Browsing by Author "Zhou, Chao"

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    Efficacy and Failure Patterns of Early SBRT to the Primary Tumor in Advanced EGFR-Mutation-Positive Lung Cancer with EFGR-TKI Treatment: A Prospective, Single Arm, Phase II Study
    (MDPI, 2022-11-22) Shi, Yangyang; Xu, Hailing; Raynor, William Y.; Ding, Jiapei; Lin, Ling; Zhou, Chao; Wang, Wei; Meng, Yinnan; Wu, Xiaomai; Chen, Xiaofeng; Lv, Dongqing; Yang, Haihua; Radiation Oncology, School of Medicine
    Early stereotactic body radiation therapy (SBRT) to the primary tumor combined with epidermal growth factor receptor tyrosine kinase inhibitor (EFGR-TKI) treatment may increase progression-free survival (PFS) by delaying resistance in patients with advanced EGFR-mutant non-small cell lung cancer (NSCLC). In this prospective, single arm, phase II study, patients with advanced NSCLC were treated with EGFR-TKI (icotinib 125 mg tid or gefitinib 250 mg qd) for one month followed by SBRT (40-60 Gy/5-8 F/5-10 d) to the primary tumor with concurrent EGFR-TKI until disease progression. The primary endpoint was PFS and the patterns of failure. Overall survival (OS) and adverse effects (AEs) were secondary endpoints. Overall, 41 advanced NSCLC patients with EGFR mutations received treatment with 24.42 months of median follow-up time. On average, SBRT was initiated 1.49 months after EGFR-TKI administration. Tumors were found to have an average shrinkage rate of 42.50%. Median PFS was 15.23 months (95% CI 13.10-17.36), while median OS was 27.57 months (95% CI 23.05-32.09). Thirty-three patients were found to have disease progression, of which new site failure (NF) (22 patients, 66.66%) was the most common pattern, followed by original site failure (OF) (7 patients, 21.21%) and simultaneous OF/NF (ONF) (4 patients, 12.12%). There were no Aes equal to or greater than grade 3, with the most frequent AE being radiation pneumonitis. Therefore, administering therapy targeted at the primary tumor using early SBRT after EGFR-TKI initiation is a new potentially safe and effective approach to treat EGFR-mutant advanced NSCLC.
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    Enhanced CT-Based Radiomics to Predict Micropapillary Pattern Within Lung Invasive Adenocarcinoma
    (Frontiers Media, 2021-08-27) Xu, Yunyu; Ji, Wenbin; Hou, Liqiao; Lin, Shuangxiang; Shi, Yangyang; Zhou, Chao; Meng, Yinnan; Wang, Wei; Chen, Xiaofeng; Wang, Meihao; Yang, Haihua; Radiation Oncology, School of Medicine
    Objective: We aimed to investigate whether enhanced CT-based radiomics can predict micropapillary pattern (MPP) of lung invasive adenocarcinoma (IAC) in the pre-op phase and to develop an individual diagnostic predictive model for MPP in IAC. Methods: 170 patients who underwent complete resection for pathologically confirmed lung IAC were included in our study. Of these 121 were used as a training cohort and the other 49 as a test cohort. Clinical features and enhanced CT images were collected and assessed. Quantitative CT analysis was performed based on feature types including first order, shape, gray-level co-occurrence matrix-based, gray-level size zone matrix-based, gray-level run length matrix-based, gray-level dependence matrix-based, neighboring gray tone difference matrix-based features and transform types including Log, wavelet and local binary pattern. Receiver operating characteristic (ROC) and area under the curve (AUC) were used to value the ability to identify the lung IAC with MPP using these characteristics. Results: Using quantitative CT analysis, one thousand three hundred and seventeen radiomics features were deciphered from R (https://www.r-project.org/). Then these radiomic features were decreased to 14 features after dimension reduction using the least absolute shrinkage and selection operator (LASSO) method in R. After correlation analysis, 5 key features were obtained and used as signatures for predicting MPP within IAC. The individualized prediction model which included age, smoking, family tumor history and radiomics signature had better identification (AUC=0.739) in comparison with the model consisting only of radiomics features (AUC=0.722). DeLong test showed that the difference in AUC between the two models was statistically significant (P<0.01). Compared with the simple radiomics model, the more comprehensive individual prediction model has better prediction performance. Conclusion: The use of radiomics approach is of great value in the diagnosis of tumors by non-invasive means. The individualized prediction model in the study, when incorporated with age, smoking and radiomics signature, had effective predictive performance of lung IAC with MPP lesions. The combination of imaging features and clinical features can provide additional diagnostic value to identify the micropapillary pattern in IAC and can affect clinical diagnosis and treatment.
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    Failure patterns of locoregional recurrence after reducing target volumes in patients with nasopharyngeal carcinoma receiving adaptive replanning during intensity-modulated radiotherapy: a single-center experience in China
    (Springer Nature, 2023-11-16) Zhou, Xiate; Zhu, Jian; Zhou, Chao; Wang, Wei; Ding, Weijun; Chen, Meng; Chen, Kuifei; Li, Shuling; Chen, Xiaofeng; Yang, Haihua; Radiation Oncology, School of Medicine
    Background: Previous researches have demonstrated that adaptive replanning during intensity-modulated radiation therapy (IMRT) could enhance the prognosis of patients with nasopharyngeal carcinoma (NPC). However, the delineation of replanning target volumes remains unclear. This study aimed to evaluate the feasibility of reducing target volumes through adaptive replanning during IMRT by analyzing long-term survival outcomes and failure patterns of locoregional recurrence in NPC. Methods: This study enrolled consecutive NPC patients who received IMRT at our hospital between August 2011 and April 2018. Patients with initially diagnosed, histologically verified, non-metastatic nasopharyngeal cancer were eligible for participation in this study. The location and extent of locoregional recurrences were transferred to pretreatment planning computed tomography for dosimetry analysis. Results: Among 274 patients, 100 (36.5%) received IMRT without replanning and 174 (63.5%) received IMRT with replanning. Five-year rates of locoregional recurrence-free survival (LRFS) were 90.1% (95%CI, 84.8% to 95.4%) and 80.8% (95%CI, 72.0% to 89.6%) for patients with and without replanning, P = 0.045. There were 17 locoregional recurrences in 15 patients among patients with replanning, of which 1 (5.9%) was out-field and 16 (94.1%) were in-field. Among patients without replanning, 19 patients developed locoregional recurrences, of which 1 (5.3%) was out-field, 2 (10.5%) were marginal, and 16 (84.2%) were in-field. Conclusions: In-field failure inside the high dose area was the most common locoregional recurrent pattern for non-metastatic NPC. Adapting the target volumes and modifying the radiation dose prescribed to the area of tumor reduction during IMRT was feasible and would not cause additional recurrence in the shrunken area.
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    The role of the gut microbiome in cancer-related fatigue: pilot study on epigenetic mechanisms
    (Springer, 2021) Xiao, Canhua; Fedirko, Veronika; Beitler, Jonathan; Bai, Jinbing; Peng, Gang; Zhou, Chao; Gu, Jianlei; Zhao, Hongyu; Lin, I-Hsin; Chico, Cynthia E.; Jeon, Sangchoon; Knobf, Tish M.; Conneely, Karen N.; Higgins, Kristin; Shin, Dong M.; Saba, Nabil; Miller, Andrew; Bruner, Deborah; Medical and Molecular Genetics, School of Medicine
    Purpose: Recent evidence supports a key role of gut microbiome in brain health. We conducted a pilot study to assess associations of gut microbiome with cancer-related fatigue and explore the associations with DNA methylation changes. Methods: Self-reported Multidimensional Fatigue Inventory and stool samples were collected at pre-radiotherapy and one-month post-radiotherapy in patients with head and neck cancer. Gut microbiome data were obtained by sequencing the 16S ribosomal ribonucleic acid gene. DNA methylation changes in the blood were assessed using Illumina Methylation EPIC BeadChip. Results: We observed significantly different gut microbiota patterns among patients with high vs. low fatigue across time. This pattern was characterized by low relative abundance in short-chain fatty acid-producing taxa (family Ruminococcaceae, genera Subdoligranulum and Faecalibacterium; all p < 0.05), with high abundance in taxa associated with inflammation (genera Family XIII AD3011 and Erysipelatoclostridium; all p < 0.05) for high-fatigue group. We identified nine KEGG Orthology pathways significantly different between high- vs. low-fatigue groups over time (all p < 0.001), including pathways related to fatty acid synthesis and oxidation, inflammation, and brain function. Gene set enrichment analysis (GSEA) was performed on the top differentially methylated CpG sites that were associated with the taxa and fatigue. All biological processes from the GSEA were related to immune responses and inflammation (FDR < 0.05). Conclusions: Our results suggest different patterns of the gut microbiota in cancer patients with high vs. low fatigue. Results from functional pathways and DNA methylation analyses indicate that inflammation is likely to be the major driver in the gut-brain axis for cancer-related fatigue.