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The present study demonstrated that the ICI score may be an effective prognostic biomarker and predictive indicator for chemotherapy and immunotherapy.

The aim of the current study was to evaluate the safety and efficacy of transcatheter arterial chemoembolization (TACE) in elderly patients diagnosed as advanced hepatocellular carcinoma (HCC) accompanied with different types of portal vein tumor thrombosis (PVTT).

Elderly HCC patients aged 70-year-old and above from January 2015 to December 2019 were included in this retrospective study. Efficacy data including OS, PFS, DCR, and ORR and safety data were collected in the indicated groups. Outcomes of HCC patients in the TACE group were compared with those patients in the best supportive care (BSC) group. Subgroup analyses were also conducted in the patients with different types of PVTT.

Among 245 elderly HCC patients, 124 were enrolled in this study. Out of these, 50.0% (n=62) underwent BSC treatment while 50.0% (n=62) underwent TACE. There were no major differences in the baseline characteristics of the two treatment groups. TACE treatment was associated with better median OS compared with BSC alone (1 2.18; 95%CI 1.29-3.70;

=0.004), tumor diameter (>5cm

≤5 cm) (HR 1.94; 95%CI 1.28-2.93;

=0.002), and treatment (TACE

BSC) (HR 0.48; 95%CI 0.32-0.72;

<0.001) were independent indicators of overall survival.

In elderly advanced HCC patients with PVTT, palliative TACE treatment can be an accessible effective measure to improve the OS and PFS for both type I and type II PVTT patients.

In elderly advanced HCC patients with PVTT, palliative TACE treatment can be an accessible effective measure to improve the OS and PFS for both type I and type II PVTT patients.The heterogeneity and complexity of non-small cell lung cancer (NSCLC) tumors mean that NSCLC patients at the same stage can have different chemotherapy prognoses. Accurate predictive models could recognize NSCLC patients likely to respond to chemotherapy so that they can be given personalized and effective treatment. We propose to identify predictive imaging biomarkers from pre-treatment CT images and construct a radiomic model that can predict the chemotherapy response in NSCLC. This single-center cohort study included 280 NSCLC patients who received first-line chemotherapy treatment. Non-contrast CT images were taken before and after the chemotherapy, and clinical information were collected. Based on the Response Evaluation Criteria in Solid Tumors and clinical criteria, the responses were classified into two categories response (n = 145) and progression (n = 135), then all data were divided into two cohorts training cohort (224 patients) and independent test cohort (56 patients). In total, 1629 features cg homogeneity was underrepresented. The proposed radiomic model with pre-chemotherapy CT features can predict the chemotherapy response of patients with non-small cell lung cancer. This radiomic model can help to stratify patients with NSCLC, thereby offering the prospect of better treatment.

The CAPRICE trial was designed to specifically evaluate neoadjuvant pegylated liposomal doxorubicin (PLD) in elderly patients or in those with other cardiovascular risk factors in whom conventional doxorubicin was contraindicated. The primary analysis of the study showed a pathological complete response (pCR) of 32% and no significant decreases in LVEF during chemotherapy. Here, we report important secondary study objectives 5-year cardiac safety, disease-free survival (DFS), overall survival (OS) and breast cancer specific survival (BCSS).

In this multicentre, single-arm, phase II trial, elderly patients or those prone to cardiotoxicity and high risk stage II-IIIB breast cancer received PLD (35 mg/m

) plus cyclophosphamide (600 mg/m

) every 4 weeks for 4 cycles, followed by paclitaxel for 12 weeks as neoadjuvant chemotherapy (NAC). Left ventricular ejection fraction (LVEF) monitorization, electrocardiograms and cardiac questionnaires were performed at baseline, during treatment and at 9, 16, 28 and 40 gov reference NCT00563953.

ClinicalTrials.gov reference NCT00563953.Sorafenib a multi-target tyrosine kinase inhibitor, is the first-line drug for treating advanced hepatocellular carcinoma (HCC). Mechanistically, it suppresses tumor angiogenesis, cell proliferation and promotes apoptosis. Although sorafenib effectively prolongs median survival rates of patients with advanced HCC, its efficacy is limited by drug resistance in some patients. In HCC, this resistance is attributed to multiple complex mechanisms. Previous clinical data has shown that HIFs expression is a predictor of poor prognosis, with further evidence demonstrating that a combination of sorafenib and HIFs-targeted therapy or HIFs inhibitors can overcome HCC sorafenib resistance. Here, we describe the molecular mechanism underlying sorafenib resistance in HCC patients, and highlight the impact of hypoxia microenvironment on sorafenib resistance.

To explore the usefulness of texture signatures based on multiparametric magnetic resonance imaging (MRI) in predicting the subtypes of growth hormone (GH) pituitary adenoma (PA).

Forty-nine patients with GH-secreting PA confirmed by the pathological analysis were included in this retrospective study. Texture parameters based on T1-, T2-, and contrast-enhanced T1-weighted images (T1C) were extracted and compared for differences between densely granulated (DG) and sparsely granulated (SG) somatotroph adenoma by using two segmentation methods [region of interest 1 (ROI

), excluding the cystic/necrotic portion, and ROI

, containing the whole tumor]. Receiver operating characteristic (ROC) curve analysis was performed to determine the differentiating efficacy.

Among 49 included patients, 24 were DG and 25 were SG adenomas. Nine optimal texture features with significant differences between two groups were obtained from ROI

. Based on the ROC analyses, T1WI signatures from ROI

achieved the highest diagnostic efficacy with an AUC of 0.918, the accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were 85.7, 72.0, 100.0, 100.0, and 77.4%, respectively, for differentiating DG from SG. selleck chemical Comparing with the T1WI signature, the T1C signature obtained relatively high efficacy with an AUC of 0.893. When combining the texture features of T1WI and T1C, the radiomics signature also had a good performance in differentiating the two groups with an AUC of 0.908. In addition, the performance got in all the signatures from ROI

was lower than those in the corresponding signature from ROI



Texture signatures based on MR images may be useful biomarkers to differentiate subtypes of GH-secreting PA patients.

Texture signatures based on MR images may be useful biomarkers to differentiate subtypes of GH-secreting PA patients.Radiomics is an emerging field in radiology that utilizes advanced statistical data characterizing algorithms to evaluate medical imaging and objectively quantify characteristics of a given disease. Due to morphologic heterogeneity and genetic variation intrinsic to neoplasms, radiomics have the potential to provide a unique insight into the underlying tumor and tumor microenvironment. Radiomics has been gaining popularity due to potential applications in disease quantification, predictive modeling, treatment planning, and response assessment - paving way for the advancement of personalized medicine. However, producing a reliable radiomic model requires careful evaluation and construction to be translated into clinical practices that have varying software and/or medical equipment. We aim to review the diagnostic utility of radiomics in otorhinolaryngology, including both cancers of the head and neck as well as the thyroid.

We previously reported that a high tumor burden is a prognostic factor based on an analysis of 26 patients with radioactive iodine-refractory differentiated thyroid cancer (RR-DTC) who were treated with lenvatinib. However, the optimal tumor burden for starting lenvatinib still remains to be defined. The aim of this retrospective study was to further explore in the same patient cohort the optimal timing for the start of lenvatinib by focusing on the pre- and post-treatment tumor burden.

The 26 patients were treated with lenvatinib from 2012 to 2017. We explored the optimal timing for the start of lenvatinib by comparing the characteristics of long-term responders who were defined as patients with progression-free survival ≥ 30 months and non-long-term responders.

Long-term responders had a smaller post-treatment tumor burden at maximum shrinkage than non-long-term responders. Further, post-treatment tumor burden had a strong linear correlation with baseline tumor burden. We created an estimation formula for baseline tumor burden related to prognosis, using these regression lines. Patients with a sum of diameters of target lesions < 60mm or maximum tumor diameter < 34mm at baseline were estimated to have significantly better survival outcomes.

We found a strong linear correlation between pre- and post-treatment tumor burden. Our results suggested a cut-off value for baseline tumor burden for long-term prognosis among patients treated with lenvatinib.

We found a strong linear correlation between pre- and post-treatment tumor burden. Our results suggested a cut-off value for baseline tumor burden for long-term prognosis among patients treated with lenvatinib.Glioblastoma multiforme (GBM) is the most common brain malignancy and major cause of high mortality in patients with GBM, and its high recurrence rate is its most prominent feature. However, the pathobiological mechanisms involved in recurrent GBM remain largely unknown. Here, whole-transcriptome sequencing (RNA-sequencing, RNA-Seq) was used in characterizing the expression profile of recurrent GBM, and the aim was to identify crucial biomarkers that contribute to GBM relapse. Differentially expressed RNAs in three recurrent GBM tissues compared with three primary GBM tissues were identified through RNA-Seq. The function and mechanism of a candidate long noncoding RNA (lncRNA) in the progression and recurrence of GBM were elucidated by performing comprehensive bioinformatics analyses, such as functional enrichment analysis, protein-protein interaction prediction, and lncRNA-miRNA-mRNA regulatory network construction, and a series of in vitro assays. As the most significantly upregulated gene identified in recy will provide new insight into the regulatory mechanisms of NONHSAT079852.2-mediated competing endogenous RNA in the pathogenesis of recurrent GBM and evidence of the potential of lncRNAs as diagnostic biomarkers or potential therapeutic targets.

Heavy ion radiotherapy (HIRT) has great advantages as tumor radiotherapy.

Based on 1,558 literatures from core collections of Web of Science from 1980 to 2020, this study visually analyzes the evolution of HIRT research, and sorts out the hotspots and trends of HIRT research using CiteSpace software.

Research on HIRT has received more extensive attention over the last 40 years. The development of HIRT is not only closely related to radiation and oncology, but also closely related to the development of human society. In terms of citation frequency, "International Journal of Radiation Oncology*Biology*Physics" was the top journal. In terms of influence, "Radiotherapy and Oncology" was the top journal. "Radiation therapy" and "carbon ion radiotherapy" were the two most frequently used keywords in this field.

The evolution of the HIRT research has occurred in approximately three stages, including technological exploration, safety and effectiveness research and technological breakthroughs. Finally, some suggestions for future research are put forward.