Molecular Markers for the Prediction of Minor Response to Neoadjuvant Chemoradiation in Esophageal Cancer: Results of the Prospective Cologne Esophageal Response Prediction (CERP) Study

Multi-omics approaches for biomarker discovery in predicting the response of esophageal cancer to neoadjuvant therapy: A multidimensional perspective

Neoadjuvant chemoradiotherapy (NCRT) followed by surgery has been established as the standard treatment strategy for operable locally advanced esophageal cancer (EC). However, achieving pathologic complete response (pCR) or near pCR to NCRT is significantly associated with a considerable improvement in survival outcomes, while pCR patients may help organ preservation for patients by active surveillance to avoid planned surgery. Thus, there is an urgent need for improved biomarkers to predict EC chemoradiation response in research and clinical settings. Advances in multiple high-throughput technologies such as next-generation sequencing have facilitated the discovery of novel predictive biomarkers, specifically based on multi-omics data, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra. The application of multi-omics data has shown the benefits in improving the understanding of underlying mechanisms of NCRT sensitivity/resistance in EC. Particularly, the prominent development of artificial intelligence (AI) has introduced a new direction in cancer research. The integration of multi-omics data has significantly advanced our knowledge of the disease and enabled the identification of valuable biomarkers for predicting treatment response from diverse dimension levels, especially with rapid advances in biotechnological and AI methodologies. Herein, we summarize the current status of research on the use of multi-omics technologies in predicting NCRT response for EC patients. Current limitations, challenges, and future perspectives of these multi-omics platforms will be addressed to assist in experimental designs and clinical use for further integrated analysis.

An artificial neural network-based radiomics model for predicting the radiotherapy response of advanced esophageal squamous cell carcinoma patients: a multicenter study

Radiotherapy benefits patients with advanced esophageal squamous cell carcinoma (ESCC) in terms of symptom relief and long-term survival. In contrast, a substantial proportion of ESCC patients have not benefited from radiotherapy. This study aimed to establish and validate an artificial neural network-based radiomics model for the pretreatment prediction of the radiotherapy response of advanced ESCC by using integrated data combined with feasible baseline characteristics of computed tomography. A total of 248 patients with advanced ESCC who underwent baseline CT and received radiotherapy were enrolled in this study and were analyzed by two types of radiomics models, machine learning and deep learning. As a result, the Att. Resnet50 pretrained network model indicated superior performance, with AUCs of 0.876, 0.802 and 0.732 in the training, internal validation, and external validation cohorts, respectively. Similarly, our Att. Resnet50 pretrained network model showed excellent calibration and significant clinical benefit according to the C index and decision curve analysis. Herein, a novel pretreatment radiomics model was established based on deep learning methods and could be used for radiotherapy response prediction in advanced ESCC patients, thus providing reliable evidence for therapeutic decision-making.

A Transcriptomic Liquid Biopsy Assay for Predicting Resistance to Neoadjuvant Therapy in Esophageal Squamous Cell Carcinoma

OBJECTIVE

The aim of this study was to establish a liquid-biopsy assay to predict response to neoadjuvant therapy (NAT) in esophageal squamous cell carcinoma (ESCC) patients.

SUMMARY BACKGROUND DATA

Pretreatment prediction of resistance to NAT is of great significance for the selection of treatment options in ESCC patients. In this study, we comprehensively translated tissue-based microRNA (miRNA) and messenger RNA (mRNA) expression biomarkers into a liquid biopsy assay.

METHODS

We analyzed 186 clinical ESCC samples, which included 128 formalin-fixed paraffin-embedded and a matched subset of 58 serum samples, from 2 independent institutions. We performed quantitative reverse-transcription polymerase chain reaction, and developed a resistance-prediction model using the logistic regression analyses.

RESULTS

We first evaluated the potential of 4-miRNAs and 3-mRNAs panel, which robustly predicted resistance to NAT [area under the curve (AUC): 0.85]. Moreover, addition of tumor size to this panel increased predictive potential to establish a combination signature (AUC: 0.92). We successfully validated this signature performance in independent cohort, and our model was more accurate when the signature was combined with clinical predictors (AUC: 0.81) to establish a NAT resistance risk (NATRR) model. Finally, we successfully translated our NATRR model into a liquid biopsy assay (AUC: 0.78), and a multivariate regression analysis revealed this model as an independent predictor for response to NAT (odds ratio: 6.10; P < 0.01).

CONCLUSIONS

We successfully developed a liquid biopsy-based assay that allows robust prediction of response to NAT in ESCC patients, and our assay provides fundamentals of developing precision-medicine.

Predicting Response to Neoadjuvant Therapy in Oesophageal Adenocarcinoma

(1) Background: Oesophageal cancers are often late-presenting and have a poor 5-year survival rate. The standard treatment of oesophageal adenocarcinomas involves neoadjuvant chemotherapy with or without radiotherapy followed by surgery. However, less than one third of patients respond to neoadjuvant therapy, thereby unnecessarily exposing patients to toxicity and deconditioning. Hence, there is an urgent need for biomarkers to predict response to neoadjuvant therapy. This review explores the current biomarker landscape. (2) Methods: MEDLINE, EMBASE and ClinicalTrial databases were searched with key words relating to “predictive biomarker”, “neoadjuvant therapy” and “oesophageal adenocarcinoma” and screened as per the inclusion and exclusion criteria. All peer-reviewed full-text articles and conference abstracts were included. (3) Results: The search yielded 548 results of which 71 full-texts, conference abstracts and clinical trials were eligible for review. A total of 242 duplicates were removed, 191 articles were screened out, and 44 articles were excluded. (4) Discussion: Biomarkers were discussed in seven categories including imaging, epigenetic, genetic, protein, immunologic, blood and serum-based with remaining studies grouped in a miscellaneous category. (5) Conclusion: Although promising markers and novel methods have emerged, current biomarkers lack sufficient evidence to support clinical application. Novel approaches have been recommended to assess predictive potential more efficiently.

The Relevance of Regenerating Gene 1a Polymorphisms to Radiation Sensitivity and Survival of Nasopharyngeal Carcinoma Receiving Radiotherapy in a Southern Chinese Population

Objective

Gene polymorphism is closely related to tumor development, therapeutic response and prognosis. The relationship between regenerating gene 1A (Reg1A) polymorphism and nasopharyngeal carcinoma (NPC) is unclear. This retrospective study aimed to analyze the association between Reg1a polymorphisms and metastasis, radiation sensitivity and survivals in patients with NPC.

Methods

A total of 308 patients who had received radiotherapy at the Affiliated Xinhua Hospital, Hainan Medical College, between January 2010 and December 2018 with NPC, were enrolled for assessment of Reg1a polymorphisms through direct DNA sequencing.

Results

In the polymorphism of gene REG1A, patients with rs10165462 20CC genotype had later T stages (OR = 4.051, 95% CI: 1.775–9.244, P = 0.001), whereas carriers with rs12072 2922CC genotype had earlier T stages (OR = 1.891, 95% CI: 1.018–3.514, P = 0.044) after adjustments for age and gender, respectively. Among rs10165462 20 C/T polymorphism, 20TT wild-type was associated with better radiation response (P = 0.0019), and multivariate analysis showed that it was the only genotype of polymorphism that was significantly associated with better radiation response (OR = 0.265, 95% CI: 0.096–0.727, P = 0.01). Patients with the 20TT wild-type had a better five-year overall survival (60.9%) rate and five-year progression-free survival (60.8%) than those with the 20CC genotype (41.8% and 39.4%, P = 0.01 and P = 0.004, respectively). Patients with variant alleles (CC + CT) had significantly poorer OS (45.2%) and PFS (41.8%) compared with wild-type (TT) carriers (60.9% and 60.8%; P = 0.037 and P = 0.015, respectively). As for rs12072, patients with variant alleles (TT + TC) had significantly adverse OS and PFS compared with wild-type (CC) carriers (62.5% vs 44.8% and 62.5% vs 42.9%; P = 0.024 and P = 0.027, respectively). Cox regression showed that rs10165462 20CT was the only prognostic factor for OS (HR = 1.642, 95% CI 1.038–2.598, P = 0.034) and PFS (HR = 1.705, 95% CI 1.080–2.692, P = 0.022).

Conclusion

Reg1a polymorphisms may be a predictor of radiation response, local invasion, OS and PFS in patients with NPC who undergo radiotherapy treatment.

Biomarkers for the prediction of esophageal cancer neoadjuvant chemoradiotherapy response: A systemic review

Neoadjuvant chemoradiotherapy followed by surgery has been established as the standard treatment for locally advanced esophageal cancer. For patients with complete regression after neoadjuvant chemotherapy, active surveillance rather than planned surgery has been proposed as an organ preservation strategy. Reliable biomarkers to predict chemoradiation response is needed. We first summarized the previous reports of biomarkers with the potential to predict the treatment response of esophageal cancer neoadjuvant chemoradiotherapy. These traditional biomarkers are classified into three groups: genetic biomarkers, RNA biomarkers, and protein biomarkers. We then summarized some special types of biomarkers, including metabolites biomarkers, immune and tumor microenvironment biomarkers, and microbiome biomarkers.

Towards Personalized Treatment Strategies for Esophageal Adenocarcinoma; A Review on the Molecular Characterization of Esophageal Adenocarcinoma and Current Research Efforts on Individualized Curative Treatment Regimens

Esophageal cancers confer a major health challenge and are highly aggressive malignancies with poor prognosis. Esophageal adenocarcinoma (EAC) is one of the two major histopathological subtypes of esophageal cancer. Despite advances in treatment modalities, the prognosis of patients with EAC remains poor, with a 5-year survival rate that rarely exceeds 30% in patients treated with curative intent. Chemoradiotherapy followed by resection is the treatment of choice for EAC patients, which are deemed to be curable. Current patient stratification and treatments are based on outcomes from clinical trials. Unfortunately, the molecular heterogeneity of EAC which determines the chemo- and radiosensitivity of these cancers are not taken into account. A more personalized approach in the treatment of EAC could improve patient outcomes. This review aims at summarizing literature on translational and clinical research in the field of EAC which could be of importance to develop personalized approaches. As suggested by the TCGA, expression data features molecular classifications by different platforms, including miRNA, genomic mutations and reverse-phase protein arrays. Here, we summarize literature on transcriptomic, data-driven approaches to identify distinct subtypes of EAC associated with molecular features. These novel classifications may determine the responsiveness to chemo(radio)therapy and help to identify novel molecular targets within cell signaling pathways. Moreover, we discuss the current clinical research efforts on tailored treatment regimens for patients with EAC taking into account the heterogeneous response to chemoradiotherapy. We summarize the evidence regarding active surveillance instead of immediate surgical resection after application of neoadjuvant chemo(radio)therapy in EAC. We consider that in future patients with complete response to chemo(radio)therapy, predicted by (transcriptomic) biomarkers, might benefit most from this approach. Finally, challenges to overcome for current findings to be implemented in clinical practice and move the field forward are being discussed.

Transcriptomic biomarkers for predicting response to neoadjuvant treatment in oesophageal cancer

Oesophageal cancer is a devastating disease with poor outcomes and is the sixth leading cause of cancer death worldwide. In the setting of resectable disease, there is clear evidence that neoadjuvant chemotherapy and chemoradiotherapy result in improved survival. Disappointingly, only 15%-30% of patients obtain a histopathological response to neoadjuvant therapy, often at the expense of significant toxicity. There are no predictive biomarkers in routine clinical use in this setting and the ability to stratify patients for treatment could dramatically improve outcomes. In this review, we aim to outline current progress in evaluating predictive transcriptomic biomarkers for neoadjuvant therapy in oesophageal cancer and discuss the challenges facing biomarker development in this setting. We place these issues in the wider context of recommendations for biomarker development and reporting. The majority of studies focus on messenger RNA (mRNA) and microRNA (miRNA) biomarkers. These studies report a range of different genes involved in a wide variety of pathways and biological processes, and this is explained to a large extent by the different platforms and analysis methods used. Many studies are also vastly underpowered so are not suitable for identifying a candidate biomarker. Multiple molecular subtypes of oesophageal cancer have been proposed, although little is known about how these relate to clinical outcomes. We anticipate that the accumulating wealth of genomic and transcriptomic data and clinical trial collaborations in the coming years will provide unique opportunities to stratify patients in this poor-prognosis disease and recommend that future biomarker development incorporates well-designed retrospective and prospective analyses.

Different response rates to chemotherapy between Japanese and German esophageal squamous cell carcinoma: patients may be influenced by ERCC1 or ABCB1

Aim: To find out differences in biomarkers between Japanese and German patients responsible for response after neoadjuvant radio/chemotherapy and survival for esophageal squamous cell carcinoma. Materials & methods: A total of 60 patients from Japan and 127 patients from Germany with esophageal squamous cell carcinoma were analyzed according to three SNPs by real-time PCR. Results: The distribution of the genotypes of ERCC1 rs16115 and ABCB1 C3435T rs1045642 was significantly different between both patients' groups. Japanese patients had significantly less good response to 5-fluorouracil/cisplatin chemotherapy. The influence of the three SNPs on response varied between patients from Japan and Germany. Conclusion: Different expressions of ERCC1 and ABCB1 SNPs of Japanese patients compared with the German patients partially explain the different response.

Predictive Value of Excision Repair Cross-Complementation Group 1 in the Response to Platinum-Based Chemotherapy in Esophageal Cancer: A Meta-Analysis

INTRODUCTION

Platinum is widely used in the treatment of esophageal cancer. In clinical practice, it is significant to distinguish patients who respond to platinum from those who do not. Excision repair cross-complementation group 1 (ERCC1) is thought to be the key in the resistance to platinum. However, whether it is related to the platinum-based chemotherapy response on real esophageal cancer patients is controversial. We conducted this meta-analysis to explore the association between ERCC1 polymorphisms, its expression levels and platinum-based chemotherapy response, and identify the most sensitive genotypes.

METHODS

The study was carried out according to the Cochrane handbook for systemic reviews of intervention. The study protocol has been registered on PROSPERO.

RESULTS

Three studies were included in the analysis of C8092A polymorphisms, 5 in the C118T, and another 6 in ERCC1 expression levels. In C118T polymorphisms, compared to wild genotype, patients with mutant genotypes had a significantly higher response rate. As for C8092A polymorphisms, the mutant genotypes also presented a better response than the wild genotype. The pooled analysis indicated a significantly higher response rate in patients with a low expression of ERCC1.

CONCLUSIONS

ERCC1 is a valuable biomarker for platinum-based chemotherapy in esophageal cancer. Patients with ERCC1 mutations or low-level ERCC1 expression are more sensitive to platinum-based chemotherapy.

Impact of single-nucleotide polymorphisms in DNA repair pathway genes on response to chemoradiotherapy in rectal cancer patients: Results from ACCORD-12/PRODIGE-2 phase III trial

We examined whether 66 germline single-nucleotide polymorphisms (SNPs) in 10 candidate genes would predict clinical outcome in 316 patients with resectable locally advanced rectal cancer (LARC) enrolled in the ACCORD-12 phase III trial who were randomly treated with preoperative radiotherapy plus capecitabine (CAP45; n = 155) or dose-intensified radiotherapy plus capecitabine and oxaliplatin (CAPOX50; n = 161). The primary endpoint was tumor response according to the Dworak score. Multivariate logistic regression models adjusted on treatment arm and T stage determined the SNPs prognostic and predictive values for tumor response. In univariate analysis, five SNPs in ERCC2, XPA, MTHFR and ERCC1 were associated with the Dworak score in the CAPOX50 arm. In the overall population, interaction with treatment arm was significant for ERCC2 rs1799787 (p_interaction = 0.05) and XPA rs3176683 (p_interaction = 0.008), suggesting a predictive effect for response to oxaliplatin-based chemoradiotherapy (CRT). All but XPA rs3176683 had a prognostic effect on tumor response. In a multivariate model, interaction remained significant for XPA rs3176683 ([OR 7.33, 95% CI 1.40-38.23], p_interaction = 0.018) and the prognostic effect significant for ERCC2 rs1799787 ([OR 0.55, 95%CI 0.32-0.93], p = 0.027) and ERCC1 rs10412761 ([OR 0.57, 95%CI 0.34-0.98], p = 0.042). Patients with the T/G haplotype of rs1799787 and rs10412761 had a 60% decrease in odds of response (p < 0.001). None of the five SNPs were associated with toxicity, overall and disease-free survival. These data suggest that genetic variation in DNA repair genes influences response to preoperative CRT in LARC and identify patients who benefit from the addition of oxaliplatin to CRT.

New approaches in esophageal carcinomas

New approaches in the treatment of esophageal cancer comprise endoscopy with refinements of esophagoscopic intraluminal resection by endoscopic submucosal dissection. Radical open surgery is more and more replaced by minimally invasive esophagectomy (MIO), especially in the hybrid technique with laparoscopic gastrolysis and transthoracic esophageal resection and gastric pull-up. Total MIO also in the robotic technique has not yet shown that it produces superior results than the hybrid technique. Fluorescent dye can improve the intraoperative visualization of the vascularization of the gastric conduit. The individualization of neoadjuvant therapy is the magic word in clinical research of multimodal treatment of esophageal cancer. This means response prediction based on molecular markers or clinical response evaluation. The documentation of the diversity of postoperative complications is now standardized by an international consensus. The value of enhanced recovery after surgery is not yet approved compared to conventional management.