A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathologists. Here we sought to develop and validate a deep learning model capable of precisely distinguishing PCNSL from non-PCNSL lesions, especially glioma, using hematoxylin and eosin (H&E)-stained frozen whole-slide images. Also, we compared its performance against pathologists of varying expertise. Additionally, a human-machine fusion approach integrated both model and pathologic diagnostics. In external cohorts, LGNet achieved AUROCs of 0.965 and 0.972 in distinguishing PCNSL from glioma and AUROCs of 0.981 and 0.993 in differentiating PCNSL from non-PCNSL lesions. Outperforming several pathologists, LGNet significantly improved diagnostic performance, further augmented to some extent by fusion approach. LGNet's proficiency in frozen section analysis and its synergy with pathologists indicate its valuable role in intraoperative diagnosis, particularly in discriminating PCNSL from glioma, alongside other lesions.

Prognostic Nutritional Index Predicts Efficacy and Immune-Related Adverse Events of First-Line Chemoimmunotherapy in Patients with Extensive-Stage Small-Cell Lung Cancer.

Background: Currently, there is a lack of well-established markers to predict the efficacy of chemoimmunotherapy in small-cell lung cancer (SCLC). Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), advanced lung cancer inflammation index (ALI) and prognostic nutritional index (PNI) are associated with prognosis in several tumors, whereas their predictive role in SCLC remains unclear. Methods: A retrospective study was conducted at Sun Yat-sen University Cancer Center, involving extensive-stage SCLC (ES-SCLC) patients who received first-line chemoimmunotherapy between January 2020 and December 2021. Peripheral blood biomarkers were extracted from medical records and their correlation with prognosis and immune-related adverse events (IRAEs) was analyzed. Results: A total of 114 patients were included. Patients with a low PLR, high ALI and high PNI had prolonged progression-free survival (PFS) compared to those with a high PLR, low ALI and low PNI. Patients with a low NLR, low PLR, high ALI and high PNI had prolonged overall survival (OS) compared to those with a high NLR, high PLR, low ALI and low PNI. Cox regression model showed that PNI was an independent risk factor for both PFS and OS. ROC curve showed that PNI outperforms NLR, PLR and ALI in predicting both PFS and OS. The PNI-based nomogram demonstrated strong predictive capability for both PFS and OS. In addition, there was a significant correlation between PNI and IRAEs. Conclusion: A high baseline PNI might be associated with improved prognosis and the occurrence of IRAEs in ES-SCLC patients treated with first-line chemoimmunotherapy.

An interpretable deep learning model for identifying the morphological characteristics of dMMR/MSI-H gastric cancer.

Accurate tumor diagnosis by pathologists relies on identifying specific morphological characteristics. However, summarizing these unique morphological features in tumor classifications can be challenging. Although deep learning models have been extensively studied for tumor classification, their indirect and subjective interpretation obstructs pathologists from comprehending the model and discerning the morphological features accountable for classifications. In this study, we introduce a new approach utilizing Style Generative Adversarial Networks, which enables a direct interpretation of deep learning models to detect significant morphological characteristics within datasets representing patients with deficient mismatch repair/microsatellite instability-high gastric cancer. Our approach effectively identifies distinct morphological features crucial for tumor classification, offering valuable insights for pathologists to enhance diagnostic accuracy and foster professional growth.

Dual specific phosphatase 4 suppresses ferroptosis and enhances sorafenib resistance in hepatocellular carcinoma.

AIMS: This investigation aims to elucidate the mechanism underlying sorafenib-induced ferroptosis in hepatocellular carcinoma (HCC). METHODS: The role of dual specificity phosphatase 4 (DUSP4) in sorafenib-treated HCC was investigated using comprehensive assessments both in vitro and in vivo, including Western blotting, qRT-PCR, cell viability assay, lipid reactive oxygen species (ROS) assay, immunohistochemistry, and xenograft tumor mouse model. Additionally, label-free quantitative proteomics was employed to identify potential proteins associated with DUSP4. RESULTS: Our study revealed that suppression of DUSP4 expression heightens the susceptibility of HCC cells to ferroptosis inducers, specifically sorafenib and erastin, in both in vitro and in vivo settings. Furthermore, we identified DUSP4-mediated regulation of key ferroptosis-related markers, such as ferritin light chain (FTL) and ferritin heavy chain 1 (FTH1). Notably, label-free quantitative proteomics unveiled the phosphorylation of threonine residue T148 on YTH Domain Containing 1 (YTHDC1) by DUSP4. Further investigations unraveled that YTHDC1, functioning as an mRNA nuclear export regulator, is a direct target of DUSP4, orchestrating the subcellular localization of FTL and FTH1 mRNAs. Significantly, our study highlights a strong correlation between elevated DUSP4 expression and sorafenib resistance in HCC. CONCLUSIONS: Our findings introduce DUSP4 as a negative regulator of sorafenib-induced ferroptosis. This discovery opens new avenues for the development of ferroptosis-based therapeutic strategies tailored for HCC treatment.

Perioperative toripalimab and chemotherapy in locally advanced gastric or gastro-esophageal junction cancer: a randomized phase 2 trial.

Perioperative chemotherapy is the standard treatment for locally advanced gastric or gastro-esophageal junction cancer, and the addition of programmed cell death 1 (PD-1) inhibitor is under investigation. In this randomized, open-label, phase 2 study (NEOSUMMIT-01), patients with resectable gastric or gastro-esophageal junction cancer clinically staged as cT3-4aN + M0 were randomized (1:1) to receive either three preoperative and five postoperative 3-week cycles of SOX/XELOX (chemotherapy group, n = 54) or PD-1 inhibitor toripalimab plus SOX/XELOX, followed by toripalimab monotherapy for up to 6 months (toripalimab plus chemotherapy group, n = 54). The primary endpoint was pathological complete response or near-complete response rate (tumor regression grade (TRG) 0/1). The results showed that patients in the toripalimab plus chemotherapy group achieved a higher proportion of TRG 0/1 than those in the chemotherapy group (44.4% (24 of 54, 95% confidence interval (CI): 30.9%-58.6%) versus 20.4% (11 of 54, 95% CI: 10.6%-33.5%)), and the risk difference of TRG 0/1 between toripalimab plus chemotherapy group and chemotherapy group was 22.7% (95% CI: 5.8%-39.6%; P = 0.009), meeting a prespecified endpoint. In addition, a higher pathological complete response rate (ypT0N0) was observed in the toripalimab plus chemotherapy group (22.2% (12 of 54, 95% CI: 12.0%-35.6%) versus 7.4% (4 of 54, 95% CI: 2.1%-17.9%); P = 0.030), and surgical morbidity (11.8% in the toripalimab plus chemotherapy group versus 13.5% in the chemotherapy group) and mortality (1.9% versus 0%), and treatment-related grade 3-4 adverse events (35.2% versus 29.6%) were comparable between the treatment groups. In conclusion, the addition of toripalimab to chemotherapy significantly increased the proportion of patients achieving TRG 0/1 compared to chemotherapy alone and showed a manageable safety profile. ClinicalTrials.gov registration: NCT04250948 .

Learning From Incorrectness: Active Learning With Negative Pre-Training and Curriculum Querying for Histological Tissue Classification.

Patch-level histological tissue classification is an effective pre-processing method for histological slide analysis. However, the classification of tissue with deep learning requires expensive annotation costs. To alleviate the limitations of annotation budgets, the application of active learning (AL) to histological tissue classification is a promising solution. Nevertheless, there is a large imbalance in performance between categories during application, and the tissue corresponding to the categories with relatively insufficient performance are equally important for cancer diagnosis. In this paper, we propose an active learning framework called ICAL, which contains Incorrectness Negative Pre-training (INP) and Category-wise Curriculum Querying (CCQ) to address the above problem from the perspective of category-to-category and from the perspective of categories themselves, respectively. In particular, INP incorporates the unique mechanism of active learning to treat the incorrect prediction results that obtained from CCQ as complementary labels for negative pre-training, in order to better distinguish similar categories during the training process. CCQ adjusts the query weights based on the learning status on each category by the model trained by INP, and utilizes uncertainty to evaluate and compensate for query bias caused by inadequate category performance. Experimental results on two histological tissue classification datasets demonstrate that ICAL achieves performance approaching that of fully supervised learning with less than 16% of the labeled data. In comparison to the state-of-the-art active learning algorithms, ICAL achieved better and more balanced performance in all categories and maintained robustness with extremely low annotation budgets. The source code will be released at https://github.com/LactorHwt/ICAL.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023.

The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence-based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti-angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)-positive and deficient DNA mismatch repair (dMMR)/microsatellite instability-high (MSI-H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

STAG2 Regulates Homologous Recombination Repair and Sensitivity to ATM Inhibition.

Stromal antigen 2 (STAG2), a subunit of the cohesin complex, is recurrently mutated in various tumors. However, the role of STAG2 in DNA repair and its therapeutic implications are largely unknown. Here it is reported that knockout of STAG2 results in increased double-stranded breaks (DSBs) and chromosomal aberrations by reducing homologous recombination (HR) repair, and confers hypersensitivity to inhibitors of ataxia telangiectasia mutated (ATMi), Poly ADP Ribose Polymerase (PARPi), or the combination of both. Of note, the impaired HR by STAG2-deficiency is mainly attributed to the restored expression of KMT5A, which in turn methylates H4K20 (H4K20me0) to H4K20me1 and thereby decreases the recruitment of BRCA1-BARD1 to chromatin. Importantly, STAG2 expression correlates with poor prognosis of cancer patients. STAG2 is identified as an important regulator of HR and a potential therapeutic strategy for STAG2-mutant tumors is elucidated.

Multimodal recurrence scoring system for prediction of clear cell renal cell carcinoma outcome: a discovery and validation study.

BACKGROUND: Improved markers for predicting recurrence are needed to stratify patients with localised (stage I-III) renal cell carcinoma after surgery for selection of adjuvant therapy. We developed a novel assay integrating three modalities-clinical, genomic, and histopathological-to improve the predictive accuracy for localised renal cell carcinoma recurrence. METHODS: In this retrospective analysis and validation study, we developed a histopathological whole-slide image (WSI)-based score using deep learning allied to digital scanning of conventional haematoxylin and eosin-stained tumour tissue sections, to predict tumour recurrence in a development dataset of 651 patients with distinctly good or poor disease outcome. The six single nucleotide polymorphism-based score, which was detected in paraffin-embedded tumour tissue samples, and the Leibovich score, which was established using clinicopathological risk factors, were combined with the WSI-based score to construct a multimodal recurrence score in the training dataset of 1125 patients. The multimodal recurrence score was validated in 1625 patients from the independent validation dataset and 418 patients from The Cancer Genome Atlas set. The primary outcome measured was the recurrence-free interval (RFI). FINDINGS: The multimodal recurrence score had significantly higher predictive accuracy than the three single-modal scores and clinicopathological risk factors, and it precisely predicted the RFI of patients in the training and two validation datasets (areas under the curve at 5 years: 0·825-0·876 vs 0·608-0·793; p<0·05). The RFI of patients with low stage or grade is usually better than that of patients with high stage or grade; however, the RFI in the multimodal recurrence score-defined high-risk stage I and II group was shorter than in the low-risk stage III group (hazard ratio [HR] 4·57, 95% CI 2·49-8·40; p<0·0001), and the RFI of the high-risk grade 1 and 2 group was shorter than in the low-risk grade 3 and 4 group (HR 4·58, 3·19-6·59; p<0·0001). INTERPRETATION: Our multimodal recurrence score is a practical and reliable predictor that can add value to the current staging system for predicting localised renal cell carcinoma recurrence after surgery, and this combined approach more precisely informs treatment decisions about adjuvant therapy. FUNDING: National Natural Science Foundation of China, and National Key Research and Development Program of China.

Intensive cycles of neoadjuvant camrelizumab combined with chemotherapy in locally advanced esophageal squamous cell carcinoma: a single-arm, phase II trial.

BACKGROUND: Two cycles of neoadjuvant PD-1 blockade plus chemotherapy induced favorable pathological response and tolerant toxicity in patients with locally advanced esophageal squamous cell carcinoma (ESCC). However, approximately 25% of patients relapsed within 1 year after surgery, indicating that a short course of treatment may not be sufficient. Therefore, exploring the effects of intensive treatment is needed for optimal clinical outcomes. METHODS: Locally advanced ESCC patients were administered three cycles of camrelizumab plus nab-paclitaxel and capecitabine, followed by thoracoscopic esophagectomy. The primary endpoint was pathologic response. Secondary endpoints included safety, feasibility, radiologic response, survival outcomes, and immunologic/genomic correlates of efficacy. RESULTS: Forty-seven patients were enrolled in the study. Forty-two patients received surgery, and R0 resection was achieved in all cases. The complete and major pathological response rates were 33.3% and 64.3%, respectively, and the objective response rate was 80.0%. Three cycles of treatment significantly improved T down-staging compared to two cycles (P = 0.03). The most common treatment-related adverse events were grades 1-2, and no surgical delay was reported. With a median follow-up of 24.3 months, the 1-year disease-free survival and overall survival rates were both 97.6%, and the 2-year disease-free survival and overall survival rates were 92.3% and 97.6%, respectively. Three patients experienced disease recurrence or metastasis ranging from 12.5 to 25.8 months after surgery, and one patient died 6 months after surgery due to cardiovascular disease. Neither programmed death-ligand 1 expression nor tumor mutational burden was associated with pathological response. An increased infiltration of CD56dim natural killer cells in the pretreatment tumor was correlated with better pathological response in the primary tumor. CONCLUSIONS: It seems probable that intensive cycles of neoadjuvant camrelizumab plus nab-paclitaxel and capecitabine increased tumor regression and improved survival outcomes. Randomized controlled trials with larger sample sizes and longer follow-up periods are needed to validate these findings. Trial registration Chinese Clinical Trial Registry, ChiCTR2000029807, Registered February 14, 2020, https://www.chictr.org.cn/showproj.aspx?proj=49459 .

Predictive value of radiological response, pathological response and relapse-free survival for overall survival in neoadjuvant immunotherapy trials: pooled analysis of 29 clinical trials.

BACKGROUND: An increasing number of clinical trials are being conducted exploring the efficacy of neoadjuvant immune checkpoint inhibitors. Surrogate end-points for overall survival (OS) are urgently needed. METHODS: Phase II or III trials of neoadjuvant immunotherapy that reported data on OS and surrogate end-points were identified from January 1, 2000, to November 25, 2022. Individual patient data, and trial-level data were requested from corresponding authors or extracted from eligible trials. At the individual level, correlations between radiological and pathological response and OS were measured by the Cox model and quantified by hazard ratio (HR). C-statistic was used to quantify the predictive performance of radiological and pathological response for OS. The coefficient of determination (R2) between RFS and OS was evaluated by a bivariate survival model. RESULTS: A total of 29 trials reporting 2901 patients were included. ORR correlated with improved OS (3-year OS: 87.0% versus 70.4% for ORR versus non-ORR, respectively; HR, 0.34, 95% confidence interval [CI], 0.17-0.68). The HRs for OS in patients achieving MPR and pCR were 0.24 (95% CI, 0.12-0.46) and 0.13 (95% CI, 0.05-0.36). The survival benefit maintained after adjusting tumour type. C-statistics of ORR, MPR and pCR were 0.63, 0.63 and 0.65, respectively. The strength of association between RFS and OS was strong (R2 = 0.88, 95% CI, 0.79-0.94). CONCLUSIONS: These findings suggest that ORR, MPR, pCR and RFS are valid predictors for OS when using neoadjuvant immune checkpoint inhibitors. Moreover, MPR, pCR and RFS may be the most optimal surrogates for OS.

Are more courses of immunochemotherapy beneficial for the short-term outcome of locally advanced esophageal squamous cell carcinoma?

BACKGROUND: Immune checkpoint inhibitor (ICI) monotherapy and neoadjuvant immunochemotherapy have shown promising results in esophageal carcinoma. However, it is still unclear whether more courses of immunochemotherapy are therapeutically better. We aimed to investigate the safety and efficacy of three courses of neoadjuvant treatment for patients with locally advanced esophageal squamous cell carcinoma (ESCC). METHODS: Patients with locally advanced ESCC received three courses of camrelizumab plus nab-paclitaxel and capecitabine before undergoing surgery. Additionally, patients received safety, computed tomography (CT), and endoscopy (with endoscopic ultrasonography and mucosal biopsy) assessments before and in the second and third courses of treatment. We used the CT and endoscopic assessment results from the second and third courses for comparison. RESULTS: From May 2020 to December 2021, 47 patients were enrolled at Sun Yat-sen University Cancer Center. In our study, 43 patients completed three courses of preoperative chemotherapy combined with anti-Programmed cell death-1 (PD-1) therapy and radical surgical resection. The toxicity of the third course of immunochemotherapy was mild and well tolerated without increased treatment-related adverse events (TRAEs) and mortality compared with that of the second course of treatment. In terms of efficacy, an additional course of treatment after the second course of treatment was effective, with increased CT and endoscopy T (clinical T stage) downstaging rates by 16.3% and 25.9%, N (clincial N stage) downstaging rates by 7.0% and 11.1%, and objective response rates (ORRs) by 13.6% and 22.0%, respectively. CONCLUSIONS: Regardless of downstaging or ORR, three courses of immunochemotherapy appear to be superior to two courses of treatment without increasing TRAEs.

Association between Early Immune-Related Adverse Events and Survival in Patients Treated with PD-1/PD-L1 Inhibitors.

BACKGROUND: Immune-related adverse events (irAEs) are side effects that reflect the activation of patients' immune systems after treatment with immune checkpoint inhibitors (ICIs). However, there is no meta-analysis on the effect of early irAEs on patient survival. Thus, we assessed the association between early irAEs and the survival of patients treated with ICIs. METHODS: PubMed, Embase, and Web of Science were searched from May 2010 to May 2020 for all the retrospective and prospective comparative studies to evaluate the hazard ratios (HRs) for death. A random-effects model was used to calculate the pooled HR for death, and heterogeneity was assessed using I² statistics. The main outcomes were overall survival (OS) and progression-free survival (PFS). RESULTS: A total of 11 reports with 2077 patients were included. A significant association was observed between early irAEs and a favorable clinical outcome. Patients with early irAEs had prolonged OS (HR: 0.62, 95% confidence interval (CI): 0.53-0.74, p < 0.001) and PFS (HR: 0.53, 95% CI: 0.41-0.66, p < 0.001) compared to those without; these results were confirmed using a sensitivity analysis. The irAE types, malignancy types, and sample size were correlated with patients' clinical outcomes. CONCLUSIONS: Early irAEs, especially cutaneous irAEs, correlated with a better clinical outcome in patients treated with ICIs.

ATOH8 binds SMAD3 to induce cellular senescence and prevent Ras-driven malignant transformation.

The process of oncogene-induced senescence (OIS) and the conversion between OIS and malignant transformation during carcinogenesis is poorly understood. Here, we show that following overactivation of oncogene Ras in lung epithelial cells, high-level transforming growth factor ß1 (TGF-ß1)-activated SMAD3, but not SMAD2 or SMAD4, plays a determinant role in inducing cellular senescence independent of the p53/p16/p15 senescence pathways. Importantly, SMAD3 binds a potential tumor suppressor ATOH8 to form a transcriptional complex that directly represses a series of cell cycle-promoting genes and consequently causes senescence in lung epithelial cells. Interestingly, the prosenescent SMAD3 converts to being oncogenic and essentially facilitates oncogenic Ras-driven malignant transformation. Furthermore, depleting Atoh8 rapidly accelerates oncogenic Ras-driven lung tumorigenesis, and lung cancers driven by mutant Ras and Atoh8 loss, but not by mutant Ras only, are sensitive to treatment of a specific SMAD3 inhibitor. Moreover, hypermethylation of the ATOH8 gene can be found in approximately 12% of clinical lung cancer cases. Together, our findings demonstrate not only epithelial cellular senescence directed by a potential tumor suppressor-controlled transcriptional program but also an important interplay between the prosenescent and transforming effects of TGF-ß/SMAD3, potentially laying a foundation for developing early detection and anticancer strategies.

Weakly supervised semantic segmentation of histological tissue via attention accumulation and pixel-level contrast learning.

Objective. Histopathology image segmentation can assist medical professionals in identifying and diagnosing diseased tissue more efficiently. Although fully supervised segmentation models have excellent performance, the annotation cost is extremely expensive. Weakly supervised models are widely used in medical image segmentation due to their low annotation cost. Nevertheless, these weakly supervised models have difficulty in accurately locating the boundaries between different classes of regions in pathological images, resulting in a high rate of false alarms Our objective is to design a weakly supervised segmentation model to resolve the above problems.Approach. The segmentation model is divided into two main stages, the generation of pseudo labels based on class residual attention accumulation network (CRAANet) and the semantic segmentation based on pixel feature space construction network (PFSCNet). CRAANet provides attention scores for each class through the class residual attention module, while the Attention Accumulation (AA) module overlays the attention feature maps generated in each training epoch. PFSCNet employs a network model containing an inflated convolutional residual neural network and a multi-scale feature-aware module as the segmentation backbone, and proposes dense energy loss and pixel clustering modules are based on contrast learning to solve the pseudo-labeling-inaccuracy problem.Main results. We validate our method using the lung adenocarcinoma (LUAD-HistoSeg) dataset and the breast cancer (BCSS) dataset. The results of the experiments show that our proposed method outperforms other state-of-the-art methods on both datasets in several metrics. This suggests that it is capable of performing well in a wide variety of histopathological image segmentation tasks.Significance. We propose a weakly supervised semantic segmentation network that achieves approximate fully supervised segmentation performance even in the case of incomplete labels. The proposed AA and pixel-level contrast learning also make the edges more accurate and can well assist pathologists in their research.

DNA methylation profile in CpG-depleted regions uncovers a high-risk subtype of early-stage colorectal cancer.

BACKGROUND: The current risk stratification system defined by clinicopathological features does not identify the risk of recurrence in early-stage (stage I-II) colorectal cancer (CRC) with sufficient accuracy. We aimed to investigate whether DNA methylation could serve as a novel biomarker for predicting prognosis in early-stage CRC patients. METHODS: We analyzed the genome-wide methylation status of CpG loci using Infinium MethylationEPIC array run on primary tumor tissues and normal mucosa of early-stage CRC patients to identify potential methylation markers for prognosis. The machine-learning approach was applied to construct a DNA methylation-based prognostic classifier for early-stage CRC (MePEC) using the 4 gene methylation markers FAT3, KAZN, TLE4, and DUSP3. The prognostic value of the classifier was evaluated in 2 independent cohorts (n = 438 and 359, respectively). RESULTS: The comprehensive analysis identified an epigenetic subtype with high risk of recurrence based on a group of CpG loci in the CpG-depleted region. In multivariable analysis, the MePEC classifier was independently and statistically significantly associated with time to recurrence in validation cohort 1 (hazard ratio = 2.35, 95% confidence interval = 1.47 to 3.76, P < .001) and cohort 2 (hazard ratio = 3.20, 95% confidence interval = 1.92 to 5.33, P < .001). All results were further confirmed after each cohort was stratified by clinicopathological variables and molecular subtypes. CONCLUSIONS: We demonstrated the prognostic statistical significance of a DNA methylation profile in the CpG-depleted region, which may serve as a valuable source for tumor biomarkers. MePEC could identify an epigenetic subtype with high risk of recurrence and improve the prognostic accuracy of current clinical variables in early-stage CRC.

Protective Effect of Natural Antioxidants on Reducing Cisplatin-Induced Nephrotoxicity.

The clinical application of cisplatin is limited by its adverse events, of which nephrotoxicity is the most commonly observed. In a cisplatin-induced pathological response, oxidative stress is one of the upstream reactions which inflicts different degrees of damages to the intracellular material components. Reactive oxygen species (ROS) are also one of the early signaling molecules that subsequently undergo a series of pathological reactions, such as apoptosis and necrosis. This review summarizes the mechanism of intracellular ROS generation induced by cisplatin, mainly from the consumption of endogenous antioxidants, destruction of antioxidant enzymes, induction of mitochondrial crosstalk between the endoplasmic reticulum by ROS and Ca2+, and destruction of the cytochrome P450 (CYP) system in the endoplasmic reticulum, all of which result in excessive accumulation of intracellular ROS and oxidative stress. In addition, studies demonstrated that natural antioxidants can protect against the cisplatin-induced nephrotoxicity, by reducing or even eliminating excess free radicals and also affecting other nonredox pathways. Therefore, this review on the one hand provides theoretical support for the research and clinical application of natural antioxidants and on the other hand provides a new entry point for the detailed mechanism of cisplatin nephrotoxicity, which may lay a solid foundation for the future clinical use of cisplatin.

Impact of WTAP in small HCC and paired adjacent non-neoplastic liver tissue on recurrence: A cohort study with external extension analysis.

Background: To evaluate prognostic value of WTAP levels in tumor and paired adjacent non-neoplastic liver tissues (PANLT) for cases of hepatitis B virus (HBV)-positive Asian small hepatocellular carcinoma (sHCC) patients who received curative partial hepatectomy. Method: The investigation with two external cohorts were included. Associations between hazard risk of recurrence and continuous WTAP levels were investigated with restricted cubic spline models. Cox and inverse probability weighting models were established for survival analysis. Based on interaction effects, further stratification analysis was performed. Landmark analysis was employed to analyze cases of late recurrence. Finally, sensitivity analysis was performed to assess unmeasured confounders. Findings: In an investigation cohort of 307 patients, restricted cubic spline models indicated that hazard risk of recurrence increases with elevated WTAP levels for sHCC and PANLT. However, using Cox and inverse probability weighting models, no significant differences were observed in recurrence-free survival (RFS) between groups with different WTAP levels in sHCC. Multivariate analysis showed that patients with high PANLT WTAP levels had significantly worse RFS (HR 1.567, 95% CI 1.065-2.307; p = 0.023). Based on the significant interaction effect between WTAP levels in sHCC and PANLT, stratification analysis revealed that recurrence risk is more pronounced in patients with high WTAP levels in both PANLT and sHCC. Landmark analysis showed that late recurrence was more likely to occur in patients with high PANLT WTAP levels (HR 2.058, 95% CI 1.113-3.805; p = 0.021). Moreover, the detrimental effects of elevated PANLT WTAP levels on RFS were validated with two external cohorts. Sensitivity analysis confirmed the robustness of results. Conclusion: Increased PANLT WTAP expression levels independently predict high recurrence risk in HBV-positive Asian sHCC patients. Both tumor tissues and PANLT need to be considered together in future clinical practice to obtain a more comprehensive and accurate evaluation for recurrence risk.