Circ0060467 sponges miR-6805 to promote hepatocellular carcinoma progression through regulating AIFM2 and GPX4 expression.

BACKGROUND: Circular RNAs (circRNAs) represent a subset of non-coding RNAs implicated in the regulation of diverse biological processes, including tumorigenesis. However, the expression and functional implications of circ0060467 in hepatocellular carcinoma (HCC) remain elusive. In this study, we aimed to elucidate the role of circ0060467 in modulating the progression of HCC. METHODS: Differentially expressed circRNAs in HCC tissues were identified through circRNA microarray assays. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) assays revealed the upregulation of circ0060467 in both HCC cell lines and tissues. Various assays were conducted to investigate the roles of circ0060467 in HCC progression. Additionally, RNA immunoprecipitation (RIP) assays and luciferase assays were carried out to assess the interactions between circ0060467, microRNA-6085 (miR-6085), apoptosis-inducing factor mitochondria-associated 2 (AIFM2), and glutathione peroxidase 4 (GPX4) in HCC. RESULTS: Microarray and qRT-PCR analyses demonstrated a marked elevation of circ0060467 in HCC tissues and cell lines. Knockdown of circ0060467 suppressed HCC cell proliferation. Luciferase reporter and RIP assays confirmed the binding of circ0060467, AIFM2, and GPX4 to miR-6805. Subsequent experiments revealed that circ0060467 competes with AIFM2 and GPX4, thereby inhibiting cancer cell ferroptosis by binding to miR-6085 and promoting hepatocellular carcinoma progression. CONCLUSIONS: Collectively, circ0060467 modulates the levels of AIFM2 and GPX4, crucial regulators of tumor cell ferroptosis, by acting as a sponge for miR-6085 in HCC. Thus, circ0060467 may represent a novel diagnostic marker and therapeutic target for HCC.

Hemophagocytic lymphohistiocytosis after autologous stem cell transplantation in angioimmunoblastic T-cell lymphoma: A case report.

BACKGROUND: Angioimmunoblastic T-cell lymphoma (AITL), a unique subtype of peripheral T-cell lymphoma, has relatively poor outcomes. High-dose chemotherapy with autologous stem cell transplantation (ASCT) can achieve complete remission and improve outcomes. Unfortunately, subsequent T-cell lymphoma-triggered hemophagocytic lymphohistiocytosis (HLH) has a worse prognosis than B-cell lymphoma-triggered HLH. CASE SUMMARY: We here report a 50-year-old woman with AITL who achieved a favorable outcome after developing HLH 2 mo after receiving high-dose chemotherapy/ ASCT. The patient was initially admitted to our hospital because of multiple enlarged lymph nodes. The final pathologic diagnosis, made on biopsy of a left axillary lymph node was AITL (Stage IV, Group A). Four cycles of the following chemotherapy regimen were administered: Cyclophosphamide 1.3 g, doxorubicin 86 mg, and vincristine 2 mg on day 1; prednisone 100 mg on days 1-5; and lenalidomide 25 mg on days 1-14. The interval between each cycle was 21 d. The patient received a conditioning regimen (busulfan, cyclophosphamide, and etoposide) followed by peripheral blood stem cell infusion. Unfortunately, she developed sustained fever and a low platelet count 17 d after ACST, leading to a diagnosis of HLH after ASCT. During treatment, she experienced thrombocytopenia and Pneumocystis carinii pneumonia. The patient was successfully treated with etoposide and glucocorticoids. CONCLUSION: It is possible that development of HLH is related to immune reconstitution after ASCT.

Efficacy and safety of different PD-1 inhibitors in combination with lenvatinib in the treatment of unresectable primary liver cancer: a multicentre retrospective study.

Immune checkpoint inhibitors (ICIs) are safe and efficacious treatments for advanced primary liver cancer (PLC). The efficacy of different ICIs in the treatment of liver cancer remains unclear. The purpose of this study was to explore whether there is a difference in the efficacy and safety of various programmed cell death protein 1 (PD-1) inhibitors in combination with lenvatinib in the treatment of unresectable PLC. Patients with PLC treated with lenvatinib in combination with PD-1 inhibitors (camrelizumab, tislelizumab, sintilimab, or pembrolizumab) between January 2018 and December 2021 were retrospectively enrolled. Tumor response, adverse events, and grades were evaluated. Kaplan-Meier analysis and log-rank test were used to compare the overall survival and progression-free survival of patients treated with different PD-1 inhibitors. Cox regression analysis was used for univariate and multivariate analyses to identify clinical variables related to treatment efficacy. This study included a total of 176 patients who received a combination of lenvatinib and PD-1 inhibitors. Of these, 103 patients received camrelizumab, 44 received tislelizumab, 20 received sintilimab, and 9 received pembrolizumab. There was no significant difference in the pairwise comparison of camrelizumab, tislelizumab, sintilimab, and pembrolizumab using Kaplan-Meier survival analysis. Adverse events occurred in 40 (22.7%) patients (grade ≥ 3, 2.3%). The incidence of grade 3 adverse events among the four PD-1 inhibitor groups was below 5%. Camrelizumab, tislelizumab, sintilimab, and pembrolizumab are viable options for patients with unresectable PLC. These PD-1 inhibitors in combination with lenvatinib showed good safety profiles. The results guide selecting treatment for patients with unresectable PLC.

Predictive Value of the Hepatic Immune Predictive Index for Patients with Primary Liver Cancer Treated with Immune Checkpoint Inhibitors.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have improved survival outcomes and resulted in long-term responses in primary liver cancer in some patients. Nevertheless, not all patients with PLC could benefit from immunotherapy. Therefore, it is necessary to identify patients suitable for such therapy. METHODS: 215 patients with primary liver cancer with immunotherapy from Nanfang Hospital were screened between August 2018 and October 2020 as a training set and our validation set included 71 patients of hepatocellular carcinoma from Jiangxi Cancer Hospital from May 2019 to July 2021. The primary endpoint was the disease control rate (DCR), and the secondary endpoints were overall survival (OS) and progression-free survival. RESULTS: In the training set, neutrophil-lymphocyte ratio (NLR) ≥3 and alpha-fetoprotein (AFP) level ≥20 ng/mL were independently associated with non-DCR in the training set after adjusting for distant metastasis at baseline and targeted therapy combination. Furthermore, a hepatic immune predictive index (HIPI) based on NLR and AFP level was developed and patients with poor HIPI associated with worse clinical outcomes. In validation set, high HIPI was associated with poor OS. CONCLUSION: HIPI, based on NLR and AFP level, is an effective indicator in ICI-treated patients with primary liver cancer. Our findings may help guide the selection and on-treatment strategies for immunotherapies for primary liver cancer patients.

CT images-based 3D convolutional neural network to predict early recurrence of solitary hepatocellular carcinoma after radical hepatectomy.

PURPOSE The high rate of recurrence of hepatocellular carcinoma (HCC) after radical hepatectomy is an important factor that affects the long-term survival of patients. This study aimed to develop a computed tomography (CT) images-based 3-dimensional (3D) convolutional neural network (CNN) for the preoperative prediction of early recurrence (ER) (≤2 years) after radical hepatectomy in patients with solitary HCC and to compare the effects of segmentation sampling (SS) and non-segmentation sampling (NSS) on the prediction performance of 3D-CNN. METHODS Contrast-enhanced CT images of 220 HCC patients were used in this study (training group=178 and test group=42). We used SS and NSS to select the volume-of-interest to train SS-3D-CNN and NSS-3D-CNN separately. The prediction accuracy was evaluated using the test group. Finally, gradient-weighted class activation mappings (Grad-CAMs) were plotted to analyze the difference of prediction logic between the SS-3D-CNN and NSS-3D-CNN. RESULTS The areas under the receiver operating characteristic curves (AUCs) of the SS-3D-CNN and NSS3D-CNN in the training group were 0.824 (95% CI: 0.764-0.885) and 0.868 (95% CI: 0.815-0.921). The AUC of the SS-3D-CNN and NSS-3D-CNN in the test group were 0.789 (95% CI: 0.637-0.941) and 0.560 (95% CI: 0.378-0.742). The SS-3D-CNN could stratify patients into low- and high-risk groups, with significant differences in recurrence-free survival (RFS) (P < .001). But NSS-3D-CNN could not effectively stratify them in the test group. According to the Grad-CAMs, compared with SS-3D-CNN, NSS-3D-CNN was obviously interfered by the nearby tissues. CONCLUSION SS-3D-CNN may be of clinical use for identifying high-risk patients and formulating individualized treatment and follow-up strategies. SS is better than NSS in improving the performance of 3D-CNN in our study.

Use of computed tomography-derived body composition to determine the prognosis of patients with primary liver cancer treated with immune checkpoint inhibitors: a retrospective cohort study.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have been used to successfully treat primary liver cancer (PLC); however, identifying modifiable patient factors associated with therapeutic benefits is challenging. Obesity is known to be associated with increased survival after ICI treatment; however, the relationship between body composition (muscle, fat) and outcomes is unclear. This study aimed to evaluate the association between sarcopenia and CT-derived fat content and the prognosis of ICIs for the treatment of PLC. METHODS: In this retrospective cohort study of 172 patients with PLC, we measured the skeletal muscle index (SMI), skeletal muscle density, visceral adipose tissue index, subcutaneous adipose tissue index, total adipose tissue index (TATI), and visceral-to-subcutaneous adipose tissue area ratio using CT. In addition, we analyzed the impact of body composition on the prognosis of the patients. Multivariate Cox regression analysis was used to screen for influencing factors. RESULTS: Among the seven body composition components, low SMI (sarcopenia) and low TATI were significantly associated with poor clinical outcomes. Multivariate analysis revealed that sarcopenia (hazard ratio [HR], 5.39; 95% confidence interval [CI], 1.74-16.74; p = 0.004) was a significant predictor of overall survival (OS). Kaplan-Meier curves showed that sarcopenia and TATI were significant predictors of OS. Body mass index was not associated with survival outcomes. CONCLUSIONS: Sarcopenia and fat tissue content appear to be independently associated with reduced survival rates in patients with PLC treated with ICIs.

Splenomegaly in predicting the survival of patients with advanced primary liver cancer treated with immune checkpoint inhibitors.

BACKGROUND & AIMS: Immune checkpoint inhibitors (ICIs) play an increasingly important role in the treatment of primary liver cancer (PLC). Some patients with PLC experience symptoms of splenomegaly. Splenomegaly may affect the efficacy of ICIs due to an imbalance of the immune microenvironment. Currently, there is a lack of evidence on the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs. This study analyzed the relationship between splenomegaly and prognosis in patients with PLC treated with ICIs. METHODS: In this retrospective cohort study of 161 patients with PLC treated with ICIs, splenomegaly was diagnosed using computed tomography or magnetic resonance imaging and the impact of splenomegaly on patient survival was analyzed. RESULTS: Through univariate and multivariate Cox regression analyses, we determined that splenomegaly was associated with shortened overall survival (p = 0.002) and progression-free survival (p = 0.013) in patients with PLC treated with ICIs. Kaplan-Meier analysis further validated our results. The overall survival and progression-free survival of patients with splenomegaly were significantly shorter than those of patients without splenomegaly (p < 0.01 and p = 0.02, respectively). CONCLUSIONS: We concluded that splenomegaly was a predictor of prognosis in patients with PLC treated with ICIs. This is the first study to report this important finding.

Gemcitabine Combined with Cisplatin Has a Better Effect in the Treatment of Recurrent/Metastatic Advanced Nasopharyngeal Carcinoma.

Objective: To explore the efficacy and safety of gemcitabine (GEM) combined with cisplatin (DDP) in the treatment of recurrent/metastatic nasopharyngeal carcinoma (NPC). Methods: A total of 100 patients with recurrent/metastatic NPC treated in the First Affiliated Hospital, Hengyang Medical School, University of South China from January 2018 to March 2020 were retrospectively enrolled. Based on different chemotherapy schemes, they were assigned to an observation (Obs) group (DDP + GEM, n = 55) and a control (Con) group [DDP + FU (fluorouracil), n = 45]. The two groups were compared regarding the following items: therapeutic efficacy; serum levels of platelet-derived growth factor-BB (PDGF-BB), soluble epithelial cadherin (SE-CAD), and inflammation-related factors before and after treatment; toxic and side effects; 1-year survival rate; and quality of life (QOL) 6 months after treatment. Results: The Obs group outperformed the Con group in therapeutic efficacy (P < 0.05). There were no significant differences in the levels of PDGF-BB, SE-CAD, interleukin (IL)-6, IL-10 and tumor necrosis factor (TNF)-α between the two groups before treatment (P > 0.05). After treatment, better improvements in PDGF-BB, SE-CAD and inflammatory factors were observed in the Obs group (P < 0.05). The toxic and side effects were significantly lower and the 1-year survival rate and patients' QOL after 6 months of treatment were significantly higher in the Obs group compared with the Con group (P < 0.05). Conclusion: GEM combined with DDP can provide more clinical benefits for patients with recurrent/metastatic advanced NPC, with less side effects, high tolerance and significant efficacy, which can be further promoted in clinical use.

Identification of MATN3 as a Novel Prognostic Biomarker for Gastric Cancer through Comprehensive TCGA and GEO Data Mining.

Gastric cancer (GC) is still a vital malignant cancer across the world with unsatisfactory prognostic results. Matrilin-3 (MATN3) is a member of the extracellular matrix (ECM) protein family. The present research intends to explore the expression level of MATN3 in patients with GC and to explore the prognosis significance of MATN3. In this study, we observed that the MATN3 expression was remarkably upregulated in GC samples in contrast to noncancer samples. Clinical analyses unveiled that high MATN3 expression was related to age, tumor status, and clinical stages. Survival analyses unveiled that patients with high MATN3 expression displayed a poorer overall survival and progression-free survival than those with low MATN3 expression. The AUC of the relevant ROC curve for 1 year, 3 years, and 5 years of survival is 0.571, 0.596, and 0.720, separately. Multivariate assays revealed that MATN3 expression and stage were independent predictors of poor prognosis of GC patients. A meta-analysis unveiled that high MATN3 expression was tightly associated with better overall survival. Overall, our data indicated that MATN3 may have a diagnostic and prognostic value for patients with advanced gastric cancer and assist to improve clinical outcomes for GC patients.

Lung metastasis and lymph node metastasis are risk factors for hyperprogressive disease in primary liver cancer patients treated with immune checkpoint inhibitors.

BACKGROUND: At present, some cancer patients experience hyperprogressive disease (HPD) after receiving immunotherapy. This study used the Response Evaluation Criteria in Solid Tumors 1.1 to evaluate the incidence of HPD in patients receiving immune checkpoint inhibitors (ICIs) for treating primary liver cancer (PLC) and to explore the risk factors for HPD. METHODS: This retrospective, single-center study included patients with PLC who were treated with ICIs. The RECIST 1.1 was used to determine patients with HPD. Univariate and multivariate regression analyses were performed to explore the risk factors for HPD, and clinical variables with prognostic significance for HPD were included to establish a risk model. RESULTS: Among 129 patients with PLC treated with ICIs, HPD occurred in 13 patients (10.1%). In the multivariate regression analysis, lymph node metastasis and lung metastasis were risk factors for HPD. The area under the curve of the risk model, established by including lymph node metastasis, lung metastasis, neutrophil-lymphocyte ratio, albumin, and performance status, was 0.801 (P<0.001). The progression-free survival of HPD patients was significantly worse than that of non-HPD patients (P<0.001). CONCLUSIONS: In this study, 10.1% of patients with PLC had HPD. Compared with the non-HPD patients, lung metastasis and lymph node metastasis were independent risk factors of HPD.

De Novo Mutation in Non-Tyrosine Kinase Domain of ROS1 as a Potential Predictor of Immune Checkpoint Inhibitors in Melanoma.

PURPOSE: Despite the success of targeted therapy in c-ros oncogene 1 (ROS1)-rearranged cancers, especially non-small cell lung cancer (NSCLC), the clinical significance of ROS1 de novo mutation has not yet been understood. We sought to elucidate the predictive effect of ROS1 mutation for immune checkpoint inhibitor (ICI) therapy in melanoma. METHODS: The Cancer Genome Atlas [TCGA (n = 10967)] and Memorial Sloan Kettering Cancer Center [MSK (n = 10,945)] datasets, as well as two clinical cohorts of melanoma received ICI [CA209-038 (n = 73) and MEL-IPI (n = 110)], were included to explore the prevalence, prognostic effect, and immunotherapeutic predictive effect of ROS1 mutation in melanoma. Overall survival (OS) was defined as the primary outcome. RESULTS: Overall, melanoma accounted for the highest proportion of ROS1 mutation (~20%) which made up the majority (~95%) of the ROS1-alterated cases. Remarkably, ROS1 mutation yielded longer OS from ICI than the wild-type counterpart in the MSK melanoma population [hazard ratio (HR) 0.47, 95% confidence interval (CI) 0.30-0.74], and two external melanoma cohorts (CA209-038: HR 0.42, 95% CI 0.20-0.89; MEL-IPI: HR 0.55, 95% CI 0.34-0.91), without affecting the prognosis of patients. Elevated tumor mutational burden and enrichment of DNA damage repair was observed in ROS1 mutated patients, providing an explanation for the favorable responses to ICI therapy. Precisely, ROS1 mutation in non-protein tyrosine kinase (PTK) domain but not PTK mutation was responsible for the immunotherapy-specific responses of the ROS1 mutated patients in melanoma. CONCLUSIONS: Collectively, ROS1 mutation, specifically the non-PTK mutation, is a potential predictor of ICI therapy in melanoma, which is distinct from the well-established role of ROS1 rearrangement for targeted therapy in NSCLC.

Integrative evaluation of primary and metastatic lesion spectrum to guide anti-PD-L1 therapy of non-small cell lung cancer: results from two randomized studies.

Objectives: Clinical benefits of immune-checkpoint blockade (ICB) versus standard chemotherapy have been established in unselected non-small cell lung cancer (NSCLC). However, the response to ICB therapy among patients is heterogeneous in clinical practice. Materials and Methods: We retrospectively assessed the predicitive effect of the primary and metastatic lesion spectrum (baseline sum of the longest diameters [SLD], number of metastatic sites and specific organ metastases) on the efficacy of atezolizumab over docetaxel in OAK and POPLAR trial cohorts. A decision model, termed DSO (Diameter-Site-Organ), based on the spectrum was developed and validated for guiding ICB. Results: Higher SLD (>38 mm) and more metastatic sites (≥2) were characterized with pronounced overall survival (OS) benefits from atezolizumab versus docetaxel. Specifically, adrenal gland and brain metastases were identified as favorable predictors of atezolizumab treatment. The DSO model was developed in the discovery cohort to integrate the directive effect of the primary and metastatic lesion spectrum. Remarkably, a general pattern of enhanced efficacy of atezolizumab versus docetaxel was observed along with the increase of the DSO score. For patients with DSO score > 0, atezolizumab yielded a significantly prolonged OS than docetaxel, whereas OS was generally similar between two treatments in patients with DSO score ≤ 0. Equivalent findings were also seen in the internal and external validation cohorts. Conclusions: The response to anti-PD-L1 therapy among patients varied with the primary and metastatic lesion spectrum. The DSO-based system might provide promising medication guidance for ICB treatment in NSCLC patients.

Development and interpretation of a pathomics-based model for the prediction of microsatellite instability in Colorectal Cancer.

Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation. Methods: Two cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from an Asian colorectal cancer (CRC) cohort (Asian-CRC). We established the pathomics model, named Ensembled Patch Likelihood Aggregation (EPLA), based on two consecutive stages: patch-level prediction and WSI-level prediction. The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model were analyzed with genomic and transcriptomic profiles for model interpretation. Results: The EPLA model achieved an area-under-the-curve (AUC) of 0.8848 (95% CI: 0.8185-0.9512) in the TCGA-COAD test set and an AUC of 0.8504 (95% CI: 0.7591-0.9323) in the external validation set Asian-CRC after transfer learning. Notably, EPLA captured the relationship between pathological phenotype of poor differentiation and MSI (P < 0.001). Furthermore, the five pathological imaging signatures identified from the EPLA model were associated with mutation burden and DNA damage repair related genotype in the genomic profiles, and antitumor immunity activated pathway in the transcriptomic profiles. Conclusions: Our pathomics-based deep learning model can effectively predict MSI from histopathology images and is transferable to a new patient cohort. The interpretability of our model by association with pathological, genomic and transcriptomic phenotypes lays the foundation for prospective clinical trials of the application of this artificial intelligence (AI) platform in ICB therapy.

Development and validation of the HNC-LL score for predicting the severity of coronavirus disease 2019.

BACKGROUND: Information regarding risk factors associated with severe coronavirus disease (COVID-19) is limited. This study aimed to develop a model for predicting COVID-19 severity. METHODS: Overall, 690 patients with confirmed COVID-19 were recruited between 1 January and 18 March 2020 from hospitals in Honghu and Nanchang; finally, 442 patients were assessed. Data were categorised into the training and test sets to develop and validate the model, respectively. FINDINGS: A predictive HNC-LL (Hypertension, Neutrophil count, C-reactive protein, Lymphocyte count, Lactate dehydrogenase) score was established using multivariate logistic regression analysis. The HNC-LL score accurately predicted disease severity in the Honghu training cohort (area under the curve [AUC]=0.861, 95% confidence interval [CI]: 0.800-0.922; P<0.001); Honghu internal validation cohort (AUC=0.871, 95% CI: 0.769-0.972; P<0.001); and Nanchang external validation cohort (AUC=0.826, 95% CI: 0.746-0.907; P<0.001) and outperformed other models, including CURB-65 (confusion, uraemia, respiratory rate, BP, age ≥65 years) score model, MuLBSTA (multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension, and age) score model, and neutrophil-to-lymphocyte ratio model. The clinical significance of HNC-LL in accurately predicting the risk of future development of severe COVID-19 was confirmed. INTERPRETATION: We developed an accurate tool for predicting disease severity among COVID-19 patients. This model can potentially be used to identify patients at risks of developing severe disease in the early stage and therefore guide treatment decisions. FUNDING: This work was supported by the National Nature Science Foundation of China (grant no. 81972897) and Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme (2015).

Development and validation of a genomic mutation signature to predict response to PD-1 inhibitors in non-squamous NSCLC: a multicohort study

BACKGROUND: Genetic variations of some driver genes in non-small cell lung cancer (NSCLC) had shown potential impact on immune microenvironment and associated with response or resistance to programmed cell death protein 1 (PD-1) blockade immunotherapy. We therefore undertook an exploratory analysis to develop a genomic mutation signature (GMS) and predict the response to anti-PD-(L)1 therapy. METHODS: In this multicohort analysis, 316 patients with non-squamous NSCLC treated with anti-PD-(L)1 from three independent cohorts were included in our study. Tumor samples from the patients were molecularly profiled by MSK-IMPACT or whole exome sequencing. We developed a risk model named GMS based on the MSK training cohort (n=123). The predictive model was first validated in the separate internal MSK cohort (n=82) and then validated in an external cohort containing 111 patients from previously published clinical trials. RESULTS: A GMS risk model consisting of eight genes (TP53, KRAS, STK11, EGFR, PTPRD, KMT2C, SMAD4, and HGF) was generated to classify patients into high and low GMS groups in the training cohort. Patients with high GMS in the training cohort had longer progression-free survival (hazard ratio (HR) 0.41, 0.28-0.61, p<0.0001) and overall survival (HR 0.53, 0.32-0.89, p=0.0275) compared with low GMS. We noted equivalent findings in the internal validation cohort and in the external validation cohort. The GMS was demonstrated as an independent predictive factor for anti-PD-(L)1 therapy comparing with tumor mutational burden. Meanwhile, GMS showed undifferentiated predictive value in patients with different clinicopathological features. Notably, both GMS and PD-L1 were independent predictors and demonstrated poorly correlated; inclusion of PD-L1 with GMS further improved the predictive capacity for PD-1 blockade immunotherapy. CONCLUSIONS: Our study highlights the potential predictive value of GMS for immunotherapeutic benefit in non-squamous NSCLC. Besides, the combination of GMS and PD-L1 may serve as an optimal partner in guiding treatment decisions for anti-PD-(L)1 based therapy.

circRNA_100859 functions as an oncogene in colon cancer by sponging the miR-217-HIF-1α pathway.

Circular RNAs (circRNAs) play an important role in cancer development and progression by regulating gene expression. The present study aimed to investigate the function of circRNA_100859 in colon cancer. circRNA expression profiles from a human circRNAs chip were analyzed. The effects of circRNA_100859 on cell proliferation and apoptosis were assessed in vitro and interactions between circRNA_100859 and its micro (mi)RNA and target genes were analyzed. The diagnostic and prognostic significance of circRNA_100859 was also investigated. It was identified that circRNA_100859 was overexpressed in colon cancer tissues and promoted cell proliferation and inhibited cell apoptosis. Additionally, bioinformatics and a dual-luciferase reporter assay confirmed that circRNA_100859 acted as a miR-217 sponge, and miR-217 directly targeted hypoxia-inducible factor (HIF)-1α. Rescue assays demonstrated that HIF-1α protein and mRNA expression levels and cell proliferation were regulated by the circRNA_100859/miR-217 axis (P<0.05). Furthermore, statistical analysis showed that the circRNA_100859-miR-217-HIF-1α axis was associated with Tumor-Node-Metastasis (TNM) stage, histological grade, and KRAS mutations, and also showed high diagnostic and prognostic value for patients with colon cancer (P<0.05). Therefore, it was concluded that circRNA_100859 functions as an oncogene in colon cancer by sponging the miR-217-HIF-1α pathway. In addition, the circRNA_100859-miR-217-HIF-1α axis may serve as a novel diagnostic and prognostic biomarker for patients with colon cancer.

Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma.

PURPOSE: The aim of this study was to develop and validate a radiomics nomogram based on radiomics features and clinical data for the non-invasive preoperative prediction of early recurrence (≤2 years) in patients with hepatocellular carcinoma (HCC). METHODS: We enrolled 262 HCC patients who underwent preoperative contrast-enhanced computed tomography and curative resection (training cohort, n=214; validation cohort, n=48). We applied propensity score matching (PSM) to eliminate redundancy between clinical characteristics and image features, and the least absolute shrinkage and selection operator (LASSO) was used to prevent overfitting. Next, a radiomics signature, clinical nomogram, and combined clinical-radiomics nomogram were built to predict early recurrence, and we compared the performance and generalization of these models. RESULTS: The radiomics signature stratified patients into low-risk and high-risk, which show significantly difference in recurrence free survival and overall survival (P ≤ 0.01). Multivariable analysis identified dichotomised radiomics signature, alpha fetoprotein, and tumour number and size as key early recurrence indicators, which were incorporated into clinical and radiomics nomograms. The radiomics nomogram showed the highest area under the receiver operating characteristic curve (AUC), with significantly superior predictive performance over the clinical nomogram in the training cohort (0.800 vs 0.716, respectively; P = 0.001) and the validation cohort (0.785 vs 0.654, respectively; P = 0.039). CONCLUSION: The radiomics nomogram is a non-invasive preoperative biomarker for predicting early recurrence in patients with HCC. This model may be of clinical utility for guiding surveillance follow-ups and identifying optimal interventional strategies.

Correlation Between Local Air Temperature and the COVID-19 Pandemic in Hubei, China.

Objective: To clarify the correlation between temperature and the COVID-19 pandemic in Hubei. Methods: We collected daily newly confirmed COVID-19 cases and daily temperature for six cities in Hubei Province, assessed their correlations, and established regression models. Results: For temperatures ranging from -3.9 to 16.5°C, daily newly confirmed cases were positively correlated with the maximum temperature ~0-4 days prior or the minimum temperature ~11-14 days prior to the diagnosis in almost all selected cities. An increase in the maximum temperature 4 days prior by 1°C was associated with an increase in the daily newly confirmed cases (~129) in Wuhan. The influence of temperature on the daily newly confirmed cases in Wuhan was much more significant than in other cities. Conclusion: Government departments in areas where temperatures range between -3.9 and 16.5°C and rise gradually must take more active measures to address the COVID-19 pandemic.

Combination of TMB and CNA Stratifies Prognostic and Predictive Responses to Immunotherapy Across Metastatic Cancer.

PURPOSE: Although tumor mutation burden (TMB) has been well known to predict the response to immune checkpoint inhibitors (ICI), lack of randomized clinical trial data has restricted its clinical application. This study aimed to explore the significance and feasibility of biomarker combination based on TMB and copy-number alteration (CNA) for the prognosis of each tumor and prediction for ICI therapy in metastatic pan-cancer milieu. EXPERIMENTAL DESIGN: Non-ICI-treated MSK pan-cancer cohort was used for prognosis analysis. Three independent immunotherapy cohorts, including non-small cell lung cancer (n = 240), skin cutaneous melanoma (n = 174), and mixed cancer (Dana-Farber, n = 98) patients from previous studies, were analyzed for efficacy of ICI therapy. RESULTS: TMB and CNA showed optimized combination for the prognosis of most metastatic cancer types, and patients with TMBlowCNAlow showed better survival. In the predictive analysis, both TMB and CNA were independent predictive factors for ICI therapy. Remarkably, when TMB and CNA were jointly analyzed, those with TMBhighCNAlow showed favorable responses to ICI therapy. Meanwhile, TMBhighCNAlow as a new biomarker showed better prediction for ICI efficacy compared with either TMB-high or CNA-low alone. Furthermore, analysis of the non-ICI-treated MSK pan-cancer cohort supported that the joint stratification of TMB and CNA can be used to categorize tumors into distinct sensitivity to ICI therapy across pan-tumors. CONCLUSIONS: The combination of TMB and CNA can jointly stratify multiple metastatic tumors into groups with different prognosis and heterogeneous clinical responses to ICI treatment. Patients with TMBhighCNAlow cancer can be an optimal subgroup for ICI therapy.

Efficacy and safety of preoperative chemoembolization for resectable hepatocellular carcinoma with portal vein invasion: a prospective comparative study.

OBJECTIVES: To evaluate the outcomes of preoperative transarterial chemoembolization (TACE) for resectable hepatocellular carcinoma (HCC) with portal vein invasion. METHODS: From February 2006 to July 2011, 320 patients initially diagnosed with resectable HCC and portal vein invasion were prospectively non-randomized into two arms. In the immediate resection arm (Arm 1, n = 205) patients received immediate surgical resection. 115 patients were included in the preoperative TACE arm (Arm 2), and eventually 85 patients underwent TACE followed by surgical resection. RESULTS: The 1-, 3- and 5-year overall survival rates were 48.3 %, 18.7 % and 13.9 % for Arm 1 and 61.2 %, 31.7 % and 25.3 % for Arm 2 (P = 0.001), respectively. In the subgroup analysis of types I and II portal vein tumour thrombus (PVTT), the preoperative TACE arm demonstrated significantly better survival rates than the immediate resection arm (P I = 0.001, P II = 0.036). However, no significant difference was found for patients with type III PVTT (P III = 0.684). No significant difference was found between the two arms in terms of complications and mortality. CONCLUSIONS: Preoperative TACE seems to confer a survival benefit for resectable HCC with PVTT, especially for types I and II PVTT, and preoperative TACE should therefore be recommended as a routine procedure. KEY POINTS: • Preoperative TACE improves the clinical outcomes for patients with PVTT • Preoperative TACE could significantly improve the rate of en bloc thrombectomy • Preoperative TACE does not increase the related adverse events.