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BackgroundThe number of patients undergoing proton therapy has increased in recent years. Current treatment planning systems (TPS) calculate dose maps using three-dimensional (3D) maps of relative stopping power (RSP) and mass density. The patient-specific maps of RSP and mass density were obtained by translating the CT number (HU) acquired using single-energy computed tomography (SECT) with appropriate conversions and coefficients. The proton dose calculation uncertainty of this approach is 2.5%-3.5% plus 1 mm margin. SECT is the major clinical modality for proton therapy treatment planning. It would be intriguing to enhance proton dose calculation accuracy using a deep learning (DL) approach centered on SECT.ObjectivesThe purpose of this work is to develop a deep learning method to generate mass density and relative stopping power (RSP) maps based on clinical single-energy CT (SECT) data for proton dose calculation in proton therapy treatment.MethodsArtificial neural networks (ANN), fully convolutional neural networks (FCNN), and residual neural networks (ResNet) were used to learn the correlation between voxel-specific mass density, RSP, and SECT CT number (HU). A stoichiometric calibration method based on SECT data and an empirical model based on dual-energy CT (DECT) images were chosen as reference models to evaluate the performance of deep learning neural networks. SECT images of a CIRS 062M electron density phantom were used as the training dataset for deep learning models. CIRS anthropomorphic M701 and M702 phantoms were used to test the performance of deep learning models.ResultsFor M701, the mean absolute percentage errors (MAPE) of the mass density map by FCNN are 0.39%, 0.92%, 0.68%, 0.92%, and 1.57% on the brain, spinal cord, soft tissue, bone, and lung, respectively, whereas with the SECT stoichiometric method, they are 0.99%, 2.34%, 1.87%, 2.90%, and 12.96%. For RSP maps, the MAPE of FCNN on M701 are 0.85%, 2.32%, 0.75%, 1.22%, and 1.25%, whereas with the SECT reference model, they are 0.95%, 2.61%, 2.08%, 7.74%, and 8.62%. ConclusionThe results show that deep learning neural networks have the potential to generate accurate voxel-specific material property information, which can be used to improve the accuracy of proton dose calculation.Advances in knowledgeDeep learning-based frameworks are proposed to estimate material mass density and RSP from SECT with improved accuracy compared with conventional methods.

BackgroundPrevious genetic-epidemiological studies considered TERT (rs2736100), CCDC26 (rs4295627), CDKN2A/B (rs4977756) and RTEL1 (rs6010620) gene polymorphisms as the risk factors specific to glioma. However, the data samples of previous genetic-epidemiological studies are modest to determine whether they have definite association with glioma.MethodThe study paid attention to systematically searching databases of PubMed, Embase, Web of Science (WoS), Scopus, Cochrane Library and Google Scholars. Meta-analysis under 5 genetic models, namely recessive model (RM), over-dominant model (O-DM), allele model (AM), co-dominant model (C-DM) and dominant model (DM) was conducted for generating odds ratios (ORs) and 95% confidence intervals (CIs). That was accompanied by subgroup analyses according to various racial groups. The software STATA 17.0 MP was implemented in the study.Result21 articles were collected. According to data analysis results, in four genetic models (AM, RM, DM and C-DM) TERT gene rs2736100 polymorphism, CCDC26 gene rs4295627 polymorphism, CDKN2A/B gene rs4977756 polymorphism and RTEL1 gene rs6010620 polymorphisms increased the risk of glioma in Caucasians to different degrees. In Asian populations, the CCDC26 gene rs4295627 polymorphism and CDKN2A/B gene rs4977756 polymorphism did not exhibit a relevance to the risk of glioma. It is suggested to cautiously explain these results as the sample size is small.ConclusionThe current meta-analysis suggested that the SNP of TERT (rs2736100), CCDC26 (rs4295627), CDKN2A/B (rs4977756) and RTEL1 (rs6010620) genes in glioma might increase risk of glioma, but there are ethnic differences. Further studies evaluating these polymorphisms and glioma risk are warranted.

Triple-negative breast cancer (TNBC) is one of the most aggressive breast cancer subtypes and is characterized by abundant infiltrating immune cells within the microenvironment. As standard care, chemotherapy remains the fundamental neoadjuvant treatment in TNBC, and there is increasing evidence that supplementation with immune checkpoint inhibitors may potentiate the therapeutic efficiency of neoadjuvant chemotherapy (NAC). However, 20-60% of TNBC patients still have residual tumor burden after NAC and require additional chemotherapy; therefore, it is critical to understand the dynamic change in the tumor microenvironment (TME) during treatment to help improve the rate of complete pathological response and long-term prognosis. Traditional methods, including immunohistochemistry, bulk tumor sequencing, and flow cytometry, have been applied to elucidate the TME of breast cancer, but the low resolution and throughput may overlook key information. With the development of diverse high-throughput technologies, recent reports have provided new insights into TME alterations during NAC in four fields, including tissue imaging, cytometry, next-generation sequencing, and spatial omics. In this review, we discuss the traditional methods and the latest advances in high-throughput techniques to decipher the TME of TNBC and the prospect of translating these techniques to clinical practice.

ObjectiveThis study aimed to prospectively observe the efficacy and safety of CalliSpheres drug-eluting beads bronchial arterial chemoembolization (DEB-BACE) for refractory non-small-cell lung cancer (NSCLC).MethodsThe interventional therapy plan was as follows: 300–500 μm CalliSpheres drug-loaded microspheres were loaded with epirubicin, and then slow embolization of tumor supplying artery was performed after microcatheter superselection. Chest enhanced computed tomography and related hematological examination were reviewed after 2 months of DEB-BACE, and the tumor response after the first interventional therapy was evaluated using modified response evaluation criteria in solid tumors. The overall survival (OS) of patients was determined, and the quality of life and the incidence rate of adverse reactions were observed.ResultsFrom January 2019 to January 2021, 43 patients with refractory NSCLC were enrolled. The patients were followed up until June 2022. All 43 patients underwent DEB-BACE 1.79 ± 0.69 times on average. The 3-, 6-, 12-, and 24-month survival rates were 100%, 86.0%, 41.9%, and 11.8%, respectively. The median OS was 11.5 months. After the first interventional treatment, cough and wheezing significantly improved in 31 patients, hemoptysis was effectively controlled in 12 patients, and superior vena cava compression disappeared in 2 patients after 2 times of treatment. The general health status of the patients after treatment significantly improved compared with that before treatment, including the improvement in physical and emotional functions. Fatigue, nausea and vomiting, dyspnea, and insomnia improved significantly after treatment. No serious adverse events, such as spinal cord injury and cerebral embolism, were observed during the perioperative period. The main adverse reaction after DEB-BACE was chest pain (13/43, grade 1) followed by fever (10/43, grade 1–2), which was significantly relieved within 3–5 days after symptomatic treatment. Other adverse reactions included irritating cough, nausea and vomiting, and bone marrow suppression, and the incidence was less than 20%.ConclusionsDEB-BACE was effective and safe in treating refractory NSCLC, which could significantly improve patients’ quality of life and was worthy of clinical promotion and application.

IntroductionCancer is a crucial public health problem and one of the leading causes of death worldwide. Previous studies have suggested that GPX3 may be involved in cancer metastasis and chemotherapy resistance. However, how GPX3 affects cancer patients’ outcomes and the underlying mechanism remains unclear.MethodsSequencing data and clinical data from TCGA, GTEx, HPA, and CPTAC were used to explore the relationship between GPX3 expression and clinical features. Immunoinfiltration scores were used to assess the relationship between GPX3 and the tumor immune microenvironment. Functional enrichment analysis was used to predict the role of GPX3 in tumors. Gene mutation frequency, methylation level, and histone modification were used to predict the GPX3 expression regulation method. Breast, ovarian, colon, and gastric cancer cells were used to investigate the relationship between GPX3 expression and cancer cell metastasis, proliferation, and chemotherapy sensitivity.ResultsGPX3 is down-regulated in various tumor tissues, and GPX3 expression level can be used as a marker for cancer diagnosis. However, GPX3 expression is associated with higher stage and lymph node metastasis, as well as poorer prognosis. GPX3 is closely related to thyroid function and antioxidant function, and its expression may be regulated by epigenetic inheritance such as methylation modification or histone modification. In vitro experiments, GPX3 expression is associated with cancer cell sensitivity to oxidant and platinum-based chemotherapy and is involved in tumor metastasis in oxidative environments.DiscussionWe explored the relationship between GPX3 and clinical features, immune infiltration characteristics, migration and metastasis, and chemotherapy sensitivities of human cancers. We further investigated the potential genetic and epigenetic regulation of GPX3 in cancer. Our results suggested that GPX3 plays a complicated role in the tumor microenvironment, simultaneously promoting metastasis and chemotherapy resistance in human cancers.

BackgroundWhole-lesion histogram analysis can provide comprehensive assessment of tissues by calculating additional quantitative metrics such as skewness and kurtosis; however, few studies have evaluated its value in the differential diagnosis of lung lesions.PurposeTo compare the diagnostic performance of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) in differentiating lung cancer from focal inflammatory lesions, based on whole-lesion volume histogram analysis.MethodsFifty-nine patients with solitary pulmonary lesions underwent multiple b-values DWIs, which were then postprocessed using mono-exponential, bi-exponential and DKI models. Histogram parameters of the apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f), apparent diffusional kurtosis (Kapp) and kurtosis-corrected diffusion coefficient (Dapp) were calculated and compared between the lung cancer and inflammatory lesion groups. Receiver operating characteristic (ROC) curves were constructed to evaluate the diagnostic performance.ResultsThe ADCmean, ADCmedian, Dmean and Dmedian values of lung cancer were significantly lower than those of inflammatory lesions, while the ADCskewness, Kappmean, Kappmedian, KappSD, Kappkurtosis and Dappskewness values of lung cancer were significantly higher than those of inflammatory lesions (all p < 0.05). ADCskewness (p = 0.019) and Dmedian (p = 0.031) were identified as independent predictors of lung cancer. Dmedian showed the best performance for differentiating lung cancer from inflammatory lesions, with an area under the ROC curve of 0.777. Using a Dmedian of 1.091 × 10-3 mm2/s as the optimal cut-off value, the sensitivity, specificity, positive predictive value and negative predictive value were 69.23%, 85.00%, 90.00% and 58.62%, respectively.ConclusionsWhole-lesion histogram analysis of DWI, IVIM and DKI parameters is a promising approach for differentiating lung cancer from inflammatory lesions, and Dmedian shows the best performance in the differential diagnosis of solitary pulmonary lesions.

BackgroundPrimary hepatocellular carcinoma is often complicated with hepatitis and liver cirrhosis. Some patients develop different degrees of splenomegaly, hypersplenism and hypohepatia due to the aggravation of liver cirrhosis, which to some extent interfere with the treatment of tumors and even affect the prognosis of patients. In this study, we prospectively evaluate the efficacy and safety of simultaneous CalliSpheres® microspheres transcatheter arterial chemoembolization (CSM-TACE) and partial splenic embolization (PSE) using 8spheres® for hepatocellular carcinoma (HCC) with hypersplenism.MethodsNinety consecutive HCC patients with hypersplenism who underwent CSM-TACE were selected: 32 patients in CSM-TACE+PSE group, and 58 patients in CSM-TACE group. The peripheral blood cell counts (leukocyte, platelet (PLT), liver function and red blood cell (RBC)), CSM-TACE and/or PSE related complications, and the tumor control rate at 1 month after CSM-TACE were compared. The survival time and prognostic factors were also observed.ResultsBefore CSM-TACE, there were no significant differences in sex, age, Child-Pugh grade, tumor size, and alpha-fetoprotein (AFP) between the two groups. After CSM-TACE, the PLT and white blood cell (WBC) counts in CSM-TACE+PSE group were significantly higher than those in the CSM-TACE group (P 0.05). In the CSM-TACE group, there were no significant differences in WBC, PLT, and RBC before and after treatment (P > 0.05). There was no significant difference in liver function at 1 month after treatment between the two groups. The cholinesterase (CHE) level in the CSM-TACE+PSE group after CSM-TACE+PSE was obviously higher than that before CSM-TACE+PSE and higher than that in the CSM-TACE group (P 0.05).ConclusionsSimultaneous CSM-TACE and PSE using domestic embolization particles for HCC with hypersplenism have good safety and efficacy and has a low incidence of PSE-related adverse events, it is conducive to improving liver function reserve, and can further improve the median OS.

Papillary thyroid cancer (PTC) is one of the malignancies with an excellent prognosis. However, in PTC, progression or dedifferentiation into poorly differentiated thyroid cancer (PDTC) or anaplastic thyroid cancer (ATC) extremely jeopardizes patients’ prognosis. MMP1 is a zinc-dependent endopeptidase, and its role in PTC progression and dedifferentiation is unclear. In this study, transcriptome data of PDTC/ATC and PTC from the Gene Expression Omnibus and The Cancer Genome Atlas databases were utilized to perform an integrated analysis of MMP1 as a potential regulator of tumor progression and dedifferentiation in PTC. Both bulk and single-cell RNA-sequencing data confirmed the high expression of MMP1 in ATC tissues and cells, and further study verified that MMP1 possessed good diagnostic and prognostic value in PTC and PDTC/ATC. Up-regulated MMP1 was found to be positively related to more aggressive clinical characteristics, worse survival, extracellular matrix-related pathways, oncogenic immune microenvironment, more mutations, higher stemness, and more dedifferentiation of PTC. Meanwhile, in vitro experiments verified the high level of MMP1 in PDTC/ATC cell lines, and MMP1 knockdown and its inhibitor triolein could both inhibit the cell viability of PTC and PDTC/ATC. In conclusion, our findings suggest that MMP1 is a potential regulator of tumor progression and dedifferentiation in PTC, and might become a novel therapeutic target for PTC, especially for more aggressive PDTC and ATC.

BackgroundClear cell renal cell carcinoma (ccRCC) is a malignant tumor with limited treatment options. A recent study confirmed the involvement of basement membrane (BM) genes in the progression of many cancers. Therefore, we studied the role and prognostic significance of BM genes in ccRCC.MethodsCo-expression analysis of ccRCC-related information deposited in The Cancer Genome Atlas database and a BM geneset from a recent study was conducted. The differentially expressed BM genes were validated using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). Least absolute shrinkage and selection operator regression and univariate Cox regression analyses were performed to identify a BM gene signature with prognostic significance for ccRCC. Multivariate Cox regression, time-dependent receiver operating characteristic, Kaplan–Meier, and nomogram analyses were implemented to appraise the prognostic ability of the signature and the findings were further verified using a Gene Expression Omnibus dataset. Additionally, immune cell infiltration and and pathway enrichment analyses were performed using ImmuCellAI and Gene Set Enrichment Analysis (GSEA), respectively. Finally, the DSIGDB dataset was used to screen small-molecule therapeutic drugs that may be useful in treating ccRCC patients.ResultsWe identified 108 BM genes exhibiting different expression levels compared to that in normal kidney tissues, among which 32 genes had prognostic values. The qRT-PCR analyses confirmed that the expression patterns of four of the ten selected genes were the same as the predicted ones. Additionally, we successfully established and validated a ccRCC patient prediction model based on 16 BM genes and observed that the model function is an independent predictor. GSEA revealed that differentially expressed BM genes mainly displayed significant enrichment of tumor and metabolic signaling cascades. The BM gene signature was also associated with immune cell infiltration and checkpoints. Eight small-molecule drugs may have therapeutic effects on ccRCC patients.ConclusionThis study explored the function of BM genes in ccRCC for the first time. Reliable prognostic biomarkers that affect the survival of ccRCC patients were determined, and a BM gene-based prognostic model was established.

BackgroundCuproptosis is a new modality of cell death regulation that is currently considered as a new cancer treatment strategy. Nevertheless, the prognostic predictive value of cuproptosis-related lncRNAs in breast cancer (BC) remains unknown. Using cuproptosis-related lncRNAs, this study aims to predict the immune microenvironment and prognosis of BC patients. and develop new therapeutic strategies that target the disease.MethodsThe Cancer Genome Atlas (TCGA) database provided the RNA-seq data along with the corresponding clinical and prognostic information. Univariate and multivariate Cox regression analyses were performed to acquire lncRNAs associated with cuproptosis to establish predictive features. The Kaplan-Meier method was used to calculate the overall survival rate (OS) in the high-risk and low-risk groups. High risk and low risk gene sets were enriched to explore functional discrepancies among risk teams. The mutation data were analyzed using the “MAFTools” r-package. The ties of predictive characteristics and immune status had been explored by single sample gene set enrichment analysis (ssGSEA). Last, the correlation between predictive features and treatment condition in patients with BC was analyzed. Based on prognostic risk models, we assessed associations between risk subgroups and immune scores and immune checkpoints. In addition, drug responses in at-risk populations were predicted.ResultsWe identified a set of 11 Cuproptosis-Related lncRNAs (GORAB-AS1, AC 079922.2, AL 589765.4, AC 005696.4, Cytor, ZNF 197-AS1, AC 002398.1, AL 451085.3, YTH DF 3-AS1, AC 008771.1, LINC 02446), based on which to construct the risk model. In comparison to the high-risk group, the low-risk patients lived longer (p < 0.001). Moreover, cuproptosis-related lncRNA profiles can independently predict prognosis in BC patients. The AUC values for receiver operating characteristics (ROC) of 1-, 3-, and 5-year risk were 0.849, 0.779, and 0.794, respectively. Patients in the high-risk group had lower OS than those in the low-risk group when they were divided into groups based on various clinicopathological variables. The tumor burden mutations (TMB) correlation analysis showed that high TMB had a worse prognosis than low-TMB, and gene mutations were found to be different in high and low TMB groups, such as PIK3CA (36% versus 32%), SYNE1 (4% versus 6%). Gene enrichment analysis indicated that the differential genes were significantly concentrated in immune-related pathways. The predictive traits were significantly correlated with the immune status of BC patients, according to ssGSEA results. Finally, high-risk patients showed high sensitivity in anti-CD276 immunotherapy and conventional chemotherapeutic drugs such as imatinib, lapatinib, and pazopanib.ConclusionWe successfully constructed of a cuproptosis-related lncRNA signature, which can independently predict the prognosis of BC patients and can be used to estimate OS and clinical treatment outcomes in BRCA patients. It will serve as a foundation for further research into the mechanism of cuproptosis-related lncRNAs in breast cancer, as well as for the development of new markers and therapeutic targets for the disease.

BackgroundsBreast cancer is a common malignant tumors in women. TIMM8A was up-regulated in different cancers. The aim of this work was to clarify the value of TIMM8A in the diagnosis, prognosis of Breast Cancer (BC), and its association with immune cells and immune detection points. Gene mutations.MethodsThe transcription and expression profile of TIMM8A between BC and normal tissues was downloaded from The Cancer Genome atlas (TCGA). The expression of TIMM8A protein was evaluated by human protein map. The correlation between TIMM8A and clinical features was analyzed using the R package to establish a ROC diagnostic curve. cBioPortal and MethSurv were used to identify gene alterations and DNA methylation and their effects on prognosis. The tumor immune estimation resource (TIMER) database and tumor immune system interaction database (TISIDB) database were used to determine the relationship between TIMM8A gene expression levels and immune infiltration. The CTD database was used to predict related drugs that inhibit TIMM8A, and the PubChem database was used to determine the molecular structure of potentially effective drug small molecules.ResultsThe expression of TIMM8A in breast cancer tissues was significantly higher than that in normally adjacent tissues to cancer. ROC curve analysis showed that the AUC value of TIMM8A was 0.679. Kaplan-Meier method showed that patients with high TIMM8A had a lower prognosis (Overall Survival HR = 1.83 (1.31 − 2.54), P < 0.001) than patients with low TIMM8A expression of breast cancer (148.5 months vs. 115.4 months, P < 0.001). Methylation levels at seven CpG were associated with prognosis. Correlation analysis showed that TIMM8A expression was associated with tumor immune cell infiltration. There was a significant positive correlation of TIMM8A with PDL-1, and CTLA-4 in BC. In addition, CTD database analysis identified 15 small molecular drugs that target TIMM8A, such as Cyclosporine, Leflunomide, and Tretinoin, which might be effective therapies for targeted inhibition of TIMM8A.ConclusionIn breast cancer, up-regulated TIMM 8A was significantly related to lower survival rate and higher immune invasiveness. Our research showed that TIMM 8A could be used as a biomarker for poor prognosis of breast cancer and a potential target of immunotherapy.

ObjectivePoor prognosis and limited treatments of liver metastases from non–small‐cell lung cancer (NSCLC) after radical surgery are critical issues. The current study aimed to evaluate the efficacy and safety of CalliSpheres® microsphere transarterial chemoembolization (CSM-TACE) plus 125I brachytherapy in these patients.MethodsA total of 23 patients with liver metastases from NSCLC after radical surgery were included. All patients received CSM-TACE 1–3 times, then 125I brachytherapy was carried out following the last CSM-TACE. Complete response (CR), objective response rate (ORR), disease control rate (DCR), survival, and adverse events were evaluated.ResultsCR, ORR and DCR were 43.5%, 87.0%, and 100%, respectively, at three months; furthermore, they were 78.3%, 100%, and 100% accordingly at six months. Moreover, most European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30 (QLQ-C30) subscales of functions (including physical and emotional function) and symptoms (including pain, nausea, and vomiting) were generally improved at three months (all P < 0.05). Furthermore, median progression-free survival (PFS) was 14.0 [95% confidence interval (CI): 10.4–17.6] months, with a 1-year PFS rate of 62.9%, but the 2-year PFS rate was not reached. Moreover, the median overall survival (OS) was 22.0 (95% CI: 16.8–27.2) months, with a 1-year OS rate of 91.3% and a 2-year OS rate of 43.5%. Additionally, the main adverse events included fever (100%), pain (65.2%), liver function impairment (65.2%), fatigue (56.5%), and nausea and vomiting (52.2%), which were all categorized as grade 1–2.ConclusionCSM-TACE plus 125I brachytherapy is effective and safe in patients with liver metastases from NSCLC after radical surgery, providing a potentially optimal option in these patients.

Cell migration inducing protein (CEMIP) has been linked to carcinogenesis in several types of cancers. However, the role and mechanism of CEMIP in osteosarcoma remain unclear. This study investigated the role of CEMIP in the progression and metastasis of osteosarcoma, CEMIP was found to be overexpressed in osteosarcoma tissues when compared to adjacent non-tumor tissues, and its expression was positively associated with a poor prognosis in osteosarcoma patients. Silencing CEMIP decreased osteosarcoma cells proliferation, migration, and invasion, but enhanced apoptosis in vitro, and suppressed tumor growth and metastasis in vivo. Mechanistically, CEMIP promoted osteosarcoma cells growth and metastasis through activating Notch signaling pathway, silencing CEMIP would reduce the protein expression and activation of Notch/Jagged1/Hes1 signaling pathway in vitro and in vivo, activation of Notch signaling pathway could partially reversed cell proliferation and migration in shCEMIP osteosarcoma cells. In conclusion, our study demonstrated that CEMIP plays a substantial role in the progression of osteosarcoma via Notch signaling pathway, providing a promising therapeutic target in osteosarcoma.

BackgroundPyrotinib, a small-molecule tyrosine kinase inhibitor, has been investigated as a component of neoadjuvant therapy in phase 2 trials of human epidermal growth factor receptor 2 (HER2)-positive breast cancer. This study aimed to evaluate the effectiveness and safety of pyrotinib-containing neoadjuvant therapy for patients with HER2-positive early or locally advanced breast cancer in the real-world setting.MethodsData of 97 patients with HER2-positive breast cancer from 21 centers across China treated with pyrotinib-containing neoadjuvant therapy were reviewed. Neoadjuvant therapy consisted of taxane/carboplatin/trastuzumab plus pyrotinib (TCbH+Py, 30 [30.9%]), anthracycline/cyclophosphamide followed by taxane/trastuzumab plus pyrotinib (AC-TH+Py) or taxane followed by anthracycline/cyclophosphamide/trastuzumab plus pyrotinib (T-ACH+Py, 29 [29.9%]), taxane/trastuzumab plus pyrotinib (TH+Py, 23 [23.7%]), and other pyrotinib-containing neoadjuvant treatment (15 [15.5%]). The primary outcome was breast pathological complete response (bpCR, ypT0/is) rate. Secondary outcomes included total pathological complete response (tpCR, ypT0/is ypN0) rate, objective response rate (ORR), and the incidence of preoperative adverse events.ResultsThe ORR of pyrotinib-containing neoadjuvant therapy was 87.6% (85/97). The bpCR and tpCR rates were 54.6% (95% confidence interval [CI], 44.2%-64.7%) and 48.5% [95% CI, 38.2%-58.8%], respectively. The most common grade 3 or 4 treatment-related adverse events included diarrhea (15 [15.5%]), decreased hemoglobin (nine [9.3%]), and decreased neutrophil count (eight [8.2%]). No treatment-related deaths occurred.ConclusionPyrotinib-containing neoadjuvant therapy for patients with HER2-positive early or locally advanced breast cancer shows favorable effectiveness with manageable toxicity in the real-world setting. Trastuzumab plus pyrotinib may be a novel option of dual HER2-targeted blockade.

BackgroundHER2-positive breast cancer was aggressive, resulting in a poorer prognosis. This multicenter study analyzed the real-world data of women treated with pyrotinib-based therapy, aiming to describe their characteristics, treatment regimens, and to investigate the clinical outcomes.MethodsA total of 141 patients with HER2-positive breast cancer were enrolled from February 2019 to April 2020. Last follow-up time was February 2021. All patients were treated with pyrotinib-based therapy in 21-day cycles. The primary endpoint was progression-free survival (PFS).ResultsThe median PFS (mPFS) for pyrotinib-based therapy was 12.0 months (95%CI 8.1-17.8) in all patients. Among the patients with liver metastases, mPFS was 8.7 months (95%CI, 6.3-15.4) compared to 12.3 months (95%CI, 8.8-23.3) for patients without liver metastases (P=0.172). In addition, patients receiving pyrotinib-based therapy as their >2 lines treatment had a numerically lower mPFS than those receiving pyrotinib-based therapy as their ≤2 lines treatment [8.4 (95%CI, 5.9-15.4) vs. 15.1 (95%CI, 9.3-22.9) months, P=0.107]. The mPFS was 12.2 months (95%CI, 7.9-18.8) in patients with previous exposure to trastuzumab and 11.8 months (95%CI, 6.8-22.9) in patients without previous exposure to trastuzumab (P=0.732). Moreover, mPFS in patients receiving regimens with and without capecitabine were 15.1 months (95%CI, 10.0-18.8) and 8.4 months (95%CI, 6.7-22.9), respectively (P=0.070). Furthermore, in patients with brain metastases, estimated 6-month PFS rate was 70.0%, and rate at 12 months was 60.0%. Seventy patients with measurable lesions were evaluable for response. The objective response rate was 38.6% and disease control rate was 85.7%. The most common adverse event was diarrhea (85.0%).ConclusionPyrotinib-based therapy showed promising efficacy in patients with HER2-positive breast cancer and was well tolerated, especially in patients treated with pyrotinib as ≤2 lines treatment and receiving regimens with capecitabine. The results of this real-world study further confirmed the intriguing efficacy of pyrotinib.

Clear cell renal cell carcinoma (ccRCC) is a common malignancy with high distant metastasis rate. Long non-coding RNAs (LncRNAs) are reported to be upregulated or downregulated in multiple cancers and play a crucial role in the metastasis of tumors or prognosis. Therefore, the purpose of our study is to construct a prognostic signature for ccRCC based on distant metastasis-related lncRNAs and explore the involved potential competitive endogenous RNA (ceRNA) network. The differentially expressed genes (DEGs) screened from the database of the cancer genome atlas (TCGA) were used to construct a co-expression network and identify the distant metastasis-related module by weighted gene co-expression network analysis (WGCNA). Key genes with metastatic and prognostic significance were identified through rigorous screening, including survival analysis, correlation analysis, and expression analyses in stage, grade, and distant metastasis, and were verified in the data set of gene expression omnibus (GEO) and the database from gene expression profiling interactive analysis (GEPIA). The potential upstream miRNAs and lncRNAs were predicted via five online databases and LncBase. Here, we constructed a ceRNA network of key genes that are significantly associated with the distant metastasis and prognosis of patients with ccRCC. The distant metastasis-related lncRNAs were used to construct a risk score model through the univariate, least absolute shrinkage selection operator (LASSO), and multivariate Cox regression analyses, and the patients were divided into high- and low-risk groups according to the median of the risk score. The Kaplan–Meier survival analysis demonstrated that mortality was significantly higher in the high-risk group than in the low-risk group. Considering the other clinical phenotype, the Cox regression analyses indicated that the lncRNAs model could function as an independent prognostic factor. Quantitative real-time (qRT)-PCR in the tissues and cells of ccRCC verified the high-expression level of three lncRNAs. Gene set enrichment analysis (GSEA) revealed that the lncRNA prognostic signature was mainly enriched in autophagy- and immune-related pathways, indicating that the autophagy and immune functions may play an important role in the distant metastasis of ccRCC. In summary, the constructed distant metastasis-related lncRNA signature could independently predict prognosis in patients with ccRCC, and the related ceRNA network provided a new sight on the potential mechanism of distant metastasis and a promising therapeutic target for ccRCC.

Background: To compare the diagnostic performance of radiomics models with that of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) perfusion parameters for the preoperative prediction of extramural venous invasion (EMVI) in rectal cancer patients and to develop a preoperative nomogram for predicting the EMVI status.Methods: In total, 106 rectal cancer patients were enrolled in our study. All patients under went preoperative rectal high-resolution MRI and DCE-MRI. We built five models based on the perfusion parameters of DCE-MRI (quantitative model), the radiomics of T2-weighted (T2W) CUBE imaging (R1 model), DCE-MRI (R2 model), clinical features (clinical model), and clinical-radiomics features. The predictive efficacy of the radiomics signature was assessed and internally verified. The area under the receiver operating curve (AUC) was used to compare the diagnostic performance of different radiomics models and DCE-MRI quantitative parameters. The radiomics score and clinical-pathologic risk factors were incorporated into an easy-to-use nomogram.Results: The quantitative parameters Ktrans and Ve were significantly higher in the EMVI-positive group than in the EMVI-negative group (both P =0.02). Ktrans combined with Ve showed a fair degree of accuracy (AUC 0.680 in the training cohort and AUC 0.715 in the validation cohort) compared with Ktrans or Ve alone. The AUCs of the R1 and R2 models were 0.826, 0.715 and 0.872, 0.812 in the training and validation cohorts, respectively. In addition, the R2-C model yielded an AUC of 0.904 in the training cohort and 0.812 in the validation cohort. The nomogram was presented based on the clinical-radiomics model. The calibration curves showed good agreement.Conclusion: The radiomics nomogram that incorporates the radiomics score, histopathological grade and T stage demonstrated better diagnostic accuracy than the DCE-MRI quantitative parameters and may have significant clinical implications for the preoperative individualized prediction of EMVI in rectal cancer patients.

Although radiotherapy is greatly successful in the treatment of prostate cancer (PCa), radioresistance is still a major challenge in the treatment. To our knowledge, this study is the first to screen long non-coding RNAs (lncRNAs) associated with radioresponse in PCa by The Cancer Genome Atlas (TCGA). Bioinformatics methods were used to identify the differentially expressed lncRNAs and protein-coding genes (PCGs) between complete response (CR) and non-complete response (non-CR) groups in radiotherapy. Statistical methods were applied to identify the correlation between lncRNAs and radioresponse as well as lncRNAs and PCGs. The correlation between PCGs and radioresponse was analyzed using weighted gene co-expression network analysis (WGCNA). The three online databases were used to predict the potential target miRNAs of lncRNAs and the miRNAs that might regulate PCGs. RT-qPCR was utilized to detect the expression of lncRNAs and PCGs in our PCa patients. A total of 65 differentially expressed lncRNAs and 468 differentially expressed PCGs were found between the two groups of PCa. After the chi-square test, LINC01600 was selected to be highly correlated with radioresponse from the 65 differentially expressed lncRNAs. Pearson correlation analysis found 558 PCGs co-expressed with LINC01600. WGCNA identified the darkred module associated with radioresponse in PCa. After taking the intersection of the darkred module of WGCNA, differentially expressed PCGs between the two groups of PCa, and the PCGs co-expressed with LINC01600, three PCGs, that is, JUND, ZFP36, and ATF3 were identified as the potential target PCGs of LINC01600. More importantly, we detected the expression of LINC01600 and three PCGs using our PCa patients, and finally verified that LINC01600 and JUND were differentially expressed between CR and non-CR groups, excluding ZFP36 and ATF3. Meantime, the potential regulation ability of LINC01600 for JUND in PCa cell lines was initially explored. In addition, we constructed the competing endogenous RNA (ceRNA) network of LINC01600—miRNA—JUND. In conclusion, we initially reveal the association of LINC01600 with radioresponse in PCa and identify its potential target PCGs for further basic and clinical research.

Purpose: Conventional iterative low-dose CBCT reconstruction techniques are slow and tend to over-smooth edges through uniform weighting of the image penalty gradient. In this study, we present a non-iterative analytical low-dose CBCT reconstruction technique by restoring the noisy low-dose CBCT projection with the non-local total variation (NLTV) method.Methods: We modeled the low-dose CBCT reconstruction as recovering high quality, high-dose CBCT x-ray projections (100 kVp, 1.6 mAs) from low-dose, noisy CBCT x-ray projections (100 kVp, 0.1 mAs). The restoration of CBCT projections was performed using the NLTV regularization method. In NLTV, the x-ray image is optimized by minimizing an energy function that penalizes gray-level difference between pair of pixels between noisy x-ray projection and denoising x-ray projection. After the noisy projection is restored by NLTV regularization, the standard FDK method was applied to generate the final reconstruction output.Results: Significant noise reduction was achieved comparing to original, noisy inputs while maintaining the image quality comparable to the high-dose CBCT projections. The experimental validations show the proposed NLTV algorithm can robustly restore the noise level of x-ray projection images while significantly improving the overall image quality. The improvement in normalized mean square error (NMSE) and peak signal-to-noise ratio (PSNR) measured from the non-local total variation-gradient projection (NLTV-GPSR) algorithm is noticeable compared to that of uncorrected low-dose CBCT images. Moreover, the difference of CNRs from the gains from the proposed algorithm is noticeable and comparable to high-dose CBCT.Conclusion: The proposed method successfully restores noise degraded, low-dose CBCT projections to high-dose projection quality. Such an outcome is a considerable improvement to the reconstruction result compared to the FDK-based method. In addition, a significant reduction in reconstruction time makes the proposed algorithm more attractive. This demonstrates the potential use of the proposed algorithm for clinical practice in radiotherapy.

Background: Previous genetic-epidemiological studies considered TERT (rs2736100), CCDC26 (rs4295627), CDKN2A/B (rs4977756) and RTEL1 (rs6010620) gene polymorphisms as the risk factors specific to glioma. However, the data samples of previous genetic-epidemiological studies are modest to determine whether they have definite association with glioma. Method: The study paid attention to systematically searching databases of PubMed, Embase, Web of Science (WoS), Scopus, Cochrane Library and Google Scholars. Meta-analysis under 5 genetic models, namely recessive model (RM), over-dominant model (O-DM), allele model (AM), co-dominant model (C-DM) and dominant model (DM) was conducted for generating odds ratios (ORs) and 95% confidence intervals (CIs). That was accompanied by subgroup analyses according to various racial groups. The software STATA 17.0 MP was implemented in the study. Result: 21 articles were collected. According to data analysis results, in four genetic models (AM, RM, DM and C-DM) TERT gene rs2736100 polymorphism, CCDC26 gene rs4295627 polymorphism, CDKN2A/B gene rs4977756 polymorphism and RTEL1 gene rs6010620 polymorphisms increased the risk of glioma in Caucasians to different degrees. In Asian populations, the CCDC26 gene rs4295627 polymorphism and CDKN2A/B gene rs4977756 polymorphism did not exhibit a relevance to the risk of glioma. It is suggested to cautiously explain these results as the sample size is small. Conclusion: The current meta-analysis suggested that the SNP of TERT (rs2736100), CCDC26 (rs4295627), CDKN2A/B (rs4977756) and RTEL1 (rs6010620) genes in glioma might increase risk of glioma, but there are ethnic differences. Further studies evaluating these polymorphisms and glioma risk are warranted. [ABSTRACT FROM AUTHOR]

Full thickness endoscopic resection of large submucosal gastric tumors (>3 cm) is a big challenge for endoscopists. Issues include how to efficiently resect the lesion, obtain homeostasis, and suture the defect. There are no guidelines regarding the importance of patient position on the success of endoscopic resections in anesthetized patients. Typically, the patient is placed in left lateral position for the endoscopic therapy and during the procedure patient’s position is changed to maintain the tumor above the gastric fluids to prevent gastric juices and tumor or tumor fragments from falling into the peritoneal cavity in the event of perforation. This study emphasized the importance of planning the procedure to ensure that the patient’s position and anesthetist’s concerns are met and allow optimal access to the lesion for endoscopic resection. Prior to sedation the patient should be positioned so that the tumor is in the up position which also prevents blood obscuring the operative field, helps detect bleeding points for immediately hemostasis. In addition, due to gravitational effect, the resected tumor will fall into the gastric cavity exposing the root of the tumor making resection easier and reduce procedure time. Preplanning avoids unnecessary readjustment of positioning and improves the ease and safety of the procedure. [ABSTRACT FROM AUTHOR]

The ectopic HLA-G expression in malignancies has been extensively explored and clinical significance of the molecule was widely acknowledged. Besides previously well-documented seven isoforms (HLA-G1-G7), other novel isoforms of HLA-G have been reported but their clinical relavenace remians evaluated. In this study, lesion HLA-G expression in 379 case-matched serial section primary colorectal cancers (CRC) were evaluated with mAb 4H84 (recognizing an epitope in HLA-G a1 domain), and mAb 5A6G7 (recognizing an epitope encoded by intron 4), respectively. Data showed that HLA-G positive staining with mAbs 4H84 and 5A6G7 was 70.7 and 60.4%, respectively. When percentage of HLA-G expression detected with mAb 4H84 subtracted that with mAb 5A6G7, the difference (1HLA-G) with negative (1HLA-Gneg), comparable (1HLA- Gcom) and positive (1HLA-Gpos) were observed in 64 (16.9%), 159 (42.0%), and 156 (41.2%) cases, respectively. Noteworthy, unexpected immunostaining was observed in 44 (11.6%) lesions that no staining was detected with mAb 4H84 but positive with mAb 5A6G7 (4H84neg5A6G7pos). This staining pattern was unpredictable because all seven known HLA-G isoforms containing the a 1 domain could be recognized by the mAb 4H84. Moreover, patients with 1HLA-Gneg had obviously better survival than those with 1HLA-Gcom and 1HLA-Gpos (p = 0.017), and 1HLA-G could be an independent prognostic factor for CRC patients (p = 0.008). Our findings provides the first report that potential unidentified HLA-G isoforms is of distinct clinical significance in CRC patients. [ABSTRACT FROM AUTHOR]