Molecular Profiling Research Articles

MAPK signaling pathway induced LOX-1+ polymorphonuclear myeloid-derived suppressor cells in biliary atresia

Biliary atresia (BA) is a severe pediatric liver disease characterized by progressive bile duct destruction and fibrosis, leading to significant liver damage and frequently necessitating liver transplantation. This study elucidates the role of LOX-1+ polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in BA pathogenesis and assesses their potential as non-invasive early diagnostic biomarkers. Using flow cytometry, immunofluorescence, and molecular profiling, we analyzed the expression and activity of these cells in peripheral blood and liver tissues from BA patients and controls. Our findings reveal a significant increase in the frequencies and function of LOX-1+PMN-MDSCs in BA patients, along with MAPK signaling pathway upregulation, indicating their involvement in disease mechanisms. Additionally, the frequencies of LOX-1+PMN-MDSC in peripheral blood significantly positively correlate with liver function parameters in BA patients, demonstrating diagnostic performance comparable to traditional serum markers. These findings suggest that LOX-1+PMN-MDSCs contribute to the immunosuppressive environment in BA and could serve as potential diagnostic targets.

Excellent concordance of the molecular classification between preoperative biopsy and final hysterectomy in endometrial carcinoma

ObjectiveThe 2023 International Federation of Gynecology and Obstetrics classification with molecular classification shows superior discriminatory ability compared to staging systems lacking molecular data. However, the accuracy of endometrial biopsy data in molecular classification remains uncertain. This study aimed to assess the concordance of molecular classifications between preoperative biopsy and hysterectomy to predict prognosis before surgical staging. MethodsEndometrial biopsies and corresponding hysterectomy specimens were collected at the National Cancer Center Hospital between 2012 and 2023. Immunohistochemistry for p53 and mismatch repair (MMR) proteins and next-generation sequencing of all exons of polymerase epsilon (POLE) were performed. Given the limited number of POLE mut cases in prior studies, we prepared a POLE mut-enriched cohort. Cohen's kappa estimates were used to determine concordance for molecular and clinicopathological subgroup assignments. ResultsAmong 70 patients classified into four molecular subtype groups, 33 exhibited POLE mutations, 15 showed loss of MMR protein expression, 13 had p53-abnormality, and 9 had no specific molecular profile. Concordance between biopsy and hysterectomy specimens was 100% (κ = 1.000). In contrast, histological types and grades between biopsy and surgical specimens showed moderate and substantial agreement (κ = 0.420 and κ = 0.780, respectively). ConclusionsMolecular subtypes were completely consistent with those derived from surgical specimens, demonstrating high concordance between preoperative and postoperative molecular classifications. This suggests that endometrial biopsies could reliably predict prognosis. Future studies should investigate how biopsy-based molecular profiling influences treatment planning and patient outcomes.

SEOM-GETNE-TTCC Clinical guideline thyroid cancer (2023).

Thyroid cancer (TC) represents 3% of global cancer incidence. Recent changes have optimized treatment decisions based on risk assessment, molecular profiling, and imaging assessment, leading the development of targeted agents that have modified the natural history of this disease. This increasing complexity on treatment options requires careful assessment at the different stages of the disease to provide the most suitable approach from diagnosis to long-term follow-up. This guideline aims to offer a comprehensive and practical overview on the current status and last updates of TC management.

Predictive genomic and transcriptomic analysis on endoscopic ultrasound-guided fine needle aspiration materials from primary pancreatic adenocarcinoma: a prospective multicentre study

We apply endoscopic ultrasound-guided fine needle aspiration biopsy to cytopathologically diagnose and sample nucleic acids from primary tumours regardless of the disease stage. 397 patients with proven pancreatic adenocarcinoma were included and followed up in a multicentre prospective study. DNA and mRNA were extracted from materials of primary tumours obtained by endoscopic ultrasound-guided fine needle aspiration biopsy and analysed using targeted deep sequencing and RNAseq respectively. The variant allele frequency of the KRAS mutation was used to evaluate the tumour cellularity, ranging from 15 to 20% in all cells, regardless of the tumour stage. The molecular profile of metastatic primary tumours significantly differed from other types of tumours, more frequently having TP53 mutations (p=0.0002), less frequently having RNF43 mutations, and possessing more basal-like mRNA component (p=0.001). Molecular markers associated with improved overall survival were: mutations in homologous recombination deficiency genes in patients who received first-line platinum-based chemotherapy (p=0.025) and wild-type TP53 gene in patients with locally advanced tumours who received radio-chemotherapy (p=0.01). The GemPred transcriptomic profile was associated with a significantly better overall survival in patients with locally advanced or metastatic pancreatic cancer who received a gemcitabine-based first-line treatment (p=0.019). The combination of genomic and transcriptomic analyses of primary pancreatic tumours enables us to distinguish metastatic tumours from other tumour types. Our molecular strategy may assist in predicting overall survival outcomes for platinum or gemcitabine-based chemotherapies, as well as radio-chemotherapy. Institut National Du Cancer (BCB INCa_7294), CHU of Toulouse, Inserm and Ligue Nationale Contre le Cancer (CIT program).

The evolving landscape of molecular profiling in early-stage endometrial cancer: An NRG Oncology cooperative group mixed-methods study

The evolving landscape of molecular profiling in early-stage endometrial cancer: An NRG Oncology cooperative group mixed-methods study

ScLTdb: a comprehensive single-cell lineage tracing database.

Single-cell lineage tracing (scLT) is a powerful technique that integrates cellular barcoding with single-cell sequencing technologies. This new approach enables the simultaneous measurement of cell fate and molecular profiles at single-cell resolution, uncovering the gene regulatory program of cell fate determination. However, a comprehensive scLT database is not yet available. Here, we present the single-cell lineage tracing database (scLTdb, https://scltdb.com) containing 109 datasets that are manually curated and analyzed through a standard pipeline. The scLTdb provides interactive analysis modules for visualizing and re-analyzing scLT datasets, especially the comprehensive cell fate analysis and lineage relationship analysis. Importantly, scLTdb also allows users to identify fate-related gene signatures. In conclusion, scLTdb provides an interactive interface of scLT data exploration and analysis, and will facilitate the understanding of cell fate decision and lineage commitment in development and diseases.

Effects of patient pleural effusion fluids on the BBSome components expression of human benign mesothelial cells.

Malignant pleural mesothelial cells are affected by the extracellular milieu while such data on benign cells are scarce. Benign cells sense the extracellular environment with the Primary Cilium (PC) and its molecular complex, the BBSome, is critical for this process. Here we aimed at assessing the changes in BBSome genes expression in ordinary 2D and spheroid 3D cell cultures after incubation with pleural effusion fluids (PF) of several etiologies. Benign human mesothelial cells MeT-5A were incubated with PF from patients with mesothelioma (Meso-PF), breast cancer (BrCa-PF), hemothorax (Hemo-PF) and congestive heart failure (CHF-PF). Gene expression of BBS1, 2, 4, 5, 7, 9, 18 was assessed by quantitative real-time PCR (qRT-PCR) to monitor PF-induced gene expression changes. MeT-5A cell migration using the PC-modulating drugs ammonium sulfate (AS) and lithium chloride (LC) during PF incubation was also determined. BBSome gene expression upon influence of BrCa-PF and Hemo-PF was more pronounced in 2D compared to 3D, inducing global changes in 2D. CHF-PF and Meso-PF also induced changes in 2D but not as many, while in all cases MeT-5A grown in 3D were more resistant to the effects of the PF. Meso-PF decreased 2D cell migration, while the disturbance of PC in all PF cases resulted in decreased cell migration. These data suggest distinct BBSome molecular profile changes in benign mesothelial cells exposed to malignant and benign PF, in each case, in both 2D and 3D. Cell migration is sensitive to drug disturbance with PC modulators in PF-exposed cells.

PD-L1 Expression Varies in Thyroid Cancer Types and Is Associated with Decreased Progression Free Survival (PFS) in Patients with Anaplastic Thyroid Cancer

Background: Thyroid cancer (TC) remains a significant clinical challenge worldwide, with a subset of patients facing aggressive disease progression and therapeutic resistance. Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have emerged as promising therapeutic approaches for various malignancies, yet their efficacy in TC remains uncertain. The objective of this study was to investigate PD-L1 expression in aggressive TC and its association with histological subtypes, molecular mutation, and progression-free survival. Methods: This is a retrospective study of patients with advanced TC seen in two tertiary health care centers. Included in this study were patients with advanced TC with recurrence or progression on therapy for whom tumor molecular profiling and PD-L1 status were available. Kaplan–Meier estimators were utilized to analyze the progression-free survival (PFS) between patients with PD-L1 positive and negative status in Anaplastic TC (ATC) subgroup. Results: A total of 176 patients with advanced thyroid cancer were included (48.9% female). Of the patients, 13 had ATC, 11 Medullary TC (MTC), 81 Papillary TC Classic Variant (PTCCV), 20 Follicular TC (FTC), 8 Oncocytic TC (OTC), 10 Poorly Differentiated TC (PDTC), and 30 had the Papillary TC Follicular Variant (PTCFV). BRAF mutation was present in 41%, TERT in 30%, RAS in 19%, TP53 in 10%, and RET in 8.6% of patients. PD-L1 positivity was significantly different across different TC types and histological subtypes (p < 0.01): Patients with OTC had the highest frequency of PD-L1 positivity (71%), followed by ATC (69%), PTCCV (28.5%), and FTC (11%). Patients with MTC and PTCFV did not exhibit any PD-L1 positivity. TP53 mutation was positively associated with PD-L1 expression (21.6% vs. 7.5%, p = 0.03), and RAS mutation was negatively associated with PD-L1 expression (8.1% vs. 24.2% p = 0.04). Among patients with ATC, positive PD-L1 expression was associated with lower PFS (p = 0.002). Conclusions: PD-L1 expression varies across different TC types and histological subtypes and may be modulated by the mutational landscape. PD-L1 expression in ATC is associated with shorter PFS. Follow up studies are warranted to elucidate the molecular mechanism driving the observed differences in immune pathways, potentially paving the way for the development of more effective and personalized immune therapies for patients with aggressive TC.

A novel classification of dyslipidaemia through the analysis of five million lipid profiles: an unsupervised machine learning approach

Abstract Background Dyslipidemia encompasses a wide range of lipoprotein disorders categorised through two classifications (Fredrickson-Levy [FL] or Sniderman).(1,2) However, both classifications are criticised for relying on incomplete knowledge of lipoprotein metabolism, especially with the emergence of novel treatment options and variations in individual treatment responses.(3) Clustering, an unsupervised machine learning (ML) algorithm that can process a wide range of variables, has the potential to unmask patient groups with distinct molecular profiles and unique therapeutic targets that can inform more effective prevention strategies for cardiovascular disease (CVD).(4) Aim We aimed to use unsupervised ML algorithms to discover intrinsic dyslipidaemia categories from lipoprotein measurements, recognise the necessary components of lipid panels for classification, and analyse the similarities between the newly formed clusters, FL and Sniderman classifications. Methods Lipid profiles of 5,080,248 patients were obtained from the ‘Very Large Database of Lipids’ database. This yielded up to 78 blood components per patient, including at least 31 lipoprotein variables. The analysis involved unsupervised K-means clustering with optimised values for K and the subset of variables, determined in an unsupervised manner using a suitable measure of complexity. We then interpreted our clusters using probabilistic decision trees to provide compact and interpretable representations. Finally, we compared the clusters with Sniderman and FL categories. Results In a completely unsupervised fashion, we identified 14 clusters that could be matched to Sniderman categories. The confusion matrix showed total agreement of 76% (see Figure 1, left panel), relative Cohen’s kappa of 0.78 (the relative version captures accuracy on categories containing smaller numbers of patient profiles) and an accuracy of 96% on the small Type III class. Similar results were observed when matching to FL types. We accurately represented our clusters using probabilistic decision trees of small depth (see Figure 2). We discovered that the data had low intrinsic dimension and a manifold-like structure in which the different clusters could be illustrated (see Figure 1, right panel). Specifically, only 3 variables were needed to obtain our classification: apolipoprotein b, total cholesterol and triglycerides. Conclusion We showed that completely unsupervised ML techniques can uncover dyslipidaemia categories in lipoprotein profiles from a large patient population. The categories largely align with existing classifications based on prior knowledge of lipoprotein metabolism. Furthermore, few lipoprotein variables were required for categorisation (low-dimension data), which could aid in determining which lipoproteins should be measured in a clinical setting. Further analysis of the differences between ML clusters and traditional classifications is needed, which may enhance CVD risk management.

Different microRNA expression in the right ventricular outflow tract myocardium of tetralogy of Fallot

Abstract Background When repairing tetralogy of Fallot (TOF), there are two surgical options according to the size of the pulmonary valve: transannular patch repair and valve-preserving repair. Since the development of the pulmonary valve depends on the degree of obstruction of the right ventricular outflow tract (RVOT), molecular profiles of the RVOT muscles may be associated with the surgical decision. As a recent study shows altered microRNA expression of the right ventricular myocardium even in TOF patients, microRNA expression of the RVOT infundibular muscle may be different between the two procedures. Purpose To evaluate differences in microRNA expression levels of RVOT infundibular muscles between the transannular patch repair and valve-preserving repair groups. Methods Surgically resected infundibular muscles from TOF patients are frozen in liquid nitrogen and stored in our hospital biobank. Nine samples collected between August 2020 and July 2022 were used in this study. Five patients underwent a valve-preserving repair and the others underwent a transannular patch repair. Six patients were female and mean age at operation was 453 ± 240 days. These samples were homogenized and total RNA including microRNAs were extracted. MicroRNA expression levels were measured using a microRNA array capable of detecting over 2000 microRNAs simultaneously. Results 1171 microRNAs were detected in all nine samples. The expression levels of 22 microRNAs were significantly different between the transannular patch repair group and the valve-preserving repair group (P<0.05). The expression levels of 19 microRNAs were significantly higher in the transannular patch repair group and the others were significantly higher in the valve-preserving repair group. More than 2-fold changes were observed in 2 microRNAs between the transannular patch repair and valve-preserving repair groups. Conclusion MicroRNA expression of RVOT infundibular muscle differs between the transannular patch repair and valve-preserving repair groups. Therefore, microRNA analysis will be useful to evaluate the pathophysiology of TOF. In addition, microRNAs may become a useful biomarker for surgical decision making in TOF.

Gut microbiota predict retinopathy in patients with diabetes: A longitudinal cohort study

The gut microbiota has emerged as an independent risk factor for diabetes and its complications. This research aimed to delve into the intricate relationship between the gut microbiome and diabetic retinopathy (DR) through a dual approach of cross-sectional and prospective cohort studies. In our cross-sectional study cross-sectional investigation involving ninety-nine individuals with diabetes, distinct microbial signatures associated with DR were identified. Specifically, gut microbiome profiling revealed decreased levels of Butyricicoccus and Ruminococcus torques group, alongside upregulated methanogenesis pathways among DR patients. These individuals concurrently exhibited lower concentrations of short-chain fatty acids in their plasma. Leveraging machine learning models, including random forest classifiers, we constructed a panel of microbial genera and genes that robustly differentiated DR cases. Importantly, these genera also demonstrated significant correlations with dietary patterns and the molecular profiles of peripheral blood mononuclear cells. Building upon these findings, our prospective cohort study followed 62 diabetes patients over a 2-year period to assess the predictive value of these microbial markers. The results underlined the panel’s efficacy in predicting DR incidence. By stratifying patients based on the predictive genera and metabolites identified in the cross-sectional phase, we established significant associations between reduced levels of Butyricicoccus, plasma acetate, and increased susceptibility to DR. This investigation not only deepens our understanding of how gut microbiota influences DR but also underscores the potential of microbial markers as early indicators of disease risk. These insights hold promise for developing targeted interventions aimed at mitigating the impact of diabetic complications.Key points• Microbial signatures are differed in diabetic patients with and without retinopathy• DR-related taxa are linked to dietary habits and transcriptomic profiles• Lower abundances of Butyricicoccus and acetate were prospectively associated with DR

Glutamine and serum starvation alters the ATP production, oxidative stress, and abundance of mitochondrial RNAs in extracellular vesicles produced by cancer cells

Induction of autophagy represents an effective survival strategy for nutrient-deprived or stressed cancer cells. Autophagy contributes to the modulation of communication within the tumor microenvironment. Here, we conducted a study of the metabolic and signaling implications associated with autophagy induced by glutamine (Gln) and serum starvation and PI3K/mTOR inhibitor and autophagy inducer NVP-BEZ235 (BEZ) in the head and neck squamous cell carcinoma (HNSCC) cell line FaDu. We compared the effect of these different types of autophagy induction on ATP production, lipid peroxidation, mitophagy, RNA cargo of extracellular vesicles (EVs), and EVs-associated cytokine secretome of cancer cells. Both BEZ and starvation resulted in a decline in ATP production. Simultaneously, Gln starvation enhanced oxidative damage of cancer cells by lipid peroxidation. In starved cells, there was a discernible fragmentation of the mitochondrial network coupled with an increase in the presence of tumor susceptibility gene 101 (TSG101) on the mitochondrial membrane, indicative of the sorting of mitochondrial cargo into EVs. Consequently, the abundance of mitochondrial RNAs (mtRNAs) in EVs released by FaDu cells was enhanced. Notably, mtRNAs were also detectable in EVs isolated from the serum of both HNSCC patients and healthy controls. Starvation and BEZ reduced the production of EVs by cancer cells, yet the characteristic molecular profile of these EVs remained unchanged. We also found that alterations in the release of inflammatory cytokines constitute a principal response to autophagy induction. Importantly, the specific mechanism driving autophagy induction significantly influenced the composition of the EVs-associated cytokine secretome.

Artificial Intelligence in Head and Neck Cancer Diagnosis: A Comprehensive Review with Emphasis on Radiomics, Histopathological, and Molecular Applications

The present review discusses the transformative role of AI in the diagnosis and management of head and neck cancers (HNCs). Methods: It explores how AI technologies, including ML, DL, and CNNs, are applied in various diagnostic tasks, such as medical imaging, molecular profiling, and predictive modeling. Results: This review highlights AI’s ability to improve diagnostic accuracy and efficiency, particularly in analyzing medical images like CT, MRI, and PET scans, where AI sometimes outperforms human radiologists. This paper also emphasizes AI’s application in histopathology, where algorithms assist in whole-slide image (WSI) analysis, tumor-infiltrating lymphocytes (TILs) quantification, and tumor segmentation. AI shows promise in identifying subtle or rare histopathological patterns and enhancing the precision of tumor grading and treatment planning. Furthermore, the integration of AI with molecular and genomic data aids in mutation analysis, prognosis, and personalized treatment strategies. Conclusions: Despite these advancements, the review identifies challenges in AI adoption, such as data standardization and model interpretability, and calls for further research to fully integrate AI into clinical practice for improved patient outcomes.

Chemical Constituents, Antioxidant, and Enzyme Inhibitory Potentials Supported by In-Silico Studies of the n-Hexane Extract and Essential Oil of Platycladus orientalis (L.) Franco Leaves.

Platycladus orientalis leaves are widely used in traditional medicine to treat different ailments. In the present study, the volatile constituents were obtained by n-hexane extraction and hydrodistillation. Comprehensive metabolomic profiling was performed using GC-MS analysis. Furthermore, in vitro antioxidant potential and enzyme-inhibitory activity were assessed and supported by in silico profiling. Results revealed the predominance of monoterpene hydrocarbons in the hydrodistilled volatile oil (42.30%) followed by oxygenated sesquiterpenes (32.10%); with cedrol as the main component. Diterpenoids (49.70%) and sesquiterpene hydrocarbons (13.43%) were the major components of the n-hexane extract; with vulgarol A, a diterpene alcohol, as the major constituent. The volatile oil demonstrated significantly higher antioxidant potential across all assays, including ABTS and DDPH scavenging activity, CUPRAC, and FRAP assays. However, the n-hexane extract demonstrated broad inhibitory effects against butyrylcholinesterase, tyrosinase, α-amylase, and α-glucosidase enzymes, supported by molecular docking study and predictive ADME profiling. Therefore, it may be concluded that the n-hexane extract is a viable option for treating dysregulated enzyme conditions. In addition, the potential use of volatile oil in the pharmaceutical industries and management of oxidative stress can be inferred. These results warrant further studies to validate the therapeutic potential of the volatile oil and the n-hexane extract.

SS18-SSX Expression and Clinicopathologic Profiles in a Contemporary Cohort of Primary Paratesticular Synovial Sarcoma: A Series of Fourteen Patients.

Synovial sarcoma (SS) is a rare genitourinary malignancy with a specific SS18::SSX 1/2 gene fusion in majority of the instances. The paratesticular location of this neoplasm is extremely rare and only 4 cases are reported in the literature. Herein, we describe the clinicopathologic features and molecular profile of paratesticular SS in the largest case series to date and to the best of our knowledge, and the only series to use novel SS18-SSX antibody for immunohistochemistry. Clinicopathologic, immunohistochemical (IHC), molecular, treatment, and follow-up data of the patients were analyzed. There were 14 patients, ranging from 15 to 47 years (mean: 30y). The tumor size ranged from 4​​​​​​ to 15cm. The tumors were unilateral, solid, and homogeneous tan-white with monomorphic spindle cell histology. All 14 tumors expressed SS18-SSX and TLE1 IHC and harbored SS18 rearrangement. In addition, the tumor with multifocal SS18-SSX expression had lower break-apart signals in the FISH assay (38% of the tumor cells; range: 29% to 85%). Radical orchiectomy was performed in all 14 patients and adjuvant chemotherapy was administered in 9 patients. Follow-up was available in 9 patients. The follow-up duration ranged from 5 to 24 months (median=10mo). Four patients died of metastatic disease (range: 5 to 16mo) and 2 patients who are alive had metastatic disease at the last follow-up. Based on our experience with the largest series to date and aggregate of the published data, paratesticular SS has a poor prognosis despite aggressive therapy. Owing to its rarity, the differential diagnosis is wide and requires a systematic approach for ruling out key morphologic mimics aided with SS18-SSX IHC and molecular confirmation because this distinction carries important therapeutic and prognostic implications. Due to the excellent concordance of SS18-SSX IHC results with FISH results as observed in our study, we would like to suggest inclusion of SS18-SSX in the diagnostic immunohistochemistry panel of all spindle cell sarcomas where synovial sarcoma is considered as a morphologic differential. SS18-SSX-positive staining may be used as a surrogate for FISH assay in a resource-limited setting where molecular assay is not available. Furthermore, IHC has a fairly shorter turn-around-time, is less complex, and of low cost.

Morphological and Molecular Profiling of Amyloid-β Species in Alzheimer's Pathogenesis.

Alzheimer's disease (AD) is the most common form of dementia around the world (~ 65%). Here, we portray the neuropathology of AD, biomarkers, and classification of amyloid plaques (diffuse, non-cored, dense core, compact). Tau pathology and its involvement with Aβ plaques and cell death are discussed. Amyloid cascade hypotheses, aggregation mechanisms, and molecular species formed in vitro and in vivo (on- and off-pathways) are described. Aβ42/Aβ40 monomers, dimers, trimers, Aβ-derived diffusible ligands, globulomers, dodecamers, amylospheroids, amorphous aggregates, protofibrils, fibrils, and plaques are characterized (structure, size, morphology, solubility, toxicity, mechanistic steps). An update on AD-approved drugs by regulatory agencies, along with new Aβ-based therapies, is presented. Beyond prescribing Aβ plaque disruptors, cholinergic agonists, or NMDA receptor antagonists, other therapeutic strategies (RNAi, glutaminyl cyclase inhibitors, monoclonal antibodies, secretase modulators, Aβ aggregation inhibitors, and anti-amyloid vaccines) are already under clinical trials. New drug discovery approaches based on "designed multiple ligands", "hybrid molecules", or "multitarget-directed ligands" are also being put forward and may contribute to tackling this highly debilitating and fatal form of human dementia.

Identification of Volatile Organic Compounds (Distinct Biomarkers) Emitted by Cancer Cells Using Gas Chromatography-mass Spectrometry – A Review

The utilization of Gas Chromatography-Mass Spectrometry (GC-MS) for the detection of Volatile Organic Compounds (VOCs) as potential biomarkers in cancer diagnostics is an evolving and promising field. This review outlines current exploratory and pilot studies that lay a fundamental groundwork for future research. Due to the complexity of the fecal and respiratory volatilome, influenced by a myriad of biological and environmental factors, it is crucial to expand research demographics to enhance data robustness and ensure the applicability of findings across diverse populations. We have also, herein, highlighted the dual capability of VOC analysis to detect cancer and differentiate between its stages, which is vital for customizing patient treatment plans and monitoring therapeutic efficacy. Furthermore, establishing quantifiable thresholds for VOC concentrations is essential for their clinical adoption as reliable indicators of cancer. The integration of GC-MS with machine learning and Artificial Intelligence (AI) could be useful for comprehensive metabolic profiles and facilitating the development of non-invasive and real-time diagnostic tools. The adoption of multi-omics approach promises a deeper understanding of cancer biology, potentially leading to personalized medicine and strategies finely tuned to individual molecular profiles. Hence, the research on VOCs as cancer biomarkers is set to offer transformative advancements in diagnostic technologies, ultimately improving patient outcomes through tailored therapeutic interventions.

A multidimensional recommendation framework for identifying biological targets to aid the diagnosis and treatment of liver metastasis in patients with colorectal cancer

The quest to understand the molecular mechanisms of tumour metastasis and identify pivotal biomarkers for cancer therapy is increasing in importance. Single-omics analyses, constrained by their focus on a single biological layer, cannot fully elucidate the complexities of tumour molecular profiles and can thus overlook crucial molecular targets. In response to this limitation, we developed a multiobjective recommendation system (RJH-Metastasis 1.0) anchored in a multiomics knowledge graph to integrate genome, transcriptome, and proteome data and corroborative literature evidence and then conducted comprehensive analyses of colorectal cancer with liver metastasis (CRCLM). A total of 25 key genes significantly associated with CRCLM were recommended by our system, and GNB1, GATAD2A, GBP2, MACROD1, and EIF5B were further highlighted. Specifically, GNB1 presented fewer mutations but elevated RNA transcription and protein expression in CRCLM patients. The role of GNB1 in promoting the malignant behaviours of colon cancer cells was demonstrated via in vitro and in vivo studies. Aberrant expression of GNB1 could be regulated by METTL1-driven m7G modification. METTL1 knockdown decreased m7G modification in the 3’ UTR of GNB1, increasing its mRNA transcription and translation during liver metastasis. Furthermore, GNB1 induced the formation of an immunosuppressive microenvironment by promoting the CLEC2C-KLRB1 interaction between memory B cells and KLRB1+PD-1+CD8+ cells. GNB1 expression and the efficacy of PD-1 antibody-based treatment in CRCLM patients were significantly correlated. In summary, our recommendation system can be used for effective exploration of key molecules in colorectal cancer, among which GNB1 was identified as a critical CRCLM promoter and immunotherapy biomarker in colorectal cancer patients.

IGF1 drives Wnt-induced joint damage and is a potential therapeutic target for osteoarthritis

Osteoarthritis is the most common joint disease and a global leading cause of pain and disability. Current treatment is limited to symptom relief, yet there is no disease-modifying therapy. Its multifactorial etiology includes excessive activation of Wnt signaling, but how Wnt causes joint destruction remains poorly understood. Here, we identify that Wnt signaling promotes the transcription of insulin-like growth factor 1 (IGF1) in articular chondrocytes and that IGF1 is a major driver of Wnt-induced joint damage. Male mice with cartilage-specific Igf1 deficiency are protected from Wnt-triggered joint disease. Mechanistically, Wnt-induced IGF1 transcription depends on β-catenin and binding of Wnt transcription factor TCF4 to the IGF1 gene promoter. In a clinically relevant mouse model of post-traumatic osteoarthritis, cartilage-specific deletion of Igf1 protects against the disease in male mice. IGF1 silencing in chondrocytes from patients with osteoarthritis restores a healthy molecular profile. Our findings reveal that reducing Wnt-induced IGF1 is a potential therapeutic strategy for osteoarthritis.

Impact of select actionable genomic alterations on efficacy of neoadjuvant immunotherapy in resectable non-small cell lung cancer

BackgroundNeoadjuvant immune checkpoint inhibitors (ICIs) have improved survival outcomes compared with chemotherapy in resectable non-small cell lung cancer (NSCLC). However, the impact of actionable genomic alterations (AGAs) on the efficacy...