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

Nomogram for predicting pathologic complete response following preoperative chemoradiotherapy in patients with esophageal squamous cell carcinoma

Background

In patients with esophageal squamous cell carcinoma (ESCC), accurately predicting a pathologic complete response (pCR) to preoperative chemoradiotherapy (PCRT) has the potential to enable an active surveillance strategy without esophagectomy. We aimed to establish a reliable multiparameter nomogram model that combines tumor characteristics, imaging modalities, and hematologic markers to predict pCR in patients with ESCC who underwent PCRT and esophagectomy.

Methods

We retrospectively reviewed the medical records of 457 patients with ESCC who received PCRT followed by esophagectomy between January 2005 and October 2020. The nomogram model was developed using logistic regression analysis with a training cohort and externally validated with a validation cohort.

Results

In the training and validation cohorts, 44.2% (126/285) and 48.3% (83/172) of patients, respectively, achieved pCR after PCRT. The 5-year rates of overall survival, progression-free survival, and freedom from local progression in the training cohort were 51.6%, 48.5%, and 77.6%, respectively. The parameters included in the nomogram were histologic grade, clinical N stage, maximum standardized uptake value on positron emission tomography, and post-PCRT biopsy. Hematologic markers were significantly associated with survival outcomes but not with pCR. The area under the receiver operating characteristic curve of the nomogram was 0.717, 0.704, and 0.707 for the training cohort, internal validation cohort, and external validation cohort, respectively.

Conclusion

Our nomogram model based on four parameters obtained from standard clinical practice demonstrated good performance in both the training and validation cohorts and could be useful to aid clinical decision-making to determine whether surgery or active surveillance strategy should be pursued.

Camrelizumab in combination with neoadjuvant chemotherapy in resectable locally advanced esophageal squamous carcinoma cancer: Results from a retrospective study

This study aimed to evaluate the safety and efficacy of camrelizumab combined with chemotherapy during preoperative neoadjuvant therapy in patients with locally advanced resectable esophageal squamous cell carcinoma (ESCC) of clinical Stages II and III. The patients received camrelizumab plus chemotherapy regimen on Day 1 for up to three to four cycles (3 weeks per cycle). The probabilities of overall survival (OS) were 55.6% at 12 months and 35.6% at 18 months (45 patients). The disease-free survival (DFS) rates were 70.0% at 12 months and 63.3% at 18 months (30 patients). The median OS and DFS were not reached. The proportion of patients at postneoadjuvant pathological tumor stages ypT0, ypT2, and ypT3 were 10 (33.3%), 14 (46.7%), and 6 (20.0%), respectively, and those at stages ypN0 and ypN1 were 19 (63.3%) and 11 (36.7%), respectively. Additionally, the pathological complete response rate was 33.3% (95% confidence interval [CI]: 0.154-0.512), and the major pathologic response rate was 46.7% (95% CI: 0.277-0.656). Grade ≥3 adverse events (AEs) were reported in five patients (11.1%), with vomiting being the most common AE (three patients; 3.3%). Other common AEs of any grade included decreased lymphocyte count (48.9%), reactive capillary endothelial proliferation (46.7%), decreased white blood cell count (40.0%), anemia (31.1%), and vomiting (31.1%). The combination of camrelizumab and neoadjuvant chemotherapy in patients with locally advanced resectable ESCC demonstrated promising efficacy and acceptable safety.

Current and future on definitive concurrent chemoradiotherapy for inoperable locally advanced esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is an aggressive and fatal disease that is usually diagnosed when the chances for surgical intervention has been missed. Definitive concurrent chemoradiotherapy (dCRT) is the first choice of treatment for inoperable locally advanced esophageal squamous cell carcinoma (LA-ESCC). Nevertheless, the local recurrence rate for esophageal cancer patients undergoing dCRT remains high at 40-60%, with a 5-year overall survival rate of solely 10-30%. Immunotherapy in combination with dCRT is a promising treatment for inoperable LA-ESCC, for that improved long-term survival is expected. The present review provides a comprehensive overview of the evolutionary trajectory of dCRT for LA-ESCC, delineates notable relevant clinical studies, addresses unresolved concerns regarding the combination of dCRT with immunotherapy, and highlights promising directions for future research. When dCRT is combined with immunotherapy, the following aspects should be carefully explored in the future studies, including the optimal irradiation dose, segmentation scheme, radiotherapy technique, timing, sequence and duration of radiotherapy, and the selection of chemotherapeutic and immunologic drugs. In addition, further investigations on the mechanisms of how dCRT combined with immunotherapy exerts synergistic anti-tumor effects and molecular biomarkers ensuring precise screening of ESCC patients are needed.

Radiotherapy combined with immune checkpoint inhibitors in locally advanced/metastatic esophageal squamous cell carcinoma: clinical trials, efficacy and future directions

Esophageal squamous cell carcinoma (ESCC) is a common malignancy worldwide and often diagnosed at advanced stages with poor prognosis. Combination of radiotherapy and immunotherapy seems to be a promising approach for treating ESCC. This comprehensive review article summarizes the current state of combination of radiotherapy and immunotherapy in locally advanced/metastatic ESCC, delineates the clinical trials that merit attention, and outlines unresolved issues and future research directions in this field. The clinical trial findings suggest that radio-immunotherapy combination may improve tumor response and overall survival with manageable side effects, highlighting the importance of patient selection and the necessity for further research to optimize treatment strategies. Issues such as irradiation dosage, fractionation regimen, irradiation site and technique of radiotherapy, as well as the timing, sequence and duration of combination therapy will all affect treatment outcomes, justifying further in-depth investigation.

Biomarkers for Early Detection, Prognosis, and Therapeutics of Esophageal Cancers

Esophageal cancer (EC) is the deadliest cancer worldwide, with a 92% annual mortality rate per incidence. Esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two major types of ECs, with EAC having one of the worst prognoses in oncology. Limited screening techniques and a lack of molecular analysis of diseased tissues have led to late-stage presentation and very low survival durations. The five-year survival rate of EC is less than 20%. Thus, early diagnosis of EC may prolong survival and improve clinical outcomes. Cellular and molecular biomarkers are used for diagnosis. At present, esophageal biopsy during upper endoscopy and histopathological analysis is the standard screening modality for both ESCC and EAC. However, this is an invasive method that fails to yield a molecular profile of the diseased compartment. To decrease the invasiveness of the procedures for diagnosis, researchers are proposing non-invasive biomarkers for early diagnosis and point-of-care screening options. Liquid biopsy involves the collection of body fluids (blood, urine, and saliva) non-invasively or with minimal invasiveness. In this review, we have critically discussed various biomarkers and specimen retrieval techniques for ESCC and EAC.

Esophageal squamous cell carcinoma: Integrated bioinformatics analysis for differential gene expression with identification of hub genes and lncRNA

Background

Esophageal squamous cell carcinoma (ESCC) is a typical Gastro-Intestinal (GI) tract neoplasm. This study was conducted to know the Differential Expressed Genes (DEGs) profile of ESCC along with hub gene screening, lncRNA identification, and drug-genes interactions.

Methods

GSE161533, GSE20347, GSE45670 microarray datasets were retrieved from the NCBI Gene Expression Omnibus (GEO) database. GEO2R was used for the DEGs identification, whereas GO (Gene Ontology) and KEGG enrichment analysis were performed in DAVID. PPI network constructed using STRING and visualized with Cytoscape app with the help of MCODE. The top ten connectivity genes were selected as hub genes—further survival analysis was performed in the Kaplan-Meier plotter. Moreover, Boxplot, pathological stage plots were constructed using GEPIA (Gene Expression Profiling Interactive Analysis). The methylation heatmap assembled in the DiseaseMeth version 2.0. lncRNA (Long non-coding RNA) was identified comparing the list of genes in HUGO, and Gene-drug interactions were accumulated from the DgiDB platform.

Results

This experiment showed 16 upregulated, and 59 downregulated DEGs shared among the three datasets. Biological process analysis showed significant terms such as extracellular matrix disassembly and collagen catabolism. The extracellular region was detected as the most crucial cellular compartment. Notably, metalloen dopeptidease and serine-type endopeptidase activity showed significant molecular functions term. In contrast, transcriptional misregulation was a highly substantial KEGG pathway. Kaplan-Meier plotter showed higher expression of CXCL8, SPP1, MMP13, CXCL1, and TOP2A have a significant impact on the overall survival of the patients. Nine out of ten hub genes have significantly different expression levels than normal and cancer tissues. HYMAI was the only lncRNA commonly expressed upregulated among the three datasets. Drug-gene interaction showed multiple genes have no drug options exist till now.

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GSE161533, GSE20347, and GSE45670 microarray datasets were analyzed.

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16 upregulated and 59 downregulated DEGs shared among the three datasets.

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CXCL8, SPP1, MMP13, CXCL1, and TOP2A have a significant impact on survival.

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HYMAI was the only lncRNA commonly expressed.

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Multiple genes have no drug options that exist.