Proteome-wide analysis reveals potential therapeutic targets for Colorectal cancer: a two-sample mendelian randomization study.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related mortality, highlighting an unmet clinical need for more effective therapies. This study aims to evaluate the causal relationship between 4,489 plasma proteins and CRC to identify potential therapeutic targets for CRC. METHODS: We conducted two-sample Mendelian randomization (MR) analysis to examine the causal effects of plasma proteins on CRC. Mediation analysis was performed to assess the indirect effects of plasma proteins on CRC through associated risk factors. In addition, we conducted a phenome-wide association study using the UK Biobank dataset to examine associations between these plasma proteins and other phenotypes. RESULTS: Out of 4,489 plasma proteins, MR analysis revealed causal associations with CRC for 23 proteins, including VIMP, MICB, TNFRSF11B, C5orf38 and SLC5A8. Our findings also confirm the associations between reported risk factors and CRC. Mediation analysis identified mediating effects of proteins on CRC outcomes through risk factors. Furthermore, MR analysis identified 154 plasma proteins are causally linked to at least one CRC risk factor. CONCLUSIONS: Our study evaluated the causal relationships between plasma proteins and CRC, providing a more complete understanding of potential therapeutic targets for CRC.

Efficacy and safety of pyrotinib in advanced lung adenocarcinoma with HER2 mutations: a multicenter, single-arm, phase II trial.

BACKGROUND: There is currently a lack of effective treatments for non-small cell lung cancer (NSCLC) patients harboring HER2 mutations. We examined the efficacy and safety of, and potential resistance mechanism to, pyrotinib, a pan-HER inhibitor, in advanced NSCLC carrying HER2 mutations. METHODS: In this multicenter, single-arm, phase II trial, stage IIIB-IV NSCLC patients harboring HER2 mutations, as determined using next-generation sequencing, were enrolled and treated with pyrotinib at a dose of 400 mg/day. The primary endpoint was 6-month progression-free survival (PFS) rate, and secondary endpoints were objective response rate (ORR), PFS, overall survival (OS), disease control rate (DCR), and safety. The impact of different HER2 mutation types on sensitivity to pyrotinib and the potential of utilizing mutational profile derived from circulating tumor DNA (ctDNA) to predict disease progression were also explored. RESULTS: Seventy-eight patients were enrolled for efficacy and safety analysis. The 6-month PFS rate was 49.5% (95% confidence interval [CI], 39.2-60.8). Pyrotinib produced an ORR of 19.2% (95% CI, 11.2-30.0), with median PFS of 5.6 months (95% CI, 2.8-8.4), and median OS of 10.5 months (95% CI, 8.7-12.3). The median duration of response was 9.9 months (95% CI, 6.2-13.6). All treatment-related adverse events (TRAEs) were grade 1-3 (all, 91.0%; grade 3, 20.5%), and the most common TRAE was diarrhea (all, 85.9%; grade 3, 16.7%). Patients with exon 20 and non-exon 20 HER2 mutations had ORRs of 17.7% and 25.0%, respectively. Brain metastases at baseline and prior exposure to afatinib were not associated with ORR, PFS, or OS. Loss of HER2 mutations and appearance of amplification in HER2 and EGFR were detected upon disease progression. CONCLUSIONS: Pyrotinib exhibited promising efficacy and acceptable safety in NSCLC patients carrying exon 20 and non-exon 20 HER2 mutations and is worth further investigation. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR1800020262.

RefineNet-based 2D and 3D automatic segmentations for clinical target volume and organs at risks for patients with cervical cancer in postoperative radiotherapy.

PURPOSE: An accurate and reliable target volume delineation is critical for the safe and successful radiotherapy. The purpose of this study is to develop new 2D and 3D automatic segmentation models based on RefineNet for clinical target volume (CTV) and organs at risk (OARs) for postoperative cervical cancer based on computed tomography (CT) images. METHODS: A 2D RefineNet and 3D RefineNetPlus3D were adapted and built to automatically segment CTVs and OARs on a total of 44 222 CT slices of 313 patients with stage I-III cervical cancer. Fully convolutional networks (FCNs), U-Net, context encoder network (CE-Net), UNet3D, and ResUNet3D were also trained and tested with randomly divided training and validation sets, respectively. The performances of these automatic segmentation models were evaluated by Dice similarity coefficient (DSC), Jaccard similarity coefficient, and average symmetric surface distance when comparing them with manual segmentations with the test data. RESULTS: The DSC for RefineNet, FCN, U-Net, CE-Net, UNet3D, ResUNet3D, and RefineNet3D were 0.82, 0.80, 0.82, 0.81, 0.80, 0.81, and 0.82 with a mean contouring time of 3.2, 3.4, 8.2, 3.9, 9.8, 11.4, and 6.4 s, respectively. The generated RefineNetPlus3D demonstrated a good performance in the automatic segmentation of bladder, small intestine, rectum, right and left femoral heads with a DSC of 0.97, 0.95, 091, 0.98, and 0.98, respectively, with a mean computation time of 6.6 s. CONCLUSIONS: The newly adapted RefineNet and developed RefineNetPlus3D were promising automatic segmentation models with accurate and clinically acceptable CTV and OARs for cervical cancer patients in postoperative radiotherapy.

The Accuracy and Radiomics Feature Effects of Multiple U-net-Based Automatic Segmentation Models for Transvaginal Ultrasound Images of Cervical Cancer.

Ultrasound (US) imaging has been recognized and widely used as a screening and diagnostic imaging modality for cervical cancer all over the world. However, few studies have investigated the U-net-based automatic segmentation models for cervical cancer on US images and investigated the effects of automatic segmentations on radiomics features. A total of 1102 transvaginal US images from 796 cervical cancer patients were collected and randomly divided into training (800), validation (100) and test sets (202), respectively, in this study. Four U-net models (U-net, U-net with ResNet, context encoder network (CE-net), and Attention U-net) were adapted to segment the target of cervical cancer automatically on these US images. Radiomics features were extracted and evaluated from both manually and automatically segmented area. The mean Dice similarity coefficient (DSC) of U-net, Attention U-net, CE-net, and U-net with ResNet were 0.88, 0.89, 0.88, and 0.90, respectively. The average Pearson coefficients for the evaluation of the reliability of US image-based radiomics were 0.94, 0.96, 0.94, and 0.95 for U-net, U-net with ResNet, Attention U-net, and CE-net, respectively, in their comparison with manual segmentation. The reproducibility of the radiomics parameters evaluated by intraclass correlation coefficients (ICC) showed robustness of automatic segmentation with an average ICC coefficient of 0.99. In conclusion, high accuracy of U-net-based automatic segmentations was achieved in delineating the target area of cervical cancer US images. It is feasible and reliable for further radiomics studies with features extracted from automatic segmented target areas.

Differentiate Thyroid Follicular Adenoma from Carcinoma with Combined Ultrasound Radiomics Features and Clinical Ultrasound Features.

Noninvasive differentiating thyroid follicular adenoma from carcinoma preoperatively is of great clinical value to decrease the risks resulted from excessive surgery for patients with follicular neoplasm. The purpose of this study is to investigate the accuracy of ultrasound radiomics features integrating with ultrasound features in the differentiation between thyroid follicular carcinoma and adenoma. A total of 129 patients diagnosed as thyroid follicular neoplasm with pathologically confirmed follicular adenoma and carcinoma were enrolled and analyzed retrospectively. Radiomics features were extracted from preoperative ultrasound images with manually contoured targets. Ultrasound features and clinical parameters were also obtained from electronic medical records. Radiomics signature, combined model integrating radiomics features, ultrasound features, and clinical parameters were constructed and validated to differentiate the follicular carcinoma from adenoma. A total of 23 optimal features were selected from 449 extracted radiomics features. Clinical and ultrasound parameters of sex (p = 0.003), interior structure (p = 0.035), edge (p = 0.02), platelets (p = 0.007), and creatinine (p = 0.001) were associated with the differentiation between benign and malignant follicular neoplasm. The values of area under curves (AUCs) of the radiomics signature, clinical model, and combined model were 0.772 (95% CI: 0.707-0.838), 0.792 (95% CI: 0.715-0.869), and 0.861 (95% CI: 0.775-0.909), respectively. A final corrected AUC of 0.844 was achieved for the combined model after internal validation. Radiomics features from ultrasound images combined with ultrasound features and clinical factors are feasible to differentiate thyroid follicular carcinoma from adenoma noninvasive before operation to decrease the unnecessary of diagnostic thyroidectomy for patients with benign follicular adenoma.

Differentiating the pathological subtypes of primary lung cancer for patients with brain metastases based on radiomics features from brain CT images.

OBJECTIVES: It is of high clinical importance to identify the primary lesion and its pathological types for patients with brain metastases (BM). The purpose of this study is to investigate the feasibility and accuracy of differentiating the primary adenocarcinoma (AD) and squamous cell carcinoma (SCC) of non-small-cell lung cancer (NSCLC) for patients with BM based on radiomics from brain contrast-enhanced computer tomography (CECT) images. METHODS: A total of 144 BM patients (94 male, 50 female) were enrolled in this study with 102 with primary lung AD and 42 with SCC, respectively. Radiomics features from manually contoured tumors were extracted using python. Mann-Whitney U test and the least absolute shrinkage and selection operator (LASSO) logistic regression were applied to select relative radiomics features. Binary logistic regression and support vector machines (SVM) were applied to build models with radiomics features alone and with radiomics features plus age and sex. RESULTS: Fourteen features were selected from a total of 105 radiomics features for the final model building. The area under the curves (AUCs) and accuracy of SVM and binary logistic regression models were 0.765 vs. 0.769, 0.795 vs.0.828, and 0.716 vs. 0.726, 0.768 vs. 0.758, respectively, for models with radiomics features alone and models with radiomics features plus sex and age. CONCLUSIONS: Brain CECT radiomics are promising in differentiating primary AD and SCC to achieve optimal therapeutic management in patients with BM from NSCLC. KEY POINTS: • It is of high clinical importance to identify the primary lesion and its pathological types for patients with brain metastases (BM) to define the prognosis and treatment. • Few studies had investigated the feasibility and accuracy of differentiating the pathological subtypes of primary non-small-cell lung cancer between adenocarcinoma (AD) and squamous cell carcinoma (SCC) for patients with BM based on radiomics from brain contrast-enhanced CT (CECT) images, although CECT images are often the initial imaging modality to screen for metastases and are recommended on equal footing with MRI for the detection of cerebral metastases. • Brain CECT radiomics are promising in differentiating primary AD and SCC to achieve optimal therapeutic management in patients with BM from NSCLC with a highest area under the curve (AUC) of 0.828 and an accuracy of 0.758, respectively.

MicroRNA-1275 induces radiosensitization in oesophageal cancer by regulating epithelial-to-mesenchymal transition via Wnt/ß-catenin pathway.

Acquired radioresistance is one of the main obstacles for the anti-tumour efficacy of radiotherapy in oesophageal cancer (EC). Recent studies have proposed microRNAs (miRNAs) as important participators in the development of radioresistance in various cancers. Here, we investigated the role of miR-1275 in acquired radioresistance and epithelial-mesenchymal transition (EMT) in EC. Firstly, a radioresistant cell line KYSE-150R was established, with an interesting discovery was observed that miR-1275 was down-regulated in KYSE-150R cells compared to the parental cells. Functionally, miR-1275 inhibition elevated radioresistance in KYSE-150 cells via promoting EMT, whereas enforced expression of miR-1275 increased radiosensitivity in KYSE-150R cells by inhibiting EMT. Mechanically, we demonstrated that miR-1275 directly targeted WNT1 and therefore inactivated Wnt/ß-catenin signalling pathway in EC cells. Furthermore, WNT1 depletion countervailed the promoting effect of miR-1275 suppression on KYSE-150 cell radioresistance through hampering EMT, whereas WNT1 overexpression rescued miR-1275 up-regulation-impaired EMT to reduce the sensitivity of KYSE-150R cells to radiation. Collectively, our findings suggested that miR-1275 suppressed EMT to encourage radiosensitivity in EC cells via targeting WNT1-activated Wnt/ß-catenin signalling, providing a new therapeutic outlet for overcoming radioresistance of patients with EC.

Chemoradiotherapy with extended nodal irradiation and/or erlotinib in locally advanced oesophageal squamous cell cancer: long-term update of a randomised phase 3 trial.

BACKGROUND: To report the long-term outcomes of a phase III trial designed to test two hypotheses: (1) elective nodal irradiation (ENI) is superior to conventional field irradiation (CFI), and (2) chemoradiotherapy plus erlotinib is superior to chemoradiotherapy in locally advanced oesophageal squamous cell cancer (ESCC). METHODS: Patients with locally advanced ESCC were randomly assigned (1:1:1:1 ratio) to one of the four groups: A: radiotherapy adoption of ENI with two cycles of concurrent TP chemotherapy (paclitaxel and cisplatin) plus erlotinib; B: radiotherapy adoption of ENI with two cycles of concurrent TP; C: radiotherapy adoption of CFI with two cycles of concurrent TP plus erlotinib and D: radiotherapy adoption of CFI with two cycles of concurrent TP. A total of 60 Gy of radiation doses was delivered over 30 fractions. We explored the impact of epidermal growth factor receptor (EGFR) expression on the efficacy of erlotinib plus chemoradiotherapy. RESULTS: A total of 352 patients (88 assigned to each treatment group) were enrolled. The 5-year survival rates were 44.9%, 34.8%, 33.8% and 19.6% in groups A, B, C and D, respectively (P = 0.013). ENI significantly improved OS compared with standard CFI (median, 38.5 vs 22.6 months; HR, 0.74; P = 0.018). The addition of erlotinib significantly improved OS (median, 39.4 vs 27.4 months; HR, 0.75; P = 0.025). Patients with overexpressing EGFR treated with erlotinib had a better OS and PFS than those without erlotinib. CONCLUSIONS: Concurrent chemoradiotherapy with ENI and/or erlotinib improved long-term survival in locally advanced ESCC. CLINICAL TRIAL REGISTRATION: Trial registration: NCT00686114.

Noninvasive prediction of lymph node status for patients with early-stage cervical cancer based on radiomics features from ultrasound images.

OBJECTIVE: To investigate the feasibility of a noninvasive detection of lymph node metastasis (LNM) for early-stage cervical cancer (ECC) patients with radiomics methods based on the textural features from ultrasound images. METHODS: One hundred seventy-two ECC patients between January 2014 and September 2018 with pathologically confirmed lymph node status (LNS) and preoperative ultrasound images were retrospectively reviewed. Regions of interest (ROIs) were delineated by a senior radiologist in the ultrasound images. LIFEx was applied to extract textural features for radiomics study. Least absolute shrinkage and selection operator (LASSO) regression was applied for dimension reduction and for selection of key features. A multivariable logistic regression analysis was adopted to build the radiomics signature. The Mann-Whitney U test was applied to investigate the correlation between radiomics and LNS for both training and validation cohorts. Receiver operating characteristic (ROC) curves were applied to evaluate the accuracy of the radiomics prediction models. RESULTS: A total of 152 radiomics features were extracted from ultrasound images, in which 6 features were significantly associated with LNS (p < 0.05). The radiomics signatures demonstrated a good discrimination between patients with LNM and non-LNM groups. The best radiomics performance model achieved an area under the curve (AUC) of 0.79 (95% confidence interval (CI), 0.71-0.88) in the training cohort and 0.77 (95% CI, 0.65-0.88) in the validation cohort. CONCLUSIONS: The feasibility of radiomics features from ultrasound images for the prediction of LNM in ECC was investigated. This noninvasive prediction method may be used to facilitate preoperative identification of LNS in patients with ECC. KEY POINTS: • Few studied had investigated the feasibility of radiomics based on ultrasound images for cervical cancer, even though it is the most common practice for gynecological cancer diagnosis and treatment. • The radiomics signatures based on ultrasound images demonstrated a good discrimination between patients with and without lymph node metastasis with an area under the curve (AUC) of 0.79 and 0.77 in the training and validation cohorts, respectively. • The radiomics model based on preoperative ultrasound images has the potential ability to predict lymph node status noninvasively in patients with early-state cervical cancer, so as to reduce the impact of invasive examination and to optimize the treatment choices.

Impact of setup errors on multi-isocenter volumetric modulated arc therapy for craniospinal irradiation.

Multi-isocenter volumetric modulated arc therapy (VMAT) is recommended for craniospinal irradiation (CSI) to smooth the dose distribution in the junction regions relying solely on inverse optimization. However, few studies have measured the dosimetric impact of setup errors on this multi-isocenter VMAT in the junction areas. The purpose of this study is to evaluate the impact of positional errors during VMAT CSI with two-dimension (2D) and three-dimension (3D) dosimetric measurements. A total of 20 patients treated by three-isocenter VMAT CSI were retrospectively reviewed and analyzed. A 3D diode array ArcCHECK and radiochromic film EBT3 were applied to measure the percentage gamma passing rates (%GPs) and dose distributions in the junction areas between the cranial/upper-spinal and the upper/lower-spinal fields with intentionally introduced setup errors of ± 1 mm, ±2 mm, ±3 mm, ±5 mm, and ± 8 mm, respectively. The length and volume of planning target volume (PTV) for these CSI patients ranged from 50.14 to 80.8 cm, and 1572.3 to 2114.5 cm3 , respectively. The %GPs for ±3 mm, ±5 mm, and ±8 mm positional errors were around 95%, 90%, and 85%, respectively, in the junction areas. The dosimetric verification results with EBT3 films indicated that cold and hot areas were observed with the increase of introduced setup errors. In conclusion, the dosimetric verification with intentionally introduced setup errors demonstrated that positional errors within 3 mm have a little impact for VMAT CSI, although setup errors should be minimized. Relying on the inverse optimization of VMAT to smooth the dose distribution in the junction areas is feasible for CSI.

Cross verification of independent dose recalculation, log files based, and phantom measurement-based pretreatment quality assurance for volumetric modulated arc therapy.

Independent treatment planning system (TPS) check with Mobius3D software, log files based quality assurance (QA) with MobiusFX, and phantom measurement-based QA with ArcCHECK were performed and cross verified for head-and-neck (17 patients), chest (16 patients), and abdominal (19 patients) cancer patients who underwent volumetric modulated arc therapy (VMAT). Dosimetric differences and percentage gamma passing rates (%GPs) were evaluated and compared for this cross verification. For the dosimetric differences in planning target volume (PTV) coverage, there was no significant difference among TPS vs. Mobius3D, TPS vs. MobiusFX, and TPS vs. ArcCHECK. For the dosimetric differences in organs at risks (OARs), the number of metrics with an average dosimetric differences higher than ±3% for TPS vs Mobius3D, TPS vs MobiusFX, and TPS vs ArcCHECK were 1, 1, 7; 2, 1, 4; 1, 1, 5 for the patients with head-and-neck, abdomen, and chest cancer, respectively. The %GPs of global gamma indices for Mobius3D and MobiousFX were above 97%, while it ranged from 92% to 96% for ArcCHECK. The %GPs of individual volume-based gamma indices were around 98% for Mobius3D and MobiousFX, except for γPTV for chest and abdominal cancer (88.9% to 92%); while it ranged from 86% to 99% for ArcCHECK. In conclusion, some differences in dosimetric metrics and gamma passing rates were observed with ArcCHECK measurement-based QA in comparison with independent dosecheck and log files based QA. Care must be taken when considering replacing phantom measurement-based IMRT/VMAT QA.

Predicting the Value of Adjuvant Therapy in Esophageal Squamous Cell Carcinoma by Combining the Total Number of Examined Lymph Nodes with the Positive Lymph Node Ratio.

BACKGROUND: The value of adjuvant therapy for esophageal squamous cell carcinoma (ESCC) has been controversial, at least partially due to the lack of efficient criteria for selecting suitable patients. This study aimed to explore the existence of parameters related to lymph node (LN) status that can predict the value of adjuvant therapy in ESCC. METHODS: The study included 298 patients with ESCC who had undergone radical esophagectomy with lymphadenectomy. Adjuvant therapy was defined as reception of adjuvant chemotherapy, radiotherapy, or chemoradiotherapy. For the study, LN ratio (LNR), total number of resected LNs (TLNs), and pN stage were selected for Cox regression analyses, including their correlations and prognostic values for survival. Log-rank tests were used to compare the survival rates of the patients with and without adjuvant therapy stratified by pN stage, TLNs, LNR, or their combinations. RESULTS: The independent prognostic factors for survival were TLNs, LNR, and pN stage. Whereas pN stage was significantly related to TLNs and LNR, TLNs were not correlated with LNR. The survival rates between the patients with and those without adjuvant therapy stratified by pN stage, TLNs, or LNR did not differ significantly. We used the median values of TLNs and LNR to group the patients into four groups. The patients in the group with fewer TLNs and higher LNR who had undergone adjuvant therapy showed a significantly better survival than those without adjuvant therapy (p = 0.030). CONCLUSIONS: In contrast to TLNs, LNR, and pN stage as single factors, the combination of TLNs and LNR can predict the value of adjuvant therapy.

Prediction of response after chemoradiation for esophageal cancer using a combination of dosimetry and CT radiomics.

PURPOSE: To investigate the treatment response prediction feasibility and accuracy of an integrated model combining computed tomography (CT) radiomic features and dosimetric parameters for patients with esophageal cancer (EC) who underwent concurrent chemoradiation (CRT) using machine learning. METHODS: The radiomic features and dosimetric parameters of 94 EC patients were extracted and modeled using Support Vector Classification (SVM) and Extreme Gradient Boosting algorithm (XGBoost). The 94-sample dataset was randomly divided into a 70-sample training subset and a 24-sample independent test set while keeping the class proportions intact via stratification. A receiver operating characteristic (ROC) curve was used to assess the performance of models using radiomic features alone and using combined radiomic features and dosimetric parameters. RESULTS: A total of 42 radiomic features and 18 dosimetric parameters plus the patients' characteristic parameters were extracted for these 94 cases (58 responders and 36 non-responders). XGBoost plus principal component analysis (PCA) achieved an accuracy and area under the curve of 0.708 and 0.541, respectively, for models with radiomic features combined with dosimetric parameters, and 0.689 and 0.479, respectively, for radiomic features alone. Image features of GlobalMean X.333.1, Coarseness, Skewness, and GlobalStd contributed most to the model. The dosimetric parameters of gross tumor volume (GTV) homogeneity index (HI), Cord Dmax, Prescription dose, Heart-Dmean, and Heart-V50 also had a strong contribution to the model. CONCLUSIONS: The model with radiomic features combined with dosimetric parameters is promising and outperforms that with radiomic features alone in predicting the treatment response of patients with EC who underwent CRT. KEY POINTS: • The model with radiomic features combined with dosimetric parameters is promising in predicting the treatment response of patients with EC who underwent CRT. • The model with radiomic features combined with dosimetric parameters (prediction accuracy of 0.708 and AUC of 0.689) outperforms that with radiomic features alone (best prediction accuracy of 0.625 and AUC of 0.412). • The image features of GlobalMean X.333.1, Coarseness, Skewness, and GlobalStd contributed most to the treatment response prediction model. The dosimetric parameters of GTV HI, Cord Dmax, Prescription dose, Heart-Dmean, and Heart-V50 also had a strong contribution to the model.

The effect of the primary tumor location on the survival of colorectal cancer patients after radical surgery.

Background and Objectives: Colorectal cancer is one of the most common cancers and the leading cause of cancer-related death worldwide. The impact of the primary tumor location on the prognosis of patients with colorectal cancer has long been a concern, but studies have led to conflicting conclusions. Methods: In total, 465 colorectal cancer patients who received radical surgery were reviewed in this study. Enrolled patients were divided into two groups according to the tumor location. Disease-free survival (DFS) and overall survival (OS) were analyzed via the Kaplan-Meier method. A Cox regression model was employed to evaluate the independent prognostic factors for DFS and OS. Results: The right colorectal cancer (RCC) and left colorectal cancer (LCC) groups comprised 202 and 140 patients, respectively. Univariate and multivariate analyses revealed that the tumor location and TNM stage were independent predictors of DFS and OS. Subgroup analyses by stage demonstrated that there were significant differences in DFS and OS between patients with stage II and III RCC and LCC, but not for those with stage I colorectal cancer. Conclusions: Patients with stage II and III LCC had better survival than those with RCC. However, this improvement in DFS and OS was not observed in patients with stage I colorectal cancer.

Dicer interacts with SIRT7 and regulates H3K18 deacetylation in response to DNA damaging agents.

Dicer participates in heterochromatin formation in fission yeast and plants. However, whether it has a similar role in mammals remains controversial. Here we showed that the human Dicer protein interacts with SIRT7, an NAD(+)-dependent H3K18Ac (acetylated lysine 18 of histone H3) deacetylase, and holds a proportion of SIRT7 in the cytoplasm. Dicer knockdown led to an increase of chromatin-associated SIRT7 and simultaneously a decrease of cytoplasmic SIRT7, while its overexpression induced SIRT7 reduction in the chromatin-associated fraction and increment in the cytoplasm. Furthermore, DNA damaging agents promoted Dicer expression, leading to decreased level of chromatin-associated SIRT7 and increased level of H3K18Ac, which can be alleviated by Dicer knockdown. Taken together with that H3K18Ac was exclusively associated with the chromatin, our findings suggest that Dicer induction by DNA damaging treatments prevents H3K18Ac deacetylation, probably by trapping more SIRT7 in the cytoplasm.

Treatment outcome comparisons between exons 19 and 21 EGFR mutations for non-small-cell lung cancer patients with malignant pleural effusion after first-line and second-line tyrosine kinase inhibitors.

Recent studies demonstrated a significantly increased frequency of epidermal growth factor receptor (EGFR) gene mutations in non-small cell lung cancer (NSCLC) patients with malignant pleural effusions (MPEs). The purpose of this study is to investigate the effect of first-line and second-line EGFR-tyrosine kinase inhibitors (TKIs) in the treatment of NSCLC with MPEs harboring exon 19 deletion and L858R mutation. From 2010 to 2015, 203 NSCLC patients with MPEs harboring EGFR mutation treated with EGFR-TKIs were reviewed. The efficacy were evaluated with Pearson chi-square or Fisher's exact tests, Log-rank test and Cox proportional hazards model. The objective response rate (ORR) and disease control rate (DCR) for patients treated with first-line and second-line EGFR-TKIs were 21.9%, 91.4% and 14.7%, 85.3%, respectively. The overall median PFS and OS of enrolled NSCLC patients with MPE were 9.3 months (95% CI, 8.4-10.2 months), 20.9 months (95% CI, 18.9-22.9 months) after first-line TKIs, and 7.6 months (95% CI, 6.6-8.6 months), 15.3 months (95% CI, 13.6-15.9 months) after second-line TKIs. The exon 19 deletion arm had a longer median PFS (9.4 vs 7.1 months, p=0.003) and OS (16.8 vs 13.8 months, p=0.003) compared with the L858R mutation arm after second-line TKIs. In a conclusion, EGFR genotype was an independent predictor of PFS and OS. No significant side effects differences between the two mutation groups was observed for first or second-line EGFR-TKIs. This study demonstrated that EGFR mutations are significant predictors for advanced NSCLC patients with MPE receiving second-line EGFR-TKIs treatment.

The efficacy and roles of combining temozolomide with whole brain radiotherapy in protection neurocognitive function and improvement quality of life of non-small-cell lung cancer patients with brain metastases.

BACKGROUND: Brain metastasis (BM) is a poor prognostic factor for non-small-cell lung cancer (NSCLC). The efficacy and roles of combining temozolomide (TMZ) with whole brain radiotherapy (WBRT) in protection neurocognitive function (NCF) and improvement quality of life (QOL) were investigated and compared with WBRT alone in the treatment of NSCLC patients with BM. METHODS: A total of 238 NSCLC patients with BM were reviewed and categorized into WBRT plus TMZ (RCT) arm and WBRT alone (RT), respectively. The efficacy was evaluated with Pearson chi-square or Fisher's exact tests, Log-rank test and Cox proportional hazards model. NCF was assessed by using revised Hopkins Verbal Learning Test (HVLT-R), Controlled Oral Word Association (COWA) test and Trail-making Test (TMT). QOL was assessed by the Functional Assessment of Cancer Treatment-Lung (FACT-L) Chinese version 4.0 questionnaire. RESULTS: The average intracranial objective response (ORR) and disease control rate (DCR) for all the patients were 26.9 and 95.8%, respectively. The intracranial ORR and DCR for RCT and RT arm were 34.9% vs. 20.2% (p = 0.01) and 98.4% vs. 92.7% (p = 0.03), respectively. The median intracranial progression-free survival (PFS) and overall survival (OS) of NSCLC patients with BM were 5.2 and 7.3 months, respectively. The median PFS of RCT arm was significantly longer than that of RT arm (5.9 vs. 4.9 months, p = 0.002). The median OS of the RCT arm was also slightly longer than that of the RT arm (8.5 vs. 5.9 months), but without statistical significance (p = 0.11). Multivariate analysis indicated that TMZ was a significant factor for PFS. Statistically significant differences on NCF and QOL were observed between CRT and RT arms at 5 months. RCT showed a trend of toxicities increase compared with RT, however, the toxicities were tolerable and manageable. CONCLUSIONS: Adding TMZ to WBRT in the treatment of NSCLC patients with BM could improve the intracranial ORR, DCR, and median PFS compared with WBRT alone. Although no remarkable difference on median OS was found, adding TMZ could prevent NCF and QOL from worsening. The side effects increased by adding TMZ, but the difference was not statistical significance and toxicities were well tolerated.

Dosimetric benefits of intensity-modulated radiotherapy and volumetric-modulated arc therapy in the treatment of postoperative cervical cancer patients.

As the advantage of using complex volumetric-modulated arc therapy (VMAT) in the treatment of gynecologic cancer has not yet been fully determined, the purpose of this study was to investigate the dosimetric advantages of VMAT by comparing directly with whole pelvic conformal radiotherapy (CRT) and intensity-modulated radiotherapy (IMRT) in the treatment of 15 postoperative cervical cancer patients. Four-field CRT, seven-field IMRT, and two-arc VMAT plans were generated for each patient with identical objective functions to achieve clinically acceptable dose distribution. Target coverage and OAR sparing differences were investigated through dose-volume histogram (DVH) analysis. Nondosimtric differences between IMRT and VMAT were also compared. Target coverage presented by V95% were 88.9% ± 3.8%, 99.9% ± 0.07%, and 99.9% ± 0.1% for CRT, IMRT, and VMAT, respectively. Significant differences on conformal index (CI) and conformal number (CN) were observed with CIs of 0.37 ± 0.07, 0.55 ± 0.04, 0.61 ± 0.04, and CNs of 0.33 ± 0.06, 0.55 ± 0.04, 0.60 ± 0.04 for CRT, IMRT, and VMAT, respectively. IMRT and VMAT decreased the dose to bladder and rectum significantly compared with CRT. No significant differences on the Dmean, V45, and V30 of small bowel were observed among CRT, IMRT, and VMAT. However, VMAT (10.4 ± 4.8 vs. 19.8 ± 11.0, P = 0.004) and IMRT (12.3 ± 5.0 vs. 19.8 ± 11.0, P = 0.02) decreased V40, increased the Dmax of small bowel and the irradiation dose to femoral heads compared with CRT. VMAT irradiated less dose to bladder, rectum, small bowel and larger volume of health tissue with a lower dose (V5 and V10) compared with IMRT, although the differences were not statistical significant. In conclusion, VMAT and IMRT showed significant dosimetric advantages both on target coverage and OAR sparing compared with CRT in the treatment of postoperative cervical cancer. However, no significant difference between IMRT and VMAT was observed except for slightly better dose conformity, slightly less MU, and significant shorter delivery time achieved for VMAT.

Individual volume-based 3D gamma indices for pretreatment VMAT QA.

Although gamma analysis is still a widely accepted quantitative tool to analyze and report patient-specific QA for intensity-modulated radiotherapy (IMRT) and volumetric-modulated arc therapy (VMAT), the correlation between the 2D percentage gamma passing rate (%GP), and the clinical dosimetric difference for IMRT and VMAT has been questioned. The purpose of this study was to investigate the feasibility of individual volume-based 3D gamma indices for pretreatment VMAT QA. Percentage dosimetric errors (%DE) of dose-volume histogram metrics (includes target volumes and organ at risks) between the treatment planning system and QA-reconstructed dose distribution, %GPs for individual volume and global gamma indices, as well their correlations and sensitivities were investigated for one- and two-arc VMAT plans. The %GPs of individual volumes had a higher percent of correlation with individual 15 %DE metrics compared with global %GPs. For two-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 9, 12, and 9 out of 15 %DE metrics, while global %GPs were correlated with only 2 out of 15 %DE metrics, respectively. For one-arc VMAT at 2%/2 mm, 3%/3 mm, and 4%/4 mm criteria, individual volume %GPs were correlated with 18, 16, and 13 out of 23 %DE metrics, and global %GPs were correlated with 19, 12, and 1 out 23 %DE metrics, respectively. The area under curves (AUC) of individual volume %GPs were higher than those of global %GPs for two-arc VMAT plans, but with mixed results for one-arc VMAT plans. In a conclusion, the idea of individual volume %GP was created and investigated to better serve for VMAT QA and individual volume-based %GP had a higher percent of correlation with DVH 15 %DE metrics compared with global %GP for both one- and two-arc VMAT plans.

Profiling and bioinformatics analyses reveal differential circular RNA expression in radioresistant esophageal cancer cells.

BACKGROUND: Acquired radioresistance during radiotherapy is considered as the most important reason for local tumor recurrence or treatment failure. Circular RNAs (circRNAs) have recently been identified as microRNA sponges and involve in various biological processes. The purpose of this study is to investigate the role of circRNAs in the radioresistance of esophageal cancer. METHODS: Total RNA was isolated from human parental cell line KYSE-150 and self-established radioresistant esophageal cancer cell line KYSE-150R, and hybridized to Arraystar Human circRNA Array. Quantitative real-time PCR was used to confirm the circRNA expression profiles obtained from the microarray data. Bioinformatic tools including gene ontology (GO) analysis, KEGG pathway analysis and network analysis were done for further assessment. RESULTS: Among the detected candidate 3752 circRNA genes, significant upregulation of 57 circRNAs and downregulation of 17 circRNAs in human radioresistant esophageal cancer cell line KYSE-150R were observed compared with the parental cell line KYSE-150 (fold change ≥2.0 and P < 0.05). There were 9 out of these candidate circRNAs were validated by real-time PCR. GO analysis revealed that numerous target genes, including most microRNAs were involved in the biological processes. There were more than 400 target genes enrichment on Wnt signaling pathway. CircRNA_001059 and circRNA_000167 were the two largest nodes in circRNA/microRNA co-expression network. CONCLUSIONS: Our study revealed a comprehensive expression and functional profile of differentially expressed circRNAs in radioresistant esophageal cancer cells, indicating possible involvement of these dysregulated circRNAs in the development of radiation resistance.