A novel risk classification system based on the eighth edition of TNM frameworks for esophageal adenocarcinoma patients: A deep learning approach.

Objective: To develop and validate a deep learning predictive model with better performance in survival estimation of esophageal adenocarcinoma (EAC). Method: Cases diagnosed between January 2010 and December 2018 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. A deep learning survival neural network was developed and validated based on 17 variables, including demographic information, clinicopathological characteristics, and treatment details. Based on the total risk score derived from this algorithm, a novel risk classification system was constructed and compared with the 8th edition of the tumor, node, and metastasis (TNM) staging system. Results: Of 7,764 EAC patients eligible for the study, 6,818 (87.8%) were men and the median (interquartile range, IQR) age was 65 (58-72) years. The deep learning model generated significantly superior predictions to the 8th edition staging system on the test data set (C-index: 0.773 [95% CI, 0.757-0.789] vs. 0.683 [95% CI, 0.667-0.699]; P < 0.001). Calibration curves revealed that the deep learning model was well calibrated for 1- and 3-year OS, most points almost directly distributing on the 45° line. Decision curve analyses (DCAs) showed that the novel risk classification system exhibited a more significant positive net benefit than the TNM staging system. A user-friendly and precise web-based calculator with a portably executable file was implemented to visualize the deep learning predictive model. Conclusion: A deep learning predictive model was developed and validated, which possesses more excellent calibration and discrimination abilities in survival prediction of EAC. The novel risk classification system based on the deep learning algorithm may serve as a useful tool in clinical decision making given its easy-to-use and better clinical applicability.

A newly defined basement membrane-related gene signature for the prognosis of clear-cell renal cell carcinoma.

Background: Basement membranes (BMs) are associated with cell polarity, differentiation, migration, and survival. Previous studies have shown that BMs play a key role in the progression of cancer, and thus could serve as potential targets for inhibiting the development of cancer. However, the association between basement membrane-related genes (BMRGs) and clear cell renal cell carcinoma (ccRCC) remains unclear. To address that gap, we constructed a novel risk signature utilizing BMRGs to explore the relationship between ccRCC and BMs. Methods: We gathered transcriptome and clinical data from The Cancer Genome Atlas (TCGA) and randomly separated the data into training and test sets to look for new potential biomarkers and create a predictive signature of BMRGs for ccRCC. We applied univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses to establish the model. The risk signature was further verified and evaluated through principal component analysis (PCA), the Kaplan-Meier technique, and time-dependent receiver operating characteristics (ROC). A nomogram was constructed to predict the overall survival (OS). The possible biological pathways were investigated through functional enrichment analysis. In this study, we also determined tumor mutation burden (TMB) and performed immunological analysis and immunotherapeutic drug analysis between the high- and low-risk groups. Results: We identified 33 differentially expressed genes and constructed a risk model of eight BMRGs, including COL4A4, FREM1, CSPG4, COL4A5, ITGB6, ADAMTS14, MMP17, and THBS4. The PCA analysis showed that the signature could distinguish the high- and low-risk groups well. The K-M and ROC analysis demonstrated that the model could predict the prognosis well from the areas under the curves (AUCs), which was 0.731. Moreover, the nomogram showed good predictability. Univariate and multivariate Cox regression analysis validated that the model results supported the hypothesis that BMRGs were independent risk factors for ccRCC. Furthermore, immune cell infiltration, immunological checkpoints, TMB, and the half-inhibitory concentration varied considerably between high- and low-risk groups. Conclusion: Employing eight BMRGs to construct a risk model as a prognostic indicator of ccRCC could provide us with a potential progression trajectory as well as predictions of therapeutic response.

Prognostic Nutritional Index Predicts Response and Prognosis in Cancer Patients Treated With Immune Checkpoint Inhibitors: A Systematic Review and Meta-Analysis.

Objective: To investigate the association between pretreatment prognostic nutritional index (PNI) and clinical survival outcomes for advanced-stage cancer patients treated with immune checkpoint inhibitors (ICIs). Methods: We conducted a comprehensive literature search to identify eligible studies concerning the relationship between pretreatment PNI and survival outcomes in advanced cancer patients treated with ICIs. Published data were extracted and pooled odds ratio (pOR) for objective response rate (ORR), disease control rate (DCR), and pooled hazard ratio (pHR) for overall survival (OS), progressive-free survival (PFS), along with 95% confidence intervals (95% CIs) were calculated. Results: Twelve studies with 1,359 participants were included in our study. A higher level of PNI indicated a greater ORR (pOR = 2.17, 95% CI = 1.52-3.10) and favorable DCR (pOR = 2.48, 95% CI = 1.87-3.29). Low PNI was associated with a shorter OS (pHR = 2.24, 95% CI = 1.57-3.20) and unfavorable PFS (pHR = 1.61, 95% CI = 1.37-1.88). Conclusion: Low PNI might be an effective biomarker of poor tumor response and adverse prognosis of advanced cancer patients with ICIs. Further studies are needed to verify the prognostic value of PNI in clinical practice.

The survival benefit of different lymph node yields in radical prostatectomy for pN1M0 prostate cancer patients: Implications from a population-based study.

Background and objectives: The extent and survival benefits of lymph node dissection (LND) in radical prostatectomy (RP) for pN1M0 prostate cancer (PCa) patients remained unclear and were controversial. This study aimed to determine the survival benefit of different lymph node yields in RP for pN1M0 PCa patients. Methods: pN1M0 PCa patients who received RP and LND were identified in Surveillance Epidemiology and End Results (SEER) (2010-2015). Patients were divided into two groups in SEER based on the removal of one to three regional lymph nodes (LND1 group) or four or more regional lymph nodes (LND4 group). Kaplan-Meier methods were used to calculate cancer-specific survival (CSS) and overall survival (OS). Results: In total, 2,200 patients were identified; 264 patients received LND1 and 1,936 patients received LND4. CSS had no significant difference between the LND4 and LND1 groups (101mon vs. 98mon, p = 0.064), and OS was higher in LND4 patients compared with LND1 patients (97mon vs. 93mon, p = 0.024); for patients with Gleason score = 9 or 10 and T3b or T4, 5-year OS was higher in patients undergoing LND4 (80.9%; 95% CI, 79.0-82.8) compared with those undergoing LND1 (67.5%; 95% CI, 60.8-74.2) (p = 0.009). Conclusion: More lymph node yield provided better survival for patients with Gleason score = 9 or 10 and T3b or T4, but not for other pN1M0 PCa patients. The extent of LND would be determined after a comprehensive evaluation including Gleason score, tumor stage, and the general condition of the patient.

Long Noncoding RNA RP11-732M18.3 Promotes Glioma Angiogenesis by Upregulating VEGFA.

Gliomas are the most aggressive and common type of malignant brain tumor, with limited treatment options and a dismal prognosis. Angiogenesis, a hallmarks of cancer, is one of two critical events in the progression of gliomas. Accumulating evidence has demonstrated that in glioma dysregulated molecules like long noncoding RNAs (lncRNAs), are closely linked to tumorigenesis and prognosis. However, the effects of and mechanisms of action of lncRNAs during tumor angiogenesis are poorly understood. The effect of lncRNA RP11-732M18.3 on angiogenesis was elucidated through an intracranial orthotopic glioma model, immunohistochemistry, and an in vitro angiogenesis assay. Co-culture experiments and cell migration assays were performed to investigate the function of lncRNA RP11-732M18.3 in vitro. lncRNA RP11-732M18.3 increased CD31+ microvessel density, and overexpression of lncRNA RP11-732M18.3 resulted in poor mouse survival. lncRNA RP11-732M18.3 promoted endothelial cell migration and tube formation. Nomogram and Kaplan-Meier survival analyses indicated that higher VEGFA is correlated with a poor prognosis. Mechanistically, lncRNA RP11-732M18.3 promotes angiogenesis by increasing the nuclear level of EP300 and facilitating the transcription and secretion of VEGFA. Our study contributes to the latest understanding of glioma angiogenesis and prognosis. lncRNA RP11-732M18.3 may be a potential treatment target in glioma.

Lymphocyte-to-Monocyte Ratio (LMR) During Induction Is a Better Predictor Than Preoperative LMR in Patients Receiving Intravesical Bacillus Calmette -Guerin for Non-Muscle-Invasive Bladder Cancer.

The prognostic value of the lymphocyte-to-monocyte ratio during induction (ILMR) remains unclear in non-muscle-invasive bladder cancer (NMIBC) patients receiving Bacillus Calmette-Guérin (BCG). We aimed to determine and compare the prognostic value of the ILMR, preoperative lymphocyte-to-monocyte ratio (PLMR) and their dynamic changes (PILMR). This study collected the data from NMIBC patients receiving BCG treatment in our institution. The prognostic value of the PLMR, ILMR and PILMR was analyzed by the Kaplan-Meier method and Cox proportional hazard regression models. The concordance index and receiver operating characteristic curve analysis were employed to compare the prognostic value of these three factors. Our study enrolled 197 patients. These patients included 170 male patients, and the mean age was 64.17 years. During the follow-up time, 85 patients experienced recurrence, and 55 patients experienced progression. According to the results of COX multivariable analysis, PLMR (P=0.011) and ILMR (P<0.001) could independently predict the recurrence of NMIBC patients receiving BCG. Meanwhile, ILMR (P=0.001) and PILMR (P=0.036) were also the independent prognostic factors of progression. Compared with PLMR and PILMR, ILMR was associated with better accuracy for NMIBC patients receiving BCG. This study first found that the ILMR could independently predict the prognosis of NMIBC patients receiving BCG. Furthermore, we also identified that ILMR was associated with higher prognostic value than PLMR and PILMR, which might help to select an optimal treatment schedule for patients with NMIBC.

OAS3 is a Co-Immune Biomarker Associated With Tumour Microenvironment, Disease Staging, Prognosis, and Treatment Response in Multiple Cancer Types.

2',5'-oligoadenylate synthase (OAS) is a class of enzymes induced by interferons and mainly encoded by the OAS1, OAS2, and OAS3 genes, which activate the potential RNA enzymes to degrade viral mRNA, inhibit viral protein synthesis and promote apoptosis in virus-infected cells. OAS3 is associated with breast cancer prognosis. However, the expression and prognosis of OAS3 and tumour-infiltrating lymphocytes in pan-cancer remain unknown. In the present study, we have systematically investigated and confirmed the role of OAS3 in tumour immune infiltration, immune escape, tumour progression, response to treatment, and prognosis of different cancer types using various bioinformatics methods. The findings suggest that OAS3 is aberrantly expressed in almost all TCGA cancer types and subtypes and is associated with tumour staging, metastasis, and prognostic deterioration in different tumours. In addition, OAS3 expression is associated with the prognosis and chemotherapeutic outcomes of various cancers. In terms of immune-infiltrating levels, OAS3 expression is positively associated with the infiltration of immunosuppressive cells. These findings suggest that OAS3 is correlated with prognosis and immune-infiltrating levels.

Development of an immune-related prognostic biomarker for triple-negative breast cancer.

Purpose: Oncology studies employing digital dissection methodologies have provided some insight on the biological features of tumor microenvironment of Triple-negative breast cancer (TNBC), but molecular diagnostics rarely have therapeutic impact. We aimed to identify a novel prognostic biomarker to investigate immune characteristics of TNBC using transcriptomic features.Patients and Methods: We extracted whole transcriptome from breast cancer tissue of 30 TNBC patients and then used bioinformatics approaches to characterize the different immune cell contents in tumor tissue and para-cancerous tissue. We extract 2 indicators to describe the major differences in immune infiltration in the microenvironment between tumor tissue and para-cancerous tissue. We then combined the 2 indicators that represent the levels of increased and decreased infiltration in each sample to obtain the Immune Infiltration Score (IIS). Then we compared the tumor-infiltrating immune cell contents and immune infiltrating status in TNBC samples with CIBERSORT and ESTIMATE score to validate the IIS. Finally, 132 TNBC patients from the Cancer Genome Atlas program (TCGA) dataset was used to validate the predictive power of IIS.Results: 4 types of upregulated and 4 types of downregulated immune cells were identified in the tumor tissue samples of the TNBC patients. Then we developed a novel biomarker, IIS. Results showed that IIS score can clearly separate cancer and para-cancerous tissue. Using the same cutoff value of 0 in the TNBC-TCGA cohort, we show that those patients with a higher IIS had significantly higher PD-L1 expression and shorter progression-free survival time than those with a lower IIS value, indicating IIS score can be generalized to other TNBC datasets.Conclusion: we explored the immune infiltration landscape in 30 TNBC patients and provided IIS as a novel and reliable biomarker to evaluate the progression-free survival and prognosis of the TNBC patients.

Comprehensive Analysis of HHLA2 as a Prognostic Biomarker and Its Association With Immune Infiltrates in Hepatocellular Carcinoma.

Background: Inhibitory immune checkpoint proteins promote tumor immune escape and are associated with inferior patient outcome. However, the biological functions and regulatory roles of one of its members, HHLA2, in the tumor immune microenvironment have not been explored. Methods: RandomForest analyses (371 cases), qRT-PCR (15 cases), and immunohistochemical staining (189 cases) were used to validate the prognostic value of HHLA2 in hepatocellular carcinoma (HCC) patients. Bioinformatic analyses were further performed to explore the biological functions and potential signaling pathways affected by HHLA2. Moreover, ESTIMATE, single sample gene set enrichment analysis, CIBERSORT, TIMER, and other deconvolution methods were used to analyze the composition and infiltration level of immune cells. Multiplex immunofluorescence assays were employed to validate the fractions of suppressive immune cells, and HHLA2-related molecular alterations were investigated. Finally, the clinical response to chemotherapy and immune checkpoint blockade was predicted by TIDE, Submap, and several other in silico analyses. Results: RandomForest analysis revealed that HHLA2 was the most important inhibitory immune checkpoint associated with HCC patient prognosis (relative importance = 1). Our HCC cohorts further revealed that high HHLA2 expression was an independent prognostic biomarker of shorter overall survival (P<0.01) and time to recurrence (P<0.001) for HCC patients. Bioinformatics experiments revealed that HHLA2 may accelerate the cell cycle of cancer cells. Additionally, we found that high expression of HHLA2 was associated with immune infiltrates, including some immunosuppressive cells, cytokines, chemokines, and corresponding receptors, resulting in an immunosuppressive environment. Notably, HHLA2 expression was positively correlated with the infiltration of exhausted CD8+ T cells, which was validated by immunofluorescence. Genomic alteration analyses revealed that promoter hypermethylation of HHLA2 may be associated with its low expression. More importantly, patients with high HHLA2 expression may be more sensitive to chemotherapy and have better responses to immunotherapy. Conclusions: High expression of HHLA2 is an independent prognostic biomarker for HCC patients. It can activate the cell cycle and foster an immunosuppressive tumor microenvironment by enriching exhausted CD8+ T cells. Promoter hypermethylation might lead to low expression of HHLA2 in HCC. Thus, targeting HHLA2 may be a practical therapeutic strategy for HCC patients in the future.

Clinical Significance and Potential Mechanisms of ATP Binding Cassette Subfamily C Genes in Hepatocellular Carcinoma.

The purpose of this investigation was to assess the diagnostic and prognostic significance of ATP binding cassette subfamily C (ABCC) genes in hepatocellular carcinoma (HCC). The Student t-test was used to compare the expression level of ABCCs between HCC and paraneoplastic tissues. Receiver operating characteristic curve (ROC) analysis was applied for diagnostic efficiency assessment. The Kaplan-Meier method and Cox proportional hazards model were respectively applied for survival analysis. Genes with prognostic significance were subsequently used to construct prognostic models. From the perspective of genome-wide enrichment analysis, the mechanisms of prognosis-related ABCC genes were attempted to be elaborated by gene set enrichment analysis (GSEA). It was observed in the TCGA database that ABCC1, ABCC4, ABCC5, and ABCC10 were significantly upregulated in tumor tissues, while ABCC6 and ABCC7 were downregulated in HCC tissues. Receiver operating characteristic analysis revealed that ABCC7 might be a potential diagnostic biomarker in HCC. ABCC1, ABCC4, ABCC5, and ABCC6 were significantly related to the prognosis of HCC in the TCGA database. The prognostic significance of ABCC1, ABCC4, ABCC5, and ABCC6 was also observed in the Guangxi cohort. In the Guangxi cohort, both polymerase chain reaction and IHC (immunohistochemical) assays demonstrated higher expression of ABCC1, ABCC4, and ABCC5 in HCC compared to liver tissues, while the opposite was true for ABCC6. GSEA analysis indicated that ABCC1 was associated with tumor differentiation, nod-like receptor signal pathway, and so forth. It also revealed that ABCC4 might play a role in HCC by regulating epithelial-mesenchymal transition, cytidine analog pathway, met pathway, and so forth. ABCC5 might be associated with the fatty acid metabolism and KRT19 in HCC. ABCC6 might impact the cell cycle in HCC by regulating E2F1 and myc. The relationship between ABCC genes and immune infiltration was explored, and ABCC1,4,5 were found to be positively associated with infiltration of multiple immune cells, while ABCC6 was found to be the opposite. In conclusion, ABCC1, ABCC4, ABCC5, and ABCC6 might be prognostic biomarkers in HCC. The prognostic models constructed with ABCC1, ABCC4, ABCC5, and ABCC6 had satisfactory efficacy.

Estrogen-Induced Extracellular Calcium Influx Promotes Endometrial Cancer Progress by Regulating Lysosomal Activity and Mitochondrial ROS.

OBJECTIVE: Calcium is present in serum mainly in filterable and bound forms, and Ca2+ is a major key to modulate signaling pathways that control oncogenesis and oncochannels associated with several types of cancer. However, the biological significance of serum calcium and its related mechanism with estrogen in endometrial cancer (EC) still remains elusive. This study aims to ascertain the relationship between serum calcium and clinicopathology in EC. METHODS: Retrospective assessment of a total of 502 patients diagnosed with EC after surgery in Peking University People's Hospital from 2010 to 2018. Preoperative serum ionized calcium and the albumin corrected calcium was calculated in quartiles for various postoperative clinicopathological characteristics, logistic regression adjusted for potential confounders. Intracellular calcium homeostasis change induced by estrogen was detected by confocal analysis. Downstream pathways were analyzed by transcriptome and proteomics. Mitochondrial Ca2+ and ROS (reactive oxygen species) level was detected by confocal and flow cytometry. Lysosomal morphological and membrane changes were verified by confocal or Western blot assays. RESULTS: High level of albumin-corrected serum calcium was significantly correlated with EC clinicopathological characteristics progression include lymph vascular space invasion, lymph nodes metastasis, myometrial invasion, and cervical invasion. Calcium homeostasis regulated by estrogen in EC cells derived from extracellular calcium influx but not the release of the endoplasmic reticulum. Proteomic and bioinformatic analysis revealed the calcium influx might be involved in the regulation of autophagy and mitochondrial-related pathways. Mechanistic investigation demonstrated that calcium influx acted on the function of mitochondrial ROS and lysosomal activity. CONCLUSION: Our findings revealed that serum calcium level was significantly related to poor outcomes. The extracellular calcium influx induced by estrogen was targeted to mitochondrial ROS and lysosome activity, which should be oriented to improve EC therapeutic strategies.

Pronounced Enhancement in Radiosensitization of Esophagus Cancer Cultivated in Docosahexaenoic Acid via the PPAR -γ Activation.

Docosahexaenoic acid (DHA) has been reported to suppress the tumor growth and improve prognosis and has been used to cooperate with many other chemotherapy medicines. Up to now, surveys focused on the Interaction between DHA and radiation are relatively modest. Our study sought to evaluate the radiosensitivity changes caused by DHA on esophageal cancer cells. We selected TE-1 and TE-10 esophagus cancer cells as models and performed routine cell proliferation assay and cloning assay to detect the impact of DHA combined with X-ray. We used cell cycle assay, lipid peroxidation assay, comet assay, and apoptosis assay to unearth the potential causes. We also launched a mouse transplanted tumor experiment to verify the synergetic effect of DHA and irradiation. Finally, a western blot assay was used to find a novel mechanism. As a result, DHA improved TE-1 and TE-10 radiosensitivity in vivo and in vitro. What's more, PPAR-γ expression increased due to the DHA supplement. Inhibiting PPAR-γ could attenuate benefits brought out by DHA somehow. Due to its explicit usage and convenience, DHA would serve as an adjuvant therapy before radiotherapy if the clinical trials indicated positive.

Clinical Significance and Prognostic Value of Human Soluble Resistance-Related Calcium-Binding Protein: A Pan-Cancer Analysis.

The soluble resistance-related calcium-binding protein (sorcin, SRI) serves as the calcium-binding protein for the regulation of calcium homeostasis and multidrug resistance. Although the mounting evidence suggests a crucial role of SRI in the chemotherapeutic resistance of certain types of tumors, insights into pan-cancer analysis of SRI are unavailable. Therefore, this study aimed to probe the multifaceted properties of SRI across the 33 cancer types. The SRI expression was analyzed via The Cancer Genome Atlas (TCGA) and Genotype Tissue-Expression (GTEX) database. The SRI genomic alterations and drug sensitivity analysis were performed based on the cBioPortal and the CellMiner database. Furthermore, the correlations among the SRI expression and survival outcomes, clinical features, stemness, tumor mutation burden (TMB), microsatellite instability (MSI), and immune cells infiltration were analyzed using TCGA data. The differential analysis showed that SRI was upregulated in 25 tumor types compared with the normal tissues. Aberrant expression of SRI was able to predict survival in different cancers. Further, the most frequent alteration of SRI genomic was amplification. Moreover, the aberrant SRI expression was related to stemness score, epithelial-mesenchymal-transition (EMT)-related genes, MSI, TMB, and tumor immune microenvironment in various types of cancer. TIMER database mining further found that the SRI expression was significantly correlated with the infiltration levels of various immune cells in certain types of cancer. Intriguingly, the SRI expression was negatively correlated with drug sensitivity of fluorouracil, paclitaxel, docetaxel, and isotretinoin. Our findings highlight the predictive value of SRI in cancer and provide insights for illustrating the role of SRI in tumorigenesis and drug resistance.

Bioinformatic Analyses and Experimental Verification Reveal that High FSTL3 Expression Promotes EMT via Fibronectin-1/α5ß1 Interaction in Colorectal Cancer.

Background: Colorectal cancer (CRC) is a typical cancer prevalent worldwide. Despite the conventional treatments, CRC has a poor prognosis due to relapse and metastasis. Moreover, there is a dearth of sensitive biomarkers for predicting prognosis in CRC. Methods: This study used a bioinformatics approach combining validation experiments to examine the value of follistatin-like 3 (FSTL3) as a prognostic predictor and therapeutic target in CRC. Results: FSTL3 was remarkably upregulated in the CRC samples. FSTL3 overexpression was significantly associated with a poor prognosis. FSTL3 was found to activate the epithelial-mesenchymal transition by promoting the binding of FN1 to α5ß1. FSTL3 expression was also positively correlated with the abundance of the potent immunosuppressors, M2 macrophages. Conclusion: FSTL3 overexpression affects CRC prognosis and thus, FSTL3 can be a prognostic biomarker and therapeutic target with potential applications in CRC.

GPI Is a Prognostic Biomarker and Correlates With Immune Infiltrates in Lung Adenocarcinoma.

BACKGROUND: Glucose-6-phosphate isomerase (GPI) plays an important role in glycolysis and gluconeogenesis. However, the role of GPI in lung adenocarcinoma (LUAD) remains unclear. METHODS: All original data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases and integrated via R 3.2.2. GPI expression was explored with TCGA, GEO, and Oncomine databases. Immunohistochemistry staining was used to analyze GPI expression in clinical specimens. The correlations between GPI and cancer immune characteristics were analyzed via the TIMER and TISIDB databases. GPI-specific siRNAs were used to verify the role of GPI expression on cell proliferation and cell cycle distribution. RESULTS: In general, GPI is predominantly overexpressed and has reference value in the diagnosis and prognostic estimation of LUAD. Upregulated GPI was associated with poorer overall survival, clinical stage, N stage, and primary therapy outcome in LUAD. Mechanistically, we identified a hub gene that included a total of 56 GPI-related genes, which were tightly associated with the cell cycle pathway in LUAD patients. Knockdown of GPI induced cell proliferation inhibition and cell cycle arrest. GPI expression was positively correlated with infiltrating levels of Th2 cells and regulatory T cells (Tregs); in contrast, GPI expression was negatively correlated with infiltrating levels of CD8+ T cells, central memory T cells, dendritic cells, macrophages, mast cells, and eosinophils. GPI was negatively correlated with the expression of immunostimulators, such as CD40L, IL6R, and TMEM173, in LUAD. CONCLUSION: GPI may play an important role in the cell cycle and can be used as a prognostic biomarker for determining the prognosis and immune infiltration in LUAD.

Prognostic Immunophenotyping Clusters of Clear Cell Renal Cell Carcinoma Defined by the Unique Tumor Immune Microenvironment.

Background: The tumor microenvironment affects the occurrence and development of cancers, including clear cell renal cell carcinoma (ccRCC). However, how the immune contexture interacts with the cancer phenotype remains unclear. Methods: We identified and evaluated immunophenotyping clusters in ccRCC using machine-learning algorithms. Analyses for functional enrichment, DNA variation, immune cell distribution, association with independent clinicopathological features, and predictive responses for immune checkpoint therapies were performed and validated. Results: Three immunophenotyping clusters with gradual levels of immune infiltration were identified. The intermediate and high immune infiltration clusters (Clusters B and C) were associated with a worse prognosis for ccRCC patients. Tumors in the immune-hot Clusters B and C showed pro-tumorigenic immune infiltration, and these patients showed significantly worse survival compared with patients in the immune-cold Cluster A in the training and testing cohorts (n = 422). In addition to distinct immune cell infiltrations of immunophenotyping, we detected significant differences in DNA variation among clusters, suggesting a high degree of genetic heterogeneity. Furthermore, expressions of multiple immune checkpoint molecules were significantly increased. Clusters B and C predicted favorable outcomes in 64 ccRCC patients receiving immune checkpoint therapies from the FUSCC cohort. In 360 ccRCC patients from the FUSCC validation cohort, Clusters B and C significantly predicted worse prognosis compared with Cluster A. After immunophenotyping of ccRCC was confirmed, significantly increased tertiary lymphatic structures, aggressive phenotype, elevated glycolysis and PD-L1 expression, higher abundance of CD8+ T cells, and TCRn cell infiltration were found in the immune-hot Clusters B and C. Conclusion: This study described immunophenotyping clusters that improved the prognostic accuracy of the immune contexture in the ccRCC microenvironment. Our discovery of the novel independent prognostic indicators in ccRCC highlights the relationship between tumor phenotype and immune microenvironment.

Immune Signatures Combined With BRCA1-Associated Protein 1 Mutations Predict Prognosis and Immunotherapy Efficacy in Clear Cell Renal Cell Carcinoma.

Immunotherapy is gradually emerging in the field of tumor treatment. However, because of the complexity of the tumor microenvironment (TME), some patients cannot benefit from immunotherapy. Therefore, we comprehensively analyzed the TME and gene mutations of ccRCC to identify a comprehensive index that could more accurately guide the immunotherapy of patients with ccRCC. We divided ccRCC patients into two groups based on immune infiltration activity. Next, we investigated the differentially expressed genes (DEGs) and constructed a prognostic immune score using univariate Cox regression analysis, unsupervised cluster analysis, and principal component analysis (PCA) and validated its predictive power in both internal and total sets. Subsequently, the gene mutations in the groups were investigated, and patients suitable for immunotherapy were selected in combination with the immune score. The prognosis of the immune score-low group was significantly worse than that of the immune score-high group. The patients with BRCA1-associated protein 1 (BAP1) mutation had a poor prognosis. Thus, this study indicated that establishing an immune score model combined with BAP1 mutation can better predict the prognosis of patients, screen suitable ccRCC patients for immunotherapy, and select more appropriate drug combinations.

Inflammation-Related Long Non-Coding RNA Signature Predicts the Prognosis of Gastric Carcinoma.

Background: Gastric carcinoma (GC) is a molecularly and phenotypically highly heterogeneous disease, making the prognostic prediction challenging. On the other hand, Inflammation as part of the active cross-talk between the tumor and the host in the tumor or its microenvironment could affect prognosis. Method: We established a prognostic multi lncRNAs signature that could better predict the prognosis of GC patients based on inflammation-related differentially expressed lncRNAs in GC. Results: We identified 10 differently expressed lncRNAs related to inflammation associated with GC prognosis. Kaplan-Meier survival analysis demonstrated that high-risk inflammation-related lncRNAs signature was related to poor prognosis of GC. Moreover, the inflammation-related lncRNAs signature had an AUC of 0.788, proving their utility in predicting GC prognosis. Indeed, our risk signature is more precise in predicting the prognosis of GC patients than traditional clinicopathological manifestations. Immune and tumor-related pathways for individuals in the low and high-risk groups were further revealed by GSEA. Moreover, TCGA based analysis revealed significant differences in HLA, MHC class-I, cytolytic activity, parainflammation, co-stimulation of APC, type II INF response, and type I INF response between the two risk groups. Immune checkpoints revealed CD86, TNFSF18, CD200, and LAIR1 were differently expressed between lowand high-risk groups. Conclusion: A novel inflammation-related lncRNAs (AC015660.1, LINC01094, AL512506.1, AC124067.2, AC016737.1, AL136115.1, AP000695.1, AC104695.3, LINC00449, AC090772.1) signature may provide insight into the new therapies and prognosis prediction for GC patients.

ARID1A Variations in Cholangiocarcinoma: Clinical Significances and Molecular Mechanisms.

Cholangiocarcinoma (CCA), a high mortality malignant carcinoma characterized by advanced disease and frequent recurrence, constitutes a major challenge for treatment and prognosis. AT-rich interaction domain 1A (ARID1A) variation is a distinct genetic entity in CCA, getting mounting concerns recently. Here, we comprehensively reviewed the clinical significance and molecular mechanisms of ARID1A alterations in CCA. Based on the independent data derived from 29 relevant studies, the variation rate of ARID1A in intrahepatic and extrahepatic CCA is reported at 6.9-68.2% and 5-55%, respectively. Most of the included studies (28/29, 96.6%) suggest that ARID1A serves as a tumor suppressor in CCA. ARID1A variation may be an important prognostic indicator to predict disease mortality, metastasis, and recurrence in patients with CCA. Multifactorial molecular mechanisms are involved in the relationship between ARID1A variations and the pathogenesis and pathophysiology of CCA, including disruption of the cell cycle, chromatin remodeling, oxidative stress damage, DNA hypermethylation, and the interaction of multiple genes being affected. This review describes that ARID1A variation might be a potential diagnostic and prognostic biomarker for CCA. Future diagnoses and treatments targeting ARID1A hint towards a precision medicine strategy in the management of CCA.