The Evolving Genomic Landscape of Esophageal Squamous Cell Carcinoma Under Chemoradiotherapy

Classification and prediction of chemoradiotherapy response and survival from esophageal carcinoma histopathology images

Whole slide imaging (WSI) of Hematoxylin and Eosin-stained biopsy specimens has been used to predict chemoradiotherapy (CRT) response and overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients. This retrospective study collected 279 specimens in 89 non-surgical ESCC patients through endoscopic biopsy between January 2010 and January 2019. These patients were divided into a CRT response group (CR + PR group) and a CRT non-response group (SD + PD group). The WSIs have segmented approximately 1,206,000 non-overlapping patches. Two experienced pathologists manually delineated the eight types of tissues on 32 WSIs, including esophagus tumor cell (TUM), cancer-associated stroma (CAS), normal epithelium layer (NEL), smooth muscle (MUS), lymphocytes (LYM), Red cells (RED), debris (DEB), uneven areas (UNE). The chemoradiotherapy response prediction models were built using maximum relevance-minimum redundancy (MRMR) feature selection and least absolute shrinkage and selection operator (LASSO) regression. However, pathological features with p < 0.1 were selected and integrated to be further screened using a LASSO Cox regression model to build a multivariate Cox proportional hazards model for predicting the OS. The testing accuracy of the tissue classification model was 91.3 %. The pathological model created using two CAS in-depth features and eight TUM in-depth features performed best for the prediction of treatment response and achieved an AUC of 0.744. For the prediction of OS, the testing AUC of this model at one year and three years were 0.675 and 0.870, respectively. The TUM model showed the highest AUC at one year (0.712). With its high accuracy rate, the deep learning model has the potential to transform from bench to bedside in clinical practice, improve patient's quality of life, and prolong the OS rate.

Targeting leucine-rich PPR motif-containing protein/LRPPRC by 5,7,4'-trimethoxyflavone suppresses esophageal squamous cell carcinoma progression

JAK2/STAT3/MYC axis is dysregulated in nearly 70 % of human cancers, but targeting this pathway therapeutically remains a big challenge in cancer therapy. In this study, genes associated with JAK2, STAT3, and MYC were analyzed, and potential target genes were selected. Leucine-rich PPR motif-containing protein (LRPPRC) whose function and regulation are not fully understood, emerged as one of top 3 genes in terms of RNA epigenetic modification. Here, we demonstrate LRPPRC may be an independent prognostic indicator besides JAK2, STAT3, and MYC. Mechanistically, LRPPRC impairs N6-methyladenosine (m6A) modification of JAK2, STAT3, and MYC to facilitate nuclear mRNA export and expression. Meanwhile, excess LRPPRC act as a scaffold protein binding to JAK2 and STAT3 to enhance stability of JAK2-STAT3 complex, thereby facilitating JAK2/STAT3/MYC axis activation to promote esophageal squamous cell carcinoma (ESCC) progression. Furthermore, 5,7,4'-trimethoxyflavone was verified to bind to LRPPRC, STAT3, and CDK1, dissociating LRPPRC-JAK2-STAT3 and JAK2-STAT3-CDK1 interaction, leading to impaired tumorigenesis in 4-Nitroquinoline N-oxide induced ESCC mouse models and suppressed tumor growth in ESCC patient derived xenograft mouse models. In summary, this study suggests regulation of m6A modification by LRPPRC, and identifies a novel triplex target compound, suggesting that targeting LRPPRC-mediated JAK2/STAT3/MYC axis may overcome JAK2/STAT3/MYC dependent tumor therapeutic dilemma.

Genetically guided precision medicine clinical decision support tools: a systematic review

OBJECTIVES

Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM).

MATERIALS AND METHODS

A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients.

RESULTS

The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy.

DISCUSSION

Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes.

CONCLUSION

We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.

LINC00963 Promotes Cisplatin Resistance in Esophageal Squamous Cell Carcinoma by Interacting with miR-10a to Upregulate SKA1 Expression

Long non-coding RNA (lncRNA) is associated with a large number of tumor cellular functions together with chemotherapy resistance in a variety of tumors. LINC00963 was identified to regulate the malignant progression of various cancers. However, whether LINC00963 affects drug resistence in esophageal squamous cell carcinoma (ESCC) and the relevant molecular mechanisms have never been reported. This study aims to investigate the effect of LINC00963 on cisplatin resistance in ESCC. After detecting the level of LINC00963 in human esophageal squamous epithelial cells (HET-1 A), ESCC cells (TE-1) and cisplatin resistant cells of ESCC (TE-1/DDP), TE-1/DDP cell line and nude mouse model that interfered with LINC00963 expression were established. Then, the interaction among LINC00963, miR-10a, and SKA1 was clarified by double luciferase and RNA immunoprecipitation (RIP) assays. Meanwhile, the biological behavior changes of TE-1/DDP cells with miR-10a overexpression or SKA1 silencing were observed by CCK-8, flow cytometry, scratch, Transwell, and colony formation tests. Finally, the biological function of the LINC00963/SKA1 axis was elucidated by rescue experiments. LINC00963 was upregulated in TE-1 and TE-1/DDP cell lines. LINC00963 knockdown inhibited SKA1 expression of both cells and impaired tumorigenicity. Moreover, LINC00963 has a target relationship with miR-10a, and SKA1 is a target gene of miR-10a. MiR-10a overexpression or SKA1 silencing decreased the biological activity of TE-1/DDP cells and the expression of SKA1. Furthermore, SKA1 overexpression reverses the promoting effect of LINC00963 on cisplatin resistance of ESCC. LINC00963 regulates TE-1/DDP cells bioactivity and mediates cisplatin resistance through interacting with miR-10a and upregulating SKA1 expression.

Unraveling Emerging Anal Cancer Clinical Biomarkers from Current Immuno-Oncogenomics Advances

Anal squamous cell carcinoma (ASCC) is a rare gastrointestinal malignancy associated with high-risk human papillomavirus (HPV) and is currently one of the fastest-growing causes of cancer incidence and mortality in developed countries. Although next-generation sequencing technologies (NGS) have revolutionized cancer and immuno-genomic research in various tumor types, a limited amount of clinical research has been developed to investigate the expression and the functional characterization of genomic data in ASCC. Herein, we comprehensively assess recent advancements in "omics" research, including a systematic analysis of genome-based studies, aiming to identify the most relevant ASCC cancer driver gene expressions and their associated signaling pathways. We also highlight the most significant biomarkers associated with anal cancer progression, gene expression of potential diagnostic biomarkers, expression of therapeutic drug targets, and emerging treatment opportunities. This review stresses the urgent need for developing target-specific therapies in ASCC. By illuminating the molecular characteristics and drug-target expression in ASCC, this study aims to provide insights for the development of precision medicine in anal cancer.

A novel pipeline for prioritizing cancer type-specific therapeutic vulnerabilities using DepMap identifies PAK2 as a target in head and neck squamous cell carcinomas

There is limited guidance on exploiting the genome-wide loss-of-function CRISPR screens in cancer Dependency Map (DepMap) to identify new targets for individual cancer types. This study integrated multiple tools to filter these data in order to seek new therapeutic targets specific to head and neck squamous cell carcinoma (HNSCC). The resulting pipeline prioritized 143 targetable dependencies that represented both well-studied targets and emerging target classes like mitochondrial carriers and RNA-binding proteins. In total, 14 targets had clinical inhibitors used for other cancers or nonmalignant diseases that hold near-term potential to repurpose for HNSCC therapy. Comparing inhibitor response data that were publicly available for 13 prioritized targets between the cell lines with high vs. low dependency on each target uncovered novel therapeutic potential for the PAK2 serine/threonine kinase. PAK2 gene dependency was found to be associated with wild-type p53, low PAK2 mRNA, and diploid status of the 3q amplicon containing PAK2. These findings establish a generalizable pipeline to prioritize clinically relevant targets for individual cancer types using DepMap. Its application to HNSCC highlights novel relevance for PAK2 inhibition and identifies biomarkers of PAK2 inhibitor response.

Genomic and Transcriptomic Remodeling by Neoadjuvant Chemoradiotherapy (nCRT) and the Indicative Role of Acquired INDEL Percentage for nCRT Efficacy in Esophageal Squamous Cell Carcinoma

PURPOSE

The effect of genomic factors on the response of patients with esophageal squamous cell carcinoma (ESCC) to neoadjuvant chemoradiotherapy (nCRT), as well as how nCRT influences the genome and transcriptome of ESCC, remain largely unknown.

METHODS AND MATERIALS

In total, 137 samples from 57 patients with ESCC undergoing nCRT were collected and subjected to whole-exome sequencing and RNA sequencing analysis. Genetic and clinicopathologic factors were compared between the patients achieving pathologic complete response and patients not achieving pathologic complete response. Genomic and transcriptomic profiles before and after nCRT were analyzed.

RESULTS

Codeficiency of the DNA damage repair and HIPPO pathways synergistically sensitized ESCC to nCRT. nCRT induced small INDELs and focal chromosomal loss concurrently. Acquired INDEL% exhibited a decreasing trend with the increase of tumor regression grade (P = .06, Jonckheere's test). Multivariable Cox analysis indicated that higher acquired INDEL% was associated with better survival (adjusted hazard ratio [aHR], 0.93; 95% CI, 0.86-1.01; P = .067 for recurrence-free survival [RFS]; aHR, 0.86; 95% CI, 0.76-0.98; P = .028 for overall survival [OS], with 1% of acquired INDEL% as unit). The prognostic value of acquired INDEL% was confirmed by the Glioma Longitudinal AnalySiS data set (aHR, 0.95; 95% CI, 0.902-0.997; P = .037 for RFS; aHR, 0.96; 95% CI, 0.917-1.004; P = .076 for OS). Additionally, clonal expansion degree was negatively associated with patient survival (aHR, 5.87; 95% CI, 1.10-31.39; P = .038 for RFS; aHR, 9.09; 95% CI, 1.10-75.36; P = .041 for OS, with low clonal expression group as reference) and also negatively correlated with acquired INDEL% (Spearman ρ = -0.45; P = .02). The expression profile was changed after nCRT. The DNA replication gene set was downregulated, while the cell adhesion gene set was upregulated after nCRT. Acquired INDEL% was negatively correlated with the enrichment of the DNA replication gene set (Spearman ρ = -0.56; P = .003) but was positively correlated with the enrichment of the cell adhesion gene set (Spearman ρ = 0.40; P = .05) in posttreatment samples.

CONCLUSIONS

nCRT remodels the genome and transcriptome of ESCC. Acquired INDEL% is a potential biomarker to indicate the effectiveness of nCRT and radiation sensitivity.

Comprehensive analysis of cuproptosis genes and cuproptosis-related genes as prognosis factors in esophageal squamous cell carcinoma

Esophageal squamous cell carcinoma (ESCC) is a common invasive and pernicious cancer with a low five-year survival rate. To identify potential therapeutic targets, we first investigated the characteristics of cuproptosis genes (CUGs) in ESCC. The expression patterns of 10 CUGs (FDX1, LIPT1, LIAS, DLAT, DLD, PDHA1, PDHB, GLS, MTF1, and CDKN2A) were analyzed to identify ESCC-relevant targets. Weighted correlation network analysis (WGCNA) was performed to obtain CUG-related genes (CRGs). A total of seven differentially expressed genes were identified (FDX1, DLAT, LIAS, PDHB, MTF1, GLS, and CDKN2A). DLAT was upregulated in stage III, and LIPT1 was upregulated in N0 + N1 cancers. The high expression of CDKN2A, and PDHA1, was related to better overall survival, whereas the low expression of LIAS was related to better clinical outcomes. WGCNA was performed to get CUG-related genes (CRGs) and showed three key modules that related to FDX1, DLAT, and LIPT1. Moreover, CRGs (BTLA, CT47A1, and PRRX1) were selected to construct a risk score model in order to predict the survival and prognosis of patients with ESCC. Additionally, the cuproptosis score based on CUGs and a nomogram constructed based on it helped accurately predict the prognosis of patients with ESCC; thus, maybe it can be used for the clinical diagnosis of ESCC. The results also showed that milciclib might inhibit the proliferation and migration of KYSE150 and KYSE510 cells by targeting CDKN2A. In conclusion, the abovementioned CUGs and CRGs play a crucial role in tumorigenesis and cancer progression in ESCC, indicating their potential as therapeutic targets.

Combining Solid and Liquid Biopsy for Therapy Monitoring in Esophageal Cancer

Esophageal cancer (EC) has one of the highest mortality rates among cancers, making it imperative that therapies are optimized and dynamically adapted to individuals. In this regard, liquid biopsy is an increasingly important method for residual disease monitoring. However, conflicting detection rates (14% versus 60%) and varying cell-free circulating tumor DNA (ctDNA) levels (0.07% versus 0.5%) have been observed in previous studies. Here, we aim to resolve this discrepancy. For 19 EC patients, a complete set of cell-free DNA (cfDNA), formalin-fixed paraffin-embedded tumor tissue (TT) DNA and leukocyte DNA was sequenced (139 libraries). cfDNA was examined in biological duplicates and/or longitudinally, and TT DNA was examined in technical duplicates. In baseline cfDNA, mutations were detected in 12 out of 19 patients (63%); the median ctDNA level was 0.4%. Longitudinal ctDNA changes were consistent with clinical presentation. Considerable mutational diversity was observed in TT, with fewer mutations in cfDNA. The most recurrently mutated genes in TT were TP53, SMAD4, TSHZ3, and SETBP1, with SETBP1 being reported for the first time. ctDNA in blood can be used for therapy monitoring of EC patients. However, a combination of solid and liquid samples should be used to help guide individualized EC therapy.

M1A and m7G modification-related genes are potential biomarkers for survival prognosis and for deciphering the tumor immune microenvironment in esophageal squamous cell carcinoma

BACKGROUND

Esophageal squamous cell carcinoma (ESCC) is the most common esophageal malignancy, and RNA methylation has been reported to be involved in the tumorigenesis of ESCC. However, no study has explored methylation modifications in m¹A and m⁷G as prognostic markers for survival prediction in ESCC.

METHODS

Public gene-expression data and clinical annotation of 254 patients obtained from The Cancer Genome Atlas and the Gene Expression Omnibus databases were analyzed to identify potential consensus clusters of m¹A and m⁷G modification-related genes. The RNA-seq of 20 patients in Sun Yat-Sen University Cancer Center was used as the validation set. Following screening for relevant differentially expressed genes (DEGs) and enrichment pathways were elucidated. DEGs were used to construct risk models using the randomForest algorithm, and the prognostic role of the models was assessed by applying Kaplan-Meier analysis. Extent of immune cell infiltration, drug resistance, and response to cancer treatment among different clusters and risk groups were also evaluated.

RESULTS

Consensus clustering analysis based on m¹A and m⁷G modification patterns revealed three potential clusters. In total, 212 RNA methylation-related DEGs were identified. The methylation-associated signature consisting of 6 genes was then constructed to calculate methylation-related score (MRScore) and patients were dived into MRScore-high and MRScore-low groups. This signature has satisfied prognostic value for survival of ESCC (AUC = 0.66, 0.67, 0.64 for 2-, 3-, 4- year OS), and has satisfied performance in the validation SYSUCC cohort (AUC = 0.66 for 2- and 3-year OS). Significant correlation between m¹A and m⁷G modification-related genes and immune cell infiltration, and drug resistance was also observed.

CONCLUSIONS

Transcriptomic prognostic signatures based on m¹A and m⁷G modification-related genes are closely associated with immune cell infiltration in ESCC patients and have important correlations with the therapeutic sensitivity of multiple chemotherapeutic agents.

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer

Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed of tumor and stromal cellular components; at the genetic levels, they comprise genetically distinct tumor clones; at the phenotypic levels, cells in distinct microenvironmental niches acquire diverse phenotypic features. This heterogeneity affects almost every process of esophageal cancer progression from onset to metastases and recurrence, etc. Intertumoral and intratumoral heterogeneity are major obstacles in the treatment of esophageal cancer, but also offer the potential to manipulate the heterogeneity themselves as a new therapeutic strategy. The high-dimensional, multi-faceted characterization of genomics, epigenomics, transcriptomics, proteomics, metabonomics, etc. of esophageal cancer has opened novel horizons for dissecting tumor heterogeneity. Artificial intelligence especially machine learning and deep learning algorithms, are able to make decisive interpretations of data from multi-omics layers. To date, artificial intelligence has emerged as a promising computational tool for analyzing and dissecting esophageal patient-specific multi-omics data. This review provides a comprehensive review of tumor heterogeneity from a multi-omics perspective. Especially, we discuss the novel techniques single-cell sequencing and spatial transcriptomics, which have revolutionized our understanding of the cell compositions of esophageal cancer and allowed us to determine novel cell types. We focus on the latest advances in artificial intelligence in integrating multi-omics data of esophageal cancer. Artificial intelligence-based multi-omics data integration computational tools exert a key role in tumor heterogeneity assessment, which will potentially boost the development of precision oncology in esophageal cancer.

The Molecular Characterization of Genetic Abnormalities in Esophageal Squamous Cell Carcinoma May Foster the Development of Targeted Therapies

Esophageal cancer is among the most common tumors in the world and is associated with poor outcomes, with a 5-year survival rate of about 10-20%. Two main histological subtypes are observed: esophageal squamous cell carcinoma (ESCC), more frequent among Asian populations, and esophageal adenocarcinoma (EAC), the predominant type in Western populations. The development of molecular analysis techniques has led to the definition of the molecular alterations observed in ESCC, consistently differing from those observed in EAC. The genetic alterations observed are complex and heterogeneous and involve gene mutations, gene deletions and gene amplifications. However, despite the consistent progress in the definition of the molecular basis of ESCC, precision oncology for these patients is still virtually absent. The recent identification of molecular subtypes of ESCC with clinical relevance may foster the development of new therapeutic strategies. It is estimated that about 40% of the genetic alterations observed in ESCC are actionable. Furthermore, the recent introduction of solid tumor immunotherapy with immune checkpoint inhibitors (ICIs) showed that a minority of ESCC patients are responsive, and the administration of ICIs, in combination with standard chemotherapy, significantly improves overall survival over chemotherapy in ESCC patients with advanced disease.

Single-cell mapping of N6-methyladenosine in esophageal squamous cell carcinoma and exploration of the risk model for immune infiltration

BACKGROUND

N6-methyladenosine (m6A) modification is the most common RNA modification, but its potential role in the development of esophageal cancer and its specific mechanisms still need to be further investigated.

METHODS

Bulk RNA-seq of 174 patients with esophageal squamous carcinoma from the TCGA-ESCC cohort, GSE53625, and single-cell sequencing data from patients with esophageal squamous carcinoma from GSE188900 were included in this study. Single-cell analysis of scRNA-seq data from GSE188900 of 4 esophageal squamous carcinoma samples and calculation of PROGENy scores. Demonstrate the scoring of tumor-associated pathways for different cell populations. Cell Chat was calculated for cell populations. thereafter, m6A-related differential genes were sought and risk models were constructed to analyze the relevant biological functions and impact pathways of potential m6A genes and their impact on immune infiltration and tumor treatment sensitivity in ESCC was investigated.

RESULTS

By umap downscaling analysis, ESCC single-cell data were labelled into clusters of seven immune cell classes. Cellchat analysis showed that the network interactions of four signaling pathways, MIF, AFF, FN1 and CD99, all showed different cell type interactions. The prognostic risk model constructed by screening for m6A-related differential genes was of significant value in the prognostic stratification of ESCC patients and had a significant impact on immune infiltration and chemotherapy sensitivity in ESCC patients.

CONCLUSION

In our study, we explored a blueprint for the distribution of single cells in ESCC based on m6A methylation and constructed a risk model for immune infiltration analysis and tumor efficacy stratification in ESCC on this basis. This may provide important potential guidance for revealing the role of m6A in immune escape and treatment resistance in esophageal cancer.

Potent molecular-targeted therapies for advanced esophageal squamous cell carcinoma

Esophageal cancer (EC) remains a public health concern with a high mortality and disease burden worldwide. Esophageal squamous cell carcinoma (ESCC) is a predominant histological subtype of EC that has unique etiology, molecular profiles, and clinicopathological features. Although systemic chemotherapy, including cytotoxic agents and immune checkpoint inhibitors, is the main therapeutic option for recurrent or metastatic ESCC patients, the clinical benefits are limited with poor prognosis. Personalized molecular-targeted therapies have been hampered due to the lack of robust treatment efficacy in clinical trials. Therefore, there is an urgent need to develop effective therapeutic strategies. In this review, we summarize the molecular profiles of ESCC based on the findings of pivotal comprehensive molecular analyses, highlighting potent therapeutic targets for establishing future precision medicine for ESCC patients, with the most recent results of clinical trials.

Dysregulation of SOX17/NRF2 axis confers chemoradiotherapy resistance and emerges as a novel therapeutic target in esophageal squamous cell carcinoma

Background

Esophageal squamous cell carcinoma (ESCC) is the sixth leading cause of cancer-associated death worldwide with a dismal overall 5-year survival rate of less than 20%. The standard first-line therapy for advanced ESCC is concomitant chemo-radiation therapy (CCRT); however, patients usually develop resistance, resulting in unfavorable outcomes. Therefore, it is urgent to identify the mechanisms underlying CCRT resistance and develop effective treatment strategies.

Methods

Patients’ endoscopic biopsy tumor tissues obtained before CCRT treatment were used to perform RNA-seq and GSEA analysis. Immunohistochemical (IHC) staining, chromatin immunoprecipitation (ChIP), and promoter reporter analyses were conducted to investigate the relationship between SOX17 and NRF2. Xenograft mouse models were used to study the role of SOX17/NRF2 axis in tumor growth and the efficacy of carboxymethyl cellulose-coated zero-valent-iron (ZVI@CMC).

Results

In this study, a notable gene expression signature associated with NRF2 activation was observed in the poor CCRT responders. Further, IHC staining of endoscopic biopsy of 164 ESCC patients revealed an inverse correlation between NRF2 and SOX17, a tumor-suppressive transcription factor with low expression in ESCC due to promoter hypermethylation. Using ChIP and promoter reporter analyses, we demonstrated that SOX17 was a novel upstream transcriptional suppressor of NRF2. In particular, SOX17^low/NRF2^high nuclear level significantly correlated with poor CCRT response and poor survival, indicating that the dysregulation of SOX17/NRF2 axis played a pivotal role in CCRT resistance and tumor progression. Notably, the in-house developed nanoparticle ZVI@CMC functioned as an inhibitor of DNA methyltransferases to restore expression of SOX17 that downregulated NRF2, thereby overcoming the resistance in ESCC. Additionally, the combination of ZVI@CMC with radiation treatment significantly augmented anticancer efficacy to inhibit tumor growth in CCRT resistant cancer.

Conclusion

This study identifies a novel SOX17^low/NRF2^high signature in ESCC patients with poor prognosis, recognizes SOX17 as a transcriptional repressor of NRF2, and provides a promising strategy targeting SOX17/NRF2 axis to overcome resistance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12929-022-00873-4.