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BackgroundMany cancer patients have not received timely treatment or even had treatment interruptions due to the COVID-19 pandemic. The objective of this investigation was to evaluate whether the prognosis of patients with breast cancer after surgery was affected by any interruptions in radiotherapy.MethodsThe healthcare documents for breast cancer patients experiencing radiotherapy interruption after surgery, including treatment-related characteristics, and time of interruption, type of disease progression, and survival status, were collected between January and April 2020 during the Wuhan blockade.ResultsThe final number of patients included was 148, and neither the Kaplan-Meier (KM) survival curve nor the cross-tabulation analysis found statistical significance. Cox regression analysis also did not identify risk factors associated with PFS.ConclusionsThe prognosis of patients with postoperative breast cancer may not be significantly impacted by the interruption of radiotherapy, given its integration with additional treatments like targeted and endocrine therapies.

Summary: Gastric cancer exerts a significant healthcare burden worldwide and is highly geographically heterogeneous. This study investigates the burden of gastric cancer in China from 1990 to 2019 and compares it with Japan, South Korea, and the United States. The results indicated a declining trend in ASIR and ASDR in four countries. However, the incidence and death rates in China remain disproportionately high. Significant gender disparities exist in the incidence and death rates, with males experiencing significantly higher rates than females. Incidence and death rates were found to increase with age in all studied countries. In China, a transient upward trend was observed in the period effect, whereas the cohort effect has been declining. In contrast, the remaining countries showed decreasing patterns in both period and cohort effects. The burden of disease remains high in China, therefore, broaden the scope of gastroscopy screening and concentrate on high-risk groups is vital.

Breast cancer remains one of the predominant malignancies worldwide. In the context of inoperable advanced or metastatic human epidermal growth factor receptor 2 (HER2)-positive breast cancer, systemic management primarily relies on HER2-targeting monoclonal antibodies. With the successful development of anti-HER2 antibody-drug conjugates (ADCs), these agents have been increasingly integrated into therapeutic regimens for metastatic breast cancer. Here, we present the case of a 42-year-old female patient with HER2-positive pulmonary metastatic breast cancer who underwent an extensive treatment protocol. This protocol included chemotherapy, radiation therapy, hormonal therapy, surgical intervention on the breast, and anti-HER2 therapies. The anti-HER2 therapies involved both singular and dual targeting strategies using trastuzumab and the ADC disitamab vedotin (RC48) over an 8-year period. After experiencing disease progression following HER2-targeted therapy with RC48, the patient achieved noticeable partial remission through a therapeutic regimen that combined trastuzumab deruxtecan (DS8201) and tislelizumab. The data suggest a promising role for DS8201 in managing advanced stages of HER2-amplified metastatic breast cancer, especially in cases that demonstrate progression after initial HER2-directed therapies using ADCs. Furthermore, its combination with anti-PD-1 agents enhances therapeutic efficacy by augmenting the anti-tumoral immune response.

ObjectiveThis study amied to investigate the prognostic characteristics of triple negative breast cancer (TNBC) patients by analyzing B cell marker genes based on single-cell and bulk RNA sequencing.MethodsUtilizing single-cell sequencing data from TNBC patients, we examined tumor-associated B cell marker genes. Transcriptomic data from The Cancer Genome Atlas (TCGA) database were used as the foundation for predictive modeling. Independent validation set was conducted using the GSE58812 dataset. Immune cell infiltration into the tumor was assessed through various, including XCELL, TIMER, QUANTISEQ, CIBERSORT, CIBERSORT-ABS, and ssGSEA. The TIDE score was utilized to predict immunotherapy outcomes. Additional investigations were conducted on the immune checkpoint blockade gene, tumor mutational load, and the GSEA enrichment analysis.ResultsOur analysis encompassed 22,106 cells and 20,556 genes in cancerous tissue samples from four TNBC patients, resulting in the identification of 116 B cell marker genes. A B cell marker gene score (BCMG score) involving nine B cell marker genes (ZBP1, SEL1L3, CCND2, TNFRSF13C, HSPA6, PLPP5, CXCR4, GZMB, and CCDC50) was developed using TCGA transcriptomic data, revealing statistically significant differences in survival analysis (P

Pancreatic acinar cell carcinoma (PACC) is a rare pancreatic malignancy with unique clinical, molecular, and morphologic features. The long-term survival of patients with PACC is substantially better than that of patients with ductal adenocarcinoma of the pancreas. Surgical resection is considered the first choice for treatment; however, there is no standard treatment option for patients with inoperable disease. The patient with metastatic PACC reported herein survived for more than 5 years with various treatments including chemotherapy, radiotherapy, antiangiogenic therapy and combined immunotherapy.

Background: M2 macrophages perform an influential role in the progression of pancreatic cancer. This study is dedicated to explore the value of M2 macrophage-related genes in the treatment and prognosis of pancreatic cancer.Methods: RNA-Seq and clinical information were downloaded from TCGA, GEO and ICGC databases. The pancreatic cancer tumour microenvironment was revealed using the CIBERSORT algorithm. Weighted gene co-expression network analysis (WGCNA) was used to detect M2 macrophage-associated gene modules. Univariate Cox regression, Least absolute shrinkage and selection operator (LASSO) regression analysis and multivariate Cox regression were applied to develop the prognostic model. The modelling and validation cohorts were divided into high-risk and low-risk groups according to the median risk score. The nomogram predicting survival was constructed based on risk scores. Correlations between risk scores and tumour mutational load, clinical variables, immune checkpoint blockade, and immune cells were further explored. Finally, potential associations between different risk models and chemotherapeutic agent efficacy were predicted.Results: The intersection of the WGCNA results from the TCGA and GEO data screened for 317 M2 macrophage-associated genes. Nine genes were identified by multivariate COX regression analysis and applied to the construction of risk models. The results of GSEA analysis revealed that most of these genes were related to signaling, cytokine receptor interaction and immunodeficiency pathways. The high and low risk groups were closely associated with tumour mutational burden, immune checkpoint blockade related genes, and immune cells. The maximum inhibitory concentrations of metformin, paclitaxel, and rufatinib lapatinib were significantly differences on the two risk groups.Conclusion: WGCNA-based analysis of M2 macrophage-associated genes can help predict the prognosis of pancreatic cancer patients and may provide new options for immunotherapy of pancreatic cancer.

Epigenetic regulation plays an important role in the occurrence, development and treatment of tumors. The histone methyltransferase SET-domain-containing 2 (SETD2) plays a key role in mammalian epigenetic regulation by catalyzing histone methylation and interacting with RNA polymerase II to mediate transcription elongation and mismatch repair. As an important bridge between the environment and tumors, SETD2-H3K36me3 plays an important role in the occurrence and development of tumors. Many tumors, including renal cancer, gastric cancer, lung cancer, are closely related to SETD2 gene mutations. As a key component of common tumor suppressor mechanisms, SETD2-H3K36me3is an important target for clinical disease diagnosis and treatment. Here, we reviewed the structure and function of the SETD2 and how SETD2-H3K36me3 functions as a bridge between the environment and tumors to provide an in-depth understanding of its role in the occurrence and development of various tumors, which is of great significance for future disease diagnosis and treatment.

Nasopharyngeal carcinoma (NPC) is a malignant tumor originating from the epithelial cells of the nasopharynx with a unique geographic distribution, and is particularly prevalent in East and Southeast Asia. Due to its anatomical location, the surgery is difficult to access and the high sensitivity of nasopharyngeal cancer to radiotherapy (RT) makes it the main treatment modality. Radical radiotherapy is the first-line treatment for early-stage nasopharyngeal carcinoma and the cornerstone of multidisciplinary treatment for patients with locally advanced nasopharyngeal carcinoma. Nevertheless, radiotherapy interruption is inevitable as a consequence of unavoidable factors such as public holidays, machine malfunction, patient compliance, and adverse response to treatment, which in turn leads to a reduction in bioactivity and causes sublethal loss of tumor cells to repair. Unirradiated tumor cells are more likely to repopulate at or near their original fastest growth rate during this interval. If no measures are taken after the radiotherapy interruption, such as increasing the dose of radiotherapy and systemic therapy, the tumor is most likely to go uncontrolled and then progress. This review describes the effects of radiotherapy interruption on nasopharyngeal carcinoma, the mechanism of the effect, and explores the measures that can be taken in response to such interruption.

Background: An imbalance of redox homeostasis participates in tumorigenesis, proliferation, and metastasis, which results from the production of reactive oxygen species (ROS). However, the biological mechanism and prognostic significance of redox-associated messenger RNAs (ramRNAs) in lung adenocarcinoma (LUAD) still remain unclear.Methods: Transcriptional profiles and clinicopathological information were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) of LUAD patients. A total of 31 overlapped ramRNAs were determined, and patients were separated into three subtypes by unsupervised consensus clustering. Biological functions and tumor immune-infiltrating levels were analyzed, and then, differentially expressed genes (DEGs) were identified. The TCGA cohort was divided into a training set and an internal validation set at a ratio of 6:4. Least absolute shrinkage and selection operator regression were used to compute the risk score and determine the risk cutoff in the training set. Both TCGA and GEO cohort were distinguished into a high-risk or low-risk group at the median cutoff, and then, relationships of mutation characteristics, tumor stemness, immune differences, and drug sensitivity were investigated.Results: Five optimal signatures (ANLN, HLA-DQA1, RHOV, TLR2, and TYMS) were selected. Patients in the high-risk group had poorer prognosis, higher tumor mutational burden, overexpression of PD-L1, and lower immune dysfunction and exclusion score compared with the low-risk group. Cisplatin, docetaxel, and gemcitabine had significantly lower IC50 in the high-risk group.Conclusion: This study constructed a novel predictive signature of LUAD based on redox-associated genes. Risk score based on ramRNAs served as a promising biomarker for prognosis, TME, and anti-cancer therapies of LUAD.

Simple summaryAccurately estimate the prognosis of patients with ECCA is important. However, the TNM system has some limitations, such as low accuracy, exclusion of other factors (e.g., age and sex), and poor performance in predicting individual survival risk. In contrast, a nomogram-based clinical model related to a comprehensive analysis of all risk factors is intuitive and straightforward, facilitating the probabilistic analysis of tumor-related risk factors. Simultaneously, a nomogram can also effectively drive personalized medicine and facilitate clinicians for prognosis prediction. Therefore, we construct a novel practical nomogram and risk stratification system to predict CSS in patients with ECCA.BackgroundAccurately estimate the prognosis of patients with extrahepatic cholangiocarcinoma (ECCA) was important, but the existing staging system has limitations. The present study aimed to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in ECCA patients.Methods3415 patients diagnosed with ECCA between 2010 and 2015 were selected from the SEER database and randomized into a training cohort and a validation cohort at 7:3. The nomogram was identified and calibrated using the C-index, receiver operating characteristic curve (ROC), and calibration plots. Decision curve analysis (DCA), net reclassification index (NRI), integrated discrimination improvement (IDI) and the risk stratification were used to compare the nomogram with the AJCC staging system.ResultsNine variables were selected to establish the nomogram. The C-index (training cohort:0.785; validation cohort:0.776) and time-dependent AUC (>0.7) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. The NRI (training cohort: 1-, 2-, and 3-year CSS:0.27, 0.27,0.52; validation cohort:1-,2-,3-year CSS:0.48,0.13,0.34), IDI (training cohort: 1-, 2-, 3-year CSS:0.22,0.18,0.16; validation cohort: 1-,2-,3-year CSS:0.18,0.16,0.17), and DCA indicated that the established nomogram significantly outperformed the AJCC staging system (P

A range of novel 1,9-disubstituted β-carboline derivatives was designed, synthesized and evaluated as potential anticancer agents. The preliminary study suggested that compounds 6a, 6b, 6c, 6d, 6e, 6f, 6g, and 6h tested in this study exerted potent antiproliferative effects on ten selected human tumor cell lines, with compound 6e being the most effective antiproliferative agent against the BGC-823, A375 and HT-29 cell lines, with IC50 values of 23.9, 9.3, and 3.6 µM, respectively. In addition, the antitumor capability of compound 6e was also evaluated in vivo, which demonstrated that compound 6e distinctly inhibited colorectal tumor growth in syngeneic BALB/c mice. Further research into the fundamental mechanism revealed that compound 6e inhibited colorectal cancer growth through the ATG5 (autophagy-related-5)/ATG7 (autophagy-related-7)-dependent autophagy pathway. This research can contribute to further clinical application of β-carboline derivatives as new antitumor drugs.

BackgroundThe goal is to establish and validate an innovative prognostic risk stratification and nomogram in patients of hepatocellular carcinoma (HCC) with microvascular invasion (MVI) for predicting the cancer-specific survival (CSS).Methods1487 qualified patients were selected from the Surveillance, Epidemiology and End Results (SEER) database and randomly assigned to the training cohort and validation cohort in a ratio of 7:3. Concordance index (C-index), area under curve (AUC) and calibration plots were adopted to evaluate the discrimination and calibration of the nomogram. Decision curve analysis (DCA) was used to quantify the net benefit of the nomogram at different threshold probabilities and compare it to the American Joint Committee on Cancer (AJCC) tumor staging system. C-index, net reclassification index (NRI) and integrated discrimination improvement (IDI) were applied to evaluate the improvement of the new model over the AJCC tumor staging system. The new risk stratifications based on the nomogram and the AJCC tumor staging system were compared.ResultsEight prognostic factors were used to construct the nomogram for HCC patients with MVI. The C-index for the training and validation cohorts was 0.785 and 0.776 respectively. The AUC values were higher than 0.7 both in the training cohort and validation cohort. The calibration plots showed good consistency between the actual observation and the nomogram prediction. The IDI values of 1-, 3-, 5-year CSS in the training cohort were 0.17, 0.16, 0.15, and in the validation cohort were 0.17, 0.17, 0.17 (P

Lake Xingkai is a large turbid lake composed of two parts, Small Lake Xingkai and Big Lake Xingkai, on the border between Russia and China, where it represents a vital source of water, fishing, water transport, recreation, and tourism. Chlorophyll-a (Chla) is a prominent phytoplankton pigment and a proxy for phytoplankton biomass, reflecting the trophic status of waters. Regularly monitoring Chla concentrations is vital for issuing timely warnings of this lake’s eutrophication. Owing to its higher spatial and temporal coverages, remote sensing can provide a synoptic complement to traditional measurement methods by targeting the optical Chla absorption signals, especially for the lakes that lack regular in situ sampling cruises, like Lake Xingkai. This study calibrated and validated several commonly used remote sensing Chla retrieval algorithms (including the two-band ratio, three-band method, four-band method, and baseline methods) by applying them to Sentinel-3 Ocean and Land Colour Instrument (OLCI) images in Lake Xingkai. Among these algorithms, the four-band model (FBA), which removes the absorption signal of detritus and colored dissolved organic matter, was the best-performing model with an R2 of 0.64 and a mean absolute percentage difference of 38.26%. With the FBA model applied to OLCI images, the monthly and spatial distributions of Chla in Lake Xingkai were studied from 2016 to 2022. The results showed that over the seven years, the Chla concentrations in Small Lake Xingkai were higher than in Big Lake Xingkai. Unlike other eutrophic lakes in China (e.g., Lake Taihu and Lake Chaohu), Lake Xingkai did not display a stable seasonal Chla variation pattern. We also found uncertainties and limitations of the Chla algorithm models when using a larger satellite zenith angle or applying it to an algal bloom area. Recent increases in anthropogenic nutrient loading, water clarity, and warming temperatures may lead to rising phytoplankton biomass in Lake Xingkai, and the results of this study can be applied for the satellite-based monitoring of its water quality.

BackgroundHepatocellular carcinoma (HCC) has the highest cancer-related mortality rate. This study aims to create a nomogram to predict the cancer-specific survival (CSS) in patients with advanced hepatocellular carcinoma.MethodsPatients diagnosed with advanced HCC (AJCC stage III and IV) during 1975 to 2018 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Qualified patents were randomized into training cohort and validation cohort at a ratio of 7:3. The results of univariate and multivariate Cox regression analyses were used to construct the nomogram. Consistency index (C-index), area under the time-dependent receiver operating characteristic (ROC) curve [time-dependent area under the curve (AUC)], and calibration plots were used to identify and calibrate the nomogram. The net reclassification index (NRI), integrated discrimination improvement (IDI), and C-index, and decision curve analysis DCA were adopted to compare the nomogram’s clinical utility with the AJCC criteria.ResultsThe 3,103 patients with advanced hepatocellular carcinoma were selected (the training cohort: 2,175 patients and the validation cohort: 928 patients). The C-index in both training cohort and validation cohort were greater than 0.7. The AUC for ROC in the training cohort was 0.781, 0.771, and 0.791 at 1, 2, and 3 years CSS, respectively. Calibration plots showed good consistency between actual observations and the 1-, 2-, and 3-year CSS predicted by the nomogram. The 1-, 2-, and 3-year NRI were 0.77, 0.46, and 0.48, respectively. The 1-, 2-, and 3-year IDI values were 0.16, 0.15, and 0.12 (P < 0.001), respectively. DCA curves in both the training and validation cohorts demonstrated that the nomogram showed better predicted 1-, 2-, and 3-year CSS probabilities than AJCC criteria.ConclusionsThis study established a practical nomogram for predicting CSS in patients with advanced HCC and a risk stratification system that provided an applicable tool for clinical management.

ObjectiveHepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths worldwide. This study aims to construct a novel practical nomogram and risk stratification system to predict cancer-specific survival (CSS) in HCC patients with severe liver fibrosis.MethodsData on 1,878 HCC patients with severe liver fibrosis in the period 1975 to 2017 were extracted from the Surveillance, Epidemiology, and End Results database (SEER). Patients were block-randomized (1,316 training cohort, 562 validation cohort) by setting random seed. Univariate and multivariate COX regression analyses were employed to select variables for the nomogram. The consistency index (C-index), the area under time-dependent receiver operating characteristic curve (time-dependent AUC), and calibration curves were used to evaluate the performance of the nomogram. Decision curve analysis (DCA), the C-index, the net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to compare the nomogram with the AJCC tumor staging system. We also compared the risk stratification of the nomogram with the American Joint Committee on Cancer (AJCC) staging system.ResultsSeven variables were selected to establish the nomogram. The C-index (training cohort: 0.781, 95%CI: 0.767–0.793; validation cohort: 0.793, 95%CI = 95%CI: 0.779–0.798) and the time-dependent AUCs (the training cohort: the values of 1-, 3-, and 5 years were 0.845, 0.835, and 0.842, respectively; the validation cohort: the values of 1-, 3-, and 5 years were 0.861, 0.870, and 0.876, respectively) showed satisfactory discrimination. The calibration plots also revealed that the nomogram was consistent with the actual observations. NRI (training cohort: 1-, 2-, and 3-year CSS: 0.42, 0.61, and 0.67; validation cohort: 1-, 2-, and 3-year CSS: 0.26, 0.52, and 0.72) and IDI (training cohort: 1-, 3-, and 5-year CSS:0.16, 0.20, and 0.22; validation cohort: 1-, 3-, and 5-year CSS: 0.17, 0.26, and 0.30) indicated that the established nomogram significantly outperformed the AJCC staging system (P