68Ga-FAPI-04 PET/CT in Non-Small Cell Lung Cancer: Accurate Evaluation of Lymph Node Metastasis and Correlation with Fibroblast Activation Protein Expression.

Fibroblast activation protein (FAP) is a promising diagnostic and therapeutic target in various solid tumors. This study aimed to assess the diagnostic efficiency of 68Ga-labeled FAP inhibitor (FAPI)-04 PET/CT for detecting lymph node metastasis in non-small cell lung cancer (NSCLC) and to investigate the correlation between tumor 68Ga-FAPI-04 uptake and FAP expression. Methods: We retrospectively enrolled 136 participants with suspected or biopsy-confirmed NSCLC who underwent 68Ga-FAPI-04 PET/CT for initial staging. The diagnostic performance of 68Ga-FAPI-04 for the detection of NSCLC was evaluated. The final histopathology or typical imaging features were used as the reference standard. The SUVmax and SUVmean, 68Ga-FAPI-avid tumor volume (FTV), and total lesion FAP expression (TLF) were measured and calculated. FAP immunostaining of tissue specimens was performed. The correlation between 68Ga-FAPI-04 uptake and FAP expression was assessed using the Spearman correlation coefficient. Results: Ninety-one participants (median age, 65 y [interquartile range, 58-70 y]; 69 men) with NSCLC were finally analyzed. In lesion-based analysis, the diagnostic sensitivity and positive predictive value of 68Ga-FAPI-04 PET/CT for detection of the primary tumor were 96.70% (88/91) and 100% (88/88), respectively. In station-based analysis, the diagnostic sensitivity, specificity, and accuracy for the detection of lymph node metastasis were 72.00% (18/25), 93.10% (108/116), and 89.36% (126/141), respectively. Tumor 68Ga-FAPI-04 uptake (SUVmax, SUVmean, FTV, and TLF) correlated positively with FAP expression (r = 0.470, 0.477, 0.582, and 0.608, respectively; all P ≤ 0.001). The volume parameters FTV and TLF correlated strongly with FAP expression in 31 surgical specimens (r = 0.700 and 0.770, respectively; both P < 0.001). Conclusion: 68Ga-FAPI-04 PET/CT had excellent diagnostic efficiency for detecting lymph node metastasis, and 68Ga-FAPI-04 uptake showed a close association with FAP expression in participants with NSCLC.

Evaluation of [18F]RoSMA-18-d6 as a CB2 PET Radioligand in Nonhuman Primates.

The cannabinoid type 2 receptor (CB2) has been implicated in a variety of central and peripheral inflammatory diseases, prompting significant interest in the development of CB2-targeted diagnostic and therapeutic agents. A validated positron emission tomography (PET) radioligand for imaging CB2 in the living human brain as well as in peripheral tissues is currently lacking. As part of our research program, we have recently identified the trisubstituted pyridine, [18F]RoSMA-18-d6, which proved to be highly suitable for in vitro and in vivo mapping of CB2 in rodents. The aim of this study was to assess the performance characteristics of [18F]RoSMA-18-d6 in nonhuman primates (NHPs) to pave the way for clinical translation. [18F]RoSMA-18-d6 was synthesized from the respective tosylate precursor according to previously reported procedures. In vitro autoradiograms with NHP spleen tissue sections revealed a high binding of [18F]RoSMA-18-d6 to the CB2-rich NHP spleen, which was significantly blocked by coincubation with the commercially available CB2 ligand, GW405833 (10 µM). In contrast, no specific binding was observed by in vitro autoradiography with NHP brain sections, which was in agreement with the notion of a CB2-deficient healthy mammalian brain. In vitro findings were corroborated by PET imaging experiments in NHPs, where [18F]RoSMA-18-d6 uptake in the spleen was dose-dependently attenuated with 1 and 5 mg/kg GW405833, while no specific brain signal was observed. Remarkably, we observed tracer uptake and retention in the NHP spinal cord, which was reduced by GW405833 blockade, pointing toward a potential utility of [18F]RoSMA-18-d6 in probing CB2-expressing cells in the bone marrow. If these observations are substantiated in NHP models of enhanced leukocyte proliferation in the bone marrow, [18F]RoSMA-18-d6 may serve as a valuable marker for hematopoietic activity in various pathologies. In conclusion, [18F]RoSMA-18-d6 proved to be a suitable PET radioligand for imaging CB2 in NHPs, supporting its translation to humans.

Development of Novel 11C-Labeled Selective Orexin-2 Receptor Radioligands for Positron Emission Tomography Imaging.

Orexin 2 receptors (OX2R) represent a vital subtype of orexin receptors intricately involved in the regulation of wakefulness, arousal, and sleep-wake cycles. Despite their importance, there are currently no positron emission tomography (PET) tracers available for imaging the OX2R in vivo. Herein, we report [11C]1 ([11C]OX2-2201) and [11C]2 ([11C]OX2-2202) as novel PET ligands. Both compounds 1 (Ki = 3.6 nM) and 2 (Ki = 2.2 nM) have excellent binding affinity activities toward OX2R and target selectivity (OX2/OX1 > 600 folds). In vitro autoradiography in the rat brain suggested good to excellent in vitro binding specificity for [11C]1 and [11C]2. PET imaging in rat brains indicated that the low brain uptake of [11C]2 may be due to P-glycoprotein and/or breast cancer resistance protein efflux interaction and/or low passive permeability. Continuous effort in medicinal chemistry optimization is necessary to improve the brain permeability of this scaffold.

Self-supervised dual-head attentional bootstrap learning network for prostate cancer screening in transrectal ultrasound images.

Current convolutional neural network-based ultrasound automatic classification models for prostate cancer often rely on extensive manual labeling. Although Self-supervised Learning (SSL) have shown promise in addressing this problem, those data that from medical scenarios contains intra-class similarity conflicts, so using loss calculations directly that include positive and negative sample pairs can mislead training. SSL method tends to focus on global consistency at the image level and does not consider the internal informative relationships of the feature map. To improve the efficiency of prostate cancer diagnosis, using SSL method to learn key diagnostic information in ultrasound images, we proposed a self-supervised dual-head attentional bootstrap learning network (SDABL), including Online-Net and Target-Net. Self-Position Attention Module (SPAM) and adaptive maximum channel attention module (CAAM) are inserted in both paths simultaneously. They captures position and inter-channel attention and of the original feature map with a small number of parameters, solve the information optimization problem of feature maps in SSL. In loss calculations, we discard the construction of negative sample pairs, and instead guide the network to learn the consistency of the location space and channel space by drawing closer to the embedding representation of positive samples continuously. We conducted numerous experiments on the prostate Transrectal ultrasound (TRUS) dataset, experiments show that our SDABL pre-training method has significant advantages over both mainstream contrast learning methods and other attention-based methods. Specifically, the SDABL pre-trained backbone achieves 80.46% accuracy on our TRUS dataset after fine-tuning.

Regionally distinct progenitor cells in the lower airway give rise to neuroendocrine and multiciliated cells in the developing human lung.

Using scRNA-seq and microscopy, we describe a cell that is enriched in the lower airways of the developing human lung and identified by the unique coexpression of SCGB3A2/SFTPB/CFTR. To functionally interrogate these cells, we apply a single-cell barcode-based lineage tracing method, called CellTagging, to track the fate of SCGB3A2/SFTPB/CFTR cells during airway organoid differentiation in vitro. Lineage tracing reveals that these cells have a distinct differentiation potential from basal cells, giving rise predominantly to pulmonary neuroendocrine cells and a subset of multiciliated cells distinguished by high C6 and low MUC16 expression. Lineage tracing results are supported by studies using organoids and isolated cells from the lower noncartilaginous airway. We conclude that SCGB3A2/SFTPB/CFTR cells are enriched in the lower airways of the developing human lung and contribute to the epithelial diversity and heterogeneity in this region.

CAXII inhibitors: Potential sensitizers for immune checkpoint inhibitors in HCC treatment.

Hepatocellular carcinoma (HCC) is a lethal malignancy with a lack of effective treatments particularly for the disease at an advanced stage. Even though immune checkpoint inhibitors (ICIs) have made great progress in the treatment of HCC, durable and ideal clinical benefits still cannot be achieved in plenty of patients with HCC. Therefore, novel and refined ICI-based combination therapies are still needed to enhance the therapeutic effect. The latest study has reported that the carbonic anhydrase XII inhibitor (CAXIIi), a novel type of anticancer drug, can modify the tumor immunosuppression microenvironment by affecting hypoxic/acidic metabolism and alter the functions of monocytes and macrophages by regulating the expression of C-C motif chemokine ligand 8 (CCL8). These observations shine a light on improving programmed cell death protein 1 (PD-1)/programmed cell death ligand-1 (PD-L1) immunotherapy in combination with CAXIIis. This mini-review aims to ignite enthusiasm to explore the potential application of CAXIIis in combination with immunotherapy for HCC.

The performance of 68Ga-FAPI-04 PET/CT in head and neck squamous cell carcinoma: a prospective comparison with 18F-FDG PET/CT.

PURPOSE: This study was designed to compare the performance of 68Ga-FAPI-04 and 18F-FDG PET/CT for initial staging and recurrence detection of head and neck squamous cell carcinoma (HNSCC). METHODS: Prospectively, 77 patients with histologically proven or highly suspected HNSCC underwent paired 18F-FDG and 68Ga-FAPI-04 PET/CT in a week for either initial staging (n = 67) or restaging (n = 10). The diagnostic performance was compared for the two imaging approaches, especially for N staging. SUVmax, SUVmean, and target-to-background ratio (TBR) were assessed for paired positive lesions. Furthermore, change in management by 68Ga-FAPI-04 PET/CT and histopathologic FAP expression of some lesions were explored. RESULTS: 18F-FDG and 68Ga-FAPI-04 PET/CT exhibited a comparable detection efficiency for primary tumor (100%) and recurrence (62.5%). In the twenty-nine patients receiving neck dissection, 68Ga-FAPI-04 PET/CT showed greater specificity and accuracy in evaluating preoperative N staging than 18F-FDG based on patient (p = 0.031 and p = 0.070), neck side (p = 0.002 and p = 0.006), and neck level (p < 0.001 and p < 0.001). As for distant metastasis, 68Ga-FAPI-04 PET/CT detected more positive lesions than 18F-FDG (25 vs 23) and with higher SUVmax (7.99 ± 9.04 vs 3.62 ± 2.68, p = 0.002) by lesion-based analysis. The type of neck dissection in 9 cases (9/33) was altered by 68Ga-FAPI-04. Overall, clinical management was significantly changed in 10 patients (10/61). Three patients had a follow-up 68Ga-FAPI-04 PET/CT post neoadjuvant therapy: One showed complete remission, and the others showed progression. The 68Ga-FAPI-04 uptake intensity was confirmed to be consistent with FAP expression. CONCLUSION: 68Ga-FAPI-04 outperforms 18F-FDG PET/CT in evaluating preoperative N staging in patients with HNSCC. Furthermore, 68Ga-FAPI-04 PET/CT also shows the potential in clinical management and monitoring response to treatment.

Yifei Sanjie Formula or Placebo With Anlotinib as Second-Line or Above Treatment for Metastatic Non-Small-Cell Lung Cancer: Study Protocol for a Double-Blind, Placebo-Controlled Randomized Pilot Study.

BACKGROUND: Anlotinib is used as a third-line treatment for advanced non-small-cell lung cancer (NSCLC), but has limited clinical benefits and several side effects, such as diarrhea and acneiform skin rash. Traditional Chinese Medicine (TCM) is commonly used to treat cancers in China. Chinese herbal medicines may have the potential as adjuvant therapies to reduce toxicity and improve the efficacy of treatments for NSCLC. Given the positive outcomes of basic research, we plan to evaluate whether the addition of the Chinese herbal medicine Yifei Sanjie formula (YFSJF) to anlotinib can improve the progression-free survival (PFS) of advanced NSCLC patients. METHODS: A multicenter, randomized, double-blind, placebo-controlled parallel-group controlled pilot trial will be performed. Forty eligible patients will be randomized in a ratio of 1:1 to the intervention (YFSJF + anlotinib) and control (placebo + anlotinib) groups. Participants will be advised to take 12 mg/day of anlotinib on days 1 to 14 of each 21-day cycle. YFSJF or placebo will be administered (15 g twice daily) during each cycle until progression of disease (PD). The primary outcome will be progression-free survival (PFS), and the secondary outcomes will be overall survival (OS), the objective response rate (ORR), and patient-reported outcomes (PRO). Tumors will be assessed based on RECIST v. 1.1 after every 2 cycles of treatment. The M. D. Anderson Symptom Inventory-Lung Cancer (MDASI-LC) will be used to evaluate PRO at baseline and weekly thereafter until PD. DISCUSSION: This will be the first trial to evaluate the effectiveness and safety of TCM combined with anlotinib for the treatment of NSCLC. The results of this randomized controlled trial will fill a gap in the research by showing whether YFSJF combined with anlotinib can improve PFS in NSCLC patients. TRIAL REGISTRATION: The study was registered on June 8th, 2021 on Chinese Clinical Registry; registration number ChiCTR2100047143. (https://www.chictr.org.cn/index.aspx). ETHICS AND DISSEMINATION: The Ethics Committee of the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine approved the study protocol (approval no.: K2020151, 2021/08/19). The study will also be supervised and managed by the Ethics Committee.

Nanomedicine for renal cell carcinoma: imaging, treatment and beyond.

The kidney is a vital organ responsible for maintaining homeostasis in the human body. However, renal cell carcinoma (RCC) is a common malignancy of the urinary system and represents a serious threat to human health. Although the overall survival of RCC has improved substantially with the development of cancer diagnosis and management, there are various reasons for treatment failure. Firstly, without any readily available biomarkers, timely diagnosis has been greatly hampered. Secondly, the imaging appearance also varies greatly, and its early detection often remains difficult. Thirdly, chemotherapy has been validated as unavailable for treating renal cancer in the clinic due to its intrinsic drug resistance. Concomitant with the progress of nanotechnological methods in pharmaceuticals, the management of kidney cancer has undergone a transformation in the recent decade. Nanotechnology has shown many advantages over widely used traditional methods, leading to broad biomedical applications ranging from drug delivery, prevention, diagnosis to treatment. This review focuses on nanotechnologies in RCC management and further discusses their biomedical translation with the aim of identifying the most promising nanomedicines for clinical needs. As our understanding of nanotechnologies continues to grow, more opportunities to improve the management of renal cancer are expected to emerge.

Use of survival support vector machine combined with random survival forest to predict the survival of nasopharyngeal carcinoma patients.

Background: The Cox regression model is not sufficiently accurate to predict the survival prognosis of nasopharyngeal carcinoma (NPC) patients. It is impossible to calculate and rank the importance of impact factors due to the low predictive accuracy of the Cox regression model. So, we developed a system. Using the SEER (The Surveillance, Epidemiology, and End Results) database data on NPC patients, we proposed the use of random survival forest (RSF) and survival-support vector machine (SVM) from the machine learning methods to develop a survival prediction system specifically for NPC patients. This approach aimed to make up for the insufficiency of the Cox regression model. We also used the Cox regression model to validate the development of the nomogram and compared it with machine learning methods. Methods: A total of 1,683 NPC patients were extracted from the SEER database from January 2010 to December 2015. We used R language for modeling work, established the nomogram of survival prognosis of NPC patients by Cox regression model, ranked the correlation of influencing factors by RSF model VIMP (variable important) method, developed a survival prognosis system for NPC patients based on survival-SVM, and used C-index for model evaluation and performance comparison. Results: Although the Cox regression models can be developed to predict the prognosis of NPC patients, their accuracy was lower than that of machine learning methods. When we substituted the data for the Cox model, the C-index for the training set was only 0.740, and the C-index for the test set was 0.721. In contrast, the C index of the survival-SVM model was 0.785. The C-index of the RSF model was 0.729. The importance ranking of each variable could be obtained according to the VIMP method. Conclusions: The prediction results from the Cox model are not as good as those of the RSF method and survival-SVM based on the machine learning method. For the survival prognosis of NPC patients, the machine learning method can be considered for clinical application.

The Prognostic Value of Serum Apolipoprotein A-I Level and Neutrophil-to-Lymphocyte Ratio in Colorectal Cancer Liver Metastasis.

Background: Colorectal cancer liver metastasis (CRLM) is a high degree of malignancy with rapid disease progression and has a poor prognosis. Both serum apolipoprotein A-I (ApoA-I) and neutrophil-to-lymphocyte ratio (NLR) play key roles in anti-inflammation and antitumor. This study is aimed at evaluating the implication of serum ApoA-I level in combination with NLR in the prognosis of CRLM. Methods: We retrospectively analyzed the serum ApoA-I level and NLR in 237 patients with CRLM. Cox regression analyses were used to identify the independent prognostic significance of these indicators. Kaplan-Meier method and Log-rank test were applied to compute overall survival (OS). Both the ApoA-I and NLR were divided into three levels, according to their medians. A risk-stratified prediction model was established to evaluate the prognosis of patients with CRLM. The ROC curve AUC values were applied to evaluate the capability of the model. Results: Higher levels of ApoA-I and lower NLR were strongly associated with prolonged OS (Log-rank test, P < 0.05). The patients were then grouped into three queues according to the ApoA-I level and NLR. There was a crucial diversity in the OS (P < 0.001) between the high-risk (ApoA - I ≤ 1.03 g/L and NLR > 3.24), medium-risk (ApoA - I > 1.03 g/L or NLR ≤ 3.24) and low-risk groups (ApoA - I > 1.03 g/L and NLR ≤ 3.24). The AUC value of the prediction model (AUC = 0.623, 95% CI: 0.557-0.639, P = 0.001) was higher than other individual indicators (including ApoA-I, NLR, cT classification, and cN classification). Additionally, the association of the prediction model and cTN classification (AUC = 0.715, 95% CI: 0.606-0.708, P < 0.001) was better than the model and cTN classification alone. Conclusion: The combination of ApoA-I level and NLR could be a prognostic indicator for CRLM.

Correction: Wang et al. TERT Promoter Revertant Mutation Inhibits Melanoma Growth through Intrinsic Apoptosis. Biology 2022, 11, 141.

The authors would like to make the following correction to the published paper [...].

Discovery of a highly specific 18F-labeled PET ligand for phosphodiesterase 10A enabled by novel spirocyclic iodonium ylide radiofluorination.

As a member of cyclic nucleotide phosphodiesterase (PDE) enzyme family, PDE10A is in charge of the degradation of cyclic adenosine (cAMP) and guanosine monophosphates (cGMP). While PDE10A is primarily expressed in the medium spiny neurons of the striatum, it has been implicated in a variety of neurological disorders. Indeed, inhibition of PDE10A has proven to be of potential use for the treatment of central nervous system (CNS) pathologies caused by dysfunction of the basal ganglia-of which the striatum constitutes the largest component. A PDE10A-targeted positron emission tomography (PET) radioligand would enable a better assessment of the pathophysiologic role of PDE10A, as well as confirm the relationship between target occupancy and administrated dose of a given drug candidate, thus accelerating the development of effective PDE10A inhibitors. In this study, we designed and synthesized a novel 18F-aryl PDE10A PET radioligand, codenamed [18F]P10A-1910 ([18F]9), in high radiochemical yield and molar activity via spirocyclic iodonium ylide-mediated radiofluorination. [18F]9 possessed good in vitro binding affinity (IC50 = 2.1 nmol/L) and selectivity towards PDE10A. Further, [18F]9 exhibited reasonable lipophilicity (logD = 3.50) and brain permeability (P app > 10 × 10-6 cm/s in MDCK-MDR1 cells). PET imaging studies of [18F]9 revealed high striatal uptake and excellent in vivo specificity with reversible tracer kinetics. Preclinical studies in rodents revealed an improved plasma and brain stability of [18F]9 when compared to the current reference standard for PDE10A-targeted PET, [18F]MNI659. Further, dose-response experiments with a series of escalating doses of PDE10A inhibitor 1 in rhesus monkey brains confirmed the utility of [18F]9 for evaluating target occupancy in vivo in higher species. In conclusion, our results indicated that [18F]9 is a promising PDE10A PET radioligand for clinical translation.

TERT Promoter Revertant Mutation Inhibits Melanoma Growth through Intrinsic Apoptosis.

Human telomerase is a specialized DNA polymerase whose catalytic core includes both TERT and human telomerase RNA (hTR). Telomerase in humans, which is silent in most somatic cells, is activated to maintain the telomere length (TEL) in various types of cancer cells, including melanoma. In the vast majority of tumor cells, the TERT promoter is mutated to promote proliferation and inhibit apoptosis. Here, we exploited NG-ABEmax to revert TERT -146 T to -146 C in melanoma, and successfully obtained TERT promoter revertant mutant cells. These TERT revertant mutant cells exhibited significant growth inhibition both in vitro and in vivo. Moreover, A375-146C/C cells exhibited telomere shortening and the downregulation of TERT at both the transcription and protein levels, and migration and invasion were inhibited. In addition, TERT promoter revertant mutation abrogated the inhibitory effect of mutant TERT on apoptosis via B-cell lymphoma 2 (Bcl-2), ultimately leading to cell death. Collectively, the results of our work demonstrate that reverting mutations in the TERT promoter is a potential therapeutic option for melanoma.

DNA damage repair gene mutations predict the efficacy of platinum-based chemotherapy and immunotherapy plus platinum-based chemotherapy in advanced non-small cell lung cancer: a retrospective Chinese cohort study.

Background: Platinum-based chemotherapy (PC) and immunotherapy plus platinum-based chemotherapy (IPC) remain the first-line treatment for advanced NSCLC. But only a minority patients benefit from PC, and existing biomarkers, such as PD-L1, have been shown to be defective in predicting the efficacy of IPC. Highlighting the need to identify novel biomarkers for the efficacy of PC and IPC. DNA damage repair (DDR) mutations are known to predict response to PC in solid tumors. However, the predictive value of DDR in PC and IPC of NSCLC remains unclear. Methods: Patients diagnosed with advanced or metastatic NSCLC were retrospectively included if they underwent next generation sequencing prior to starting treatment. Primary endpoints were to explore whether DDR mutations (DDRmut) are associated with clinical outcomes of PC and IPC. Secondary end point were to explore the association between DDRmut and the choice to add immunotherapy to chemotherapy, and the impact of different DDR pathways on efficacy in PC and IPC. Results: DDRmut showed a strong association with tumor mutation burden-high (TMB-H) versus DDR wild-type (DDRwt) and higher rates of PD-L1 TPS ≥50% positivity. In 63 patients treated with PC, ORRs were 15.38% and 2.86% for DDRmut and DDRwt subgroup (P=0.1536), and DCRs were 88.46% and 45.72% (P=0.00097) at 6 months after PC. The DDRmut patients had significantly improved median PFS (mPFS) and median overall survival (mOS) than DDRwt group (mPFS: 7.6 vs. 3.9 months, HR =1.93, 95% CI: 1.09 to 3.14, P=0.0220. mOS: 29.9 vs. 20.7 months, HR =2.31, 95% CI: 1.09 to 4.9, P=0.0250). Moreover, among 37 patients treated with IPC, ORRs were 45% and 11.76% for DDRmut and DDRwt patients (P=0.0365), and the DCRs were 95% and 70.58% (P=0.0752), respectively at 6 months after IPC. The DDRmut patients had significantly improved mPFS compared to the DDRwt group (19.5 vs. 4.5 months, HR =3.28, 95% CI: 1.53 to 9.56, P=0.0022). In DDRmut group, mPFS of IPC recipients was significantly better than that of PC recipients (19.5 vs. 7.6 months, HR =2.09, 95% CI: 0.98 to 4.42, P=0.050). Conclusions: There is potential for DDR to serve as a positive predictor of PC and IPC in advanced NSCLC patients.

Comparisons of Forecasting for Survival Outcome for Head and Neck Squamous Cell Carcinoma by using Machine Learning Models based on Multi-omics.

Background: Machine learning methods showed excellent predictive ability in a wide range of fields. For the survival of head and neck squamous cell carcinoma (HNSC), its multi-omics influence is crucial. This study attempts to establish a variety of machine learning multi-omics models to predict the survival of HNSC and find the most suitable machine learning prediction method. Methods: The HNSC clinical data and multi-omics data were downloaded from the TCGA database. The important variables were screened by the LASSO algorithm. We used a total of 12 supervised machine learning models to predict the outcome of HNSC survival and compared the results. In vitro qPCR was performed to verify core genes predicted by the random forest algorithm. Results: For omics of HNSC, the results of the twelve models showed that the performance of multi-omics was better than each single-omic alone. Results were presented, which showed that the Bayesian network(BN) model (area under the curve [AUC] 0.8250, F1 score=0.7917) and random forest(RF) model (area under the curve [AUC] 0.8002,F1 score=0.7839) played good prediction performance in HNSC multi-omics data. The results of in vitro qPCR were consistent with the RF algorithm. Conclusion: Machine learning methods could better forecast the survival outcome of HNSC. Meanwhile, this study found that the BN model and the RF model were the most superior. Moreover, the forecast result of multi-omics was better than single-omic alone in HNSC.

Imaging Autotaxin In Vivo with 18F-Labeled Positron Emission Tomography Ligands.

Autotaxin (ATX) is a secreted phosphodiesterase that has been implicated in a remarkably wide array of pathologies, especially in fibrosis and cancer. While ATX inhibitors have entered the clinical arena, a validated probe for positron emission tomography (PET) is currently lacking. With the aim to develop a suitable ATX-targeted PET radioligand, we have synthesized a focused library of fluorinated imidazo[1,2-a]pyridine derivatives, determined their inhibition constants, and confirmed their binding mode by crystallographic analysis. Based on their promising in vitro properties, compounds 9c, 9f, 9h, and 9j were radiofluorinated. Also, a deuterated analog of [18F]9j, designated as [18F]ATX-1905 ([18F]20), was designed and proved to be highly stable against in vivo radiodefluorination compared with [18F]9c, [18F]9f, [18F]9h, and [18F]9j. These results along with in vitro and in vivo studies toward ATX in a mouse model of LPS-induced liver injury suggest that [18F]ATX-1905 is a suitable PET probe for the non-invasive quantification of ATX.

DNA repair genes are associated with tumor tissue differentiation and immune environment in lung adenocarcinoma: a bioinformatics analysis based on big data.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DNA repair genes (DRGs) is important in lung cancer. The relationship between the immune environment and the expression levels of DRGs in LUAD remains unclear. The purpose of this study is to assess the relationship between DRGs and the immune environment and clinical characteristics of LUAD. METHODS: Data of 169 LUAD cases were obtained from cbioportal. The RNA-seq data came from the The Cancer Genome Atlas (TCGA) database. We collected DRGs from the Reactom database (KW0037, Reactom.org). The 302 genes expressed in each sample were analyzed by hierarchical clustering and grouped using the Gene Cluster 3.0 program. The Java Treeview program was used to generate heat maps of cluster indications and tumor staging patterns. GraphPad Prism 8 was used to draw survival curves and compare overall survival (OS). For single genes, an OS difference analysis between low and high expression populations was performed in GraphPad Prism 8. RESULTS: Matrix clustering showed no difference in the prognosis of the two clusters. The comparison of subgroups showed that Subcluster 1 (SC1) had the best prognosis, and Subcluster 2 (SC2) had the worst. There was a significant difference in tumor grades between Cluster 1 and Cluster 2 (P=0.01). There were significant differences in smoking status, histological grade and adenocarcinoma subtype among subgroups. In Subcluster 3 (SC3), the proportion of poorly differentiated cases was highest. Immunological index analysis showed that there were significant differences between Cluster 1 and Cluster 2 in interferon, macrophages, monocytes, neutrophils, natural killer (NK) cells, and T cells. Tumor purity, interferon, macrophages, monocytes, neutrophils, NK cells, T cells, translation, and proliferation all showed significant differences between subgroups. In SC2, the proliferation index increased (0.082 vs. 0.070); the protein translation index decreased (0.134 vs. 0.137); and the interferon level increased (0.099 vs. 0.097). In SC3, the proliferation index decreased (0.076 vs. 0.071); the protein translation index decreased (0.140 vs. 0.136); and the level of neutrophils increased (0.083 vs. 0.086). CONCLUSIONS: The differences of DRGs in LUAD are related to tissue differentiation and immune indicators but not to prognosis.

Network Pharmacology/Metabolomics-Based Validation of AMPK and PI3K/AKT Signaling Pathway as a Central Role of Shengqi Fuzheng Injection Regulation of Mitochondrial Dysfunction in Cancer-Related Fatigue.

Chinese herbal medicines have multiple targets and properties, and their use in multidisciplinary cancer therapies has consequently received increasing attention. Here, we have investigated the possible active ingredients associated with cancer-related fatigue (CRF) in the Shengqi Fuzheng Injection (SFI). In vitro cell models were used to measure the regulation effects of SFI on CRF. Metabolomic analysis was used to identify the potential genes and pathways in C2C12 mouse myoblasts treated with SFI, and the interaction of compounds and CRF targets was predicted using network pharmacology and molecular docking analyses. The putative pathways were further verified using immuno-blotting assays. The results showed that SFI significantly inhibited muscle cell apoptosis and increased the mitochondrial membrane potential of muscle cells. The network pharmacology analysis results identified 36 candidate compounds, and 244 potential targets were yielded by SFI, and they shared 10 key targets associated with cancer-related fatigue. According to the enrichment analysis and experimental validation, SFI might ameliorate muscle cell mitochondrial function by activating AMPK and inhibiting the PI3K/Akt signaling pathways, and the expression changes of mitochondrial metabolic enzymes MnSOD and apoptosis-associated proteins Bax and Bcl-2 were also triggered. The functions and mechanisms of SFI in anticancer-related fatigue were found here to be at least partly due to the targeting of the AMPK and PI3K/Akt signaling pathways, and this has highlighted new potential applications for network pharmacology when researching Chinese Medicines.

Advances in Cyclic Nucleotide Phosphodiesterase-Targeted PET Imaging and Drug Discovery.

Cyclic nucleotide phosphodiesterases (PDEs) control the intracellular concentrations of cAMP and cGMP in virtually all mammalian cells. Accordingly, the PDE family regulates a myriad of physiological functions, including cell proliferation, differentiation and apoptosis, gene expression, central nervous system function, and muscle contraction. Along this line, dysfunction of PDEs has been implicated in neurodegenerative disorders, coronary artery diseases, chronic obstructive pulmonary disease, and cancer development. To date, 11 PDE families have been identified; however, their distinct roles in the various pathologies are largely unexplored and subject to contemporary research efforts. Indeed, there is growing interest for the development of isoform-selective PDE inhibitors as potential therapeutic agents. Similarly, the evolving knowledge on the various PDE isoforms has channeled the identification of new PET probes, allowing isoform-selective imaging. This review highlights recent advances in PDE-targeted PET tracer development, thereby focusing on efforts to assess disease-related PDE pathophysiology and to support isoform-selective drug discovery.