Publications by authors named "Xiangbo Wan"

12 Publications

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Targeting cancer cell plasticity by HDAC inhibition to reverse EBV-induced dedifferentiation in nasopharyngeal carcinoma.

Signal Transduct Target Ther 2021 09 4;6(1):333. Epub 2021 Sep 4.

Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine; Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China.

Application of differentiation therapy targeting cellular plasticity for the treatment of solid malignancies has been lagging. Nasopharyngeal carcinoma (NPC) is a distinctive cancer with poor differentiation and high prevalence of Epstein-Barr virus (EBV) infection. Here, we show that the expression of EBV latent protein LMP1 induces dedifferentiated and stem-like status with high plasticity through the transcriptional inhibition of CEBPA. Mechanistically, LMP1 upregulates STAT5A and recruits HDAC1/2 to the CEBPA locus to reduce its histone acetylation. HDAC inhibition restored CEBPA expression, reversing cellular dedifferentiation and stem-like status in mouse xenograft models. These findings provide a novel mechanistic epigenetic-based insight into virus-induced cellular plasticity and propose a promising concept of differentiation therapy in solid tumor by using HDAC inhibitors to target cellular plasticity.
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http://dx.doi.org/10.1038/s41392-021-00702-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8418605PMC
September 2021

Molecular profiling and identification of prognostic factors in Chinese patients with small bowel adenocarcinoma.

Cancer Sci 2021 Nov 12;112(11):4758-4771. Epub 2021 Sep 12.

Department of Medical Oncology, Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University, Hangzhou, China.

Small bowel adenocarcinoma (SBA) is a rare malignancy with a poor prognosis and limited treatment options. Despite prior studies, molecular characterization of this disease is not well defined, and little is known regarding Chinese SBA patients. In this study, we conducted multigene next-generation sequencing and 16S ribosomal RNA gene sequencing on samples from 76 Chinese patients with surgically resected primary SBA. Compared with colorectal cancer and Western SBA cohorts, a distinctive genomic profile was revealed in Chinese SBA cohorts. According to the levels of clinical actionability to targetable alterations stratified by OncoKB system, 75% of patients harbored targetable alterations, of which ERBB2, BRCA1/2, and C-KIT mutations were the most common targets of highest-level actionable alterations. In DNA mismatch repair-proficient (pMMR) patients, significant associations between high tumor mutational burden and specific genetic alterations were identified. Moreover, KRAS mutations/TP53 wild-type/nondisruptive mutations (KRAS /TP53 ) were independently associated with an inferior recurrence-free survival (hazard ratio [HR] = 4.21, 95% confidence interval [CI] = 1.94-9.14, P < .001). The bacterial profile revealed Proteobacteia, Actinobacteria, Firmicutes, Bacteroidetes, Fusobacteria, and Cyanobacteria were the most common phyla in SBA. Furthermore, patients were clustered into three subgroups based on the relative abundance of bacterial phyla, and the distributions of the subgroups were significantly associated with the risk of recurrence stratified by TP53 and KRAS mutations. In conclusion, these findings provided a comprehensive molecular basis for understanding SBA, which will be of great significance in improving the treatment strategies and clinical management of this population.
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http://dx.doi.org/10.1111/cas.15119DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8586671PMC
November 2021

Management of Clinically Involved Lateral Lymph Node Metastasis in Locally Advanced Rectal Cancer: A Radiation Dose Escalation Study.

Front Oncol 2021 16;11:674253. Epub 2021 Jul 16.

Department of Radiation Oncology, The Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.

Background: Patients with lateral lymph nodes (LLNs) metastasis are not effectively treated with neoadjuvant chemoradiotherapy. This study aimed to compare the efficacy of three neoadjuvant therapeutic regimens, namely, chemotherapy, chemoradiotherapy, and chemoradiotherapy with a dose boost of LLNs, and to identify the optimal approach for treating LLNs metastasis of locally advanced rectal cancer.

Methods: A total of 202 patients with baseline LLNs metastasis (short axis ≥5 mm) and treated with neoadjuvant treatment, followed by radical surgery from 2011 to 2019, were enrolled. The short axis of the LLNs on baseline and restaging MRI were recorded. Survival outcomes were compared.

Results: In the booster subgroup, shrinkage of LLNs was significantly greater than in the neoadjuvant chemotherapy and chemoradiotherapy subgroups (0.001), without increasing radiation related side effects ( 0.121). For patients with baseline LLNs of short axis ≥5 mm in the booster subgroup, the response rate (short axis <5 mm on restaging MRI) was 72.9%, significantly higher than patients in the neoadjuvant chemotherapy subgroup (48.9%, = 0.007) and higher than for patients in the neoadjuvant chemoradiotherapy group (65.0%), but there was no statistical difference ( = 0.411). The 3-year local recurrence and lateral local recurrence rates were both 2.3% in the dose booster group, which were lower than those of the other two subgroups (local recurrence: 0.001; lateral local recurrence: 0.001). The short axis of lateral lymph nodes (≥5 and <5 mm) on restaging MRI was an independent risk factor for prognosis (0.05).

Conclusion: Radiation dose boost is an effective way of increasing the response rate and decreasing recurrence rates. The restaging LLNs with short axis ≥5 mm is a predictor of poor prognosis.
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http://dx.doi.org/10.3389/fonc.2021.674253DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8322741PMC
July 2021

Risk-Adapted Postmastectomy Radiotherapy Decision Based on Prognostic Nomogram for pT1-2N1M0 Breast Cancer: A Multicenter Study.

Front Oncol 2020 11;10:588859. Epub 2020 Dec 11.

Geneplus-Beijing Institute, Beijing, China.

Purpose: The aim of this study was to develop a widely accepted prognostic nomogram and establish a risk-adapted PMRT strategy based on locoregional recurrence for pT1-2N1M0 breast cancer.

Methods And Materials: A total of 3,033 patients with pT1-2N1M0 breast cancer treated at 6 participating institutions between 2000 and 2016 were retrospectively reviewed. A nomogram was developed to predicted locoregional recurrence-free survival (LRFS). A propensity score-matched (PSM) analyses was performed in risk-adapted model.

Results: With the median follow-up of 65.0 months, the 5-year overall survival (OS), disease free survival (DFS) and LRFS were 93.0, 84.8, and 93.6%, respectively. There was no significant difference between patients who received PMRT or not for the entire group. A nomogram was developed and validated to estimate the probability of 5-year LRFS based on five independent factors including age, primary tumor site, positive lymph nodes number, pathological T stage, and molecular subtype that were selected by a multivariate analysis of patients who did not receive PMRT in the primary cohort. According to the total nomogram risk scores, the entire patients were classified into low- (40.0%), moderate- (42.4%), and high-risk group (17.6%). The 5-year outcomes were significantly different among these three groups (P<0.001). In low-risk group, patients who received PMRT or not both achieved a favorable OS, DFS, and LRFS. In moderate-risk group, no differences in OS, DFS, and LRFS were observed between PMRT and no PMRT patients. In high-risk group, compared with no PMRT, PMRT resulted in significantly different OS (86.8 vs 83.9%, P = 0.050), DFS (77.2 vs 70.9%, P = 0.049), and LRFS (90.8 vs. 81.6%, P = 0.003). After PSM adjustment, there were no significant differences in OS, DFS, and LRFS in low-risk and moderate-risk groups. However, in the high-risk group, PMRT still resulted in significantly better OS, DFS and improved LRFS.

Conclusions: The proposed nomogram provides an individualized risk estimate of LRFS in patients with pT1-2N1M0 breast cancer. Risk-adapted PMRT for high-risk patients is a viable effective strategy.
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http://dx.doi.org/10.3389/fonc.2020.588859DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7761288PMC
December 2020

Colorectal cancer under 20 years old: a retrospective analysis from three tertiary hospitals.

J Cancer Res Clin Oncol 2021 Apr 23;147(4):1145-1155. Epub 2020 Sep 23.

Department of Radiation Oncology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, 651 Dongfeng Road East, Guangzhou, 510060, China.

Purpose: Colorectal cancer (CRC) rarely occurs in children and adolescents. This study aimed to perform a retrospective analysis and disclose more detailed information about CRC in patients under 20 years old.

Methods: Medical records of CRCs in patients under 20 years old referred to three tertiary hospitals in China from September 2000 to July 2019 were retrospectively reviewed. Clinicopathological characteristics, treatment processes and laboratory findings were summarized and treatment outcomes and prognostic factors were analyzed.

Results: A total of 33,394 CRC medical records were analyzed, and we identified seventy (0.21%) CRCs in patients under 20. The most common primary tumor location was the left hemicolon (35.7%). The prominent pathological types were mucinous adenocarcinoma (22.9%) and signet ring cell carcinoma (22.9%). Nearly half (47.1%) of the patients presented with distant metastasis at diagnosis. The fractions of patients with deficient mismatch repair (dMMR) protein expression and microsatellite instability-high (MSI-H) were 23.8% (5/21) and 71.4% (5/7), respectively. Forty-four patients underwent radical surgery. Fifty-five patients received chemotherapy and six patients received radiotherapy. One dMMR/MSI-H rectal cancer patient received immunotherapy and achieved a clinically complete response. The median overall survival (OS) time was 80 months. The 3-year and 5-year OS rates were 61.8% and 57.2%, respectively. An absence of distant metastasis was a favorable factor for OS. For stage II/III CRCs, classic adenocarcinoma and radical surgery were favorable factors for OS. For stage IV CRCs, primary location at the colon was a favorable factor for OS.

Conclusion: Child and adolescent CRC patients are likely to have distant metastasis, undifferentiated, left hemicolon location, and a dMMR/MSI-H phenotype at diagnosis. Additional efforts are needed to improve their survival outcomes.
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http://dx.doi.org/10.1007/s00432-020-03397-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7954766PMC
April 2021

Multiparametric MRI and Whole Slide Image-Based Pretreatment Prediction of Pathological Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer: A Multicenter Radiopathomic Study.

Ann Surg Oncol 2020 Oct 29;27(11):4296-4306. Epub 2020 Jul 29.

CAS Key Laboratory of Molecular Imaging, Institute of Automation, Beijing, China.

Background: The aim of this work is to combine radiological and pathological information of tumor to develop a signature for pretreatment prediction of discrepancies of pathological response at several centers and restage patients with locally advanced rectal cancer (LARC) for individualized treatment planning.

Patients And Methods: A total of 981 consecutive patients with evaluation of response according to tumor regression grade (TRG) who received nCRT were retrospectively recruited from four hospitals (primary cohort and external validation cohort 1-3); both pretreatment multiparametric MRI (mp-MRI) and whole slide image (WSI) of biopsy specimens were available for each patient. Quantitative image features were extracted from mp-MRI and WSI and used to construct a radiopathomics signature (RPS) powered by an artificial-intelligence model. Models based on mp-MRI or WSI alone were also constructed for comparison.

Results: The RPS showed overall accuracy of 79.66-87.66% in validation cohorts. The areas under the curve of RPS at specific response grades were 0.98 (TRG0), 0.93 (≤ TRG1), and 0.84 (≤ TRG2). RPS at each grade of pathological response revealed significant improvement compared with both signatures constructed without combining multiscale tumor information (P < 0.01). Moreover, RPS showed relevance to distinct probabilities of overall survival and disease-free survival in patients with LARC who underwent nCRT (P < 0.05).

Conclusions: The results of this study suggest that radiopathomics, combining both radiological information of the whole tumor and pathological information of local lesions from biopsy, could potentially predict discrepancies of pathological response prior to nCRT for better treatment planning.
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http://dx.doi.org/10.1245/s10434-020-08659-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7497677PMC
October 2020

Distant Metastasis Risk Definition by Tumor Biomarkers Integrated Nomogram Approach for Locally Advanced Nasopharyngeal Carcinoma.

Cancer Control 2019 Jan-Dec;26(1):1073274819883895

Department of Radiation Oncology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

Identifying metastasis remains a challenge for death control and tailored therapy for nasopharyngeal carcinoma (NPC). Here, we addressed this by designing a nomogram-based Cox proportional regression model through integrating a panel of tumor biomarkers. A total of 147 locally patients with advanced NPC, derived from a randomized phase III clinical trial, were enrolled. We constructed the model by selecting the variables from 31 tumor biomarkers, including 6 pathological signaling pathway molecules and 3 Epstein-Barr virus-related serological variables. Through the least absolute shrinkage and selection operator (LASSO) Cox proportional regression analysis, a nomogram was designed to refine the metastasis risk of each NPC individuals. Using the LASSO Cox regression model, we constructed a 9 biomarkers-based prognostic nomogram: Beclin 1, Aurora-A, Cyclin D1, Ki-67, P27, Bcl-2, MMP-9, 14-3-3σ, and VCA-IgA. The time-dependence receiver operating characteristic analysis at 1, 3, and 5 years showed an appealing prognostic accuracy with the area under the curve of 0.830, 0.827, and 0.817, respectively. In the validation subset, the concordance index of this nomogram reached to 0.64 to identify the individual metastasis pattern. Supporting by this nomogram algorithm, the individual metastasis risk might be refined personally and potentially guiding the treatment decisions and target therapy against the related signaling pathways for patients with locally advanced NPC.
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http://dx.doi.org/10.1177/1073274819883895DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6811765PMC
May 2020

RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification.

Med Image Anal 2019 12 30;58:101549. Epub 2019 Aug 30.

Department of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.

The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how to select informative regions and analyze them are quite challenging during the automatic diagnosis process. The multi-instance learning based on the most discriminative instances can be of great benefit for whole slide gastric image diagnosis. In this paper, we design a recalibrated multi-instance deep learning method (RMDL) to address this challenging problem. We first select the discriminative instances, and then utilize these instances to diagnose diseases based on the proposed RMDL approach. The designed RMDL network is capable of capturing instance-wise dependencies and recalibrating instance features according to the importance coefficient learned from the fused features. Furthermore, we build a large whole-slide gastric histopathology image dataset with detailed pixel-level annotations. Experimental results on the constructed gastric dataset demonstrate the significant improvement on the accuracy of our proposed framework compared with other state-of-the-art multi-instance learning methods. Moreover, our method is general and can be extended to other diagnosis tasks of different cancer types based on WSIs.
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http://dx.doi.org/10.1016/j.media.2019.101549DOI Listing
December 2019

Molecular Decision Tree Algorithms Predict Individual Recurrence Pattern for Locally Advanced Nasopharyngeal Carcinoma.

J Cancer 2019 2;10(15):3323-3332. Epub 2019 Jun 2.

Department of Radiation Oncology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China.

: Recurrence remains one of the key reasons of relapse after the radical radiation for locally advanced nasopharyngeal carcinoma (NPC). Here, the multiple molecular and clinical variables integrated decision tree algorithms were designed to predict individual recurrence patterns (with VS without recurrence) for locally advanced NPC. : A total of 136 locally advanced NPC patients retrieved from a randomized controlled phase III trial, were included. For each patient, the expression levels of 33 clinicopathological biomarkers in tumor specimen, 3 Epstein-Barr virus related serological antibody titer and 5 clinicopathological variables, were detected and collected to construct the decision tree algorithm. The expression level of 33 clinicopathological biomarkers in tumor specimen was evaluated by immunohistochemistry staining. : Three algorithm classifiers, augmented by the adaptive boosting algorithm for variable selection and classification, were designed to predict individual recurrence pattern. The classifiers were trained in the training subset and further tested using a 10-fold cross-validation scheme in the validation subset. In total, 13 molecules expression level in tumor specimen, including AKT1, Aurora-A, Bax, Bcl-2, N-Cadherin, CENP-H, HIF-1α, LMP-1, C-Met, MMP-2, MMP-9, Pontin and Stathmin, and N stage were selected to construct three 10-fold cross-validation decision tree classifiers. These classifiers showed high predictive sensitivity (87.2-93.3%), specificity (69.0-100.0%), and overall accuracy (84.5-95.2%) to predict recurrence pattern individually. Multivariate analyses confirmed the decision tree classifier was an independent prognostic factor to predict individual recurrence (algorithm 1: hazard ration (HR) 0.07, 95% confidence interval (CI) 0.03-0.16, < 0.01; algorithm 2: HR 0.13, 95% CI 0.04-0.44, < 0.01; algorithm 3: HR 0.13, 95% CI 0.03-0.68, = 0.02). : Multiple molecular and clinicopathological variables integrated decision tree algorithms may individually predict the recurrence pattern for locally advanced NPC. This decision tree algorism provides a potential tool to select patients with high recurrence risk for intensive follow-up, and to diagnose recurrence at an earlier stage for salvage treatment in the NPC endemic region.
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http://dx.doi.org/10.7150/jca.29693DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6603411PMC
June 2019

Impact of Chemotherapy Regimens on Normal Tissue Complication Probability Models of Acute Hematologic Toxicity in Rectal Cancer Patients Receiving Intensity Modulated Radiation Therapy With Concurrent Chemotherapy From a Prospective Phase III Clinical Trial.

Front Oncol 2019 9;9:244. Epub 2019 Apr 9.

Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Department of Radiation Oncology, Guangdong Institute of Gastroenterology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.

To determine whether there are differences in bone marrow tolerance to chemoradiotherapy (CRT) between two chemotherapy regimens according to FOWARC protocol and how chemotherapy regimens affect radiation dose parameters and normal tissue complication probability (NTCP) modelings that correlate with acute hematologic toxicity (HT) in rectal cancer patients treated with intensity modulated radiation therapy (IMRT) and concurrent chemotherapy. One hundred and twenty-eight rectal cancer patients who received IMRT from a single institution were recruited from Chinese FOWARC multicenter, open-label, randomized phase III trial. We assessed HT in these patients who were separated into two groups: Oxaliplatin (L-OHP) + 5- fluorouracil (5FU) (FOLFOX, 70 of 128) and 5FU (58 of 128). The pelvic bone marrow (PBM) was divided into three subsites: lumbosacral spine (LSS), ilium (I), and lower pelvic (LP). The endpoint for HT was grade ≥3 (HT3+) and grade ≥2 (HT2+) leukopenia, neutropenia, anemia and thrombocytopenia. Logistic regression was used to analyze the association between HT2+/HT3+ and dosimetric parameters. Lyman-Kutcher-Burman (LKB) model was used to calculate NTCP. Sixty-eight patients experienced HT2+: 22 of 58 (37.9%) 5FU and 46 of 70 (65.7%) FOLFOX ( = 0.008), while twenty-six patients experienced HT3+: 4 of 58 (6.9%) 5FU and 22 of 70 (31.4%) FOLFOX ( = 0.016). PBM and LP dosimetric parameters were correlated with HT2+ in the 5FU group but not in the FOLFOX group. No PBM dosimetric parameters were correlated with HT3+ in both groups. For PBM, NTCP at HT3+ was 0.32 in FOLFOX group relative to 0.10 in 5FU subset ( < 0.05). Patients receiving FOLFOX have lower BM tolerance to CRT than those receiving 5FU. Low-dose radiation to the PBM is predictive for HT2+ in patients who received 5FU. NTCP modeling in FOLFOX group predicts much higher risk of HT3+ than 5FU group.
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http://dx.doi.org/10.3389/fonc.2019.00244DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6465593PMC
April 2019

Preoperative radiomic signature based on multiparametric magnetic resonance imaging for noninvasive evaluation of biological characteristics in rectal cancer.

Eur Radiol 2019 Jun 9;29(6):3200-3209. Epub 2018 Nov 9.

Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, 88 Keling Road, Suzhou New District, Suzhou, 215163, Jiangsu, China.

Objectives: To develop and validate radiomic models in evaluating biological characteristics of rectal cancer based on multiparametric magnetic resonance imaging (MP-MRI).

Methods: This study consisted of 345 patients with rectal cancer who underwent MP-MRI. We focused on evaluating five postoperative confirmed characteristics: lymph node (LN) metastasis, tumor differentiation, fraction of Ki-67-positive tumor cells, human epidermal growth factor receptor 2 (HER-2), and KRAS-2 gene mutation status. Data from 197 patients were used to develop the biological characteristics evaluation models. Radiomic features were extracted from MP-MRI and then refined for reproducibility and redundancy. The refined features were investigated for usefulness in building radiomic signatures by using two feature-ranking methods (MRMR and WLCX) and three classifiers (RF, SVM, and LASSO). Multivariable logistic regression was used to build an integrated evaluation model combining radiomic signatures and clinical characteristics. The performance was evaluated using an independent validation dataset comprising 148 patients.

Results: The MRMR and LASSO regression produced the best-performing radiomic signatures for evaluating HER-2, LN metastasis, tumor differentiation, and KRAS-2 gene status, with AUC values of 0.696 (95% CI, 0.610-0.782), 0.677 (95% CI, 0.591-0.763), 0.720 (95% CI, 0.621-0.819), and 0.651 (95% CI, 0.539-0.763), respectively. The best-performing signatures for evaluating Ki-67 produced an AUC value of 0.699 (95% CI, 0.611-0.786), and it was developed by WLCX and RF algorithm. The integrated evaluation model incorporating radiomic signature and MRI-reported LN status had improved AUC of 0.697 (95% CI, 0.612-0.781).

Conclusion: Radiomic signatures based on MP-MRI have potential to noninvasively evaluate the biological characteristics of rectal cancer.

Key Points: • Radiomic features were extracted from MP-MRI images of the rectal tumor. • The proposed radiomic signatures demonstrated discrimination ability in identifying the histopathological, immunohistochemical, and genetic characteristics of rectal cancer. • All MRI sequences were important and could provide complementary information in radiomic analysis.
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http://dx.doi.org/10.1007/s00330-018-5763-xDOI Listing
June 2019
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