iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is poised to revolutionize clinical care in the coming decade. However, there is a lack of effective and interpretable genome-wide modeling methods for the rational selection of patients for personalized interventions. To address this, we present iGenSig-Rx, an integral genomic signature-based approach, as a transparent tool for modeling therapeutic response using clinical trial datasets. This method adeptly addresses challenges related to cross-dataset modeling by capitalizing on high-dimensional redundant genomic features, analogous to reinforcing building pillars with redundant steel rods. Moreover, it integrates adaptive penalization of feature redundancy on a per-sample basis to prevent score flattening and mitigate overfitting. We then developed a purpose-built R package to implement this method for modeling clinical trial datasets. When applied to genomic datasets for HER2 targeted therapies, iGenSig-Rx model demonstrates consistent and reliable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We anticipate that iGenSig-Rx, as an interpretable class of multi-omics modeling methods, will find broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx .

IndepthPathway: an integrated tool for in-depth pathway enrichment analysis based on single-cell sequencing data.

MOTIVATION: Single-cell sequencing enables exploring the pathways and processes of cells, and cell populations. However, there is a paucity of pathway enrichment methods designed to tolerate the high noise and low gene coverage of this technology. When gene expression data are noisy and signals are sparse, testing pathway enrichment based on the genes expression may not yield statistically significant results, which is particularly problematic when detecting the pathways enriched in less abundant cells that are vulnerable to disturbances. RESULTS: In this project, we developed a Weighted Concept Signature Enrichment Analysis specialized for pathway enrichment analysis from single-cell transcriptomics (scRNA-seq). Weighted Concept Signature Enrichment Analysis took a broader approach for assessing the functional relations of pathway gene sets to differentially expressed genes, and leverage the cumulative signature of molecular concepts characteristic of the highly differentially expressed genes, which we termed as the universal concept signature, to tolerate the high noise and low coverage of this technology. We then incorporated Weighted Concept Signature Enrichment Analysis into an R package called "IndepthPathway" for biologists to broadly leverage this method for pathway analysis based on bulk and single-cell sequencing data. Through simulating technical variability and dropouts in gene expression characteristic of scRNA-seq as well as benchmarking on a real dataset of matched single-cell and bulk RNAseq data, we demonstrate that IndepthPathway presents outstanding stability and depth in pathway enrichment results under stochasticity of the data, thus will substantially improve the scientific rigor of the pathway analysis for single-cell sequencing data. AVAILABILITY AND IMPLEMENTATION: The IndepthPathway R package is available through: https://github.com/wangxlab/IndepthPathway.

AHNAK2 Regulates NF-κB/MMP-9 Signaling to Promote Pancreatic Cancer Progression.

Early metastasis of pancreatic cancer (PaC) is a major cause of its high mortality rate. Previous studies have shown that AHNAK2 is involved in the progression of some tumors and is predicted to be an independent prognostic factor for PaC; however, the specific mechanisms through which AHNAK2 regulates PaC remain unclear. In this study, we examined the role of AHNAK2 in PaC and its potential molecular mechanisms. AHNAK2 mRNA and protein expression in PaC tissues and cells were measured using qRT-PCR and western blot analysis. After AHNAK2 knockdown using small interfering RNA, PaC cells were subjected to CCK-8 scratch, and Transwell assays to assess cell proliferation, migration, and invasion, respectively. Furthermore, the validation of the mechanistic pathway was achieved by western blot analysis. AHNAK2 mRNA and protein levels were up-regulated in PaC and silencing AHNAK2 significantly inhibited the proliferation, migration, and invasion of PaC cells. Mechanistically, AHNAK2 knockdown decreased the expression of phosphorylated p65, phosphorylated IκBα, and matrix metalloproteinase-9 (MMP-9), suggesting that activation of the NF-κB/MMP-9 signaling pathway was inhibited. Importantly, activation of NF-κB reversed the effects of AHNAK2 knockdown. Our findings indicate that AHNAK2 promotes PaC progression through the NF-kB/MMP-9 pathway and provides a theoretical basis for targeting AHNAK2 for the treatment of PaC.

Landscape analysis of adjacent gene rearrangements reveals BCL2L14-ETV6 gene fusions in more aggressive triple-negative breast cancer.

Triple-negative breast cancer (TNBC) accounts for 10 to 20% of breast cancer, with chemotherapy as its mainstay of treatment due to lack of well-defined targets, and recent genomic sequencing studies have revealed a paucity of TNBC-specific mutations. Recurrent gene fusions comprise a class of viable genetic targets in solid tumors; however, their role in breast cancer remains underappreciated due to the complexity of genomic rearrangements in this cancer. Our interrogation of the whole-genome sequencing data for 215 breast tumors catalogued 99 recurrent gene fusions, 57% of which are cryptic adjacent gene rearrangements (AGRs). The most frequent AGRs, BCL2L14-ETV6, TTC6-MIPOL1, ESR1-CCDC170, and AKAP8-BRD4, were preferentially found in the more aggressive forms of breast cancers that lack well-defined genetic targets. Among these, BCL2L14-ETV6 was exclusively detected in TNBC, and interrogation of four independent patient cohorts detected BCL2L14-ETV6 in 4.4 to 12.2% of TNBC tumors. Interestingly, these fusion-positive tumors exhibit more aggressive histopathological features, such as gross necrosis and high tumor grade. Amid TNBC subtypes, BCL2L14-ETV6 is most frequently detected in the mesenchymal entity, accounting for ∼19% of these tumors. Ectopic expression of BCL2L14-ETV6 fusions induce distinct expression changes from wild-type ETV6 and enhance cell motility and invasiveness of TNBC and benign breast epithelial cells. Furthermore, BCL2L14-ETV6 fusions prime partial epithelial-mesenchymal transition and endow resistance to paclitaxel treatment. Together, these data reveal AGRs as a class of underexplored genetic aberrations that could be pathological in breast cancer, and identify BCL2L14-ETV6 as a recurrent gene fusion in more aggressive form of TNBC tumors.

Fusion-associated carcinomas of the breast: Diagnostic, prognostic, and therapeutic significance.

Recurrent gene fusions comprise a class of viable genetic targets in solid tumors that have culminated several recent breakthrough cancer therapies. Their role in breast cancer, however, remains largely underappreciated due to the complexity of genomic rearrangements in breast malignancy. Just recently, we and others have identified several recurrent gene fusions in breast cancer with important clinical and biological implications. Examples of the most significant recurrent gene fusions to date include (1) ESR1::CCDC170 gene fusions in luminal B and endocrine-resistant breast cancer that exert oncogenic function via modulating the HER2/HER3/SRC Proto-Oncogene (SRC) complex, (2) ESR1 exon 6 fusions in metastatic disease that drive estrogen-independent estrogen-receptor transcriptional activity, (3) BCL2L14::ETV6 fusions in a more aggressive form of the triple-negative subtype that prime epithelial-mesenchymal transition and endow paclitaxel resistance, (4) the ETV6::NTRK3 fusion in secretory breast carcinoma that constitutively activates NTRK3 kinase, (5) the oncogenic MYB-NFIB fusion as a genetic driver underpinning adenoid cystic carcinomas of the breast that activates MYB Proto-Oncogene (MYB) pathway, and (6) the NOTCH/microtubule-associated serine-threonine (MAST) kinase gene fusions that activate NOTCH and MAST signaling. Importantly, these fusions are enriched in more aggressive and lethal breast cancer presentations and appear to confer therapeutic resistance. Thus, these gene fusions could be utilized as genetic biomarkers to identify patients who require more intensive treatment and surveillance. In addition, kinase fusions are currently being evaluated in breast cancer clinical trials and ongoing mechanistic investigation is exposing therapeutic vulnerabilities in patients with fusion-positive disease.

Universal concept signature analysis: genome-wide quantification of new biological and pathological functions of genes and pathways.

Identifying new gene functions and pathways underlying diseases and biological processes are major challenges in genomics research. Particularly, most methods for interpreting the pathways characteristic of an experimental gene list defined by genomic data are limited by their dependence on assessing the overlapping genes or their interactome topology, which cannot account for the variety of functional relations. This is particularly problematic for pathway discovery from single-cell genomics with low gene coverage or interpreting complex pathway changes such as during change of cell states. Here, we exploited the comprehensive sets of molecular concepts that combine ontologies, pathways, interactions and domains to help inform the functional relations. We first developed a universal concept signature (uniConSig) analysis for genome-wide quantification of new gene functions underlying biological or pathological processes based on the signature molecular concepts computed from known functional gene lists. We then further developed a novel concept signature enrichment analysis (CSEA) for deep functional assessment of the pathways enriched in an experimental gene list. This method is grounded on the framework of shared concept signatures between gene sets at multiple functional levels, thus overcoming the limitations of the current methods. Through meta-analysis of transcriptomic data sets of cancer cell line models and single hematopoietic stem cells, we demonstrate the broad applications of CSEA on pathway discovery from gene expression and single-cell transcriptomic data sets for genetic perturbations and change of cell states, which complements the current modalities. The R modules for uniConSig analysis and CSEA are available through https://github.com/wangxlab/uniConSig.

Artificial neural networks modeling for lead removal from aqueous solutions using iron oxide nanocomposites from bio-waste mass.

Heavy metal ions in aqueous solutions are taken into account as one of the most harmful environmental issues that ominously affect human health. Pb(II) is a common pollutant among heavy metals found in industrial wastewater, and various methods were developed to remove the Pb(II). The adsorption method was more efficient, cheap, and eco-friendly to remove the Pb(II) from aqueous solutions. The removal efficiency depends on the process parameters (initial concentration, the adsorbent dosage of T-Fe3O4 nanocomposites, residence time, and adsorbent pH). The relationship between the process parameters and output is non-linear and complex. The purpose of the present study is to develop an artificial neural networks (ANN) model to estimate and analyze the relationship between Pb(II) removal and adsorption process parameters. The model was trained with the backpropagation algorithm. The model was validated with the unseen datasets. The correlation coefficient adj.R2 values for total datasets is 0.991. The relationship between the parameters and Pb(II) removal was analyzed by sensitivity analysis and creating a virtual adsorption process. The study determined that the ANN modeling was a reliable tool for predicting and optimizing adsorption process parameters for maximum lead removal from aqueous solutions.

Therapeutic role of recurrent ESR1-CCDC170 gene fusions in breast cancer endocrine resistance.

BACKGROUND: Endocrine therapy is the most common treatment for estrogen receptor (ER)-positive breast cancer, but its effectiveness is limited by high rates of primary and acquired resistance. There are likely many genetic causes, and recent studies suggest the important role of ESR1 mutations and fusions in endocrine resistance. Previously, we reported a recurrent ESR1 fusion called ESR1-CCDC170 in 6-8% of the luminal B breast cancers that has a worse clinical outcome after endocrine therapy. Despite being the most frequent ESR1 fusion, its functional role in endocrine resistance has not been studied in vivo, and the engaged mechanism and therapeutic relevance remain uncharacterized. METHODS: The endocrine sensitivities of HCC1428 or T47D breast cancer cells following genetic perturbations of ESR1-CCDC170 were assessed using clonogenic assays and/or xenograft mouse models. The underlying mechanisms were investigated by reverse phase protein array, western blotting, immunoprecipitation, and bimolecular fluorescence complementation assays. The sensitivity of ESR1-CCDC170 expressing breast cancer cells to concomitant treatments of tamoxifen and HER/SRC inhibitors was assessed by clonogenic assays. RESULTS: Our results suggested that different ESR1-CCDC170 fusions endow different levels of reduced endocrine sensitivity in vivo, resulting in significant survival disadvantages. Further investigation revealed a novel mechanism that ESR1-CCDC170 binds to HER2/HER3/SRC and activates SRC/PI3K/AKT signaling. Silencing of ESR1-CCDC170 in the fusion-positive cell line, HCC1428, downregulates HER2/HER3, represses pSRC/pAKT, and improves endocrine sensitivity. More important, breast cancer cells expressing ectopic or endogenous ESR1-CCDC170 are highly sensitive to treatment regimens combining endocrine agents with the HER2 inhibitor lapatinib and/or the SRC inhibitor dasatinib. CONCLUSION: ESR1-CCDC170 may endow breast cancer cell survival under endocrine therapy via maintaining/activating HER2/HER3/SRC/AKT signaling which implies a potential therapeutic strategy for managing these fusion positive tumors.

Therapeutic potential of aryl hydrocarbon receptor in autoimmunity.

Aryl hydrocarbon receptor (AhR), a type of transcriptional factor, is widely expressed in immune cells. The activation of AhR signaling pathway depends on its ligands, which exist in environment and can also be produced by metabolism. Normal expressions of AhR and AhR-mediated signaling may be essential for immune responses, and effects of AhR signaling on the development and function of innate and adaptive immune cells have also been revealed in previous studies. Recent studies also indicate that aberrant AhR signaling may be related to autoimmune diseases, including rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis (MS), autoimmune uveitis (AU), autoimmune diabetes, Behcet's disease (BD) and myasthenia gravis (MG). Moreover, administration of AhR ligands or drugs has been proven effective for improving pathological outcomes in some autoimmune diseases or models. In this review, we summarize the effects of AhR on several innate and adaptive immune cells associated with autoimmunity, and the mechanism on how AhR participates in autoimmune diseases. In addition, we also discuss therapeutic potential and application prospect of AhR in autoimmune diseases, so as to provide valuable information for exploring novel and effective approaches to autoimmune disease treatments.

Is there an incremental value to use myocardial perfusion imaging with or without CT attenuation for the diagnosis of coronary artery disease? A study in Chinese patients.

OBJECTIVE: To evaluate whether computed tomography attention correction (CTAC) has incremental diagnostic value for single photon emission tomography (SPET) myocardial perfusion imaging (MPI) for the detection of coronary artery disease (CAD) in Chinese patients. SUBJECTS AND METHODS: This retrospective study consisted of 181 suspected CAD patients who underwent one-stop SPET examination by MPI combined with a CT scan. Two observers independently evaluated non-attenuation correction (NAC) and CTAC MPI images, and coronary angiography (CAG) results were used as reference standards. The diagnostic efficacies of the two methods were compared. RESULTS: a) In the whole group, the sensitivity, specificity and accuracy for the detection of CAD were found to be 75.7%, 55.1% and 63.5% for NAC images and 52.7%, 86.9% and 72.9% for CTAC images, respectively; the areas under the receiver operating characteristic curves (AUC) were 0.654 and 0.698 (P>0.05). b) The accuracy of CTAC and the AUC were significantly higher than those for NAC in Chinese males. c) The accuracy of CTAC was also significantly increased for the right coronary artery (RCA) territory and in overweight patients (BMI≥24), although differences in the AUC were marginally insignificant. CONCLUSION: Compared to NAC MPI, CTAC improved SPET MPI specificity but decreased sensitivity, leading to no obvious improvement in overall accuracy for the diagnosis of CAD in Chinese patients. However, CTAC might be of value in the subgroups of males and overweight patients and for the RCA territory. In routine clinical application, the integration of NAC and CTAC findings combined with CAD pre-test probability could improve MPI diagnostic performance.

Recurrent and pathological gene fusions in breast cancer: current advances in genomic discovery and clinical implications.

Gene fusions have long been considered principally as the oncogenic events of hematologic malignancies, but have recently gained wide attention in solid tumors due to several milestone discoveries and the advancement of deep sequencing technologies. With the progress in deep sequencing studies of breast cancer transcriptomes and genomes, the discovery of recurrent and pathological gene fusions in breast cancer is on the focus. Recently, driven by new deep sequencing studies, several recurrent or pathological gene fusions have been identified in breast cancer, including ESR1-CCDC170, SEC16A-NOTCH1, SEC22B-NOTCH2, and ESR1-YAP1 etc. More important, most of these gene fusions are preferentially identified in the more aggressive breast cancers, such as luminal B, basal-like, or endocrine-resistant breast cancer, suggesting recurrent gene fusions as additional key driver events in these tumors other than the known drivers such as the estrogen receptor. In this paper, we have comprehensively summarized the newly identified recurrent or pathological gene fusion events in breast cancer, reviewed the contributions of new genomic and deep sequencing technologies to new fusion discovery and the integrative bioinformatics tools to analyze these data, highlighted the biological relevance and clinical implications of these fusion discoveries, and discussed future directions of gene fusion research in breast cancer.

Arterial compression of nerve is the primary cause of trigeminal neuralgia.

Whether arterial or venous compression or arachnoid adhesions are primarily responsible for compression of the trigeminal nerve in patients with trigeminal neuralgia is unclear. The aim of this study was to determine the causes of trigeminal nerve compression in patients with trigeminal neuralgia. The surgical findings in patients with trigeminal neuralgia who were treated by micro vascular decompression were compared to those in patients with hemifacial spasm without any signs or symptoms of trigeminal neuralgia who were treated with microvascular decompression. The study included 99 patients with trigeminal neuralgia (median age, 57 years) and 101 patients with hemifacial spasm (median age, 47 years). There were significant differences between the groups in the relationship of artery to nerve (p < 0.001) and the presence of arachnoid adhesions (p < 0.001) but no significant difference in relationship of vein to nerve. After adjustment for age, gender, and other factors, patients with vein compression of nerve or with artery compression of nerve were more likely to have trigeminal neuralgia (OR = 5.21 and 42.54, p = 0.026 and p < 0.001, respectively). Patients with arachnoid adhesions were less likely to have trigeminal neuralgia (OR = 0.15, p = 0.038). Arterial compression of the trigeminal nerve is the primary cause of trigeminal neuralgia and therefore, decompression of veins need not be a priority when performing microvascular dissection in patients with trigeminal neuralgia.

Intragenic Rearrangement Burden Associates with Immune Cell Infiltration and Response to Immune Checkpoint Blockade in Cancer.

Immune checkpoint blockade (ICB) can induce durable cancer remission. However, only a small subset of patients gains benefits. While tumor mutation burden (TMB) differentiates responders from nonresponders in some cases, it is a weak predictor in tumor types with low mutation rates. Thus, there is an unmet need to discover a new class of genetic aberrations that predict ICB responses in these tumor types. Here, we report analyses of pan-cancer whole genomes which revealed that intragenic rearrangement (IGR) burden is significantly associated with immune infiltration in breast, ovarian, esophageal, and endometrial cancers, particularly with increased M1 macrophage and CD8+ T-cell signatures. Multivariate regression against spatially counted tumor-infiltrating lymphocytes in breast, endometrial, and ovarian cancers suggested that IGR burden is a more influential covariate than other genetic aberrations in these cancers. In the MEDI4736 trial evaluating durvalumab in esophageal adenocarcinoma, IGR burden correlated with patient benefits. In the IMVigor210 trial evaluating atezolizumab in urothelial carcinoma, IGR burden increased with platinum exposure and predicted patient benefit among TMB-low, platinum-exposed tumors. Altogether, we have demonstrated that IGR burden correlates with T-cell inflammation and predicts ICB benefit in TMB-low, IGR-dominant tumors, and in platinum-exposed tumors.

Assessing the association between a sedentary lifestyle and prevalence of primary osteoporosis: a community-based cross-sectional study among Chinese population.

OBJECTIVES: To reveal the association between a sedentary lifestyle and the prevalence of primary osteoporosis (POP). DESIGN: A community-based cross-sectional study was conducted. SETTING: This study was conducted in communities in Hefei city, Anhui province, China. PARTICIPANTS: A total of 1346 residents aged 40 and above underwent POP screening via calcaneus ultrasound bone mineral density (BMD) testing and completed a questionnaire survey. OUTCOME MEASURES: The average daily sitting time was included in the study variable and used to assess sedentary behaviour. The 15 control variables included general information, dietary information and life behaviour information. Logistic regression was used to analyse the association between the POP prevalence and study or control variables in different models. RESULTS: 1346 participants were finally included in the study. According to the 15 control variables, the crude model and 4 models were established. The analysis revealed that the average daily sitting time showed a significant correlation with the prevalence of POP in the crude model (OR=2.02, 95% CI=1.74 to 2.36, p<0.001), Model 1 (OR=2.65, 95% CI=2.21 to 3.17, p<0.001), Model 2 (OR=2.63, 95% CI=2.19 to 3.15, p<0.001), Model 3 (OR=2.62, 95% CI=2.18 to 3.15, p<0.001) and Model 4 (OR=2.58, 95% CI=2.14 to 3.11, p<0.001). Besides, gender, age and body mass index showed a significant correlation with the POP prevalence in all models. CONCLUSIONS: This study suggests a potential association between a sedentary lifestyle and the prevalence of POP within the Chinese population. Modifying sedentary behaviours could contribute to a reduction in POP risk. However, longitudinal cohort studies are necessary to confirm this hypothesis in the future.

Surgical management of nervus intermedius neuralgia: A report of 4 cases and literature review.

BACKGROUND: Nervus intermedius neuralgia (NIN) is characterized by paroxysmal episodes of sharp, lancinating pain in the deep ear. Unfortunately, only a few studies exist in the literature on this pain syndrome, its pathology and postoperative outcomes. METHOD: We conducted a retrospective review of four cases diagnosed with NIN who underwent a neurosurgical intervention at our center from January 2015 to January 2023. Detailed information on their MRI examinations, intraoperative findings and other clinical presentations were obtained, and the glossopharyngeal and vagus nerves were isolated for immunohistochemistry examination. RESULTS: A total of 4 NIN patients who underwent a microsurgical intervention at our institution were included in this report. The NI was sectioned in all patients and 3 of them underwent a microvascular decompression. Of these 4 patients, 1 had a concomitant trigeminal neuralgia (TN), and 1 a concomitant glossopharyngeal neuralgia (GPN). Three patients underwent treatment for TN and 2 for GPN. Follow-up assessments ranged from 8 to 99 months. Three patients reported complete pain relief immediately after the surgery until last follow-up, while in the remaining patient the preoperative pain gradually resolved over the 3 month period. Immunohistochemistry revealed that a greater amount of CD4+ and CD8+ T cells had infiltrated the glossopharyngeal versus vagus nerve. CONCLUSIONS: NIN is an extremely rare condition showing a high degree of overlap with TN/GPN. An in depth neurosurgical intervention is effective to completely relieve NIN pain, without any serious complications. It appears that T cells may play regulatory role in the pathophysiology of CN neuralgia.

Meiotic protein SYCP2 confers resistance to DNA-damaging agents through R-loop-mediated DNA repair.

Drugs targeting the DNA damage response (DDR) are widely used in cancer therapy, but resistance to these drugs remains a major clinical challenge. Here, we show that SYCP2, a meiotic protein in the synaptonemal complex, is aberrantly and commonly expressed in breast and ovarian cancers and associated with broad resistance to DDR drugs. Mechanistically, SYCP2 enhances the repair of DNA double-strand breaks (DSBs) through transcription-coupled homologous recombination (TC-HR). SYCP2 promotes R-loop formation at DSBs and facilitates RAD51 recruitment independently of BRCA1. SYCP2 loss impairs RAD51 localization, reduces TC-HR, and renders tumors sensitive to PARP and topoisomerase I (TOP1) inhibitors. Furthermore, our studies of two clinical cohorts find that SYCP2 overexpression correlates with breast cancer resistance to antibody-conjugated TOP1 inhibitor and ovarian cancer resistance to platinum treatment. Collectively, our data suggest that SYCP2 confers cancer cell resistance to DNA-damaging agents by stimulating R-loop-mediated DSB repair, offering opportunities to improve DDR therapy.

Simulation-assisted self-assembly of multicomponent polymers into hierarchical assemblies with varied morphologies.

As you like it: The synthesis of supramolecular hierarchical nanostructures with designed morphologies has been realized through computer-simulation-guided multicomponent assembly of polypeptide-based block copolymers and homopolymers. By adjusting the attraction between hydrophobic polypeptide rods, as well as other parameters such as the molar ratio of copolymers and the rigidity of polymers, a variety of morphologies were obtained.

Giant myxofibrosarcoma of the esophagus treated by endoscopic submucosal dissection: A case report.

BACKGROUND: Myxofibrosarcoma (MFS) is a fibroblast-derived sarcoma that mainly occurs in subcutaneous tissue. MFS rarely occurs in the gastrointestinal tract, especially in the esophagus. CASE SUMMARY: A 79-year-old male patient was admitted to our hospital for dysphagia for a week. Computed tomography and electronic gastroscopy showed that a giant mass was located 30 cm from the incisor and extended to the cardia. There was incomplete esophageal stenosis. Endoscopic pathology showed spindle cell lesions, which were considered inflammatory myofibroblast like hyperplasia. Considering the strong demands of the patient and his family, and the fact that most inflammatory myofibroblast tumors are benign, we decided to perform endoscopic submucosal dissection (ESD) even if the tumor size was giant (9.0 cm × 3.0 cm). Postoperative pathological examination resulted in a final diagnosis of MFS. MFS rarely occurs in the gastrointestinal tract, especially in the esophagus. Surgical resection and local adjuvant radiotherapy are the first choices to improve the prognosis. This case report firstly described the ESD for esophageal giant MFS. It suggests that ESD may be an alternative treatment for primary esophageal MFS. CONCLUSION: This case report for the first time describe the successful treatment of a giant esophageal MFS by ESD, suggesting that ESD may be an alternative treatment for primary esophageal MFS, especially in elderly high-risk patients with obvious dysphagia symptoms.

iGenSig-Rx: an integral genomic signature based white-box tool for modeling cancer therapeutic responses using multi-omics data.

Multi-omics sequencing is expected to become clinically routine within the next decade and transform clinical care. However, there is a paucity of viable and interpretable genome-wide modeling methods that can facilitate rational selection of patients for tailored intervention. Here we develop an integral genomic signature-based method called iGenSig-Rx as a white-box tool for modeling therapeutic response based on clinical trial datasets with improved cross-dataset applicability and tolerance to sequencing bias. This method leverages high-dimensional redundant genomic features to address the challenges of cross-dataset modeling, a concept similar to the use of redundant steel rods to reinforce the pillars of a building. Using genomic datasets for HER2 targeted therapies, the iGenSig-Rx model demonstrates stable predictive power across four independent clinical trials. More importantly, the iGenSig-Rx model offers the level of transparency much needed for clinical application, allowing for clear explanations as to how the predictions are produced, how the features contribute to the prediction, and what are the key underlying pathways. We expect that iGenSig-Rx as a class of biologically interpretable multi-omics modeling methods will have broad applications in big-data based precision oncology. The R package is available: https://github.com/wangxlab/iGenSig-Rx. NOTE: the Github website will be released upon publication and the R package is available for review through google drive: https://drive.google.com/drive/folders/1KgecmUoon9-h2Dg1rPCyEGFPOp28Ols3?usp=sharing.

An integral genomic signature approach for tailored cancer therapy using genome-wide sequencing data.

Low-cost multi-omics sequencing is expected to become clinical routine and transform precision oncology. Viable computational methods that can facilitate tailored intervention while tolerating sequencing biases are in high demand. Here we propose a class of transparent and interpretable computational methods called integral genomic signature (iGenSig) analyses, that address the challenges of cross-dataset modeling through leveraging information redundancies within high-dimensional genomic features, averaging feature weights to prevent overweighing, and extracting unbiased genomic information from large tumor cohorts. Using genomic dataset of chemical perturbations, we develop a battery of iGenSig models for predicting cancer drug responses, and validate the models using independent cell-line and clinical datasets. The iGenSig models for five drugs demonstrate predictive values in six clinical studies, among which the Erlotinib and 5-FU models significantly predict therapeutic responses in three studies, offering clinically relevant insights into their inverse predictive signature pathways. Together, iGenSig provides a computational framework to facilitate tailored cancer therapy based on multi-omics data.