A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.

Despite a standardized diagnostic examination, cancer of unknown primary (CUP) is a rare metastatic malignancy with an unidentified tissue of origin (TOO). Patients diagnosed with CUP are typically treated with empiric chemotherapy, although their prognosis is worse than those with metastatic cancer of a known origin. TOO identification of CUP has been employed in precision medicine, and subsequent site-specific therapy is clinically helpful. For example, molecular profiling, including genomic profiling, gene expression profiling, epigenetics and proteins, has facilitated TOO identification. Moreover, machine learning has improved identification accuracy, and non-invasive methods, such as liquid biopsy and image omics, are gaining momentum. However, the heterogeneity in prediction accuracy, sample requirements and technical fundamentals among the various techniques is noteworthy. Accordingly, we systematically reviewed the development and limitations of novel TOO identification methods, compared their pros and cons and assessed their potential clinical usefulness. Our study may help patients shift from empirical to customized care and improve their prognoses.

Stem cell landscape aids in tumor microenvironment identification and selection of therapeutic agents in gastric cancer.

Gastric cancer stem cells (GCSCs) are strongly associated with the refractory characteristics of gastric cancer, including drug resistance, recurrence, and metastasis. The prognosis for advanced gastric cancer patients treated with multimodal therapy after surgery remains discouraging. GCSCs hold promise as therapeutic targets for GC patients. We obtained 26 sets of stem cell-related genes from the StemChecker database. The Consensus clustering algorithm was employed to discern three distinct stemness subtypes. Prognostic outcomes, components of the tumor microenvironment (TME), and responses to therapies were compared among these subtypes. Following this, a stemness-risk model was formulated using weighted gene correlation network analysis (WGCNA), alongside Cox regression and random survival forest analyses. The C2 subtype predominantly showed enrichment in negative prognostic CSC gene sets and demonstrated an immunosuppressive TME. This specific subtype exhibited minimal responsiveness to immunotherapies and demonstrated reduced sensitivity to drugs. Four pivotal genes were integrated into the construction of the stemness model. Gastric cancer patients with higher stemness-risk scores demonstrated poorer prognoses, a greater presence of immunosuppressive components in TME, and lower rates of treatment response. Subset analysis indicated that only the low-stemness risk subtype derives benefit from 5-fluorouracil-based adjuvant chemotherapy. The model's effectiveness in immunotherapeutic prediction was further validated in the PRJEB25780 cohort. Our study categorized gastric cancer patients into three stemness subtypes, each demonstrating distinct prognoses, components of TME infiltration, and varying sensitivity or resistance to standard chemotherapy or targeted therapy. We propose that the stemness risk model may help the development of well-grounded treatment recommendations and prognostic assessments.

The Memorial Sloan Kettering Prognostic Score: Correlation with survival in patients with advanced gastric cancer.

BACKGROUND: Notwithstanding that the past decade has witnessed unprecedented medical progress, gastric cancer (GC) remains a leading cause of cancer death, highlighting the need for effective prognostic markers. The Memorial Sloan Kettering Prognostic Score (MPS) has been validated as a valuable prognostic tool for patients with metastatic pancreatic adenocarcinoma (mPDAC). This study aimed to assess the prognostic value of the MPS in advanced GC. METHODS: Data from 367 patients were analyzed in the present study. The MPS for each patient was calculated based on the sum of scores based on the neutrophil-to-lymphocyte ratio and serum albumin levels. Multivariate analyses were performed to identify the independent clinicopathological parameters associated with overall survival (OS). Further subgroup analyses based on clinicopathological features were conducted. RESULTS: Patients with MPS 0 (n = 161), MPS 1 (n = 158), and MPS 2 (n = 48) exhibited significantly different OS, with a median survival duration of 20.7 (95%CI: 12.2-29.2), 14.9 (95%CI: 12.5-17.3), and 12.7 (95%CI: 9.3-16.0) months, respectively (p < 0.001). Significant differences in survival were observed among different groups of patients receiving chemotherapy (18.5 months vs. 14.7 months vs. 11.0 months, p = 0.03) or the subgroup receiving chemotherapy plus immunotherapy as first-line treatment (32.6 months vs. 17.7 months vs. 12.7 months, p = 0.02). The MPS was identified as an independent prognostic factor in multivariate analysis. During subgroup analyses, MPS-low (MPS 0) was consistently associated with a better prognosis than MPS-high (MPS 1 or 2). CONCLUSIONS: MPS is a practical, simple, and useful prognostic tool for patients with advanced GC. Further studies are warranted to validate its prognostic value in advanced GC.

Heterogeneity and Adjuvant Therapeutic Approaches in MSI-H/dMMR Resectable Gastric Cancer: Emerging Trends in Immunotherapy.

Gastric cancer (GC) remains one of the world's most common and fatal malignant tumors. With a refined understanding of molecular typing in recent years, microsatellite instability (MSI) has become a major molecular typing approach for gastric cancer. MSI is well recognized for its important role during the immunotherapy of advanced GC. However, its value remains unclear in resectable gastric cancer. The reported incidence of microsatellite instability-high (MSI-H)/deficient mismatch repair (dMMR) in resectable gastric cancer varies widely, with no consensus reached on the value of postoperative adjuvant therapy in patients with MSI-H/dMMR resectable GC. It has been established that MSI-H/dMMR tumor cells can elicit an endogenous immune antitumor response and ubiquitously express immune checkpoint ligands such as PD-1 or PD-L1. On the basis of these considerations, MSI-H/dMMR resectable GCs are responsive to adjuvant immunotherapy, although limited research has hitherto been conducted. In this review, we comprehensively describe the differences in geographic distribution and pathological stages in patients with MSI-H/dMMR with resectable gastric cancer and explore the value of adjuvant chemotherapy and immunotherapy on MSI-H/dMMR to provide a foothold for the individualized treatment of this patient population.

Proteomic profiling of gastric cancer with peritoneal metastasis identifies a protein signature associated with immune microenvironment and patient outcome.

BACKGROUND: Peritoneal metastasis (PM) frequently occurs in patients with gastric cancer (GC) and is a major cause of mortality. Risk stratification for PM can optimize decision making in GC treatment. METHODS: A total of 25 GC patients (13 with synchronous, 6 with metachronous PM and 6 PM-free) were included in this study. Quantitative proteomics by high-depth tandem mass tags labeling and whole-exome sequencing were conducted in primary GC and PM samples. Proteomic signature and prognostic model were established by machine learning algorithms in PM and PM-free GC, then validated in two external cohorts. Tumor-infiltrating immune cells in GC were analyzed by CIBERSORT. RESULTS: Heterogeneity between paired primary and PM samples was observed at both genomic and proteomic levels. Compared to primary GC, proteome of PM samples was enriched in RNA binding and extracellular exosomes. 641 differently expressed proteins (DEPs) between primary GC of PM group and PM-free group were screened, which were enriched in extracellular exosome and cell adhesion pathways. Subsequently, a ten-protein signature was derived based on DEPs by machine learning. This signature was significantly associated with patient prognosis in internal cohort and two external proteomic datasets of diffuse and mixed type GC. Tumor-infiltrating immune cell analysis showed that the signature was associated with immune microenvironment of GC. CONCLUSIONS: We characterized proteomic features that were informative for PM progression of GC. A protein signature associated with immune microenvironment and patient outcome was derived, and it could guide risk stratification and individualized treatment.

Combined fine-needle aspiration and selective intraoperative frozen section to optimize prediction of malignant thyroid nodules: A retrospective cohort study of more than 3000 patients.

Background: Preoperative fine-needle aspiration (FNA) is widely used to differentiate malignant from benign thyroid nodules, while intraoperative frozen sections (FS) are suggested as a systematic supplement for intraoperative decision-making, but limitations still remain for both procedures. Methods: Medical records of 3807 patients with thyroid nodules who underwent both pathological diagnoses (FS and FNA) at our hospital were reviewed. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FNA and FS were also evaluated. We further designed an optimal integration scheme (FNA+selective FS) to predict thyroid nodule malignancy. Finally, the efficiency of the proposed integrated diagnostic model was validated using an independent external cohort. Results: For distinguishing malignant nodules, FNA had an accuracy of 90.3%, sensitivity of 90.7%, specificity of 85.2%, PPV of 98.8% and NPV of 40.4%. In contrast, the FS represented higher discriminative power (Accuracy, 94.5%; Sensitivity, 94.1%; Specificity, 100%; PPV, 100%; and NPV, 55.6%). we proposed the selective usage of FS (removed nodules with Bethesda category VI from routine FS, ~1/3 of total). The integrated new diagnostic model of FNA plus selective FS (FNA+sFS) achieved accuracy of 96.9%, sensitivity of 97.3%, specificity of 92%, PPV of 99.4%, and NPV of 71.6% (NRI=0.135, 95% CI 0.103-0.167, P <0.001) and was successfully applied to an external cohort (N=554). Conclusion: Compared with the FNA diagnostic system, FS has an increased ability to distinguish benign and malignant thyroid nodules. The newly proposed integrated diagnostic model of FNA + selective FS can optimize the accuracy of diagnosis.

Insights into As accumulation in soil-groundwater-wheat-hair system of suburban farmland: Distribution, transfer and potential health risk.

Health risks caused by arsenic (As) contamination in soils and its migration in environmental media have attracted much attention. In this study, suburban farmland of KF city in the ecotone of the Yellow River and Huaihe River Basin was taken as the research area. A series of samples including topsoils (246), profile soils (280), matched wheat grains (22 groups), groundwater (26) and human hair (355) were collected. As distribution and transfer in soil-groundwater-wheat-hair (SGWH) system in typical sites were explored, and comprehensive health risk of As in SGWH system was assessed based on US EPA model and local exposure parameters. The results showed that spatial distribution of total As presented a significant high value area, and higher As contents (in the range of 0.45-29.86 mg kg-1) and bioavailability was mainly in topsoils, which indicated that anthropogenic sources have led to As enrichment in studied area. Also, it was found that the As contents in 95 % of wheat grain samples were higher than that in the control soils, and 9 % groundwater samples were above national Class I standards. Especially, average As content in hair in typical sites was obviously influenced by that in soil, wheat and groundwater. Moreover, As migration curve along soil → wheat (groundwater) → hair appeared an irregular 'V' shape, and transfer coefficients of Tf water/soil (10-5), Tf wheat/soil (10-3), Tf hair/soil (10-2), Tf hair/wheat (101) and Tf hair/water (104) presented an obvious increasing trend of magnitude, implying that human body has a higher As enrichment risk. Furthermore, comprehensive health risks for children and adults in typical sites were significant, while wheat is the main risk medium. In general, arsenic accumulation in human hair is good consistent with EPA health risk model, and their combination can better evaluate environmental exposure risk of As.

Patient-derived xenograft models for gastrointestinal tumors: A single-center retrospective study.

Background: Patient-derived xenograft (PDX) models have shown a great efficiency in preclinical and translational applications. Gastrointestinal (GI) tumors have a strong heterogeneity, and the engraftment rate of PDX models remarkably vary. However, the clinicopathological and molecular characteristics affecting the engraftment rate still remain elusive. Methods: A total of 312 fresh tumor tissue samples from patients with GI cancer were implanted into immunodeficient mice. The median follow-up time of patients was 37 months. Patients' characteristics were compared in terms of PDX growth and overall survival. PDX models of 3-6 generations were used for drug evaluation. Results: In total, 171 (54.8%, 171/312) PDX models were established, including 85 PDX models of colorectal cancer, 21 PDX models of esophageal cancer, and 65 PDX models of gastric cancer. Other than tumor site, histology, differentiation degree, and serum alpha-fetoprotein (AFP) level, no significant differences were found between transplantation of xenografts and patients' characteristics. For patients who had undergone neoadjuvant therapy, the incidence of tumor formation was higher in those with progressive disease (PD) or stable disease (SD). In gastric cancer, the results showed a higher transplantation rate in deficient mismatch repair (dMMR) tumors, and Ki-67 could be an important factor affecting the engraftment rate. The gene mutation status of RAS and BRAF, two important molecular markers in colorectal cancer, showed a high degree of consistency between patients' tumors and PDXs. However, no significant effects of these two mutations on PDX engraftment rate were observed. More importantly, in this study although KRAS mutations were detected in two clinical cases, evident tumor inhibition was still observed after cetuximab treatment in both PDX models and patients. Conclusion: A large-scale PDX model including 171 cases was successfully established for GI tumors in our center. The relationship between clinicopathological and molecular features and engraftment rates were clarified. Furthermore, this resource provides us with profound insights into tumor heterogeneity, making these models valuable for PDX-guided treatment decisions, and offering the PDX model as a great tool for personalized treatment and translation research.

Nomogram Based on Monocyte-to-Lymphocyte Ratio to Predict Survival of Unresectable Esophageal Squamous Cell Carcinoma Who Receive First-Line PD-1/PD-L1 Inhibitors Combined with Chemotherapy.

BACKGROUND: Chemoimmunotherapy has become the first-line treatment for unresectable esophageal squamous cell carcinoma (ESCC). Still, reliable biomarkers to identify patients who could benefit from this combined therapy remain uncertain. This study focused on elucidating the predictive significance of the monocyte-to-lymphocyte ratio (MLR) and establishing the prognostic nomogram for unresectable ESCC treated with chemoimmunotherapy. METHODS: Data of clinical features, peripheral blood parameters, and treatment records were collected in unresectable ESCC patients who received PD-1/PD-L1 inhibitors plus chemotherapy as the first-line treatment from September 2017 to August 2021. The nomogram based on MLR and clinical parameters for predicting the overall survival (OS) was developed and validated. RESULTS: Out of 81 patients enrolled, patients with a lower MLR had significantly longer progression-free survival (PFS) and OS than patients with a higher pretreatment MLR (p = 0.0067; p = 0.00069). The OS nomogram integrating MLR, performance status (PS) score, and body mass index (BMI) achieved a C-index of 0.770 (95%CI 0.645-0.896). The area under the ROC curve (AUC) value of the nomogram predicting 12-, 18-, and 24-month OS rates were 0.855, 0.792, and 0.744, respectively, which were higher than the clinical TNM staging system or the MLR. Stratified by the nomogram-generated scores, three risk groups (low, moderate, and high) in survival curves manifested a distinct difference (p < 0.0001). CONCLUSION: MLR emerged as an independent predictive factor for PFS and OS in treatment-naive unresectable ESCC patients treated with chemoimmunotherapy. The constructed nomogram of MLR and clinical parameters was a reliable model for prognostic estimation.

Association of inflammatory markers with survival in patients with advanced gastric cancer treated with immune checkpoint inhibitors combined with chemotherapy as first line treatment.

Background: The emergence of immune checkpoint inhibitors has changed the landscape of first-line treatment of patients with advanced gastric cancer. Currently, the prognostic significance of inflammatory markers in first-line immunotherapy combined with chemotherapy for gastric cancer is currently unclear. This study aimed to identify inflammatory markers with potential to predict treatment outcome in advanced gastric cancer patients receiving immunotherapy combined with chemotherapy. Methods: This retrospective study enrolled untreated advanced or metastatic gastric or gastro-esophageal junction cancer patients from 5 clinical trials (the clinical trial cohort) and the real world (the real-word cohort). Inflammatory markers included in the analysis included neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic inflammation index (SII), and derived neutrophil-to-lymphocyte ratio (dNLR). Receiver operating characteristic (ROC) curves were constructed to identify optimal cut-off values. The prognostic potential of the markers was determined using Kaplan-Meier analysis, univariate and multivariate Cox-regression analyses in the clinical trial cohort and the findings were validated in the real-world cohort. Results: In the clinical trial cohort (n=45), MLR, PLR and SII were associated with PFS but not OS (All P<0.05), while dNLR was not correlated with PFS or OS. Only NLR was associated with PFS and OS and identified as an independent prognostic predictor in the univariate and multivariate analyses. The prognostic value of NLR was validated in the real-world cohort (n=55). Conclusions: NLR was a strong predictor of PFS and OS in patients with advanced gastric cancer receiving immune checkpoint inhibitors combined with chemotherapy. Further prospective studies are required to validate our results.

Expression and Prognostic Value of Chromobox Family Proteins in Esophageal Cancer.

BACKGROUND: Esophageal cancer (EC) is one of the most common human malignant tumors worldwide. Chromobox (CBX) family proteins are significant components of epigenetic regulatory complexes. It is reported that CBXs play critical roles in the oncogenesis and development of various tumors. Nonetheless, their functions and specific roles in EC remain vague and obscure. METHODS AND MATERIALS: We used multiple bioinformatics tools, including Oncomine, Gene Expression Profiling Interactive Analysis 2 (GEPIA2), UALCAN, Kaplan-Meier plotter, cBioPortal, Metascape, TIMER2 and TISIDB, to investigate the expression profile, gene alterations and prognostic roles of CBX family proteins, as well as their association with clinicopathologic parameters, immune cells and immune regulators. In addition, RT-qPCR, Western blot, CCK8, colony formation, wound healing and transwell assays were performed to investigate the biological functions of CBX3 in EC cells. RESULTS: CBX3 and CBX5 were overexpressed in EC compared to normal tissues. Survival analysis revealed that high expression of CBX1 predicted worse disease-free survival (DFS) in EC patients. Functionally, CBXs might participate in mismatch repair, spliceosome, cell cycle, the Fanconi anemia pathway, tight junction, the mRNA surveillance pathway and the Hippo signaling pathway in EC development. Furthermore, CBXs were related to distinct immune cells infiltration and immune regulators. Additionally, depletion of CBX3 inhibited the proliferation, migration and invasion abilities of EC cells. CONCLUSIONS: Our study comprehensively investigated the expression pattern, prognostic value, and gene alterations of CBXs in EC, as well as their relationships with clinicopathologic variables, immune cells infiltration and immune regulators. These results suggested that CBX family proteins, especially CBX3, might be potential biomarkers in the progression of EC.

Long-term survival of gastric mixed neuroendocrine-non-neuroendocrine neoplasm: Two case reports.

BACKGROUND: Gastric mixed neuroendocrine-non-neuroendocrine neoplasm (MiNEN), which consists of neuroendocrine and non-neuroendocrine components, is quite rare. Until now, most data on gastric MiNEN come from clinical cases, without large-scale retrospective studies or controlled clinical trials. Consequently, no consensus regarding the origin, molecular characteristics, or appropriate treatment of MiNEN has been reached so far. We conducted chemotherapy of irinotecan plus cisplatin (IP regimen) and surgery in two patients with gastric MiNEN, which had never been used in treating this kind of tumor, leading to their long-term survival for more than 3 and 7 years, respectively. CASE SUMMARY: We present two patients (one male and one female) with gastric MiNEN, with the primary manifestation of recurrent upper abdominal pain. After they were referred to our hospital, a diagnosis of gastric MiNEN was defined with the help of CT scan, and histopathological and immunohistochemical examinations on the samples of gastrointestinal endoscopy or radical surgery. The male patient (case 1) were found to have metastases in the reginal lymph nodes and the left liver. He received four cycles of IP regimens first, then the gastrectomy and partial left liver resection, followed by additional two cycles of IP chemotherapy. The female patient (case 2) underwent a laparoscopic gastrectomy, and received six cycles of IP regimen. She was found to have metastatic lesions in the right lung 2 years after that, and underwent video-assisted thoracoscopic surgery (VATS) of the lower lobe of the right lung. The two patients have now survived for more than 3 years and 7 years, respectively, without any evidence of recurrence or metastases. CONCLUSION: IP regimen, combined with curative-intent surgery if feasible, could be considered as the priority in the choice of front-line chemotherapy for gastric MiNEN.

Integrative analysis reveals a clinicogenomic landscape associated with liver metastasis and poor prognosis in hepatoid adenocarcinoma of the stomach.

Hepatoid adenocarcinoma of the stomach (HAS) is a rare subtype of gastric cancer (GC) that histologically resembles hepatocellular carcinoma (HCC). Despite its low incidence, HAS had a poor 5-year survival rate. Currently, the linkages between clinicopathological and genomic features of HAS and its therapeutic targets remain largely unknown. Herein, we enrolled 90 HAS patients and 270 stage-matched non-HAS patients from our institution for comparing clinicopathological features. We found that HAS had worse overall survival and were more prone to develop liver metastasis than non-HAS in our cohort, which was validated via meta-analysis. By comparing whole-exome sequencing data of HAS (n=30), non-HAS (n=63), and HCC (n=355, The Cancer Genome Atlas), we identified a genomic landscape associated with unfavorable clinical features in HAS, which contained frequent somatic mutations and widespread copy number variations. Notably, signaling pathways regulating pluripotency of stem cells affected by frequent genomic alterations might contribute to liver metastasis and poor prognosis in HAS patients. Furthermore, HAS developed abundant multiclonal architecture associated with liver metastasis. Encouragingly, target analysis suggested that HAS patients might potentially benefit from anti-ERBB2 or anti-PD-1 therapy. Taken together, this study systematically demonstrated a high risk of liver metastasis and poor prognosis in HAS, provided a clinicogenomic landscape underlying these unfavorable clinical features, and identified potential therapeutic targets, laying the foundations for developing precise diagnosis and therapy in this rare but lethal disease.

Development of a Humanized VHH Based Recombinant Antibody Targeting Claudin 18.2 Positive Cancers.

Claudin 18.2 (CLDN18.2), a tight junction (TJ) family protein controlling molecule exchange between cells, is frequently over-expressed in gastric cancer, pancreatic adenocarcinomas and in a fraction of non-small cell lung cancer cases. The tumor properties indicate that CLDN18.2 could be an attractive drug target for gastric and pancreatic cancers. In this study, we present effective strategies for developing anti-CLDN18.2 therapeutic candidates, based on variable domain of heavy chain of heavy chain antibodies (VHHs). CLDN18.2-specific VHHs were isolated by panning a phage display library from an alpaca immunized with a stable cell line highly expressing CLDN18.2. Humanized VHHs fused with human IgG1 Fc, as potential therapeutic candidates, exhibited desirable binding specificity and affinity to CLDN18.2. In vitro experiments showed that hu7v3-Fc was capable of eliciting both antibody-dependent cellular cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC) on CLDN18.2 positive tumor cells. In the mouse xenograft model, the anti-tumor efficacy of hu7v3-Fc was significantly more potent than Zolbetuximab, the benchmark anti-CLDN18.2 monoclonal antibody. Moreover, in vivo biodistribution using zirconium-89 (89Zr) labeled antibodies demonstrated that hu7v3-Fc (89Zr-hu7v3-Fc) exhibited a better tumor penetration and a faster tumor uptake than Zolbetuximab (89Zr-Zolbetuximab), which might be attributed to its smaller size and higher affinity. Taken together, anti-CDLN18.2 hu7v3-Fc is a promising therapeutic agent for human CLDN18.2 positive cancers. Furthermore, hu7v3 has emerged as a potential module for novel CLDN18.2 related therapeutics.

Molecular Subgroups of Intrahepatic Cholangiocarcinoma Discovered by Single-Cell RNA Sequencing-Assisted Multiomics Analysis.

Intrahepatic cholangiocarcinoma (ICC) is a relatively rare but highly aggressive tumor type that responds poorly to chemotherapy and immunotherapy. Comprehensive molecular characterization of ICC is essential for the development of novel therapeutics. Here, we constructed two independent cohorts from two clinic centers. A comprehensive multiomics analysis of ICC via proteomic, whole-exome sequencing (WES), and single-cell RNA sequencing (scRNA-seq) was performed. Novel ICC tumor subtypes were derived in the training cohort (n = 110) using proteomic signatures and their associated activated pathways, which were further validated in a validation cohort (n = 41). Three molecular subtypes, chromatin remodeling, metabolism, and chronic inflammation, with distinct prognoses in ICC were identified. The chronic inflammation subtype was associated with a poor prognosis. Our random forest algorithm revealed that mutation of lysine methyltransferase 2D (KMT2D) frequently occurred in the metabolism subtype and was associated with lower inflammatory activity. scRNA-seq further identified an APOE+C1QB+ macrophage subtype, which showed the capacity to reshape the chronic inflammation subtype and contribute to a poor prognosis in ICC. Altogether, with single-cell transcriptome-assisted multiomics analysis, we identified novel molecular subtypes of ICC and validated APOE+C1QB+ tumor-associated macrophages as potential immunotherapy targets against ICC.

Preoperative Thyroid Peroxidase Antibody Predicts Recurrence in Papillary Thyroid Carcinoma: A Consecutive Study With 5,770 Cases.

Background: Thyroid autoimmunity is common in papillary thyroid carcinoma (PTC) and was believed to confer a better prognosis; however, controversy still remains. This study aimed to investigate the prognostic value of chronic lymphocytic thyroiditis (CLT) and preoperative thyroid peroxidase antibody (TPOAb) in PTC patients. Methods: A retrospective analysis was performed on 5,770 PTC patients who underwent surgical treatment with pathologically confirmed PTC in our institution between 2012 to 2016. The patients were divided into groups with respect to the coexistence of CLT or preoperative TPOAb levels. The clinicopathological characteristics and disease-free survival (DFS) rates were compared between the groups. Results: The coexistence of CLT was likely to have bilateral, multifocal tumors. Particularly, PTC patients with TPOAb++ (>1,000 IU/L) had a larger tumor size (p = 0.007) and higher rates of bilaterality and multifocality than those with TPOAb- (TPOAb< 100 IU/L), while for lymph node metastasis and extrathyroidal extension, there is no statistical difference. Tumor recurrence was found in 15 of 425 (3.5%), 9 of 436 (2.1%), and 56 of 3,519 (1.6%) patients with TPOAb++, TPOAb+, and TPOAb-, respectively (p = 0.017). On univariate analysis, TPOAb++ was correlated with tumor recurrence, with a hazard ratio of 2.20 [95% confidence interval (CI), 1.25-3.89], which remained as an independent risk factor at 1.98 (95% CI, 1.10-3.55) on multivariate analysis. PTC patients with TPOAb++ had the lowest DFS rates (96.5 vs. 97.9 vs. 98.4%, p = 0.020). Conclusion: CLT is not a protective factor in PTC patients. We provide initial evidence that the preoperative TPOAb instead predicts recurrence in papillary thyroid carcinoma.

EXOSC5 promotes proliferation of gastric cancer through regulating AKT/STAT3 signaling pathways.

Purpose: Exosome component 5 (EXOSC5) is a non-catalytic component of the RNA exosome complex, which is interacted with the Zinc-finger antiviral protein to degrade the target RNA and aberrantly expressed in various malignances. We explored the molecular mechanisms and biological roles by which EXOSC5 promotes the progression of GC. Methods: We used quantitative real-time PCR, Western blotting and immunohistochemistry to analyze EXOSC5 expression in GC samples. An GC organoid-based functional model was assessed, and cancer cell CCK-8 assay, colony formation assay and flow cytometry were performed to reveal the role of EXOSC5 in GC cell proliferation and tumorigenesis. In vivo, nude mice tumorigenesis assay were performed to explore the effects of EXOSC5 knockdown on growth of GC. The roles of EXOSC5 on AKT and STAT3 signaling pathways were measured by Western blot. Results: The expression of EXOSC5 was up-regulated in GC tissues and cell lines compared with normal group, and highly expressed EXOSC5 indicated a poorer clinical outcome for GC patients and was positively correlated with tumor size and TNM stage. EXOSC5 overexpression facilitated the growth of GC cells and organoids, while EXOSC5 downregulation inhibited proliferation and induced G1/S phase transition arrest. Moreover, mechanistic studies demonstrated that EXOSC5 increased cyclinD1 expression levels and decreasing the expression levels of p21 and p27 via regulation of the AKT and STAT3 pathway. Conclusion: The expression of EXOSC5 is upregulated and correlated with tumorigenesis and poor prognosis of GC. EXOSC5 increases GC proliferation partly through activating AKT and STAT3 pathways.

Identification of Tumor Mutation Burden, Microsatellite Instability, and Somatic Copy Number Alteration Derived Nine Gene Signatures to Predict Clinical Outcomes in STAD.

Genomic features, including tumor mutation burden (TMB), microsatellite instability (MSI), and somatic copy number alteration (SCNA), had been demonstrated to be involved with the tumor microenvironment (TME) and outcome of gastric cancer (GC). We obtained profiles of TMB, MSI, and SCNA by processing 405 GC data from The Cancer Genome Atlas (TCGA) and then conducted a comprehensive analysis though "iClusterPlus." A total of two subgroups were generated, with distinguished prognosis, somatic mutation burden, copy number changes, and immune landscape. We revealed that Cluster1 was marked by a better prognosis, accompanied by higher TMB, MSIsensor score, TMEscore, and lower SCNA burden. Based on these clusters, we screened 196 differentially expressed genes (DEGs), which were subsequently projected into univariate Cox survival analysis. We constructed a 9-gene immune risk score (IRS) model using LASSO-penalized logistic regression. Moreover, the prognostic prediction of IRS was verified by receiver operating characteristic (ROC) curve analysis and nomogram plot. Another independent Gene Expression Omnibus (GEO) contained specimens from 109 GC patients was designed as an external validation. Our works suggested that the 9-gene-signature prediction model, which was derived from TMB, MSI, and SCNA, was a promising predictive tool for clinical outcomes in GC patients. This novel methodology may help clinicians uncover the underlying mechanisms and guide future treatment strategies.

Combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions for quantitative source apportionment of heavy metals in suburban agricultural soils.

Quantitative identification of heavy metals (HM) sources in soils is key to prevention and control of heavy metal pollution. In this study, UNMIX, PMF (Positive matrix factorization) model and Pb-Zn-Cu isotopic compositions were combined to quantitatively identify heavy metal sources in a suburban agricultural area of Kaifeng, China. Using multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS) and ICP-MS, we measured Pb, Zn and Cu stable isotopic compositions, HM concentrations and HM chemical fractions in studied soils, as well as potential sources around the highly polluted site, including total suspended particle, compound fertilizer, irrigated river water and sediments. The results showed that total contents and chemical fractions of heavy metals, as well as Pb-Zn-Cu isotopic compositions presented great variation in different sites, which implied that heavy metal accumulation was obviously affected by local anthropogenic pollution source. UNMIX and PMF presented good agreement on source apportionment that industrial and agricultural activities (61.74% and 60.75% for UNMIX and PMF, respectively) were the major contributors to heavy metal accumulation in the study area. Especially, sewage irrigation and atmosphere deposition accounted for a large proportion (28.14% and 41.03% for UNMIX and PMF, respectively). Moreover, isotopic compositions of Pb, Zn and Cu in highly polluted soils and environment media gave further confirmation that sewage irrigation and atmosphere deposition were primary anthropogenic source. Therefore, combination of UNMIX, PMF model and Pb-Zn-Cu isotopic compositions showed good coordination in quantitative and specific source identification of heavy metals in agricultural soils.