Pan-cancer characterization of cell-free immune-related miRNA identified as a robust biomarker for cancer diagnosis.

Minimally invasive testing is essential for early cancer detection, impacting patient survival rates significantly. Our study aimed to establish a pioneering cell-free immune-related miRNAs (cf-IRmiRNAs) signature for early cancer detection. We analyzed circulating miRNA profiles from 15,832 participants, including individuals with 13 types of cancer and control. The data was randomly divided into training, validation, and test sets (7:2:1), with an additional external test set of 684 participants. In the discovery phase, we identified 100 differentially expressed cf-IRmiRNAs between the malignant and non-malignant, retaining 39 using the least absolute shrinkage and selection operator (LASSO) method. Five machine learning algorithms were adopted to construct cf-IRmiRNAs signature, and the diagnostic classifies based on XGBoost algorithm showed the excellent performance for cancer detection in the validation set (AUC: 0.984, CI: 0.980-0.989), determined through 5-fold cross-validation and grid search. Further evaluation in the test and external test sets confirmed the reliability and efficacy of the classifier (AUC: 0.980 to 1.000). The classifier successfully detected early-stage cancers, particularly lung, prostate, and gastric cancers. It also distinguished between benign and malignant tumors. This study represents the largest and most comprehensive pan-cancer analysis on cf-IRmiRNAs, offering a promising non-invasive diagnostic biomarker for early cancer detection and potential impact on clinical practice.

The Battle for Accuracy: Identifying the Most Effective Grading System for Lung Invasive Mucinous Adenocarcinoma.

BACKGROUND: The prognostic analysis of lung invasive mucinous adenocarcinoma (IMA) is deficient due to the lack of a universally recommended histological grading system, leading to unregulated treatment approaches. OBJECTIVE: We aimed to examine the clinical trajectory of IMA and assess the viability of utilizing the existing grading system for lung invasive non-mucinous adenocarcinoma in the context of IMA. METHODS: We retrospectively collected clinicopathological data from 265 IMA patients. Each case re-evaluated the tumor grade using the following three classification systems: the 4th Edition of the World Health Organization classification system, the International Association for the Study of Lung Cancer (IASLC) grading system, and a two-tier grading system. We performed a comparative analysis of these grading systems and identified the most effective grading system for IMA. RESULTS: The study comprised a total of 214 patients with pure IMA and 51 patients with mixed IMA. The 5-year overall survival (OS) rates for pure IMA and mixed IMA were 86.7% and 57.8%, respectively. All three grading systems proved to be effective prognostic classifiers for IMA. The value of area under the curve at 1-, 3-, and 5-year OS was highest for the IASLC grading system compared with the other grade systems and the clinical stage. The IASLC classification system was an independent prognostic predictor (p = 0.009, hazard ratio 2.243, 95% confidence interval 1.219-4.127). CONCLUSION: Mixed IMA is more aggressive than pure IMA, with an OS rate on par with that of high-grade pure IMA. The IASLC grading system can better indicate prognosis and is recommended for lung IMA.

LINC00520 promotes colorectal cancer progression through miRNA-195-3p / NAT2 axis.

In this study, we investigated the role of LINC00520 in colorectal cancer (CRC) progression. We analyzed LINC00520 expression in 15 pairs of CRC tissues and adjacent tissues using qRT-PCR, revealing significantly elevated levels in CRC tissues and cell lines. Lentivirus-mediated up/down-regulation of LINC00520 in CRC cell lines demonstrated that increased LINC00520 expression enhanced cell invasiveness, as confirmed by transwell and wound healing assays. Bioinformatics analysis identified a regulatory axis involving LINC00520, microRNA-195-3p, and NAT2. Luciferase assays confirmed direct binding between LINC00520 and microRNA-195-3p, as well as microRNA-195-3p and NAT2. Overexpression of NAT2 reversed the inhibitory effects on invasion and migration induced by LINC00520 silencing. This suggests that LINC00520, highly expressed in CRC tissues, may modulate tumor biological functions through the microRNA-195-3p/NAT2 axis. Our findings provide insights into the mechanism underlying CRC progression, highlighting the potential of LINC00520 as a therapeutic target.

The impact of open access on citations, Pageviews, and downloads: a scientometric analysis in Postgraduate Medical Journal.

PURPOSE: The influence of Open Access (OA) on the citation impact of scholarly articles remains a topic of considerable debate. This study aims to elucidate the relationship between OA publication and citation metrics, as well as article visibility, within the context of the Postgraduate Medical Journal (PMJ). METHODS: We conducted a retrospective analysis of 373 articles published in PMJ between 2020 and 2021. Data on OA status, citations, page views, PDF downloads, and other relevant variables were extracted from Journal Citation Reports and PMJ's official website. Multivariable linear regression and other statistical analyses were used to assess the impact of OA on these metrics. RESULTS: OA articles (n = 78) demonstrated significantly higher citation counts, page views, and PDF downloads compared with subscription-based articles (n = 295). Specifically, OA articles showed a significant increase in citation frequency with a ß coefficient of 25.08 and a 95% CI of 17.168-32.992 (P < .001). Similarly, OA status was independently associated with increases in page views [ß = 288.636, 95%CI: 177.749-399.524, P < .001] and PDF downloads [ß = 118.966, 95%CI: 86.357-151.575, P < .001]. Strong correlations among total citations, page views, and PDF downloads were observed in both OA and subscription articles. CONCLUSION: The study highlights a significant and independent association of OA publishing with increased citation counts, page views, and PDF downloads in PMJ, suggesting that OA articles have broader reach and greater visibility. Further research, including randomized controlled studies across various journals, is needed to confirm these findings and explore the full impact of OA publishing.

Short-and long-term outcomes of one-stage versus two-stage gastrectomy for perforated gastric cancer: a multicenter retrospective propensity score-matched study.

OBJECTIVE: There is no scientific consensus about the treatment of perforated gastric cancer (PGC). Therefore, the aim of this study was to investigate which is the better treatment option for PGC between the single-stage and two-stage strategies. METHODS: All 81 PGC patients from 13 medical institutions were retrospectively enrolled in this study. The PGC patients who underwent R0 gastrectomy were divided into one-stage surgery and two-stage surgery groups. The clinicopathological characteristics of the two groups were compared, and 415 regular gastric cancer patients without perforation were randomly selected as a control. The propensity score matching (PSM) method was used to find matched regular GC patients with similar clinicopathological parameters. The OS (overall survival) and the number harvested lymph nodes from PGC patients and regular GC patients were compared. RESULTS: Compared with PGC patients who underwent one-stage surgery, those who underwent two-stage surgery harvested significantly more lymph nodes [31(27, 38) vs 17 (12, 24), P < 0.001], required less blood transfusion [0 (0, 100) vs 200 (0, 800), P = 0.034], had a shorter ICU stay [0 (0, 1.5) vs 3 (0, 3), P = 0.009], and had a significantly better OS (Median OS: 45 months vs 11 months, P = 0.007). Compared with propensity score-matched regular GC patients without perforation, PGC patients who underwent one-stage gastrectomy had a poorer quality of lymphadenectomy [17 (12, 24) vs 29 (21, 37), P < 0.001] and suffered a worse OS (Median OS: 18 months vs 30 months, P = 0.024). Conversely, two-stage gastrectomy can achieve a comparable quality of lymphadenectomy (P = 0.506) and a similar OS (P = 0.096) compared to propensity score-matched regular GC patients. CONCLUSIONS: For PGC patients in poor condition, two-stage treatment is a better option when D2 radical gastrectomy cannot be achieved in emergency surgery, based on our findings that two-stage gastrectomy could provide PGC patients with a better quality of lymphadenectomy and a better OS.

Navigating Challenges and Seizing Opportunities in China's Era of Online Health Education.

The rapid growth of internet users in China presents opportunities for advancing the "Healthy China 2030" initiative through online health education. Platforms like "Shanghai Health Cloud" and "National Health Information Platform" improve health literacy and management, enhancing overall public health. However, challenges such as the digital divide and the spread of unverified health information hinder progress. Addressing these issues requires enhancing digital infrastructure, employing advanced technologies for information validation, and setting high standards for online health services. Integrated efforts from various sectors are essential to maximize the benefits of online health education in China.

Costimulatory molecule expression profile as a biomarker to predict prognosis and chemotherapy response for patients with small cell lung cancer.

Owing to the paucity of specimens, progress in identifying prognostic and therapeutic biomarkers for small cell lung cancer (SCLC) has been stagnant for decades. Considering that the costimulatory molecules are essential elements in modulating immune responses and determining therapeutic response, we systematically revealed the expression landscape and identified a costimulatory molecule-based signature (CMS) to predict prognosis and chemotherapy response for SCLCs for the first time. We found T cell activation was restrained in SCLCs, and costimulatory molecules exhibited widespread abnormal genetic alterations and expression. Using a LASSO Cox regression model, the CMS was built with a training cohort of 77 cases, which successfully divided patients into high- or low-risk groups with significantly different prognosis and chemotherapy benefit (both P < 0.001). The CMS was well validated in an independent cohort containing 131 samples with qPCR data. ROC and C-index analysis confirmed the superior predictive performance of the CMS in comparison with other clinicopathological parameters from different cohorts. Importantly, the CMS was confirmed as a significantly independent prognosticator for clinical outcomes and chemotherapy response in SCLCs through multivariate Cox analysis. Further analysis revealed that low-risk patients were characteristic by an activated immune phenotype with distinct expression of immune checkpoints. In summary, we firstly uncovered the expression heterogeneity of costimulatory molecules in SCLC and successfully constructed a novel predictive CMS. The identified signature contributed to more accurate patient stratification and provided robust prognostic value in estimating survival and the clinical response to chemotherapy, allowing optimization of treatment and prognosis management for patients with SCLC.

Optimal velocity loss threshold for inducing post activation potentiation in track and field athletes.

The aim of this study was to determine the optimal velocity loss (VL) threshold that maximises the post activation potentiation (PAP) stimulus for achieving larger and more consistent performance gains in track and field athletes. Twenty-two athletes from athletics participated in four back squat PAP tests with four different VL threshold (5%, 10%, 15% and 20% VL) at an intensity of 85%1RM. Countermovement jump (CMJ) height, power, and momentum were assessed before, and 10 s, 4, 8, 12, 16 minutes after the PAP condition. Repetitions of the squat in all the PAP conditions were also recorded. Only the 5% VL condition produced significant improvements in height (ES = 0.73, P = 0.038), peak power output (ES = 0.73, P = 0.038) and momentum (ES = 0.72, P = 0.041) of CMJ, and these changes appeared 8 minutes after the condition. The total number of repetitions during the 5% VL condition was significantly lower than that observed in the 15% (P = 0.003) and 20% VL (P < 0.001) trials. The results from this study indicate that 5%VL during the 2 sets preconditioning squat at 85%1RM was optimal for eliciting PAP in a CMJ exercise, and resulted in significant increases at the 8-min recovery period. The same squat condition also had the least number of repetitions. However, considering the efficiency in practice, athletes can also choose the rest time of 4-min, which can also achieve similar results.

Comprehensive analyses of N6 -methyladenosine-related long noncoding RNA profiles with prognosis, chemotherapy response, and immune landscape in small cell lung cancer.

Small cell lung cancer (SCLC) is the most devastating subtype of lung cancer with no clinically available prognostic biomarkers. N6 -methyladenosine (m6 A) and noncoding RNAs play critical roles in cancer development and treatment response. However, little is known about m6 A-related long noncoding RNAs (lncRNAs) in SCLC. We used 206 limited-stage SCLC (LS-SCLC) samples from two cohorts to undertake the first and most comprehensive exploration of the m6 A-related lncRNA profile in SCLC and constructed a relevant prognostic signature. In total, 289 m6 A-related lncRNAs were screened out. We then built a seven-lncRNA-based signature in the training cohort with 48 RNA sequencing data using univariate and multivariate Cox regression models. The signature was well validated in an independent cohort containing 158 cases with quantitative PCR data. In both cohorts, the signature divided patients into high- and low-risk groups with significantly different survival rates (both p < 0.001). Our signature predicted chemotherapy survival benefit in patients with LS-SCLC. Receiver operating characteristic and C-index analyses indicated that the signature was better at predicting prognosis and chemotherapy benefit than other clinicopathologic features. Moreover, the signature was identified as an independent predictor of prognosis and chemotherapy response in different cohorts. Furthermore, functional analysis showed that multiple activated immune-related pathways were enriched in the low-risk group. Additionally, the signature was also closely related to various immune checkpoints and inflammatory responses. We generated the first clinically available m6 A-related lncRNA signature to predict prognosis and chemotherapy benefit in patients with LS-SCLC. Our findings could help optimize the clinical management of patients with LS-SCLC and inform future therapeutic targets for SCLC.

High-Precision Intelligent Cancer Diagnosis Method: 2D Raman Figures Combined with Deep Learning.

Raman spectroscopy, as a label-free detection technology, has been widely used in tumor diagnosis. However, most tumor diagnosis procedures utilize multivariate statistical analysis methods for classification, which poses a major bottleneck toward achieving high accuracy. Here, we propose a concept called the two-dimensional (2D) Raman figure combined with convolutional neural network (CNN) to improve the accuracy. Two-dimensional Raman figures can be obtained from four transformation methods: spectral recurrence plot (SRP), spectral Gramian angular field (SGAF), spectral short-time Fourier transform (SSTFT), and spectral Markov transition field (SMTF). Two-dimensional CNN models all yield more than 95% accuracy, which is higher than the PCA-LDA method and the Raman-spectrum-CNN method, indicating that 2D Raman figure inputs combined with CNN may be one reason for gaining excellent performances. Among 2D-CNN models, the main difference is the conversion, where SRP is based on the structure of wavenumber series with the best performances (98.9% accuracy, 99.5% sensitivity, 98.3% specificity), followed by SGAF on the wavenumber series, SSTFT on wavenumber and intensity information, and SMTF on wavenumber position information. The inclusion of external information in the conversion may be another reason for improvement in the accuracy. The excellent capability shows huge potential for tumor diagnosis via 2D Raman figures and may be applied in other spectroscopy analytical fields.

A novel immune checkpoints-based signature to predict prognosis and response to immunotherapy in lung adenocarcinoma.

BACKGROUND: Except for B7-CD28 family members, more novel immune checkpoints are being discovered. They are closely associated with tumor immune microenvironment and regulate the function of many immune cells. Various cancer therapeutic studies targeting these novel immune checkpoints are currently in full swing. However, studies concerning novel immune checkpoints phenotypes and clinical significance in lung adenocarcinoma (LUAD) are still limited. METHODS: We enrolled 1883 LUAD cases from nine different cohorts. The samples from The Cancer Genome Atlas (TCGA) were used as a training set, whereas seven microarray data cohorts and an independent cohort with 102 qPCR data were used for validation. The immune profiles and potential mechanism of the system were also explored. RESULTS: After univariate Cox proportional hazards regression and stepwise multivariable Cox analysis, a novel immune checkpoints-based system (LTA, CD160, and CD40LG) were identified from the training set, which significantly stratified patients into high- and low-risk groups with different survivals. Furthermore, this system has been well validated in different clinical subgroups and multiple validation cohorts. It also acted as an independent prognostic factor for patients with LAUD in different cohorts. Further exploration suggested that high-risk patients exhibited distinctive immune cells infiltration and suffered an immunosuppressive state. Additionally, this system is closely linked to various classical immunotherapy biomarkers. CONCLUSION: we constructed a novel immune checkpoints-based system for LUAD, which predicts prognosis and immunotherapeutic implications. We believe that these findings will not only aid in clinical management but will also shed some light on screening appropriate patients for immunotherapy.

Sentinel Lymph Node Positive Rate Predicts Non-Sentinel Lymph Node Metastasis in Breast Cancer.

BACKGROUND: To investigate retrospectively an association between the number of metastatic sentinel lymph nodes (SLNs) per total number of SLNs per patient (i.e., the SLN positive rate, or SLN-PR) and non-SLN metastasis in breast cancer. METHODS: A large population (n = 2250) underwent SLN dissection from January 1, 2014 to January 1, 2020; 627 (27.87%) had at least one positive SLN (SLN+). Among these, 283 underwent axillary lymph node (ALN) dissection, and formed the test group. Four external validation groups comprised 43 patients treated in 2019. SLN mappings were examined using methylene blue and indocyanine green. Lymph node ultrasound, SLN-PR, and pathological characteristics were compared between patients with and without non-SLN metastasis. An SLN-PR cutoff value was calculated using receiver operating characteristic (ROC) curves. Associations between clinicopathological variables and SLN-PR with non-SLN metastasis were analyzed by multivariate logistic regression model. RESULTS: The median age was 47 years (IQR: 42-56 y). The median number of resected SLNs was 4. Patients with positive non-SLNs (126/283, 44.52%) had a median of 2 positive node. SLN-PR > 0.333 was a risk factor for non-SLN positivity (area under the ROC curve, 0.726); and carried significantly higher risk of non-SLN metastasis (P < 0.001). This was validated in the external group. CONCLUSIONS: SLN-PR > 0.333 was associated with greater risk of non-SLN metastasis. This provides a reference to non-SLN metastasis in patients with SLN metastasis, an indication for ALN dissection and choice of adjuvant treatment.

Association between preoperative dementia and hospital mortality in old old patients undergoing elective gastrointestinal surgery.

BACKGROUND: Although many reports have shown that preoperative dementia affects surgical prognosis, it is unclear whether the dementia based on Mini-Mental State Examination (MMSE) affect hospital mortality in old old patients undergoing elective gastrointestinal surgery. AIMS: This study aims to investigate whether preoperative dementia might affect the outcomes of old old patients undergoing elective gastrointestinal surgery by evaluating with the MMSE. METHODS: All patients aged ≥ 75 years who undergoing elective gastrointestinal surgery form January 2015 to December 2021 in a Chinese tertiary hospital were retrospectively analyzed. Their preoperative cognitive status was evaluated using the MMSE, and analysis was performed to compare the patients with MMSE score < 24 (dementia group) or MMSE score 24-30 (non-dementia group). Risk factors for hospital mortality were explored using multivariate logistic regression analysis. RESULTS: 980 patients were rolled in the study, and 102 (10.4%) patients were in the dementia group. ICU and hospital stay were longer in the dementia group. Regarding the postoperative complications, the incidence of cerebral infarction (P = 0.014), delirium (P = 0.019), and pulmonary infection (P = 0.017) was more frequent in dementia group. Hospital mortality was 11% in the dementia group and 3% in the non-dementia group (P = 0.009). Multivariate logistic regression analysis revealed that dementia (P = 0.0135), preoperative lower albumin (P = 0.0018) and malignancy (P = 0.0212) were independent risk factors for hospital mortality. CONCLUSIONS: Among old old patients undergoing elective gastrointestinal surgery, hospital mortality was increased significantly for patients with dementia evaluating with the MMSE.

Time-series gene expression patterns and their characteristics of Beauveria bassiana in the process of infecting pest insects.

Beauveria bassiana has been widely used as an important biological control fungus for agricultural and forest pests, and clarifying the interaction mechanism between B. bassiana and its host will help to better exert the efficacy of the mycoinsecticide. Here, we proposed a novel pattern analysis (PA) method for analyzing time-series data and applied it to a transcriptomic data set of B. bassiana infecting Galleria mellonella. We screened out 14 patterns including 868 genes, which had some characteristics that were not inferior to differentially expressed genes (DEGs). Compared with the previous analysis of this data set, we had three novel discoveries during B. bassiana infection, including overall downregulation of gene expression, the more critical first 24 h, and enrichment of regulatory functions of downregulated genes. Our new PA method promises to be an important complement to DEGs analysis for time-series transcriptomic data, and our findings enrich our knowledge of molecular mechanisms of fungal-host interactions.

m6A regulator expression profile predicts the prognosis, benefit of adjuvant chemotherapy, and response to anti-PD-1 immunotherapy in patients with small-cell lung cancer.

BACKGROUND: Small cell lung cancer (SCLC) is lethal and possesses limited therapeutic options. Platinum-based chemotherapy-with or without immune checkpoint inhibitors (anti-PDs)-is the current first-line therapy for SCLCs; however, its associated outcomes are heterogeneous. N6-methyladenosine (m6A) is a novel and decisive factor in tumour progression, chemotherapy resistance, and immunotherapy response. However, m6A modification in SCLC remains poorly understood. METHODS: We systematically explored the molecular features and clinical significance of m6A regulators in SCLC. We then constructed an m6A regulator-based prognostic signature (m6A score) based on our examination of 256 cases with limited-stage SCLC (LS-SCLC) from three different cohorts-including an independent cohort that contained 150 cases with qPCR data. We additionally evaluated the relationships between the m6A score and adjuvant chemotherapy (ACT) benefits and the patients' responses to anti-PD-1 treatment. Immunohistochemical (IHC) staining and the HALO digital pathological platform were used to calculate CD8+ T cell density. RESULTS: We observed abnormal somatic mutations and expressions of m6A regulators. Using the LASSO Cox model, a five-regulator-based (G3BP1, METTL5, ALKBH5, IGF2BP3, and RBM15B) m6A score was generated from the significant regulators to classify patients into high- and low-score groups. In the training cohort, patients with high scores had shorter overall survival (HR, 5.19; 2.75-9.77; P < 0.001). The prognostic accuracy of the m6A score was well validated in two independent cohorts (HR 4.6, P = 0.006 and HR 3.07, P < 0.001). Time-dependent ROC and C-index analyses found the m6A score to possess superior predictive power than other clinicopathological parameters. A multicentre multivariate analysis revealed the m6A score to be an independent prognostic indicator. Additionally, patients with low scores received a greater survival benefit from ACT, exhibited more CD8+ T cell infiltration, and were more responsive to cancer immunotherapy. CONCLUSIONS: Our results, for the first time, affirm the significance of m6A regulators in LS-SCLC. Our multicentre analysis found that the m6A score was a reliable prognostic tool for guiding chemotherapy and immunotherapy selections for patients with SCLC.

Survival Nomogram for Stage IB Non-Small-Cell Lung Cancer Patients, Based on the SEER Database and an External Validation Cohort.

OBJECTIVE: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with stage IB non-small-cell lung cancer (NSCLC). METHODS: In total, 5513 patients with stage IB NSCLC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database and used as the training cohort. We enrolled 440 patients from the Cancer Hospital, Chinese Academy of Medical Sciences, for the external validation cohort. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. The discrimination and calibration of the nomogram were evaluated by C-indexes and calibration curves. RESULTS: Six independent risk factors for OS were identified and integrated into the nomogram. The discrimination of the nomogram revealed good prognostic accuracy and clinical applicability as indicated by C-index values of 0.637 (95% CI 0.634-0.641) and 0.667 (95% CI 0.656-0.678) for the training cohort and the external validation cohort, respectively. Additionally, the patients were divided into two groups according to risk (sum-score > 185), and significant differences in OS were observed between the high-risk and low-risk groups in the training and external validation cohorts (P < 0.001). Finally, chemotherapy was significantly associated with OS in patients with differentiation grades II-IV (P = 0.004) and patients with adenocarcinoma (P = 0.005). CONCLUSION: This nomogram provides a convenient and reliable tool for individual evaluations and clinical decision-making for patients with stage IB NSCLC; among these patients, those with differentiation grades II-IV or adenocarcinoma could benefit from chemotherapy.

An immune-related lncRNA signature predicts prognosis and adjuvant chemotherapeutic response in patients with small-cell lung cancer.

BACKGROUND: Patients with small-cell lung cancer (SCLC) are burdened by limited treatment options and the disease's dismal prognosis. Long non-coding RNAs (lncRNAs) are essential regulators of genetic alteration and are actively involved in tumor immunity. However, few studies have examined interactions between immune genes and lncRNAs in SCLC. METHODS: Immune-related lncRNA (irlncRNA) expression profiles and their clinical significance were explored. We enrolled 227 patients with SCLC, including 79 cases from GSE65002 and 148 cases from a validation cohort with corresponding qPCR data. The least absolute shrinkage and selection operator (LASSO) model was applied to identify prognostic irlncRNAs for an irlncRNA-based SCLC signature. We additionally investigated the potential mechanisms and immune landscape of the signature using bioinformatics methods. RESULTS: An irlncRNA signature including 8 irlncRNAs (ENOX1-AS1, AC005162, LINC00092, RPL34-AS1, AC104135, AC015971, AC126544, AP001189) was established for patients with SCLC in the training cohort. Low-risk patients were more likely to benefit from chemotherapy and achieve a favorable prognosis. The signature was also well-validated in the validation cohort and various clinical subgroups. Compared to other clinical parameters, the irlncRNA signature exhibited superior predictive performance for chemotherapy response and prognosis. The signature was as an independent prognostic factor in the training and validation cohorts. Interestingly, low-risk patients showed an activated immune phenotype. CONCLUSION: We constructed the first irlncRNA-based signature for chemotherapy efficacy and outcome prediction. The irlncRNA signature is a reliable and robust prognostic classifier that could be useful for clinical management and determination of potential chemotherapy benefit for patients with SCLC.

The prognostic value of tumor deposits and the impact on the TNM classification system in esophageal cancer patients.

OBJECTIVE: To explore the prognostic significance of tumor deposits (TDs), isolated tumor foci lacking residual lymph nodes, in esophageal cancer (EC). METHODS: A retrospective review of patients with EC undergoing esophagectomy between 2005 and 2017 was conducted. The prognostic value of TD was evaluated using a Cox regression model. Patients from different sources and periods were split into discovery and validation sets. A propensity score matching model was used in the validation set to reduce the confounding bias. The impact of TD on the TNM classification system was evaluated. RESULTS: The discovery and validation sets included 179 and 2875 patients, respectively. Propensity-matched patients with and without TDs were constructed in the validation set with 132 patients in each group. Overall survival (p < .001 and p = .004, respectively) and disease-free survival (p < .001 and p = .019, respectively) were both decreased in TD positive patients in the discovery set and propensity-matched groups of validation set. Classifying patients with TDs into pN3 stage improved the discriminative power of the current TNM staging system. CONCLUSIONS: TD is an independent prognostic factor for EC. The inclusion of TD in the TNM staging system may upstage appropriate patients to help guide therapy, and future studies are warranted.

miR-4458 regulates cell proliferation and apoptosis through targeting SOCS1 in triple-negative breast cancer.

Our previous study has suggested suppressor of cytokine signaling 1 (SOCS1) is associated with clinical progression and functions as an oncogenic role to regulate cell proliferation and apoptosis in triple-negative breast cancer (TNBC). Several microRNA-messenger RNA (miRNA-mRNA) relationship databases show SOCS1 is identified as a direct target gene of miRNA-4458 (miR-4458). The purpose of this study was to study the relationship between miR-4458 and SOCS1 in TNBC. In our results, miR-4458 expression was decreased in TNBC tissues and cells compared with adjacent normal tissues and normal mammary epithelial cell line, respectively. Moreover, miR-4458 directly bound to SOCS1, and negatively regulated SOCS1 mRNA and protein expression. Furthermore, miR-4458 suppressed cell proliferation and promote cell apoptosis through regulating SOCS1 in TNBC. Besides, levels of miR-4458 expression in patients with advanced clinical stage were obviously lower than in patients with early clinical stage. In conclusion, miR-4458 mediates SOCS1 to play a tumor-suppressive role in TNBC.

HIF1A-AS2 predicts poor prognosis and regulates cell migration and invasion in triple-negative breast cancer.

The aberrant expression of hypoxia-inducible factor 1 alpha (HIF1A)-antisense RNA 2 (HIF1A-AS2) was found in various human cancers including breast cancer. The aim of this study was to present more evidence about the role HIF1A-AS2 on triple-negative breast cancer (TNBC). In our results, HIF1A-AS2 was also found to be upregulated in TNBC tissues compared with non-TNBC tissues or adjacent normal tissues. Besides, HIF1A-AS2 expression was also elevated in TNBC cell lines compared with the normal breast epithelial cell line. Moreover, high expression of HIF1A-AS2 was associated with lymph node metastasis, distant metastasis and unfavorable histological grade in TNBC patients. Survival analysis showed a TNBC patient with high HIF1A-AS2 expression had shorter overall survival than patients with low HIF1A-AS2 expression, and HIF1A-AS2 high expression acted as an independent poor prognostic factor for overall survival in TNBC patients. The cell migration and invasion assays suggested inhibition of HIF1A-AS2 obviously depressed TNBC cell migration and invasion. In conclusion, HIF1A-AS2 serves as a novel biomarker for predicting clinical progression and prognosis in TNBC.