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Zhong X, Zeng G, Zhang L, You S, Fu Y, He W, Liao G. Prediction of pathologic complete response to neoadjuvant chemoradiation in locally advanced rectal cancer. Front Oncol 2024; 14:1361300. [PMID: 38529385 PMCID: PMC10961458 DOI: 10.3389/fonc.2024.1361300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 02/19/2024] [Indexed: 03/27/2024] Open
Abstract
Purpose To investigate the predictive factors of pathologic complete response (pCR) in locally advanced rectal cancer (LARC) patients who had been treated with neoadjuvant chemoradiation (nCRT). Methods and materials For this retrospective study, 53 LARC patients (37 males and 16 females; age range 25 to 79 years) were selected. Clinical characteristics, baseline mrTNM staging, MR gross tumor volumes (GTV), and pCR were evaluated. The diagnostic accuracy of GTV for predicting pCR was calculated. Results Among 53 LARC patients, 15 patients achieved pCR (28.3%), while 38 patients achieved non-pCR. Only three (5.7%) out of 53 patients did not downstage after nCRT. GTV and tumor differentiation were the significant prognostic parameters for predicting pCR. A tumor volume threshold of 21.1 cm3 was determined as a predictor for pCR, with a sensitivity of 84% and specificity of 47%. In addition, GTV was associated with mrN stage, circumferential resection margin (CRM) status, extramural vascular invasion (EMVI) status, and pretreatment serum CEA level. Conclusion Tumor volume and tumor differentiation have significant predictive values in preoperative assessment of pCR among LARC patients. These findings aid clinicians to discriminate those patients who may likely benefit from preoperative regimens and to make optimal treatment plans.
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Affiliation(s)
- Xiaoling Zhong
- Department of Radiology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China
| | - Guohua Zeng
- Department of Radiology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China
| | - Lixiang Zhang
- Department of Radiology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China
| | - Shuyuan You
- Department of Pathology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, China
| | - Yuxiang Fu
- Department of Gastrointestinal surgery, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, China
| | - Wan He
- Department of Oncology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, China
| | - Guixiang Liao
- Department of Radiation Oncology, Shenzhen People's Hospital (The Second Clinical Medical College of Jinan University, the First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, China
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Tanaka MD, Geubels BM, Grotenhuis BA, Marijnen CAM, Peters FP, van der Mierden S, Maas M, Couwenberg AM. Validated Pretreatment Prediction Models for Response to Neoadjuvant Therapy in Patients with Rectal Cancer: A Systematic Review and Critical Appraisal. Cancers (Basel) 2023; 15:3945. [PMID: 37568760 PMCID: PMC10417363 DOI: 10.3390/cancers15153945] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/27/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023] Open
Abstract
Pretreatment response prediction is crucial to select those patients with rectal cancer who will benefit from organ preservation strategies following (intensified) neoadjuvant therapy and to avoid unnecessary toxicity in those who will not. The combination of individual predictors in multivariable prediction models might improve predictive accuracy. The aim of this systematic review was to summarize and critically appraise validated pretreatment prediction models (other than radiomics-based models or image-based deep learning models) for response to neoadjuvant therapy in patients with rectal cancer and provide evidence-based recommendations for future research. MEDLINE via Ovid, Embase.com, and Scopus were searched for eligible studies published up to November 2022. A total of 5006 studies were screened and 16 were included for data extraction and risk of bias assessment using Prediction model Risk Of Bias Assessment Tool (PROBAST). All selected models were unique and grouped into five predictor categories: clinical, combined, genetics, metabolites, and pathology. Studies generally included patients with intermediate or advanced tumor stages who were treated with neoadjuvant chemoradiotherapy. Evaluated outcomes were pathological complete response and pathological tumor response. All studies were considered to have a high risk of bias and none of the models were externally validated in an independent study. Discriminative performances, estimated with the area under the curve (AUC), ranged per predictor category from 0.60 to 0.70 (clinical), 0.78 to 0.81 (combined), 0.66 to 0.91 (genetics), 0.54 to 0.80 (metabolites), and 0.71 to 0.91 (pathology). Model calibration outcomes were reported in five studies. Two collagen feature-based models showed the best predictive performance (AUCs 0.83-0.91 and good calibration). In conclusion, some pretreatment models for response prediction in rectal cancer show encouraging predictive potential but, given the high risk of bias in these studies, their value should be evaluated in future, well-designed studies.
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Affiliation(s)
- Max D. Tanaka
- Department of Radiation Oncology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Barbara M. Geubels
- Department of Surgery, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Department of Surgery, Catharina Hospital, 5602 ZA Eindhoven, The Netherlands
- GROW School for Oncology and Reproduction, Maastricht University, 6200 MD Maastricht, The Netherlands
| | - Brechtje A. Grotenhuis
- Department of Surgery, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Corrie A. M. Marijnen
- Department of Radiation Oncology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
- Department of Radiation Oncology, Leiden University Medical Centre, 2333 ZA Leiden, The Netherlands
| | - Femke P. Peters
- Department of Radiation Oncology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Stevie van der Mierden
- Scientific Information Service, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Monique Maas
- GROW School for Oncology and Reproduction, Maastricht University, 6200 MD Maastricht, The Netherlands
- Department of Radiology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
| | - Alice M. Couwenberg
- Department of Radiation Oncology, The Netherlands Cancer Institute, 1066 CX Amsterdam, The Netherlands
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Accurate tumor segmentation and treatment outcome prediction with DeepTOP. Radiother Oncol 2023; 183:109550. [PMID: 36813177 DOI: 10.1016/j.radonc.2023.109550] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/15/2023] [Accepted: 02/09/2023] [Indexed: 02/24/2023]
Abstract
BACKGROUND Accurate outcome prediction prior to treatment can facilitate trial design and clinical decision making to achieve better treatment outcome. METHOD We developed the DeepTOP tool with deep learning approach for region-of-interest segmentation and clinical outcome prediction using magnetic resonance imaging (MRI). DeepTOP was constructed with an automatic pipeline from tumor segmentation to outcome prediction. In DeepTOP, the segmentation model used U-Net with a codec structure, and the prediction model was built with a three-layer convolutional neural network. In addition, the weight distribution algorithm was developed and applied in the prediction model to optimize the performance of DeepTOP. RESULTS A total of 1889 MRI slices from 99 patients in the phase III multicenter randomized clinical trial (NCT01211210) on neoadjuvant treatment for rectal cancer was used to train and validate DeepTOP. We systematically optimized and validated DeepTOP with multiple devised pipelines in the clinical trial, demonstrating a better performance than other competitive algorithms in accurate tumor segmentation (Dice coefficient: 0.79; IoU: 0.75; slice-specific sensitivity: 0.98) and predicting pathological complete response to chemo/radiotherapy (accuracy: 0.789; specificity: 0.725; and sensitivity: 0.812). DeepTOP is a deep learning tool that could avoid manual labeling and feature extraction and realize automatic tumor segmentation and treatment outcome prediction by using the original MRI images. CONCLUSION DeepTOP is open to provide a tractable framework for the development of other segmentation and predicting tools in clinical settings. DeepTOP-based tumor assessment can provide a reference for clinical decision making and facilitate imaging marker-driven trial design.
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Automatic treatment outcome prediction with DeepInteg based on multimodal radiological images in rectal cancer. Heliyon 2023; 9:e13094. [PMID: 36785834 PMCID: PMC9918765 DOI: 10.1016/j.heliyon.2023.e13094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 01/04/2023] [Accepted: 01/16/2023] [Indexed: 01/26/2023] Open
Abstract
Neoadjuvant systemic treatment before surgery is a prevalent regimen in the patients with advanced-stage or high-risk tumor, which has shaped the treatment strategies and cancer survival in the past decades. However, some patients present with poor response to the neoadjuvant treatment. Therefore, it is of great significance to develop tools to help distinguish the patients that could achieve pathological complete response before surgery to avoid inappropriate treatment. Here, this study demonstrated a multi-task deep learning tool called DeepInteg. In the DeepInteg framework, the segmentation module was constructed based on the CE-Net with a context extractor to achieve end-to-end delineation of region of interest (ROI) from radiological images, then the features of segmented Magnetic Resonance Imaging (MRI) and Computed Tomography (CT) images of each case were fused and input to the classification module based on a convolution neural network for treatment outcome prediction. The dataset with 1700 MRI and CT slices collected from the prospectively randomized clinical trial (NCT01211210) on systemic treatment for rectal cancer was used to develop and systematically optimize DeepInteg. As a result, DeepInteg achieved automatic segmentation of tumoral ROI with Dices of 0.766 and 0.719 and mIoUs of 0.788 and 0.756 in CT and MRI images, respectively. In addition, DeepInteg achieved AUC of 0.833, accuracy of 0.826 and specificity of 0.856 in the prediction for pathological complete response after treatment, which showed better performance compared with the model based on CT or MRI alone. This study provide a robust framework to develop disease-specific tools for automatic delineation of ROI and clinical outcome prediction. The well-trained DeepInteg could be readily applied in clinic to predict pathological complete response after neoadjuvant therapy in rectal cancer patients.
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Luo Y, Liu L, Liu D, Shen H, Wang X, Fan C, Zeng Z, Zhang J, Tan Y, Zhang X, Wu J, Zhang J. Extracellular volume fraction determined by equilibrium contrast-enhanced CT for the prediction of the pathological complete response to neoadjuvant chemoradiotherapy for locally advanced rectal cancer. Eur Radiol 2022; 33:4042-4051. [PMID: 36462046 DOI: 10.1007/s00330-022-09307-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 10/31/2022] [Accepted: 11/21/2022] [Indexed: 12/04/2022]
Abstract
OBJECTIVES To determine the extracellular volume (ECV) fraction derived from equilibrium contrast-enhanced CT for predicting pathological complete response (pCR) after neoadjuvant chemoradiotherapy (NCRT) in locally advanced rectal cancer (LARC). METHODS The ECV fraction before NCRT (ECVpre) and/or ECV after NCRT (ECVpost) of rectal tumors was assessed, and ECVΔ was calculated as ECVpost - ECVpre. The histopathologic tumor regression grading (TRG) was assessed. pCR (TRG 0 grade) was defined as the absence of viable tumor cells in the primary tumor and lymph nodes. Demographic and clinicopathological characteristics and ECV fraction were compared between the pCR and non-pCR groups. A mixed model was constructed by logistic regression. The performance for predicting pCR was assessed with the area under the receiver-operator curve (AUC). The AUCs of the different methods were compared by the method proposed by DeLong et al. RESULTS: Seventy-five patients were included; 17 achieved pCR, and 58 achieved non-pCR. The ECVpost (17.05 ± 2.36% vs. 29.94 ± 1.20%; p < 0.001) and ECVΔ (- 17.01 ± 3.01% vs. 0.44 ± 1.45%; p < 0.001) values in the pCR group were significantly lower than those in the non-pCR group. The mixed model that combined ECVpost with ECVΔ achieved an AUC of 0.92 (95% confidence interval (CI) = 0.81-0.98), which was higher than that of ECVpost (AUC, 0.91 (95% CI = 0.80-0.97); p = 0.60) or ECVΔ (AUC, 0.90 (95% CI = 0.79-0.97); p = 0.61). CONCLUSIONS ECVpost and ECVΔ determined by using equilibrium contrast-enhanced CT were useful in distinguishing between pCR and non-pCR patients with LARC who received NCRT. KEY POINTS • ECVpost and ECVΔ (ECVpost - ECVpre) differed significantly between the non-pCR and pCR groups. • ECVpre cannot be used to predict the efficacy of neoadjuvant chemoradiotherapy. • ECVpost combined with ECVΔ had the best performance with an AUC of 0.92 for predicting pCR after NCRT in LARC.
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6
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Lu S, Liu Z, Wang Y, Meng Y, Peng R, Qu R, Zhang Z, Fu W, Wang H. A novel prediction model for pathological complete response based on clinical and blood parameters in locally advanced rectal cancer. Front Oncol 2022; 12:932853. [PMID: 36505836 PMCID: PMC9727231 DOI: 10.3389/fonc.2022.932853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Accepted: 10/19/2022] [Indexed: 11/24/2022] Open
Abstract
Background The aim of this study was to investigate whether clinical and blood parameters can be used for predicting pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC). Methods We retrospectively enrolled 226 patients with LARC [allocated in a 7:3 ratio to a training (n = 158) or validation (n = 68) cohort] who received nCRT before radical surgery. Backward stepwise logistic regression was performed to identify clinical and blood parameters associated with achieving pCR. Models based on clinical parameters (CP), blood parameters (BP), and clinical-blood parameters (CBP) were constructed for comparison with previously reported Tan's model. The performance of the four models was evaluated by receiver operating characteristic (ROC) curve analysis, calibration, and decision curve analysis (DCA) in both cohorts. A dynamic nomogram was constructed for the presentation of the best model. Results The CP and BP models based on multivariate logistic regression analysis showed that interval, Grade, CEA and fibrinogen-albumin ratio index (FARI), sodium-to-globulin ratio (SGR) were the independent clinical and blood predictors for achieving pCR, respectively. The area under the ROC curve of the CBP model achieved a score of 0.818 and 0.752 in both cohorts, better than CP (0.762 and 0.589), BP (0.695 and 0.718), Tan (0.738 and 0.552). CBP also showed better calibration and DCA than other models in both cohorts. Moreover, CBP revealed significant improvement compared with other models in training cohort (P < 0.05), and CBP showed significant improvement compared with CP and Tan's model in validation cohort (P < 0.05). Conclusion We demonstrated that CBP predicting model have potential in predicting pCR to nCRT in patient with LARC.
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Affiliation(s)
- Siyi Lu
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Zhenzhen Liu
- Department of Thoracic Surgery, Beijing Jishuitan Hospital, Beijing, China
| | - Yuxia Wang
- Department of Radiation Oncology, Peking University Third Hospital, Beijing, China
| | - Yan Meng
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Ran Peng
- Department of Radiation Oncology, Peking University Third Hospital, Beijing, China
| | - Ruize Qu
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Zhipeng Zhang
- Department of General Surgery, Peking University Third Hospital, Beijing, China,*Correspondence: Hao Wang, ; Wei Fu, ; Zhipeng Zhang,
| | - Wei Fu
- Department of General Surgery, Peking University Third Hospital, Beijing, China,Cancer Center, Peking University Third Hospital, Beijing, China,*Correspondence: Hao Wang, ; Wei Fu, ; Zhipeng Zhang,
| | - Hao Wang
- Department of Radiation Oncology, Peking University Third Hospital, Beijing, China,Cancer Center, Peking University Third Hospital, Beijing, China,*Correspondence: Hao Wang, ; Wei Fu, ; Zhipeng Zhang,
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7
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Liu M, Feng Y, Zhang Y, Liu H. Evaluation of Neutrophil-Lymphocyte Ratio and Platelet-Lymphocyte Ratio on Predicting Responsiveness to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Patients. BIOMED RESEARCH INTERNATIONAL 2022; 2022:3839670. [PMID: 36212713 PMCID: PMC9534654 DOI: 10.1155/2022/3839670] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 08/31/2022] [Accepted: 09/03/2022] [Indexed: 11/17/2022]
Abstract
Objective Neutrophil-lymphocyte ratio (NLR) and Platelet-lymphocyte ratio (PLR) have been proposed as prognostic biomarkers in multiple cancers. However, the implications of NLR and PLR in the responsiveness to neoadjuvant chemoradiotherapy (nCRT) remain to be clarified in locally advanced rectal cancer (LARC) patients. This retrospective study investigated the prognostic value of NLR and PLR in nCRT responsiveness of LARC patients. Methods A total number of 86 patients diagnosed with LARC and treated with nCRT and total mesorectal excision were retrospectively followed from 2013 to 2016. Receiver operating characteristic (ROC) curve was used to determine the cutoff values of NLR and PLR, and the patients were divided into NLR elevation and NLR decrease groups, or PLR elevation and PLR decrease groups. The correlation between NLR and PLR changes, and clinicopathological factors were analyzed. The relationship between NLR and PLR changes and the curative responsiveness towards nCRT were further evaluated. Results NLR and PLR changes after nCRT were significantly correlated with the distance of tumors to the anus and BMI (body mass index) (P < 0.05). The clinical remission rate of patients with NLR reduction was 72.09% (31/43), which was significantly higher than that in patients with NLR increment (22/43, 51.16%). There was no significant difference in the clinic remission rate between the patients with PLR reduction and those with PLR increment (P > 0.05). However, the pathological responsiveness rate was significantly higher in patients with PLR reduction (21/43, 48.84%) when compared to the ones with PLR increment (9/43, 20.9%) (P = 0.036). Conclusion Our data indicate that in LARC patients with nCRT, the reduction of NLR and the reduction of PLR could serves as predictors for the clinic remission rate and pathological responsiveness rate, respectively. The combination of NLR and PLR changes may be employed as a simple and effective prognostic parameter to predict the treatment outcome of nCRT in LARC.
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Affiliation(s)
- Maoxi Liu
- Department of Anorectal Surgery, Shanxi Cancer Hospital, Taiyuan, 030013 Shanxi, China
| | - Yi Feng
- Department of Anorectal Surgery, Shanxi Cancer Hospital, Taiyuan, 030013 Shanxi, China
| | - Yixun Zhang
- Department of Anorectal Surgery, Shanxi Cancer Hospital, Taiyuan, 030013 Shanxi, China
| | - Haiyi Liu
- Department of Anorectal Surgery, Shanxi Cancer Hospital, Taiyuan, 030013 Shanxi, China
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Kohl VKB, Weber K, Brunner M, Geppert CI, Fietkau R, Grützmann R, Semrau S, Merkel S. Factors influencing downstaging after neoadjuvant long-course chemoradiotherapy in rectal carcinoma. Int J Colorectal Dis 2022; 37:1355-1365. [PMID: 35545701 PMCID: PMC9167202 DOI: 10.1007/s00384-022-04174-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/23/2022] [Indexed: 02/04/2023]
Abstract
PURPOSE This single-centre cohort study was designed to identify factors that can predict primary tumour downstaging by neoadjuvant chemoradiotherapy (nCRT) in rectal carcinoma. METHODS Prospectively collected data from 555 patients with clinical T category (cT) cT3-4 rectal carcinoma treated between 1995 and 2019 were retrospectively analysed. All patients received long-term neoadjuvant chemoradiotherapy followed by surgery with curative intent at the Department of Surgery, University Hospital Erlangen, Germany. Patient-, tumour- and treatment-related factors with a potential impact on the downstaging of rectal carcinoma to pathological T category (pT) ≤ ypT2 and ypT0 were analysed in univariate and multivariate logistic regression analyses. The prognosis of patients with and without downstaging of the primary tumour was compared. RESULTS A total of 288 (51.9%) patients showed downstaging to ≤ ypT2. Eighty-six (15.5%) patients achieved clinical complete regression (ypT0). In the multivariate logistic regression analysis, the factors cT category, BMI, ECOG score, CEA, histological type, extension in the rectum and year of the start of treatment were found to be independent factors for predicting downstaging to ≤ ypT2 after neoadjuvant chemoradiotherapy. The year of treatment initiation also remained an independent significant predictor for pathological complete regression. The prognosis was superior in patients with downstaging to ≤ ypT2 in terms of locoregional and distant recurrence as well as disease-free and overall survival. CONCLUSION Factors predicting downstaging after long-term nCRT could be identified. This may be helpful for counselling patients and selecting the optimal treatment for patients with advanced rectal carcinoma.
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Affiliation(s)
- Valerie K. B. Kohl
- Department of Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ,Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Klaus Weber
- Department of Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ,Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Maximilian Brunner
- Department of Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ,Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Carol I. Geppert
- Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany ,Institute of Pathology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Rainer Fietkau
- Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany ,Department of Radiation Oncology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Robert Grützmann
- Department of Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ,Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany
| | - Sabine Semrau
- Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany ,Department of Radiation Oncology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Susanne Merkel
- Department of Surgery, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany ,Comprehensive Cancer Center Erlangen–European Metropolitan Area of Nuremberg (CCC ER-EMN), Erlangen, Germany ,Department of Surgery, University Hospital Erlangen, Krankenhausstr. 12, 91054 Erlangen, Germany
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Wada Y, Shimada M, Morine Y, Ikemoto T, Saito Y, Zhu Z, Wang X, Etxart A, Park Y, Bujanda L, Park IJ, Goel A. Circulating miRNA Signature Predicts Response to Preoperative Chemoradiotherapy in Locally Advanced Rectal Cancer. JCO Precis Oncol 2021; 5:PO.21.00015. [PMID: 34913022 DOI: 10.1200/po.21.00015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Revised: 08/22/2021] [Accepted: 10/15/2021] [Indexed: 11/20/2022] Open
Abstract
Patients with locally advanced rectal cancer (LARC) are recommended to receive preoperative chemoradiotherapy (PCRT) followed by surgery. Response to PCRT varies widely: 60%-70% of patients with LARC do not derive therapeutic benefit from PCRT, whereas 15%-20% of patients achieve pathologic complete response (pCR). We sought to develop a liquid biopsy assay for identifying response to PCRT in patients with LARC. MATERIALS AND METHODS We analyzed two genome-wide microRNA (miRNA) expression profiling data sets from tumor tissue samples for in silico discovery (GSE68204) and validation (GSE29298). We prioritized biomarkers in pretreatment plasma specimens from clinical training (n = 41; 15 responders and 26 nonresponders) and validation (n = 65; 29 responders and 36 nonresponders) cohorts of patients with LARC. We developed an integrated miRNA panel and established a risk assessment model, which was combined with the miRNA panel and carcinoembryonic antigen levels. RESULTS Our comprehensive discovery effort identified an 8-miRNA panel that robustly predicted response to PCRT, with an excellent accuracy in the discovery (area under the curve [AUC] = 0.95) and validation (AUC = 0.92) cohorts. We successfully established a circulating miRNA panel with remarkable diagnostic accuracy in the clinical training (AUC = 0.82) and validation (AUC = 0.81) cohorts. Moreover, the predictive accuracy of the panel was significantly superior to conventional clinical factors in both cohorts (P < .01) and the risk assessment model was superior (AUC = 0.83). Finally, we applied our model to detect patients with pathologic complete response and showed that it was dramatically superior to currently used pathologic features (AUC = 0.92). CONCLUSION Our novel risk assessment signature for predicting response to PCRT has a potential for clinical translation as a liquid biopsy assay in patients with LARC.
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Affiliation(s)
- Yuma Wada
- Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Monrovia, CA.,Department of Surgery, Tokushima University, Tokushima, Japan.,Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX
| | - Mitsuo Shimada
- Department of Surgery, Tokushima University, Tokushima, Japan
| | - Yuji Morine
- Department of Surgery, Tokushima University, Tokushima, Japan
| | - Tetsuya Ikemoto
- Department of Surgery, Tokushima University, Tokushima, Japan
| | - Yu Saito
- Department of Surgery, Tokushima University, Tokushima, Japan
| | - Zhongxu Zhu
- Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
| | - Xin Wang
- Department of Biomedical Sciences, City University of Hong Kong, Hong Kong, China
| | - Ane Etxart
- Department of Surgery, Donostia Hospital University, Instituto Biodonostia, San Sebastián, Spain
| | - Yangsoon Park
- Department of Pathology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Luis Bujanda
- Gastroenterology Department, Instituto Biodonostia, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), Universidad del País Vasco (UPV/EHU), San Sebastián, Spain
| | - In Ja Park
- Division of Colon and Rectal Surgery, Department of Surgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Ajay Goel
- Department of Molecular Diagnostics and Experimental Therapeutics, Beckman Research Institute of City of Hope, Monrovia, CA.,Center for Gastrointestinal Research, Baylor Scott & White Research Institute and Charles A. Sammons Cancer Center, Baylor University Medical Center, Dallas, TX.,City of Hope Comprehensive Cancer Center, Duarte, CA
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10
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Li J, Xie Y, Huang Z, Shen D, Zhuang Z, Zhu M, Huang Y, He R, Wang X, Huang M, Luo Y, Yu H. Current treatment and surveillance modalities are not sufficient for advanced stage III colon cancer: Result from a multicenter cohort analysis. Cancer Med 2021; 10:8924-8933. [PMID: 34786881 PMCID: PMC8683545 DOI: 10.1002/cam4.4417] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 10/02/2021] [Accepted: 10/25/2021] [Indexed: 01/05/2023] Open
Abstract
OBJECTIVE We conducted this multicenter cohort study to evaluate the current tumor-node-metastasis staging system and treatment modality by analyzing the survival outcomes of patient groups with stage III and IV colon cancer. PATIENTS AND METHODS Stage III and IV colon cancer patients from the Surveillance, Epidemiology, and End Results (SEER) database (SEER cohort) and prospectively maintained Sun Yat-sen University (SYSU) cohort were included in this study. Kaplan-Meier method was used to estimate the cumulative rate of overall survival (OS) between patient groups, and the inverse probability weighting method was used to calculated age and sex-adjusted survival curves. The Cox regression model was used to identify the risk factors for OS. RESULTS A total of 17,911 and 1135 stage III-IV cases were included in the SEER and SYSU cohorts, respectively. Among them, 1448 and 124 resectable stage IV cases underwent curative-intent treatment in the SEER and SYSU cohorts, respectively. The T4N2b group showed a significantly worse survival outcome compared with the M1a subset receiving curative-intent treatment (HR, 1.46; p < 0.001). This finding was validated in the SYSU cohort, in which the T4N2 group had a worse outcome than that of the M1 group receiving curative-intent treatment (HR, 2.44; p < 0.001). These findings were confirmed in the adjusted survival analysis. In the multivariate analysis, the right-side tumor, poor-undifferentiated tumor, and age over 60 years were identified as independent risk factors for T4N2b patients. Based on this multivariate model, the high-risk T4N2b subgroup had a worse survival outcome compared with resectable M1b patients (HR, 1.24; p = 0.03). CONCLUSION By comparing stage III with stage IV colon cancer patients, we identified a subgroup of stage III patients at a higher risk of death than more advanced stages, implying that current cancer care modalities are not sufficient for these high-risk substages.
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Affiliation(s)
- Juan Li
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Yumo Xie
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Ziying Huang
- Zhongshan School of MedicineSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Dingcheng Shen
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Zhuokai Zhuang
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Mingxuan Zhu
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Yaoyi Huang
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Rongzhao He
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Xiaolin Wang
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Meijin Huang
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Yanxin Luo
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
| | - Huichuan Yu
- Department of Colorectal SurgeryThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
- Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor DiseaseGuangdong Institute of GastroenterologyThe Sixth Affiliated HospitalSun Yat‐sen UniversityGuangzhouGuangdongChina
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11
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Pyo DH, Choi JY, Lee WY, Yun SH, Kim HC, Huh JW, Park YA, Shin JK, Cho YB. A Nomogram for Predicting Pathological Complete Response to Neoadjuvant Chemoradiotherapy Using Semiquantitative Parameters Derived From Sequential PET/CT in Locally Advanced Rectal Cancer. Front Oncol 2021; 11:742728. [PMID: 34676170 PMCID: PMC8523984 DOI: 10.3389/fonc.2021.742728] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 09/14/2021] [Indexed: 12/25/2022] Open
Abstract
We evaluated the predictive value of semiquantitative volumetric parameters derived from sequential PET/CT and developed a nomogram to predict pathological complete response (pCR) in patients with rectal cancer treated by neoadjuvant chemoradiotherapy (nCRT). From April 2008 to December 2013, among the patients who underwent nCRT, those who were taken sequential PET/CT before and after nCRT were included. MRI-based staging and semiquantitative parameters of PET/CT including standardized uptake value (SUV), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were evaluated before and after nCRT. Multivariable analysis was performed to select significant predictors to construct a nomogram. Sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve (AUC) of the model were evaluated to determine its performance. Among 137 eligible patients, 17 (12.4%) had pCR. All post-PET/CT parameters showed significant differences between pCR and non-pCR groups. Patients were randomly assigned to a training group (91 patients) and a validation group (46 patients). In multivariable analysis with the training group, post-CEA, post-MRI T staging, post-SUVmax, and post-MTV were significantly associated with pCR. There was no significant pre-nCRT variable for predicting pCR. Using significant predictors, a nomogram was developed. Sensitivity, specificity, accuracy, and AUC of the nomogram were 0.882, 0.808, 0.848, and 0.884 with the training group and 0.857, 0.781, 0.783, and 0.828 with the validation group, respectively. This model showed the better performance than other predictive models that did not contain PET/CT parameters. A nomogram containing semiquantitative post-PET/CT could effectively select candidates for organ-sparing strategies.
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Affiliation(s)
- Dae Hee Pyo
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Joon Young Choi
- Department of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Woo Yong Lee
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea
| | - Seong Hyeon Yun
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hee Cheol Kim
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jung Wook Huh
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yoon Ah Park
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Jung Kyong Shin
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Yong Beom Cho
- Department of Surgery, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.,Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences & Technology (SAIHST), Sungkyunkwan University, Seoul, South Korea.,Department of Biopharmaceutical Convergence, Sungkyunkwan University, Seoul, South Korea
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12
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Cao X, Wang X, Wang H, Xu G, Yu H. Systemic Inflammation Status Relates to Anti-Inflammatory Drug Benefit and Survival in Rectal Cancer. J Surg Res 2021; 269:249-259. [PMID: 34624724 DOI: 10.1016/j.jss.2021.08.028] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/17/2021] [Accepted: 08/27/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Systemic inflammation status has been recognized as a sensitive marker associated with survival in cancers and anti-inflammatory treatment outcomes in inflammation-derived diseases. This study aimed to investigate the role of systemic inflammation status as a predictive marker for survival and anti-inflammatory treatment benefit in rectal cancer patients. METHODS A total of 475 patients with stage I-III rectal cancer receiving curative resection were prospectively enrolled. The platelet-neutrophils to lymphocytes ratio (PNLR) that integrates neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios was applied to enable a comprehensive evaluation of systemic inflammation status and investigate its association with survival and nonsteroidal anti-inflammatory drugs (NSAIDs) benefit. Patients were grouped according to baseline PNLR and perioperative use of NSAIDs. RESULTS The high-PNLR group had worse 5-y disease-free survival (DFS) compared with the low-PNLR group (61.2% versus 70.9%, P = 0.014). Multivariate analyses confirmed that PNLR was an independent predictor for DFS (hazard ratio [HR] 1.42, 95% CI: 1.03-1.97, P = 0.031). A nomogram including PNLR and other independent prognostic factors was developed and validated to predict DFS. In the high-PNLR subset, NSAIDs group had a 21.3% lower risk of recurrence than non-NSAIDs group (P = 0.009), and multivariate analysis confirmed the independently significant association of perioperative NSAIDs use with better DFS (hazard ratio 0.36, 95% CI 0.16-0.78, P = 0.010). However, this association was not significant in the low-PLR subset. CONCLUSIONS Baseline PNLR could be used to predict DFS and NSAIDs benefit in rectal cancer patients. This study highlights the potential survival benefit from the anti-inflammatory treatment in the patients with elevated systemic inflammation status in cancer patients.
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Affiliation(s)
- Xue Cao
- Department of Oncology, Guizhou Provincial People's Hospital, Guiyang, Guizhou, China; Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Xiaolin Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Heng Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Gaopo Xu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Huichuan Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China; Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong, China.
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13
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Suwanthanma W, Kitudomrat S, Euanorasetr C. Clinical outcome of neoadjuvant chemoradiation in rectal cancer treatment. Medicine (Baltimore) 2021; 100:e27366. [PMID: 34559161 PMCID: PMC8462585 DOI: 10.1097/md.0000000000027366] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 09/09/2021] [Indexed: 01/05/2023] Open
Abstract
To determine the clinical and pathological outcome of locally advanced rectal cancer patients treated with neoadjuvant chemoradiation (chemoradiotherapy [CRT]) followed by curative surgery and to identify predictive factors of pathological complete response (pCR).Locally advanced rectal cancer patients undergoing CRT followed by curative surgery from January 2012 to December 2017 were included. Patient's demographic data, pretreatment tumor characteristics, type of CRT regimens, type of surgery, postoperative complications, pathological reports and follow up records were analyzed. Univariate and multivariate analyses were applied to identify predictive factors for pCR. Five-year disease free and overall survival were estimated by Kaplan-Meier method and compared between pCR and non-pCR groups.A total of 85 patients were analyzed. Eighteen patients (21.1%) achieved pCR. The sphincter-saving surgery rate was 57.6%. After univariate analyses, tumor length >4 cm (P = .007) and positive lymph nodes (P = .040) were significantly associated with decreased rate of pCR. Complete clinical response was significantly associated with higher rate of pCR (P = .015). Multivariate analyses demonstrated that tumor length >4 cm (P = .010) was significantly associated with decreased rate of pCR. After a median follow-up of 65 months (IQR 34-79), the calculated 5-year overall survival and disease-free survival rates were 81.4% and 69.7%, respectively. Patients who achieved pCR tend to had longer 5-year disease-free survival (P = .355) and overall survival (P = .361) than those who did not.Tumor length >4 cm was associated with decreased rate of pCR in locally advanced rectal cancer who had CRT followed by surgery. Longer waiting time or more intense adjuvant treatment may be considered to improved pCR and oncological outcomes.
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14
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Ono Y, Cates JMM, Gonzalez RS. Can histologic features predict neoadjuvant therapy response in rectal adenocarcinoma? Pathol Res Pract 2021; 226:153608. [PMID: 34530256 DOI: 10.1016/j.prp.2021.153608] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2021] [Revised: 08/30/2021] [Accepted: 08/31/2021] [Indexed: 02/07/2023]
Abstract
Current standard therapy for locally advanced rectal cancer (LARC) is neoadjuvant therapy followed by surgical resection; however, treatment response is variable among patients. This study aimed to identify histologic features that predict tumor response. This retrospective study included 105 patients with LARC, all of whom underwent biopsy followed by neoadjuvant therapy and subsequent surgical resection. Each patient's initial biopsy was evaluated for tumor grade, tumor budding, intraepithelial lymphocytes, intraepithelial neutrophils, desmoplasia, apoptosis, adjacent stromal lymphocytes, signet ring cells, mucinous features, tumoral Paneth cells, dirty necrosis, microscopic ulceration, and prominent lymphoid aggregates. These histologic features, along with patient age at diagnosis and tumor microsatellite status, were compared to tumor regression grades from the respective resection specimens. No histologic factors in tumor biopsies predictive of treatment response in post-therapy resection specimens were identified. Histologic features in pre-therapy biopsy samples of LARC do not predict subsequent response to neoadjuvant therapy. Effective and reliable methods to predict response to neoadjuvant therapy in rectal cancer remain elusive.
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Affiliation(s)
- Yuho Ono
- Beth Israel Deaconess Medical Center, Department of Pathology, 330 Brookline Avenue, Boston, MA 02215, United States
| | - Justin M M Cates
- Vanderbilt University Medical Center, Department of Pathology, Microbiology, and Immunology, 1161 21st Avenue South, Nashville, TN 37232, United States
| | - Raul S Gonzalez
- Beth Israel Deaconess Medical Center, Department of Pathology, 330 Brookline Avenue, Boston, MA 02215, United States.
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15
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Arslan FD, Kocak A, Aydın C, Pala EE, Oncel D, Diniz G, Kaya T, Ugurlu L, Degirmenci M, Ozkan B, Soysal Y, Said HM. Evaluation of potential tumor markers that may predict neoadjuvant treatment efficiency in rectal cancer. TURKISH JOURNAL OF BIOCHEMISTRY 2021; 46:445-454. [DOI: 10.1515/tjb-2020-0507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/01/2024]
Abstract
Abstract
Objectives
The recurrence of rectal cancer or its resistance to neoadjuvant treatment develops due to the adaptation to hypoxia, apoptosis or autophagy. Survivin, one of the inhibitors of apoptosis; Beclin 1, which is a positive regulator in the autophagy pathway; and hypoxia-inducible factor-1α (HIF-1α) and carbonic anhydrase-9 (CA9), which are associated with tumor tissue hypoxia, may be related to resistance to treatment. Our aim was to evaluate the potential tumor markers that may help to monitor the response to neoadjuvant treatment in locally advanced rectal cancer (RC).
Methods
Twenty-five patients with locally advanced RC were included in the study. Gene expression and protein levels of Beclin 1, Survivin, HIF-1α, and CA9 were analyzed in fresh tissue specimens and blood samples. The relationships of these markers to tumor staging and regression grade were evaluated.
Results
Higher blood CA9 gene expression levels and lower blood HIF-1α protein levels were found in the response group according to tumor regression grade. After neoadjuvant treatment, tissue Beclin 1 and blood Survivin gene expressions and tissue CA9, blood Beclin 1 and blood HIF-1α protein levels decreased significantly.
Conclusion
Beclin 1, Survivin, HIF-1α ve CA9 may help to predict the effects of the applied treatment approach.
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Affiliation(s)
- Fatma Demet Arslan
- Department of Medical Biochemistry , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
- Department of Molecular Medicine, Institute of Health Sciences , Dokuz Eylül University , Izmir , Turkey
| | - Ayse Kocak
- Department of Molecular Medicine, Institute of Health Sciences , Dokuz Eylül University , Izmir , Turkey
| | - Cengiz Aydın
- General Surgery Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Emel Ebru Pala
- Medical Pathology Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Dilek Oncel
- Radiology Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Gulden Diniz
- Medical Pathology Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Tayfun Kaya
- General Surgery Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Levent Ugurlu
- General Surgery Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Mustafa Degirmenci
- Oncology Clinic , University of Health Sciences, Tepecik Training and Research Hospital , Izmir , Turkey
| | - Bulent Ozkan
- Department of Biostatistics , Faculty of Medicine, Katip Çelebi University , Izmir , Turkey
| | - Yasemin Soysal
- Department of Molecular Medicine, Institute of Health Sciences , Dokuz Eylül University , Izmir , Turkey
| | - Harun Muayad Said
- Department of Molecular Medicine, Institute of Health Sciences , Dokuz Eylül University , Izmir , Turkey
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16
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Ouyang G, Yang X, Deng X, Meng W, Yu Y, Wu B, Jiang D, Shu P, Wang Z, Yao J, Wang X. Predicting Response to Total Neoadjuvant Treatment (TNT) in Locally Advanced Rectal Cancer Based on Multiparametric Magnetic Resonance Imaging: A Retrospective Study. Cancer Manag Res 2021; 13:5657-5669. [PMID: 34285586 PMCID: PMC8286103 DOI: 10.2147/cmar.s311501] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Accepted: 06/19/2021] [Indexed: 02/05/2023] Open
Abstract
Purpose To investigate the potential value of magnetic resonance imaging (MRI) in predicting response relevance to total neoadjuvant treatment (TNT) in locally advanced rectal cancer. Methods We analyzed MRI of 71 patients underwent TNT from 2015 to 2017 retrospectively. We categorized the response of TNT as CR (complete response) vs non-CR, and high vs moderate vs low sensitivity. Logistic regression analysis was used to identify the best predictors of response. Diagnostic performance was assessed using receiver operating characteristic curve analysis. Results Post-ICT (induction chemotherapy) ∆TL (tumor length), post-CRT (concurrent chemoradiotherapy) ∆LNN (the numbers of lymph node metastases), post-CCT (consolidation chemotherapy) ∆SDWI (maximum cross-sectional area of tumor on diffusion-weighted imaging), post-CCT ADCT (the mean apparent diffusion coefficient values of tumor) and post-CCT ∆LNV (volume of lymph node) were the best CR predictors. Post-ICT ∆TL, post-CRT EMVI (extramural vascular invasion) and post-CCT ∆ST2 (S on T2-weight) were the best significant factors for high sensitivity. Conclusion Post-ICT ∆TL may be an early predictor of CR and high sensitivity to TNT. Dynamic analysis based on MRI between baseline and post-CCT could provide the most valuable prediction of CR. The grouping modality of CR vs non-CR may be more suitable for treatment response prediction than high vs moderate vs low sensitivity.
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Affiliation(s)
- Ganlu Ouyang
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Xibiao Yang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Xiangbing Deng
- Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Wenjian Meng
- Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Yongyang Yu
- Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Bing Wu
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Dan Jiang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Pei Shu
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Ziqiang Wang
- Department of Gastrointestinal Surgery, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Jin Yao
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
| | - Xin Wang
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, People's Republic of China
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17
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Jiang W, Li M, Tan J, Feng M, Zheng J, Chen D, Liu Z, Yan B, Wang G, Xu S, Xiao W, Gao Y, Zhuo S, Yan J. A Nomogram Based on a Collagen Feature Support Vector Machine for Predicting the Treatment Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer Patients. Ann Surg Oncol 2021; 28:6408-6421. [PMID: 34148136 DOI: 10.1245/s10434-021-10218-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 04/09/2021] [Indexed: 12/21/2022]
Abstract
BACKGROUND The relationship between collagen features (CFs) in the tumor microenvironment and the treatment response to neoadjuvant chemoradiotherapy (nCRT) is still unknown. This study aimed to develop and validate a perdition model based on the CFs and clinicopathological characteristics to predict the treatment response to nCRT among locally advanced rectal cancer (LARC) patients. METHODS In this multicenter, retrospective analysis, 428 patients were included and randomly divided into a training cohort (299 patients) and validation cohort (129 patients) [7:3 ratio]. A total of 11 CFs were extracted from a multiphoton image of pretreatment biopsy, and a support vector machine (SVM) was then used to construct a CFs-SVM classifier. A prediction model was developed and presented with a nomogram using multivariable analysis. Further validation of the nomogram was performed in the validation cohort. RESULTS The CFs-SVM classifier, which integrated collagen area, straightness, and crosslink density, was significantly associated with treatment response. Predictors contained in the nomogram included the CFs-SVM classifier and clinicopathological characteristics by multivariable analysis. The CFs nomogram demonstrated good discrimination, with area under the receiver operating characteristic curves (AUROCs) of 0.834 in the training cohort and 0.854 in the validation cohort. Decision curve analysis indicated that the CFs nomogram was clinically useful. Moreover, compared with the traditional clinicopathological model, the CFs nomogram showed more powerful discrimination in determining the response to nCRT. CONCLUSIONS The CFs-SVM classifier based on CFs in the tumor microenvironment is associated with treatment response, and the CFs nomogram integrating the CFs-SVM classifier and clinicopathological characteristics is useful for individualized prediction of the treatment response to nCRT among LARC patients.
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Affiliation(s)
- Wei Jiang
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.,School of Science, Jimei University, Xiamen, Fujian, People's Republic of China
| | - Min Li
- Department of Radiation Oncology, Sun Yat sen University Cancer Center; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People's Republic of China
| | - Jie Tan
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Mingyuan Feng
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Jixiang Zheng
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Dexin Chen
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Zhangyuanzhu Liu
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Botao Yan
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Guangxing Wang
- Key Laboratory of OptoElectronic Science and Technology for Medicine of Ministry of Education, Fujian Normal University, Fuzhou, Fujian, People's Republic of China
| | - Shuoyu Xu
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.,Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, People's Republic of China
| | - Weiwei Xiao
- Department of Radiation Oncology, Sun Yat sen University Cancer Center; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People's Republic of China
| | - Yuanhong Gao
- Department of Radiation Oncology, Sun Yat sen University Cancer Center; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, Guangdong, People's Republic of China.
| | - Shuangmu Zhuo
- School of Science, Jimei University, Xiamen, Fujian, People's Republic of China.
| | - Jun Yan
- Department of General Surgery, Guangdong Provincial Key Laboratory of Precision Medicine for Gastrointestinal Tumor, Nanfang Hospital, The First School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, People's Republic of China.
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Zhuang Z, Liu Z, Li J, Wang X, Xie P, Xiong F, Hu J, Meng X, Huang M, Deng Y, Lan P, Yu H, Luo Y. Radiomic signature of the FOWARC trial predicts pathological response to neoadjuvant treatment in rectal cancer. J Transl Med 2021; 19:256. [PMID: 34112180 PMCID: PMC8194221 DOI: 10.1186/s12967-021-02919-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/31/2021] [Indexed: 01/06/2023] Open
Abstract
Background We aimed to develop a radiomic model based on pre-treatment computed tomography (CT) to predict the pathological complete response (pCR) in patients with rectal cancer after neoadjuvant treatment and tried to integrate our model with magnetic resonance imaging (MRI)-based radiomic signature. Methods This was a secondary analysis of the FOWARC randomized controlled trial. Radiomic features were extracted from pre-treatment portal venous-phase contrast-enhanced CT images of 177 patients with rectal cancer. Patients were randomly allocated to the primary and validation cohort. The least absolute shrinkage and selection operator regression was applied to select predictive features to build a radiomic signature for pCR prediction (rad-score). This CT-based rad-score was integrated with clinicopathological variables using gradient boosting machine (GBM) or MRI-based rad-score to construct comprehensive models for pCR prediction. The performance of CT-based model was evaluated and compared by receiver operator characteristic (ROC) curve analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare CT-based rad-score, MRI-based rad-score and the combined rad-score. Results We developed a CT-based rad-score for pCR prediction and a gradient boosting machine (GBM) model was built after clinicopathological variables were incorporated, with improved AUCs of 0.997 [95% CI 0.990–1.000] and 0.822 [95% CI 0.649–0.995] in the primary and validation cohort, respectively. Moreover, we constructed a combined model of CT- and MRI-based radiomic signatures that achieve better AIC (75.49 vs. 81.34 vs.82.39) than CT-based rad-score (P = 0.005) and MRI-based rad-score (P = 0.003) alone did. Conclusions The CT-based radiomic models we constructed may provide a useful and reliable tool to predict pCR after neoadjuvant treatment, identify patients that are appropriate for a 'watch and wait' approach, and thus avoid overtreatment. Moreover, the CT-based radiomic signature may add predictive value to the MRI-based models for clinical decision making. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-021-02919-x.
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Affiliation(s)
- Zhuokai Zhuang
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Zongchao Liu
- Department of Biostatistics, Columbia University, New York, NY, 10032, USA
| | - Juan Li
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Xiaolin Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Peiyi Xie
- Department of Radiology, Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Fei Xiong
- Department of Radiology, Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Jiancong Hu
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Xiaochun Meng
- Department of Radiology, Sixth Affiliated Hospital of Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Meijin Huang
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Yanhong Deng
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Department of Medical Oncology, Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Ping Lan
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.,Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Huichuan Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.
| | - Yanxin Luo
- Department of Colorectal Surgery, Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.
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Zhuang Z, Wang X, Huang M, Luo Y, Yu H. Serum calcium improved systemic inflammation marker for predicting survival outcome in rectal cancer. J Gastrointest Oncol 2021; 12:568-579. [PMID: 34012650 DOI: 10.21037/jgo-20-479] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background Systemic inflammation markers have shown prognostic values with variability in rectal cancer. Considering the association of serum calcium with inflammation, we aimed to examine whether it could improve systemic inflammation markers for survival prediction. Methods We enrolled 508 patients with stage I to III rectal cancer who underwent curative resection. The cohort was grouped by corrected serum calcium (cCa), platelet-to-lymphocyte ratio (PLR), and CaPLR (a score model combining cCa with PLR) for survival analysis. The LR (likelihood ratio) test and AIC (Akaike information criterion) were applied to compare models in survival prediction. The primary endpoint was disease-free survival (DFS). Results A total of 26.7% (136/508) patients reached recurrence after curative surgery. Both high cCa (HR 1.486; 95% CI, 1.018-2.171; P=0.040) and high PLR (HR 1.452; 95% CI, 1.059-1.991; P=0.021) were significantly associated with worse DFS. In model comparison, the AIC and LR were improved after cCa was added to PLR model in DFS prediction (AIC: 1,704.83 vs. 1,707.14 vs. 1,707.15; LR: 8.68 vs. 4.37 vs. 4.36; P=0.037). The CaPLR was developed for DFS prediction with adjusted HRs of 2.216 (95% CI, 1.256-3.909; P=0.006) and 1.679 (95% CI, 1.004-2.836; P=0.047) for high and intermediate score group respectively compared to low score group. A nomogram for predicting DFS was generated by using CaPLR and other clinical predictors, with a concordance index of 0.705 (95% CI, 0.620-0.789; P<0.001). Conclusions Serum calcium could improve systemic inflammation markers in survival prediction for patients with rectal cancer.
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Affiliation(s)
- Zhuokai Zhuang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiaolin Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Meijin Huang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Yanxin Luo
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Huichuan Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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20
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Chen Y, Liu D, Xiao J, Xiang J, Liu A, Chen S, Liu J, Hu X, Peng J. Nomogram for Predicting Survival in Advanced Gastric Cancer after Neoadjuvant Chemotherapy and Radical Surgery. Gastroenterol Res Pract 2021; 2021:2923700. [PMID: 34367276 PMCID: PMC8337164 DOI: 10.1155/2021/2923700] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 06/09/2021] [Accepted: 07/10/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Neoadjuvant chemotherapy (NAC) with subsequent radical surgery has become a popular treatment modality for advanced gastric cancer (AGC) worldwide. However, the survival benefit is still controversial, and prognostic factors remain undetermined. AIM To identify clinical parameters that are associated with the survival of AGC patients after NAC and radical surgery and to establish a nomogram integrating multiple factors to predict survival. METHODS We reviewed the medical profiles of 215 AGC patients who received NAC and radical resection, and clinical parameters concerning NAC, surgery, pathological findings, and adjuvant chemotherapy were analyzed using a Cox regression model to determine their impact on survival. Based on these factors, a nomogram was developed and validated. RESULTS The overall 1-year and 3-year survival rates were 85.8% and 55.6%, respectively. Younger age (<60 years old), increased examined lymph nodes (exLNs), successful R0 resection, the achievement of pathological complete response (pCR), and acceptance of adjuvant chemotherapy were positive predictors of survival. The C-index of the established nomogram was 0.785. The area under receiver operating curve (ROC) at 1/3 years of prediction was 0.694/0.736, respectively. The model showed an ideal calibration following internal bootstrap validation. CONCLUSION A nomogram predicting survival after NAC and surgery was established. Since this nomogram exhibited satisfactory and stable predictive power, it can be inferred that this is a practical tool for predicting AGC patient survival after NAC and radical surgery.
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Affiliation(s)
- Yonghe Chen
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Dan Liu
- Department of Laboratory Science, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510105, China
| | - Jian Xiao
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
- Department of Medical Oncology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
| | - Jun Xiang
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Aihong Liu
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Shi Chen
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Junjie Liu
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Xiansheng Hu
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
| | - Junsheng Peng
- Department of Gastric Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou 510655, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Diseases, Guangzhou 510655, China
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21
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Improved Survival Outcome and Access to Cancer Screening from Hemorrhoid in Patients with Rectal Cancer. Gastroenterol Res Pract 2020; 2020:5045142. [PMID: 33381167 PMCID: PMC7749767 DOI: 10.1155/2020/5045142] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 11/24/2020] [Accepted: 12/01/2020] [Indexed: 02/08/2023] Open
Abstract
Background The interventions for hemorrhoid increase access to rectal cancer screening and thus might reduce cancer death. We aimed to examine the impact of hemorrhoid on survival outcomes in rectal cancer. Methods We identified 510 patients with stage I to III rectal cancer from a prospectively collected database. Patients were divided into hemorrhoid and non-hemorrhoid group. The primary endpoints were disease-free survival (DFS) and overall survival (OS). Results Hemorrhoid group had significantly more stage I-II diseases in comparison to nonhemorrhoid group (71.1% vs. 55.9%, P = 0.049). The hemorrhoid group had significantly better DFS and OS compared to nonhemorrhoid group, the hazard ratios (HRs) of which were 0.39 (95% CI 0.17-0.88, P = 0.018) and 0.33 (95% CI 0.12-0.92, P = 0.034), respectively. Multivariate analysis revealed that hemorrhoid was independently associated with DFS [adjusted HR 0.43 (95% CI 0.17-0.95, P = 0.045)]. A nomogram for predicting DFS outcome was generated based on hemorrhoid history, with a concordance index of 0.71 (95% CI 0.66-0.75, P < 0.001). Conclusions There may exist a screening effect and survival benefit from hemorrhoid in rectal cancer, which supports the significance of rectal cancer screening in lowering its mortality.
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Wei FZ, Mei SW, Chen JN, Wang ZJ, Shen HY, Li J, Zhao FQ, Liu Z, Liu Q. Nomograms and risk score models for predicting survival in rectal cancer patients with neoadjuvant therapy. World J Gastroenterol 2020; 26:6638-6657. [PMID: 33268952 PMCID: PMC7673964 DOI: 10.3748/wjg.v26.i42.6638] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2020] [Revised: 09/15/2020] [Accepted: 09/25/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Colorectal cancer is a common digestive cancer worldwide. As a comprehensive treatment for locally advanced rectal cancer (LARC), neoadjuvant therapy (NT) has been increasingly used as the standard treatment for clinical stage II/III rectal cancer. However, few patients achieve a complete pathological response, and most patients require surgical resection and adjuvant therapy. Therefore, identifying risk factors and developing accurate models to predict the prognosis of LARC patients are of great clinical significance. AIM To establish effective prognostic nomograms and risk score prediction models to predict overall survival (OS) and disease-free survival (DFS) for LARC treated with NT. METHODS Nomograms and risk factor score prediction models were based on patients who received NT at the Cancer Hospital from 2015 to 2017. The least absolute shrinkage and selection operator regression model were utilized to screen for prognostic risk factors, which were validated by the Cox regression method. Assessment of the performance of the two prediction models was conducted using receiver operating characteristic curves, and that of the two nomograms was conducted by calculating the concordance index (C-index) and calibration curves. The results were validated in a cohort of 65 patients from 2015 to 2017. RESULTS Seven features were significantly associated with OS and were included in the OS prediction nomogram and prediction model: Vascular_tumors_bolt, cancer nodules, yN, body mass index, matchmouth distance from the edge, nerve aggression and postoperative carcinoembryonic antigen. The nomogram showed good predictive value for OS, with a C-index of 0.91 (95%CI: 0.85, 0.97) and good calibration. In the validation cohort, the C-index was 0.69 (95%CI: 0.53, 0.84). The risk factor prediction model showed good predictive value. The areas under the curve for 3- and 5-year survival were 0.811 and 0.782. The nomogram for predicting DFS included ypTNM and nerve aggression and showed good calibration and a C-index of 0.77 (95%CI: 0.69, 0.85). In the validation cohort, the C-index was 0.71 (95%CI: 0.61, 0.81). The prediction model for DFS also had good predictive value, with an AUC for 3-year survival of 0.784 and an AUC for 5-year survival of 0.754. CONCLUSION We established accurate nomograms and prediction models for predicting OS and DFS in patients with LARC after undergoing NT.
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Affiliation(s)
- Fang-Ze Wei
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Shi-Wen Mei
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Jia-Nan Chen
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Zhi-Jie Wang
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Hai-Yu Shen
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Juan Li
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Fu-Qiang Zhao
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Zheng Liu
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
| | - Qian Liu
- Department of Colorectal Surgery, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union College, Beijing 100021, China
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Xue M, Su Y, Feng Z, Wang S, Zhang M, Wang K, Yao H. A nomogram model for screening the risk of diabetes in a large-scale Chinese population: an observational study from 345,718 participants. Sci Rep 2020; 10:11600. [PMID: 32665620 PMCID: PMC7360758 DOI: 10.1038/s41598-020-68383-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 06/23/2020] [Indexed: 12/31/2022] Open
Abstract
Our study is major to establish and validate a simple type||diabetes mellitus (T2DM) screening model for identifying high-risk individuals among Chinese adults. A total of 643,439 subjects who participated in the national health examination had been enrolled in this cross-sectional study. After excluding subjects with missing data or previous medical history, 345,718 adults was included in the final analysis. We used the least absolute shrinkage and selection operator models to optimize feature selection, and used multivariable logistic regression analysis to build a predicting model. The results showed that the major risk factors of T2DM were age, gender, no drinking or drinking/time > 25 g, no exercise, smoking, waist-to-height ratio, heart rate, systolic blood pressure, fatty liver and gallbladder disease. The area under ROC was 0.811 for development group and 0.814 for validation group, and the p values of the two calibration curves were 0.053 and 0.438, the improvement of net reclassification and integrated discrimination are significant in our model. Our results give a clue that the screening models we conducted may be useful for identifying Chinses adults at high risk for diabetes. Further studies are needed to evaluate the utility and feasibility of this model in various settings.
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Affiliation(s)
- Mingyue Xue
- College of Public Health, Xinjiang Medical University, Ürümqi, 830011, China
| | - Yinxia Su
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, 830011, China
| | - Zhiwei Feng
- College of Basic Medicine, Xinjiang Medical University, Ürümqi, 830011, China
| | - Shuxia Wang
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, 830011, China
| | - Mingchen Zhang
- The First Affiliated Hospital of Xinjiang Medical University, Ürümqi, 830011, China
| | - Kai Wang
- College of Medical Engineering and Technology, Xinjiang Medical University, Ürümqi, 830011, China.
| | - Hua Yao
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Ürümqi, 830011, China.
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An inflammation index-based prediction of treatment response to neoadjuvant chemoradiotherapy for rectal mucinous adenocarcinoma. Int J Clin Oncol 2020; 25:1299-1307. [PMID: 32274615 DOI: 10.1007/s10147-020-01670-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Accepted: 03/30/2020] [Indexed: 12/16/2022]
Abstract
OBJECTIVE This study aimed to evaluate the predictive value of hematological inflammation-based indexes in the treatment response to neoadjuvant chemoradiotherapy (NCRT) in rectal mucinous adenocarcinomas (MACs). METHODS Patients with rectal MACs undergoing NCRT and curative resection were included. Inflammation-based indexes such as systemic immune-inflammation index (SII), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and prognostic nutritional index (PNI) were calculated. Receiver operator characteristics analysis was used to determine the optimal cutoff points. Multivariable logistic analysis identified predictors of good response to NCRT. A nomogram was developed and validated internally. RESULTS A total of 100 patients met the inclusion criteria, with 32 patients developing good response (tumor regression grade, TRG 0 + 1) to NCRT. Lower pre-treatment SII, NLR, and PLR levels were associated with a higher probability of good response to NCRT (P = 0.025, P < 0.001, P = 0.003, respectively), and a higher pre-treatment PNI level was associated with a higher probability of good response to NCRT (P = 0.005). Logistic regression analysis demonstrated that tumor size (< 3 cm, OR = 5.489, P = 0.025), pre-treatment NLR level (< 3.05, OR = 4.025, P = 0.028), pre-treatment PLR level (< 145.98, OR = 4.337, P = 0.038), and pre-treatment PNI level (≥ 41.32, OR = 3.477, P = 0.039) were independent predictors of good response to NCRT. A nomogram was developed with a C-index of 0.827. CONCLUSION Hematological inflammation-based indexes, in terms of pre-treatment NLR, PLR, and PNI levels, can help in predicting the treatment response to NCRT for rectal MACs.
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Huang Z, Wang X, Zou Q, Zhuang Z, Xie Y, Cai D, Bai L, Tang G, Huang M, Luo Y, Yu H. High platelet-to-lymphocyte ratio predicts improved survival outcome for perioperative NSAID use in patients with rectal cancer. Int J Colorectal Dis 2020; 35:695-704. [PMID: 32040733 DOI: 10.1007/s00384-020-03528-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/05/2020] [Indexed: 02/04/2023]
Abstract
PURPOSE Nonsteroidal anti-inflammatory drugs (NSAIDs) have been shown to block tumor-associated inflammation in rectal cancer. However, the perioperative use of NSAIDs remains controversial. This study was designed to investigate whether the perioperative use of NSAIDs influences outcomes and to provide a predictive marker to identify patients who would benefit from NSAIDs. METHODS We enrolled 515 patients with stage I to III rectal cancer in this retrospective study. Patients were classified into the NSAID and non-NSAID groups according to their perioperative use of NSAIDs. The whole cohort was stratified by platelet-to-lymphocyte ratio (PLR). The primary endpoints were disease-free survival (DFS) and overall survival (OS). RESULTS The NSAID group had a 12.6% lower risk of recurrence than the non-NSAID group (P = 0.015), while the association with survival was nonsignificant. In the high-PLR subset, the NSAID group had a 17.3% lower risk of recurrence (P = 0.003) and a better DFS (P = 0.033) outcome than the non-NSAID group. Multivariate analysis confirmed this independent significant association with DFS (P = 0.023). In the low-PLR subset, the association of NSAID use with survival was nonsignificant. CONCLUSION Perioperative use of NSAIDs was associated with improved survival outcomes in rectal cancer patients with high PLR.
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Affiliation(s)
- Zenghong Huang
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Xiaolin Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Qi Zou
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
- Department of Colorectal and Anal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Zhuokai Zhuang
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Yumo Xie
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Du Cai
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Liangliang Bai
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Guannan Tang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China
| | - Meijin Huang
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Yanxin Luo
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, 510655, Guangdong, China
| | - Huichuan Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, 26 Yuancun Erheng Road, Guangzhou, 510655, Guangdong, China.
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Yu Z, Yu H, Zou Q, Huang Z, Wang X, Tang G, Bai L, Zhou C, Zhuang Z, Xie Y, Wang H, Xu G, Chen Z, Fu X, Huang M, Luo Y. Nomograms for Prediction of Molecular Phenotypes in Colorectal Cancer. Onco Targets Ther 2020; 13:309-321. [PMID: 32021277 PMCID: PMC6968822 DOI: 10.2147/ott.s234495] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2019] [Accepted: 12/24/2019] [Indexed: 12/24/2022] Open
Abstract
Background Colorectal cancer (CRC) patients with different molecular phenotypes, including microsatellite instability (MSI), CpG island methylator phenotype (CIMP), and somatic mutations in BRAF and KRAS gene, vary in treatment response and prognosis. However, molecular phenotyping under adequate quality control in a community-based setting may be difficult. We aimed to build the nomograms based on easily accessible clinicopathological characteristics to predict molecular phenotypes. Methods Three hundred and six patients with pathologically confirmed stage I-IV CRC were included in the cohort. The assays for MSI, CIMP, and mutations in BRAF and KRAS gene were performed using resected tumor samples. The candidate predictors were identified from clinicopathological variables using multivariate Logistic regression analyses to construct the nomograms that could predict each molecular phenotype. Results The incidences of MSI, CIMP, BRAF mutation and KRAS mutation were 25.3% (72/285), 2.5% (7/270), 3.4% (10/293), and 34.8% (96/276) respectively. In the multivariate Logistic analysis, poor differentiation and high neutrophil/lymphocyte ratio (NLR) were independently associated with MSI; poor differentiation, high NLR and high carcinoembryonic antigen/tumor size ratio (CSR) were independently associated with CIMP; poor differentiation, lymphovascular invasion and high CSR were independently associated with BRAF mutation; poor differentiation, proximal tumor, mucinous tumor and high NLR were independently associated with KRAS mutation. Four nomograms for MSI, CIMP, BRAF mutation and KRAS mutation were developed based on these independent predictors, the C-indexes of which were 61.22% (95% CI: 60.28–62.16%), 95.57% (95% CI: 95.20–95.94%), 83.56% (95% CI: 81.54–85.58%), and 69.12% (95% CI: 68.30–69.94%) respectively. Conclusion We established four nomograms using easily accessible variables that could well predict the presence of MSI, CIMP, BRAF mutation and KRAS mutation in CRC patients.
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Affiliation(s)
- Zhuojun Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Huichuan Yu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Qi Zou
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal and Anal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Zenghong Huang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Xiaolin Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Guannan Tang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Liangliang Bai
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Chuanhai Zhou
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Zhuokai Zhuang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Yumo Xie
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Heng Wang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Gaopo Xu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Zijian Chen
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Gastrointestinal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Xinhui Fu
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Pathology, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Meijin Huang
- Guangdong Institute of Gastroenterology, Guangdong Provincial Key Laboratory of Colorectal and Pelvic Floor Disease, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China.,Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
| | - Yanxin Luo
- Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510655, People's Republic of China
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Braun LH, Baumann D, Zwirner K, Eipper E, Hauth F, Peter A, Zips D, Gani C. Neutrophil-to-Lymphocyte Ratio in Rectal Cancer-Novel Biomarker of Tumor Immunogenicity During Radiotherapy or Confounding Variable? Int J Mol Sci 2019; 20:ijms20102448. [PMID: 31108935 PMCID: PMC6566677 DOI: 10.3390/ijms20102448] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 05/10/2019] [Accepted: 05/13/2019] [Indexed: 12/14/2022] Open
Abstract
The aim of this study was to investigate the predictive value of blood-derived makers of local and systemic inflammatory responses on early and long-term oncological outcomes. A retrospective analysis of patients with locally advanced rectal cancer treated with preoperative long-course 5-fluorouracil-based radiochemotherapy was performed. Differential blood counts before neoadjuvant treatment were extracted from the patients' electronic charts. Optimal cut-off values for neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR) were determined. Potential clinical and hematological prognostic factors for disease-free survival (DFS) were studied using uni- and multivariate analysis. A total of 220 patients were included in the analysis. Median follow-up was 67 months. Five-year DFS and overall survival (OS) were 70% and 85%, respectively. NLR with a cut-off value of 4.06 was identified as optimal to predict DFS events. In multivariate analysis, only tumor volume (HR 0.33, 95% CI (0.14-0.83), p = 0.017) and NLR (HR 0.3, 95% CI (0.11-0.81), p = 0.017) remained significant predictors of DFS. Patients with a good histological response (Dworak 3 and 4) to radiotherapy also had a lower NLR than patients with less pronounced tumor regression (3.0 vs. 4.2, p = 0.015). A strong correlation between primary tumor volume and NLR was seen (Pearson's r = 0.64, p < 0.001). Moreover, patients with T4 tumors had a significantly higher NLR than patients with T1-T3 tumors (6.6 vs. 3.3, p < 0.001). An elevated pretherapeutic NLR was associated with higher T stage, inferior DFS, and poor pathological response to neoadjuvant radiochemotherapy. A strong correlation between NLR and primary tumor volume was seen. This association is important for the interpretation of study results and for the design of translational studies which are warranted.
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Affiliation(s)
- Lore Helene Braun
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
| | - David Baumann
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
| | - Kerstin Zwirner
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
| | - Ewald Eipper
- Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, 72076 Tübingen, Germany.
| | - Franziska Hauth
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
| | - Andreas Peter
- Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tübingen, 72076 Tübingen, Germany.
| | - Daniel Zips
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
- German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
- Gastrointestinal Cancer Center, Comprehensive Cancer Center Tübingen-Stuttgart, 72076 Tübingen, Germany.
| | - Cihan Gani
- Department of Radiation Oncology, University Hospital and Medical Faculty Tübingen, Eberhard Karls University Tübingen, 72076 Tübingen, Germany.
- German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK), 69120 Heidelberg, Germany.
- Gastrointestinal Cancer Center, Comprehensive Cancer Center Tübingen-Stuttgart, 72076 Tübingen, Germany.
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