promotes PD-L1 stabilization through inactivating GSK3ß in melanoma.

BACKGROUND: Immune checkpoint blockade (ICB) targeting programmed death ligand-1 (PD-L1)/programmed cell death protein-1 (PD-1) pathway has become an attractive strategy for cancer treatment; however, unsatisfactory efficacy has limited its clinical benefits. Therefore, a more comprehensive understanding of the regulation of PD-L1 expression is essential for developing more effective cancer immunotherapy. Recent studies have revealed the important roles of eukaryotic elongation factor 2 kinase (eEF2K) in promoting epithelial-mesenchymal transition (EMT), angiogenesis, tumor cell migration and invasion; nevertheless, the exact role of eEF2K in the regulation of tumor immune microenvironment (TIME) remains largely unknown. METHODS: In this study, we used a cohort of 38 patients with melanoma who received anti-PD-1 treatment to explore the association between eEF2K expression and immunotherapy efficacy against melanoma. Immunoprecipitation-mass spectrometry analysis and in vitro assays were used to examine the role and molecular mechanism of eEF2K in regulating PD-L1 expression. We also determined the effects of eEF2K on tumor growth and cytotoxicity of CD8+ T cells in TIME in a mouse melanoma model. We further investigated the efficacy of the eEF2K inhibition in combination with anti-PD-1 treatment in vivo. RESULTS: High eEF2K expression is correlated with better therapeutic response and longer survival in patients with melanoma treated with PD-1 monoclonal antibody (mAb). Moreover, eEF2K protein expression is positively correlated with PD-L1 protein expression. Mechanistically, eEF2K directly bound to and inactivated glycogen synthase kinase 3 beta (GSK3ß) by phosphorylating it at serine 9 (S9), leading to PD-L1 protein stabilization and upregulation, and subsequently tumor immune evasion. Knockdown of eEF2K decreased PD-L1 expression and enhanced CD8+ T cell activity, thus dramatically attenuating murine B16F10 melanoma growth in vivo. Clinically, p-GSK3ß/S9 expression is positively correlated with the expressions of eEF2K and PD-L1, and the response to anti-PD-1 immunotherapy. Furthermore, eEF2K inhibitor, NH125 treatment or eEF2K knockdown enhanced the efficacy of PD-1 mAb therapy in a melanoma mouse model. CONCLUSIONS: Our results suggest that eEF2K may serve as a biomarker for predicting therapeutic response and prognosis in patients receiving anti-PD-1 therapy, reveal a vital role of eEF2K in regulating TIME by controlling PD-L1 expression and provide a potential combination therapeutic strategy of eEF2K inhibition with ICB therapy.

Breast Cancer Molecular Subtype Prediction on Pathological Images with Discriminative Patch Selection and Multi-Instance Learning.

Molecular subtypes of breast cancer are important references to personalized clinical treatment. For cost and labor savings, only one of the patient's paraffin blocks is usually selected for subsequent immunohistochemistry (IHC) to obtain molecular subtypes. Inevitable block sampling error is risky due to the tumor heterogeneity and could result in a delay in treatment. Molecular subtype prediction from conventional H&E pathological whole slide images (WSI) using the AI method is useful and critical to assist pathologists to pre-screen proper paraffin block for IHC. It is a challenging task since only WSI-level labels of molecular subtypes from IHC can be obtained without detailed local region information. Gigapixel WSIs are divided into a huge amount of patches to be computationally feasible for deep learning, while with coarse slide-level labels, patch-based methods may suffer from abundant noise patches, such as folds, overstained regions, or non-tumor tissues. A weakly supervised learning framework based on discriminative patch selection and multi-instance learning was proposed for breast cancer molecular subtype prediction from H&E WSIs. Firstly, co-teaching strategy using two networks was adopted to learn molecular subtype representations and filter out some noise patches. Then, a balanced sampling strategy was used to handle the imbalance in subtypes in the dataset. In addition, a noise patch filtering algorithm that used local outlier factor based on cluster centers was proposed to further select discriminative patches. Finally, a loss function integrating local patch with global slide constraint information was used to fine-tune MIL framework on obtained discriminative patches and further improve the prediction performance of molecular subtyping. The experimental results confirmed the effectiveness of the proposed AI method and our models outperformed even senior pathologists, which has the potential to assist pathologists to pre-screen paraffin blocks for IHC in clinic.

MoS2-based nanocomposites for cancer diagnosis and therapy.

Molybdenum is a trace dietary element necessary for the survival of humans. Some molybdenum-bearing enzymes are involved in key metabolic activities in the human body (such as xanthine oxidase, aldehyde oxidase and sulfite oxidase). Many molybdenum-based compounds have been widely used in biomedical research. Especially, MoS2-nanomaterials have attracted more attention in cancer diagnosis and treatment recently because of their unique physical and chemical properties. MoS2 can adsorb various biomolecules and drug molecules via covalent or non-covalent interactions because it is easy to modify and possess a high specific surface area, improving its tumor targeting and colloidal stability, as well as accuracy and sensitivity for detecting specific biomarkers. At the same time, in the near-infrared (NIR) window, MoS2 has excellent optical absorption and prominent photothermal conversion efficiency, which can achieve NIR-based phototherapy and NIR-responsive controlled drug-release. Significantly, the modified MoS2-nanocomposite can specifically respond to the tumor microenvironment, leading to drug accumulation in the tumor site increased, reducing its side effects on non-cancerous tissues, and improved therapeutic effect. In this review, we introduced the latest developments of MoS2-nanocomposites in cancer diagnosis and therapy, mainly focusing on biosensors, bioimaging, chemotherapy, phototherapy, microwave hyperthermia, and combination therapy. Furthermore, we also discuss the current challenges and prospects of MoS2-nanocomposites in cancer treatment.