Integrating Radiomics and Neural Networks for Knee Osteoarthritis Incidence Prediction.

OBJECTIVE: Accurately predicting knee osteoarthritis (KOA) is essential for early detection and personalized treatment. We aimed to develop and test an MRI-based Joint Space Radiomic Model (JS-RM) to predict radiographic KOA incidence through neural networks by integrating meniscus and femorotibial cartilage radiomic features. METHODS: In the Osteoarthritis Initiative cohort, knees without radiographic KOA at baseline but at high risk for radiographic KOA were included. Case knees developed radiographic KOA whereas control knees did not over 4-year. We randomly split the knees into development and test cohorts (D/T=8/2) and extracted features from baseline 3D-DESS-sequence MRI. Model performance was evaluated using an area under the receiver operating characteristic curve (AUC), sensitivity, and specificity in both cohorts. Nine resident surgeons performed the reader experiment without/with the JS-RM aid. RESULTS: Our study included 549 knees in the development cohort (275 cases vs. 274 controls) and 137 knees in the test cohort (68 cases vs. 69 controls). In the test cohort, JS-RM had a favorable accuracy for predicting the radiographic KOA incidence with an AUC of 0.931 (95%CI: 0.876-0.963), a sensitivity of 84.4% (95%CI: 83.9%-84.9%), and a specificity of 85.6% (95%CI: 85.2%-86.0%). The mean specificity and sensitivity of resident surgeons through MRI reading in predicting radiographic KOA incidence were increased from 0.474 (95%CI: 0.333-0.614) and 0.586 (95%CI: 0.429-0.743) without the assistance of JS-RM to 0.874 (95%CI: 0.847-0.901) and 0.812 (95%CI: 0.742-0.881) with JS-RM assistance, respectively (p<.001). CONCLUSION: JS-RM integrating the features of the meniscus and cartilage showed improved predictive values in radiographic KOA incidence.

Cancer immunometabolism: advent, challenges, and perspective.

For decades, great strides have been made in the field of immunometabolism. A plethora of evidence ranging from basic mechanisms to clinical transformation has gradually embarked on immunometabolism to the center stage of innate and adaptive immunomodulation. Given this, we focus on changes in immunometabolism, a converging series of biochemical events that alters immune cell function, propose the immune roles played by diversified metabolic derivatives and enzymes, emphasize the key metabolism-related checkpoints in distinct immune cell types, and discuss the ongoing and upcoming realities of clinical treatment. It is expected that future research will reduce the current limitations of immunotherapy and provide a positive hand in immune responses to exert a broader therapeutic role.

Desulfurative Functionalization of ß-Acyl Allylic Sulfides with N-H Free Indoles Highly Regioselective at C3 and N1 Positions: Rapid Access to α-Branched Enones.

A regiodivergent allylation of 1H-indoles highly selectively at the C3 and N1 positions with ß-acyl allylic sulfides through desulfurative C-C/C-N bond-forming reactions has been developed under mild conditions. Notably, the remarkable site-selective switch can be achieved by a delicate choice of solvents and bases. This cost-efficient method displays a broad substrate scope, good functional compatibility, and excellent site-selectivity, thus offering a divergent synthesis of indole substituted α-branched enones, which possess diverse potential opportunities for further applications and derivatization.

MPDZ is associated with immune infiltration and regulates migration and invasion by switching YAP1 phosphorylation in colorectal cancer.

BACKGROUND: Multiple PDZ Domain Crumbs Cell Polarity Complex Component (MPDZ) is involved in a few human cancers. However, the features and potential mechanisms of MPDZ in progression of colorectal cancer (CRC) remains unknown. METHODS: The prognostic role of MPDZ in CRC was determined by Kaplan-Meier and univariate regression analysis. Enrichment analysis was performed to characterize crucial pathways of MPDZ. Immune infiltration and immunotherapeutic outcome were further evaluated. CCK8, EDU, transwell, and wound healing assay were used to assess the influence of MPDZ on pernicious performance of CRC cells. CD8+ T cells and CRC cells were co-cultured to explore the effect of MPDZ on the tumor microenvironment. qRT-PCR, western blot, immunoprecipitation (IP), and methylated RNA immunoprecipitation (me-RIP) were implemented in seeking for the potential mechanisms of MPDZ in CRC. RESULTS: CRC patients with elevated MPDZ expression suffered from significantly worse prognosis. Enrichment analysis revealed that MPDZ involved in pathways related to metastasis and cell cycle in CRC. In addition, MPDZ expression were related to several immunoinhibitors and had the ability to predict immunotherapy response. Finally, in vitro assays demonstrated that MPDZ knockdown inhibited migration, invasion and immune evasion of CRC cells. Mechanistically, MPDZ knockdown enhanced YAP1 phosphorylation by increased LATS1 expression. Moreover, m6A-MPDZ mRNA may be recognized and degraded by m6A recognition protein YTHDF2. CONCLUSIONS: MPDZ was critical for CRC development and could be a promising candidate for the treatment of CRC patients.

Multifaceted role of redox pattern in the tumor immune microenvironment regarding autophagy and apoptosis.

The reversible oxidation-reduction homeostasis mechanism functions as a specific signal transduction system, eliciting related physiological responses. Disruptions to redox homeostasis can have negative consequences, including the potential for cancer development and progression, which are closely linked to a series of redox processes, such as adjustment of reactive oxygen species (ROS) levels and species, changes in antioxidant capacity, and differential effects of ROS on downstream cell fate and immune capacity. The tumor microenvironment (TME) exhibits a complex interplay between immunity and regulatory cell death, especially autophagy and apoptosis, which is crucially regulated by ROS. The present study aims to investigate the mechanism by which multi-source ROS affects apoptosis, autophagy, and the anti-tumor immune response in the TME and the mutual crosstalk between these three processes. Given the intricate role of ROS in controlling cell fate and immunity, we will further examine the relationship between traditional cancer therapy and ROS. It is worth noting that we will discuss some potential ROS-related treatment options for further future studies.

Ferroptosis and EMT: key targets for combating cancer progression and therapy resistance.

Iron-dependent lipid peroxidation causes ferroptosis, a form of regulated cell death. Crucial steps in the formation of ferroptosis include the accumulation of ferrous ions (Fe2+) and lipid peroxidation, of which are controlled by glutathione peroxidase 4 (GPX4). Its crucial role in stopping the spread of cancer has been shown by numerous studies undertaken in the last ten years. Epithelial-mesenchymal transition (EMT) is the process by which epithelial cells acquire mesenchymal characteristics. EMT is connected to carcinogenesis, invasiveness, metastasis, and therapeutic resistance in cancer. It is controlled by a range of internal and external signals and changes the phenotype from epithelial to mesenchymal like. Studies have shown that mesenchymal cancer cells tend to be more ferroptotic than their epithelial counterparts. Drug-resistant cancer cells are more easily killed by inducers of ferroptosis when they undergo EMT. Therefore, understanding the interaction between ferroptosis and EMT will help identify novel cancer treatment targets. In-depth discussion is given to the regulation of ferroptosis, the potential application of EMT in the treatment of cancer, and the relationships between ferroptosis, EMT, and signaling pathways associated with tumors. Invasion, metastasis, and inflammation in cancer all include ferroptosis and EMT. The goal of this review is to provide suggestions for future research and practical guidance for applying ferroptosis and EMT in clinical practice.

Bone marrow lesions in osteoarthritis: From basic science to clinical implications.

Osteoarthritis (OA) is the most prevalent musculoskeletal disease characterized by multiple joint structure damages, including articular cartilage, subchondral bone and synovium, resulting in disability and economic burden. Bone marrow lesions (BMLs) are common and important magnetic resonance imaging (MRI) features in OA patients. Basic and clinical research on subchondral BMLs in the pathogenesis of OA has been a hotspot. New evidence shows that subchondral bone degeneration, including BML and angiogenesis, occurs not only at or after cartilage degeneration, but even earlier than cartilage degeneration. Although BMLs are recognized as important biomarkers for OA, their exact roles in the pathogenesis of OA are still unclear, and disputes about the clinical impact and treatment of BMLs remain. This review summarizes the current basic and clinical research progress of BMLs. We particularly focus on molecular pathways, cellular abnormalities and microenvironmental changes of subchondral bone that contributed to the formation of BMLs, and emphasize the crosstalk between subchondral bone and cartilage in OA development. Finally, potential therapeutic strategies targeting BMLs in OA are discussed, which provides novel strategies for OA treatment.

Exploring the roles of intestinal flora in enhanced recovery after surgery.

Striving to optimize surgical outcomes, the Enhanced Recovery After Surgery (ERAS) pathway mitigates patients' stress through the implementation of evidence-based practices during the pre-, intra-, and postoperative periods. Intestinal flora is a sophisticated ecosystem integrating with the host and the external environment, which serves as a mediator in diverse interventions of ERAS to regulate human metabolism and inflammation. This review linked gut microbes and their metabolites with ERAS interventions, offering novel high-quality investigative proponents for ERAS. ERAS could alter the composition and function of intestinal flora in patients by alleviating various perioperative stress responses. Modifying gut flora through multiple modalities, such as diet and nutrition, to accelerate recovery might be a complementary approach when exploring novel ERAS initiatives. Meanwhile, the pandemic of COVID-19 and the availability of promising qualitative evidence created both challenges and opportunities for the establishment of ERAS mode.

Machine learning algorithm-generated and multi-center validated melanoma prognostic signature with inspiration for treatment management.

BACKGROUND: Although immunotherapy and targeted treatments have dramatically improved the survival of melanoma patients, the intra- or intertumoral heterogeneity and drug resistance have hindered the further expansion of clinical benefits. METHODS: The 96 combination frames constructed by ten machine learning algorithms identified a prognostic consensus signature based on 1002 melanoma samples from nine independent cohorts. Clinical features and 26 published signatures were employed to compare the predictive performance of our model. RESULTS: A machine learning-based prognostic signature (MLPS) with the highest average C-index was developed via 96 algorithm combinations. The MLPS has a stable and excellent predictive performance for overall survival, superior to common clinical traits and 26 collected signatures. The low MLPS group with a better prognosis had significantly enriched immune-related pathways, tending to be an immune-hot phenotype and possessing potential immunotherapeutic responses to anti-PD-1, anti-CTLA-4, and MAGE-A3. On the contrary, the high MLPS group with more complex genomic alterations and poorer prognoses is more sensitive to the BRAF inhibitor dabrafenib, confirmed in patients with BRAF mutations. CONCLUSION: MLPS could independently and stably predict the prognosis of melanoma, considered a promising biomarker to identify patients suitable for immunotherapy and those with BRAF mutations who would benefit from dabrafenib.

Biological and pharmacological roles of m6A modifications in cancer drug resistance.

Cancer drug resistance represents the main obstacle in cancer treatment. Drug-resistant cancers exhibit complex molecular mechanisms to hit back therapy under pharmacological pressure. As a reversible epigenetic modification, N6-methyladenosine (m6A) RNA modification was regarded to be the most common epigenetic RNA modification. RNA methyltransferases (writers), demethylases (erasers), and m6A-binding proteins (readers) are frequently disordered in several tumors, thus regulating the expression of oncoproteins, enhancing tumorigenesis, cancer proliferation, development, and metastasis. The review elucidated the underlying role of m6A in therapy resistance. Alteration of the m6A modification affected drug efficacy by restructuring multidrug efflux transporters, drug-metabolizing enzymes, and anticancer drug targets. Furthermore, the variation resulted in resistance by regulating DNA damage repair, downstream adaptive response (apoptosis, autophagy, and oncogenic bypass signaling), cell stemness, tumor immune microenvironment, and exosomal non-coding RNA. It is highlighted that several small molecules targeting m6A regulators have shown significant potential for overcoming drug resistance in different cancer categories. Further inhibitors and activators of RNA m6A-modified proteins are expected to provide novel anticancer drugs, delivering the therapeutic potential for addressing the challenge of resistance in clinical resistance.

Integrative insights and clinical applications of single-cell sequencing in cancer immunotherapy.

Recently, immunotherapy has gained increasing popularity in oncology. Several immunotherapies obtained remarkable clinical effects, but the efficacy varied, and only subsets of cancer patients benefited. Breaking the constraints and improving immunotherapy efficacy is extremely important in precision medicine. Whereas traditional sequencing approaches mask the characteristics of individual cells, single-cell sequencing provides multiple dimensions of cellular characterization at the single-cell level, including genomic, transcriptomic, epigenomic, proteomic, and multi-omics. Hence, the complexity of the tumor microenvironment, the universality of tumor heterogeneity, cell composition and cell-cell interactions, cell lineage tracking, and tumor drug resistance mechanisms are revealed in-depth. However, the clinical transformation of single-cell technology is not to the point of in-depth study, especially in the application of immunotherapy. The newly discovered vital cells and tremendous biomarkers facilitate the development of more efficient individualized therapeutic regimens to guide clinical treatment and predict prognosis. This review provided an overview of the progress in distinct single-cell sequencing methods and emerging strategies. For perspective, the expanding utility of combining single-cell sequencing and other technologies was discussed.

Ferroptosis: a double-edged sword mediating immune tolerance of cancer.

The term ferroptosis was put forward in 2012 and has been researched exponentially over the past few years. Ferroptosis is an unconventional pattern of iron-dependent programmed cell death, which belongs to a type of necrosis and is distinguished from apoptosis and autophagy. Actuated by iron-dependent phospholipid peroxidation, ferroptosis is modulated by various cellular metabolic and signaling pathways, including amino acid, lipid, iron, and mitochondrial metabolism. Notably, ferroptosis is associated with numerous diseases and plays a double-edged sword role. Particularly, metastasis-prone or highly-mutated tumor cells are sensitive to ferroptosis. Hence, inducing or prohibiting ferroptosis in tumor cells has vastly promising potential in treating drug-resistant cancers. Immunotolerant cancer cells are not sensitive to the traditional cell death pathway such as apoptosis and necroptosis, while ferroptosis plays a crucial role in mediating tumor and immune cells to antagonize immune tolerance, which has broad prospects in the clinical setting. Herein, we summarized the mechanisms and delineated the regulatory network of ferroptosis, emphasized its dual role in mediating immune tolerance, proposed its significant clinical benefits in the tumor immune microenvironment, and ultimately presented some provocative doubts. This review aims to provide practical guidelines and research directions for the clinical practice of ferroptosis in treating immune-resistant tumors.

Gene interaction perturbation network deciphers a high-resolution taxonomy in colorectal cancer.

Molecular subtypes of colorectal cancer (CRC) are currently identified via the snapshot transcriptional profiles, largely ignoring the dynamic changes of gene expressions. Conversely, biological networks remain relatively stable irrespective of time and condition. Here, we introduce an individual-specific gene interaction perturbation network-based (GIN) approach and identify six GIN subtypes (GINS1-6) with distinguishing features: (i) GINS1 (proliferative, 24%~34%), elevated proliferative activity, high tumor purity, immune-desert, PIK3CA mutations, and immunotherapeutic resistance; (ii) GINS2 (stromal-rich, 14%~22%), abundant fibroblasts, immune-suppressed, stem-cell-like, SMAD4 mutations, unfavorable prognosis, high potential of recurrence and metastasis, immunotherapeutic resistance, and sensitive to fluorouracil-based chemotherapy; (iii) GINS3 (KRAS-inactivated, 13%~20%), high tumor purity, immune-desert, activation of EGFR and ephrin receptors, chromosomal instability (CIN), fewer KRAS mutations, SMOC1 methylation, immunotherapeutic resistance, and sensitive to cetuximab and bevacizumab; (iv) GINS4 (mixed, 10%~19%), moderate level of stromal and immune activities, transit-amplifying-like, and TMEM106A methylation; (v) GINS5 (immune-activated, 12%~24%), stronger immune activation, plentiful tumor mutation and neoantigen burden, microsatellite instability and high CpG island methylator phenotype, BRAF mutations, favorable prognosis, and sensitive to immunotherapy and PARP inhibitors; (vi) GINS6, (metabolic, 5%~8%), accumulated fatty acids, enterocyte-like, and BMP activity. Overall, the novel high-resolution taxonomy derived from an interactome perspective could facilitate more effective management of CRC patients.

Engineering neoantigen vaccines to improve cancer personalized immunotherapy.

Immunotherapy treatments harnessing the immune system herald a new era of personalized medicine, offering considerable benefits for cancer patients. Over the past years, tumor neoantigens emerged as a rising star in immunotherapy. Neoantigens are tumor-specific antigens arising from somatic mutations, which are proceeded and presented by the major histocompatibility complex on the cell surface. With the advancement of sequencing technology and bioinformatics engineering, the recognition of neoantigens has accelerated and is expected to be incorporated into the clinical routine. Currently, tumor vaccines against neoantigens mainly encompass peptides, DNA, RNA, and dendritic cells, which are extremely specific to individual patients. Due to the high immunogenicity of neoantigens, tumor vaccines could activate and expand antigen-specific CD4+ and CD8+ T cells to intensify anti-tumor immunity. Herein, we introduce the origin and prediction of neoantigens and compare the advantages and disadvantages of multiple types of neoantigen vaccines. Besides, we review the immunizations and the current clinical research status in neoantigen vaccines, and outline strategies for enhancing the efficacy of neoantigen vaccines. Finally, we present the challenges facing the application of neoantigens.

Artificial intelligence-driven consensus gene signatures for improving bladder cancer clinical outcomes identified by multi-center integration analysis.

To accurately predict the prognosis and further improve the clinical outcomes of bladder cancer (BLCA), we leveraged large-scale data to develop and validate a robust signature consisting of small gene sets. Ten machine-learning algorithms were enrolled and subsequently transformed into 76 combinations, which were further performed on eight independent cohorts (n = 1218). We ultimately determined a consensus artificial intelligence-derived gene signature (AIGS) with the best performance among 76 model types. In this model, patients with high AIGS showed a higher risk of mortality, recurrence, and disease progression. AIGS is not only independent of traditional clinical traits [(e.g., American Joint Committee on Cancer (AJCC) stage)] and molecular features (e.g., TP53 mutation) but also demonstrated superior performance to these variables. Comparisons with 58 published signatures also indicated that AIGS possessed the best performance. Additionally, the combination of AIGS and AJCC stage could achieve better performance. Patients with low AIGS scores were sensitive to immunotherapy, whereas patients with high AIGS scores might benefit from seven potential therapeutics: BRD-K45681478, 1S,3R-RSL-3, RITA, U-0126, temsirolimus, MRS-1220, and LY2784544. Additionally, some mutations (TP53 and RB1), copy number variations (7p11.2), and a methylation-driven target were characterized by AIGS-related multi-omics alterations. Overall, AIGS provides an attractive platform to optimize decision-making and surveillance protocol for individual BLCA patients.

Immunosuppression in tumor immune microenvironment and its optimization from CAR-T cell therapy.

Chimeric antigen receptor (CAR)-T cell therapy represents a landmark advance in personalized cancer treatment. CAR-T strategy generally engineers T cells from a specific patient with a new antigen-specificity, which has achieved considerable success in hematological malignancies, but scarce benefits in solid tumors. Recent studies have demonstrated that tumor immune microenvironment (TIME) cast a profound impact on the immunotherapeutic response. The immunosuppressive landscape of TIME is a critical obstacle to the effector activity of CAR-T cells. Nevertheless, every cloud has a silver lining. The immunosuppressive components also shed new inspiration on reshaping a friendly TIME by targeting them with engineered CARs. Herein, we summarize recent advances in disincentives of TIME and discuss approaches and technologies to enhance CAR-T cell efficacy via addressing current hindrances. Simultaneously, we firmly believe that by parsing the immunosuppressive components of TIME, rationally manipulating the complex interactions of immunosuppressive components, and optimizing CAR-T cell therapy for each patient, the CAR-T cell immunotherapy responsiveness for solid malignancies will be substantially enhanced, and novel therapeutic targets will be revealed.

Liquid Biopsy in Pre-Metastatic Niche: From Molecular Mechanism to Clinical Application.

Metastatic dissemination represents a hallmark of cancer that is responsible for the high mortality rate. Recently, emerging evidence demonstrates a time-series event-pre-metastatic niche (PMN) has a profound impact on cancer metastasis. Exosomes, cell-free DNA (cfDNA), circulating tumor cells (CTC), and tumor microenvironment components, as critical components in PMN establishment, could be monitored by liquid biopsy. Intensive studies based on the molecular profile of liquid biopsy have made it a viable alternative to tissue biopsy. Meanwhile, the complex molecular mechanism and intercellular interaction are great challenges for applying liquid biopsy in clinical practice. This article reviews the cellular and molecular components involved in the establishment of the PMN and the promotion of metastasis, as well as the mechanisms of their interactions. Better knowledge of the characteristics of the PMN may facilitate the application of liquid biopsy for clinical diagnosis, prognosis, and treatment.

LncRNA profiles from Notch signaling: Implications for clinical management and tumor microenvironment of colorectal cancer.

The interplay between long non-coding RNAs (lncRNAs) and the Notch pathway involves a variety of malignancies. However, Notch-derived lncRNAs and their latent clinical significance remain elusive in colorectal cancer (CRC). In this study, we introduced a framework that could screen Notch-derived lncRNAs (named "NLncer") and ultimately identified 24 NLncers. To further explore the clinical significance of these NLncers, we performed LASSO and Cox regression in TCGA-CRC cohort (n = 584) and then retained six lncRNAs tightly associated with prognosis. The final model (termed "NLncS") was subsequently tested in GSE38832 (n = 122), GSE39582 (n = 573), and an in-house clinical cohort (n = 115). Ultimately, our NLncS model could serve as an independent risk factor and afford a robust performance for assessing the prognosis of CRC patients. Additionally, patients with high NLncS risk scores were characterized by upregulation of immune pathways, strong immunogenicity, abundant CD8 + T-cell infiltration, and potentially higher response rates to CTLA4 blockers, which turned out to be suitable for immunotherapy. Aiming at globally observing the characteristics of high-risk patients, somatic mutation and methylation modification analysis provide us with evidence at the genomic and transcriptomic levels. To facilitate the clinical transformability, we mined deeply into the sensitive compounds targeting high-risk individuals and identified dasatinib as a candidate agent for patients with a high Notch risk score. In conclusion, our NLncS model is a promising biomarker for optimizing the clinical management of CRC patients.

Roles of circulating tumor DNA in PD-1/PD-L1 immune checkpoint Inhibitors: Current evidence and future directions.

Circulating tumor DNA (ctDNA) sequencing holds considerable promise for early diagnosis and detection of surveillance and minimal residual disease. Blood ctDNA monitors specific cancers by detecting the alterations found in cancer cells, such as apoptosis and necrosis. Due to the short half-life, ctDNA reflects the actual burden of other treatments on tumors. In addition, ctDNA might be preferable to monitor tumor development and treatment compared with invasive tissue biopsy. ctDNA-based liquid biopsy brings remarkable strength to targeted therapy and precision medicine. Notably, multiple ctDNA analysis platforms have been broadly applied in clinical immunotherapy. Through targeted sequencing, early variations in ctDNA could predict response to immune checkpoint inhibitor (ICI). Several studies have demonstrated a correlation between ctDNA kinetics and anti-PD1 antibodies. The need for further research and development remains, although this biomarker holds significant prospects for early cancer detection. This review focuses on describing the basis of ctDNA and its current utilities in oncology and immunotherapy, either for clinical management or early detection, highlighting its advantages and inherent limitations.

SCG2: A Prognostic Marker That Pinpoints Chemotherapy and Immunotherapy in Colorectal Cancer.

Background: Fluorouracil (FU)-based chemotherapy regimens are indispensable in the comprehensive treatment of colorectal cancer (CRC). However, the heterogeneity of treated individuals and the severe adverse effects of chemotherapy results in limited overall benefit. Methods: Firstly, Weighted gene co-expression network analysis (WGCNA) identified modules tightly associated with chemotherapy response. Then, the in-house cohort and prognostic cohorts from TCGA and GEO were subjected to Cox proportional hazards model and survival analysis to ascertain the predictable function of SCG2 on the prognosis of CRC patients. Finally, we performed In vitro experiments, functional analysis, somatic mutation, and copy number variation research to explore the biological characteristics of SCG2. Results: We identified red and green as the modules most associated with chemotherapy response, in which SCG2 was considered a risky factor with higher expression predicting poorer prognosis. SCG2 expression in the APC non-mutation group was remarkably higher than in the mutation group. The mutation frequencies of amplified genes differed significantly between different SCG2 expression subgroups. Besides, CRC cell lines with SCG2 knockdown have reduced invasive, proliferative, and proliferative capacity. We discovered that the SCG2 high expression subgroup was the immune hot type and considered more suitable for immunotherapy. Conclusion: This study demonstrates the clinical significance and biological characteristics of SCG2, which could serve as a promising biomarker to identify patients who may benefit from chemotherapy and immunotherapy.