circLIFR-007 reduces liver metastasis via promoting hnRNPA1 nuclear export and YAP phosphorylation in breast cancer.

Cancer metastasis is the major cause of death in patients with breast cancer (BC). The liver is a common site of breast cancer metastasis, and the 5-year survival rate of patients with breast cancer liver metastases (BCLMs) is only about 8.5 %. CircRNAs are involved in a variety of cancer-related pathological behaviors, and their unique structure and resistance to RNA degradation enable them to serve as ideal diagnostic biomarkers and therapeutic targets. Therefore, it is important to investigate the role and molecular mechanism of circRNAs in cancer metastasis. CircLIFR-007 was identified as a critical circular RNA in BC metastasis by circRNAs microarray and qRT-PCR experiment. Cell function assays were performed to explore the effect of circLIFR-007 in breast cancer cells. Experiments in vivo validated the function of circLIFR-007. Several molecular assays were performed to investigate the underlying mechanisms. We found that circLIFR-007 acted as a negative controller in breast cancer liver metastasis. CircLIFR-007 upregulates the phosphorylation level of YAP by exporting hnRNPA1 to promote the combination between hnRNPA1 and YAP in the cytoplasm. Overexpression of circLIFR-007 suppressed the expression of liver metastasis-related proteins, SREBF1 and SNAI1, which were regulated by transcription factor YAP. Functionally, circLIFR-007 inhibits the proliferation and metastasis of breast cancer cells both in vivo and in vitro.

Advancements in technology for characterizing the tumor immune microenvironment.

Immunotherapy plays a key role in cancer treatment, however, responses are limited to a small number of patients. The biological basis for the success of immunotherapy is the complex interaction between tumor cells and tumor immune microenvironment (TIME). Historically, research on tumor immune constitution was limited to the analysis of one or two markers, more novel technologies are needed to interpret the complex interactions between tumor cells and TIME. In recent years, major advances have already been made in depicting TIME at a considerably elevated degree of throughput, dimensionality and resolution, allowing dozens of markers to be labeled simultaneously, and analyzing the heterogeneity of tumour-immune infiltrates in detail at the single cell level, depicting the spatial landscape of the entire microenvironment, as well as applying artificial intelligence (AI) to interpret a large amount of complex data from TIME. In this review, we summarized emerging technologies that have made contributions to the field of TIME, and provided prospects for future research.

Deep lymph node enlargement and renal failure caused by hypercalcemia­associated sarcoidosis: A case report.

Sarcoidosis is a rare disease that severely affects the lungs and superficial lymph nodes. In addition, this disease can also affect the skin, eyes and kidneys to varying degrees. The present report described a 32-year-old male patient who was admitted to Renmin Hospital of Wuhan University (Wuhan, China) due to joint pain in the extremities. He was diagnosed with uncorrectable hypercalcemia. A lymph node biopsy revealed the hypercalcemia to be associated with sarcoidosis, with the patient also demonstrating renal failure and lymph node enlargement. Administration of glucocorticoids provided benefits in terms of both primary and recurrent sarcoidosis, which also improved and preserved renal function. After being prescribed with oral prednisone treatment, blood calcium levels returned to normal, which indicated markedly improving renal function. However, the discontinuation of glucocorticoids for 2 months resulted in increased serum calcium and creatinine levels, both of which returned to abnormal levels. Overall, the present case report suggests that clinicians should actively perform sarcoidosis treatment in clinical practice to overcome any unexpected results associated with organ damage.

The proportion of tumour stroma predicts response to treatment of immune checkpoint inhibitor in combination with chemotherapy in patients with stage IIIB-IV non-small cell lung cancer.

AIMS: Immunotherapy has brought a new era to cancer treatment, yet we lack dependable predictors for its effectiveness. This study explores the predictive significance of intratumour stroma proportion (iTSP) for treatment success and prognosis in non-small cell lung cancer (NSCLC) patients undergoing treatment with immune check-point inhibitors (ICIs) together with chemotherapy. METHODS AND RESULTS: We retrospectively collected data from patients with unresectable stage IIIB-IV NSCLC who were treated with first-line ICIs and chemotherapy. Each patient received a confirmed pathological diagnosis, and the pathologist evaluated the iTSP on haematoxylin and eosin (H&E)-stained sections of diagnostic tissue slides. Among the 102 H&E-stained biopsy samples, 61 (59.8%) were categorised as stroma-L (less than 50% iTSP), while 41 (40.2%) were classified as stroma-H (more than 50% iTSP). We observed that the stroma-L group exhibited a significantly better objective response rate (ORR) (72.1 versus 51.2%, P = 0.031) and deeper response depth (DpR) (-50.49 ± 28.79% versus -35.83 ± 29.91%, P = 0.015) compared to the stroma-H group. Furthermore, the stroma-L group showed longer median progression-free survival (PFS) (9.6 versus 6.0 months, P = 0.011) and overall survival (OS) (24.0 versus 12.2 months, P = 0.001) compared to the stroma-H group. Multivariate Cox proportional hazards regression analysis indicated that iTSP was a highly significant prognostic factor for both PFS [hazard ratio (HR) = 1.713; P = 0.030] and OS (HR = 2.225; P = 0.003). CONCLUSION: Our findings indicate that a lower iTSP corresponds to improved clinical outcomes and greater DpR in individuals with stage IIIB-IV NSCLC treated with first-line ICIs and chemotherapy. The iTSP could potentially serve as a predictive biomarker for ICIs therapy response.

Expert Consensus on the Diagnosis and Treatment of NRG1/2 Gene Fusion Solid Tumors.

The fusion genes NRG1 and NRG2 , members of the epidermal growth factor (EGF) receptor family, have emerged as key drivers in cancer. Upon fusion, NRG1 retains its EGF-like active domain, binds to the ERBB ligand family, and triggers intracellular signaling cascades, promoting uncontrolled cell proliferation. The incidence of NRG1 gene fusion varies across cancer types, with lung cancer being the most prevalent at 0.19 to 0.27%. CD74 and SLC3A2 are the most frequently observed fusion partners. RNA-based next-generation sequencing is the primary method for detecting NRG1 and NRG2 gene fusions, whereas pERBB3 immunohistochemistry can serve as a rapid prescreening tool for identifying NRG1 -positive patients. Currently, there are no approved targeted drugs for NRG1 and NRG2 . Common treatment approaches involve pan-ERBB inhibitors, small molecule inhibitors targeting ERBB2 or ERBB3, and monoclonal antibodies. Given the current landscape of NRG1 and NRG2 in solid tumors, a consensus among diagnostic and treatment experts is proposed, and clinical trials hold promise for benefiting more patients with NRG1 and NRG2 gene fusion solid tumors.

Methylation of GPRC5A promotes liver metastasis and docetaxel resistance through activating mTOR signaling pathway in triple negative breast cancer.

AIMS: This study aims to explore the function and mechanism of G Protein-coupled receptor class C group 5 member A (GPRC5A) in docetaxel-resistance and liver metastasis of breast cancer. METHODS: Single-cell RNA transcriptomic analysis and bioinformatic analysis are used to screen relevant genes in breast cancer metastatic hepatic specimens. MeRIP, dual-luciferase analysis and bioinformation were used to detect m6A modulation. Mass spectrometry (MS), co-inmunoprecipitation (co-IP) and immunofluorescence colocalization were executed to explore the mechanism of GPRC5A in breast cancer cells. RESULT: GPRC5A was upregulated in triple-negative breast cancer (TNBC) and was associated with a poor prognosis. In vitro and in vivo experiments demonstrated that knockdown of GPRC5A alleviated metastasis and resistance to docetaxel in TNBC. Overexpression of GPRC5A had the opposite effects. The m6A methylation of GPRC5A mRNA was modulated by METTL3 and YTHDF1, which facilitates its translation. GPRC5A inhibited the ubiquitination-dependent degradation of LAMTOR1, resulting in the recruitment of mTORC1 to lysosomes and activating the mTORC1/p70s6k signaling pathway. CONCLUSION: METTL3/YTHDF1 axis up-regulates GPRC5A expression by m6A methylation. GPRC5A activates mTORC1/p70s6k signaling pathway by recruiting mTORC1 to lysosomes, consequently promotes docetaxel-resistance and liver metastasis.

Colorectal cancer histopathology image analysis: A comparative study of prognostic values of automatically extracted morphometric nuclear features in multispectral and red-blue-green imagery.

OBJECTIVES: Multispectral imaging (MSI) has been utilized to predict the prognosis of colorectal cancer (CRC) patients, however, our understanding of the prognostic value of nuclear morphological parameters of bright-field MSI in CRC is still limited. This study was designed to compare the efficiency of MSI and standard red-green-blue (RGB) images in predicting the prognosis of CRC. METHODS: We compared the efficiency of MS and conventional RGB images on the quantitative assessment of hematoxylin-eosin (HE) stained histopathology images. A pipeline was developed using a pixel-wise support vector machine (SVM) classifier for gland-stroma segmentation, and a marker-controlled watershed algorithm was used for nuclei segmentation. The correlation between extracted morphological parameters and the five-year disease-free survival (5-DFS) was analyzed. RESULTS: Forty-seven nuclear morphological parameters were extracted in total. Based on Kaplan-Meier analysis, eight features derived from MS images and seven featured derived from RGB images were significantly associated with 5-DFS, respectively. Compared with RGB images, MSI showed higher accuracy, precision, and Dice index in nuclei segmentation. Multivariate analysis indicated that both integrated parameters 1 (factors negatively correlated with CRC prognosis including nuclear number, circularity, eccentricity, major axis length) and 2 (factors positively correlated with CRC prognosis including nuclear average area, area perimeter, total area/total perimeter ratio, average area/perimeter ratio) in MS images were independent prognostic factors of 5-DFS, in contrast with only integrated parameter 1 (P<0.001) in RGB images. More importantly, the quantification of HE-stained MS images displayed higher accuracy in predicting 5-DFS compared with RGB images (76.9% vs 70.9%). CONCLUSIONS: Quantitative evaluation of HE-stained MS images could yield more information and better predictive performance for CRC prognosis than conventional RGB images, thereby contributing to precision oncology.

Demethylase FTO-Mediated m6A Modification of lncRNA MEG3 Activates Neuronal Pyroptosis via NLRP3 Signaling in Cerebral Ischemic Stroke.

Neuronal death following ischemia is the primary cause of death and disability in patients with ischemic stroke. N6-methyladenosine (m6A) modification plays essential role in various physiological and pathological conditions, but its role and mechanism in ischemic neuronal death remain unclear. In the present study, neuronal pyroptosis was an important event in brain injury caused by ischemic stroke, and the upregulation of long non-coding RNA (lncRNA) maternally expressed gene 3 (MEG3) following cerebral ischemia was a key factor in activating ischemic neuronal pyroptosis via NLRP3/caspase-1/GSDMD signaling. Moreover, we first demonstrated that the demethylase fat mass and obesity-associated protein (FTO), which was decreased following ischemia, regulated MEG3 expression in an m6A-dependent manner by affecting its stability, thereby activating neuronal pyroptosis via NLRP3/caspase-1/GSDMD signaling, and ultimately leading to ischemic brain damage. Therefore, the present study provides new insights for the mechanism of ischemic stroke, and suggests that FTO may be a potential therapeutic target for ischemic stroke.

Primary acinic cell carcinoma of the breast: A case report and literature review.

Acinic cell carcinoma (ACCA), a type of malignant epithelial neoplasm, tends to occur in the parotid gland, and is occasionally found within the breast. Published literature regarding primary ACCA of the breast is scarce, and the number of reports may be fewer than 100. At present, full clinical details have not been published. As an extremely rare disorder, ACCA cannot be definitively diagnosed depending on microscopic structure alone and often requires the assistance of immunohistochemistry. Currently, universal therapies are not available. Here, we present a 47-year-old patient with a history of a palpable mass in the outer upper quadrant of the left breast for more than 2 years, which had obviously increased in size in the last half year. This patient was definitively diagnosed with primary ACCA of the breast. Neoadjuvant chemotherapy was performed preoperatively, and drug sensitivity tests based on primary tumor cells were conducted after surgery and successfully screened chemotherapy schemes for the patient's greater benefit. The whole treatment course followed the guidelines for invasive breast cancer. The patient was free of symptoms for 14 months after surgery. Long-term follow-up is in progress. Altogether, to further broaden the understanding of primary ACCA of the breast, we detail the diagnosis and treatment of one patient and review the relevant literature.

Expert consensus on the diagnosis and treatment of RET gene fusion non-small cell lung cancer in China.

The rearranged during transfection (RET) gene is one of the receptor tyrosine kinases and cell-surface molecules responsible for transmitting signals that regulate cell growth and differentiation. In non-small cell lung cancer (NSCLC), RET fusion is a rare driver gene alteration associated with a poor prognosis. Fortunately, two selective RET inhibitors (sRETi), namely pralsetinib and selpercatinib, have been approved for treating RET fusion NSCLC due to their remarkable efficacy and safety profiles. These inhibitors have shown the ability to overcome resistance to multikinase inhibitors (MKIs). Furthermore, ongoing clinical trials are investigating several second-generation sRETis that are specifically designed to target solvent front mutations, which pose a challenge for first-generation sRETis. The effective screening of patients is the first crucial step in the clinical application of RET-targeted therapy. Currently, four methods are widely used for detecting gene rearrangements: next-generation sequencing (NGS), reverse transcription-polymerase chain reaction (RT-PCR), fluorescence in situ hybridization (FISH), and immunohistochemistry (IHC). Each of these methods has its advantages and limitations. To streamline the clinical workflow and improve diagnostic and treatment strategies for RET fusion NSCLC, our expert group has reached a consensus. Our objective is to maximize the clinical benefit for patients and promote standardized approaches to RET fusion screening and therapy.

Integrative multi-omics analyses unravel the immunological implication and prognostic significance of CXCL12 in breast cancer.

Background: CXCL12 is a vital factor in physiological and pathological processes, by inducing migration of multiple cells. We aimed to comprehensively detect the role of CXCL12 in breast cancer, and explore novel CXCL12-related biomarkers through integrative multi-omics analyses to build a powerful prognostic model for breast cancer patients. Methods: Immunohistochemistry analysis of the tissue microarray was performed to evaluate the correlation between CXCL12 expression levels and breast cancer patient outcomes. Combined single-nucleus and spatial transcriptomics data was used to uncover the expression distribution of CXCL12 in breast cancer microenvironment. CXCL12-related genes were identified by WGCNA analysis. Univariate Cox and LASSO regression analyses were then conducted to screen prognostic genes from above CXCL12-related genes, followed by the construction of the CXCL12-related prognostic signature, identification of risk groups, and external validation of the prognostic signature. Analyses of biological function, mutation landscape, immune checkpoint genes and immune cells, were performed to further reveal the differences between high/low-risk groups. Paired single-cell RNA-seq and bulk RNA-seq were analyzed to further disclose the association between the risk score and the complex tumor immune microenvironment. To screen potential therapeutic agents for breast cancer patients, analyses of gene-drug correlation and sensitivity to immunotherapy were conducted. Results: High expression of CXCL12 was linked with a prolonged survival in breast cancer. A total of 402 genes were identified by WGCNA analysis and 11 genes, covering VAT1L, TMEM92, SDC1, RORB, PCSK9, NRN1, NACAD, JPH3, GJA1, BMP8B and ADAMTS2, were screened as the candidate prognostic genes. Next, the prognostic signature was built and validated using these genes to predict the outcomes of breast cancers. The high-risk group patients exhibited significantly inferior prognoses. The combination of the risk score and tumor mutational burden (TMB) had remarkably improved performance in predicting patient outcomes. Besides, high-risk group patients showed higher infiltration of M2-like macrophages. Finally, several potential anticancer drugs were identified. The high-risk group patients were more sensitive to immunotherapy but resistant to docetaxel. Conclusions: CXCL12 has important immunological implication and prognostic significance in breast cancer. The CXCL12-related prognostic model could well predict the prognosis and treatment response of breast cancers.

A novel transcription factor SIPA1: identification and verification in triple-negative breast cancer.

Transcription factors (TFs) regulate the expression of genes responsible for cell growth, differentiation, and responses to environmental factors. In this study, we demonstrated that signal-induced proliferation-associated 1 (SIPA1), known as a Rap-GTPase-activating protein, bound DNA and served as a TF. Importin ß1 was found to interact with SIPA1 upon fibronectin treatment. A TGAGTCAB motif was recognized and bound by DNA-binding region (DBR) of SIPA1, which was confirmed by electrophoretic mobility shift assay. SIPA1 regulated the transcription of multiple genes responsible for signal transduction, DNA synthesis, cell adhesion, cell migration, and so on. Transcription of fibronectin 1, which is crucial for cell junction and migration of triple-negative breast cancer (TNBC) cells, was regulated by SIPA1 in a DBR-dependent manner both in vivo and in vitro. Furthermore, single-cell transcriptome sequencing analysis of specimens from a metastatic TNBC patient revealed that SIPA1 was highly expressed in metastatic TNBC. Hence, this study demonstrated that SIPA1 served as a TF, promoting TNBC migration, invasion, and metastasis.

Exploring the glycolytic cross-talk genes between inflammatory bowel disease and colorectal cancer.

Patients with inflammatory bowel disease (IBD) have a higher risk of developing colorectal cancer (CRC). Glycolysis is involved in the development of both IBD and CRC. However, the mechanisms and outcomes of glycolysis shared between IBD and CRC remain unclear. This study aimed to explore the glycolytic cross-talk genes between IBD and CRC integrating bioinformatics and machine learning. With WGCNA, LASSO, COX, and SVM-RFE algorithms, P4HA1 and PMM2 were identified as glycolytic cross-talk genes. The independent risk signature of P4HA1 and PMM2 was constructed to predict the overall survival rate of patients with CRC. The risk signature correlated with clinical characteristics, prognosis, tumor microenvironment, immune checkpoint, mutants, cancer stemness, and chemotherapeutic drug sensitivity. CRC patients with high risk have increased microsatellite instability, tumor mutation burden. The nomogram integrating risk score, tumor stage, and age showed high accuracy for predicting overall survival rate. In addition, the diagnostic model for IBD based on P4HA1 and PMM2 showed excellent accuracy. Finally, immunohistochemistry results showed that P4HA1 and PMM2 were significantly upregulated in IBD and CRC. Our study reveals the presence of glycolytic cross-talk genes P4HA1 and PMM2 between IBD and CRC. This may prove to be beneficial in advancing research on the mechanism of development of IBD-associated CRC.

Chinese expert consensus on the diagnosis and treatment of malignant pleural mesothelioma.

Malignant pleural mesothelioma (MPM) is a malignant tumor originating from the pleura, and its incidence has been increasing in recent years. Due to the insidious onset and strong local invasiveness of MPM, most patients are diagnosed in the late stage and early screening and treatment for high-risk populations are crucial. The treatment of MPM mainly includes surgery, chemotherapy, and radiotherapy. Immunotherapy and electric field therapy have also been applied, leading to further improvements in patient survival. The Mesothelioma Group of the Yangtze River Delta Lung Cancer Cooperation Group (East China LUng caNcer Group, ECLUNG; Youth Committee) developed a national consensus on the clinical diagnosis and treatment of MPM based on existing clinical research evidence and the opinions of national experts. This consensus aims to promote the homogenization and standardization of MPM diagnosis and treatment in China, covering epidemiology, diagnosis, treatment, and follow-up.

Function of BrSOC1b gene in flowering regulation of Chinese cabbage and its protein interaction.

MAIN CONCLUSION: BrSOC1b may promote early flowering of Chinese cabbage by acting on BrAGL9 a, BrAGL9 b, BrAGL2 and BrAGL8 proteins. SOC1 is a flowering signal integrator that acts as a key regulator in controlling plant flowering time. This study focuses on the cloning of the open reading frame of SOC1b (BrSOC1b, Gene ID: Bra000393) gene, and analyzes its structure and phylogenetic relationships. Additionally, various techniques such as vector construction, transgenic technology, virus-induced gene silencing technology, and protein interaction technology were employed to investigate the function of the BrSOC1b gene and its interactions with other proteins. The results indicate that BrSOC1b consists of 642 bp and encodes 213 amino acids. It contains conserved domains such as the MADS domain, K (keratin-like) domain, and SOC1 box. The phylogenetic analysis reveals that BrSOC1b shares the closest homology with BjSOC1 from Brassica juncea. Tissue localization analysis demonstrates that BrSOC1b exhibits the highest expression in the stem during the seedling stage and the highest expression in flowers during the early stage of pod formation. Sub-cellular localization analysis reveals that BrSOC1b is localized in the nucleus and plasma membrane. Furthermore, through genetic transformation of the BrSOC1b gene, it was observed that Arabidopsis thaliana plants expressing BrSOC1b flowered earlier and bolted earlier than wild-type plants. Conversely, Chinese cabbage plants with silenced BrSOC1b exhibited delayed bolting and flowering compared to the control plants. These findings indicate that BrSOC1b promotes early flowering in Chinese cabbage. Yeast two-hybrid and quantitative real-time PCR (qRT-PCR) analyses suggest that BrSOC1b may participate in the regulation of flowering by interacting with BrAGL9a, BrAGL9b, BrAGL2, and BrAGL8 proteins. Overall, this research holds significant implications for the analysis of key genes involved in regulating bolting and flowering in Chinese cabbage, as well as for enhancing germplasm innovation in Chinese cabbage breeding.

Case Report: Gastric cancer with chondromyxoid matrix similar matrix-producing metaplastic breast carcinoma: report of an undescribed entity.

Gastric cancer is a malignant epithelial neoplasm of the stomach, including adenocarcinoma, squamous cell carcinoma, adenosquamous carcinoma, undifferentiated carcinoma, gastroblastoma and neuroendocrine neoplasms, without gastric metaplastic carcinoma. We describe a 69-year-old male patient with gastric cancer who presented with a novel, biphasic histologic morphology with one component consisting of poorly differentiated adenocarcinoma and the other component consisting of chondromyxoid matrix with adenocarcinoma transition to, between the two components without a spindle cell component. The histological morphology of this case is similar to matrix-producing metaplastic breast carcinoma. Therefore, we diagnose this case as gastric carcinoma with chondromyxoid matrix similar matrix-producing metaplastic breast carcinoma.

Predicting Lymph Node Metastasis Status from Primary Muscle-Invasive Bladder Cancer Histology Slides Using Deep Learning: A Retrospective Multicenter Study.

BACKGROUND: Accurate prediction of lymph node metastasis (LNM) status in patients with muscle-invasive bladder cancer (MIBC) before radical cystectomy can guide the use of neoadjuvant chemotherapy and the extent of pelvic lymph node dissection. We aimed to develop and validate a weakly-supervised deep learning model to predict LNM status from digitized histopathological slides in MIBC. METHODS: We trained a multiple instance learning model with an attention mechanism (namely SBLNP) from a cohort of 323 patients in the TCGA cohort. In parallel, we collected corresponding clinical information to construct a logistic regression model. Subsequently, the score predicted by the SBLNP was incorporated into the logistic regression model. In total, 417 WSIs from 139 patients in the RHWU cohort and 230 WSIs from 78 patients in the PHHC cohort were used as independent external validation sets. RESULTS: In the TCGA cohort, the SBLNP achieved an AUROC of 0.811 (95% confidence interval [CI], 0.771-0.855), the clinical classifier achieved an AUROC of 0.697 (95% CI, 0.661-0.728) and the combined classifier yielded an improvement to 0.864 (95% CI, 0.827-0.906). Encouragingly, the SBLNP still maintained high performance in the RHWU cohort and PHHC cohort, with an AUROC of 0.762 (95% CI, 0.725-0.801) and 0.746 (95% CI, 0.687-0.799), respectively. Moreover, the interpretability of SBLNP identified stroma with lymphocytic inflammation as a key feature of predicting LNM presence. CONCLUSIONS: Our proposed weakly-supervised deep learning model can predict the LNM status of MIBC patients from routine WSIs, demonstrating decent generalization performance and holding promise for clinical implementation.

A Weakly Supervised Deep Learning Model and Human-Machine Fusion for Accurate Grading of Renal Cell Carcinoma from Histopathology Slides.

(1) Background: The Fuhrman grading (FG) system is widely used in the management of clear cell renal cell carcinoma (ccRCC). However, it is affected by observer variability and irreproducibility in clinical practice. We aimed to use a deep learning multi-class model called SSL-CLAM to assist in diagnosing the FG status of ccRCC patients using digitized whole slide images (WSIs). (2) Methods: We recruited 504 eligible ccRCC patients from The Cancer Genome Atlas (TCGA) cohort and obtained 708 hematoxylin and eosin-stained WSIs for the development and internal validation of the SSL-CLAM model. Additionally, we obtained 445 WSIs from 188 ccRCC eligible patients in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) cohort as an independent external validation set. A human-machine fusion approach was used to validate the added value of the SSL-CLAM model for pathologists. (3) Results: The SSL-CLAM model successfully diagnosed the five FG statuses (Grade-0, 1, 2, 3, and 4) of ccRCC, and achieved AUCs of 0.917 and 0.887 on the internal and external validation sets, respectively, outperforming a junior pathologist. For the normal/tumor classification (Grade-0, Grade-1/2/3/4) task, the SSL-CLAM model yielded AUCs close to 1 on both the internal and external validation sets. The SSL-CLAM model achieved a better performance for the two-tiered FG (Grade-0, Grade-1/2, and Grade-3/4) task, with AUCs of 0.936 and 0.915 on the internal and external validation sets, respectively. The human-machine diagnostic performance was superior to that of the SSL-CLAM model, showing promising prospects. In addition, the high-attention regions of the SSL-CLAM model showed that with an increasing FG status, the cell nuclei in the tumor region become larger, with irregular contours and increased cellular pleomorphism. (4) Conclusions: Our findings support the feasibility of using deep learning and human-machine fusion methods for FG classification on WSIs from ccRCC patients, which may assist pathologists in making diagnostic decisions.

Acrylamide interferes with autophagy and induces apoptosis in Neuro-2a cells by interfering with TFEB-regulated lysosomal function.

Acrylamide (ACR), a well-documented human neurotoxicant that is widely exists in starchy foods. More than 30% of human daily energy is provided by ACR-containing foods. Evidence indicated that ACR can induce apoptosis and inhibit autophagy, but the mechanisms are limited. Transcription Factor EB (TFEB) is a major transcriptional regulator of the autophagy-lysosomal biogenesis that regulates autophagy processes and cell degradation. Our study aimed to investigated the potential mechanisms of TFEB-regulated lysosomal function in ACR-caused autophagic flux inhibition and apoptosis in Neuro-2a cells. Our results found that ACR exposure inhibited the autophagic flux, as revealed by the elevated LC3-II/LC3-I and p62 levels and a notable increased autophagosomes. ACR exposure reduced the amounts of LAMP1 and mature cathepsin D and caused an accumulation of ubiquitinated proteins, which suggests lysosomal dysfunction. In addition, ACR increased cellular apoptosis via decreasing Bcl-2 expression, increasing Bax and cleaved caspase-3 expression, and raising the apoptotic rate. Interestingly, TFEB overexpression alleviated the ACR-induced lysosomal dysfunction, and then mitigated the autophagy flux inhibition and cellular apoptosis. On the other hand, TFEB knockdown exacerbated the ACR-induced lysosomal dysfunction, autophagy flux inhibition, and cellular apoptosis. These findings strongly suggested that TFEB- regulated lysosomal function is responsible for ACR-caused autophagic flux inhibition and apoptosis in Neuro-2a cells. The present study hopes to explore new sensitive indicators in the mechanism of ACR neurotoxicity and thus provide new targets for the prevention and treatment of ACR intoxication.