Myelination potential and injury susceptibility of grey versus white matter human oligodendrocytes.

Increasing evidence indicates heterogeneity in functional and molecular properties of oligodendrocyte lineage cells both during development and under pathologic conditions. In multiple sclerosis, remyelination of grey matter lesions exceeds that in white matter. Here we used cells derived from grey matter versus white matter regions of surgically resected human brain tissue samples, to compare the capacities of human A2B5-positive progenitor cells and mature oligodendrocytes to ensheath synthetic nanofibers, and relate differences to the molecular profiles of these cells. For both cell types, the percentage of ensheathing cells was greater for grey matter versus white matter cells. For both grey matter and white matter samples, the percentage of cells ensheathing nanofibers was greater for A2B5-positive cells versus mature oligodendrocytes. Grey matter A2B5-positive cells were more susceptible than white matter A2B5-positive cells to injury induced by metabolic insults. Bulk RNA sequencing indicated that separation by cell type (A2B5-positive vs mature oligodendrocytes) is more significant than by region but segregation for each cell type by region is apparent. Molecular features of grey matter versus white matter derived A2B5-positive and mature oligodendrocytes were lower expression of mature oligodendrocyte genes and increased expression of early oligodendrocyte lineage genes. Genes and pathways with increased expression in grey matter derived cells with relevance for myelination included those related to responses to external environment, cell-cell communication, cell migration, and cell adhesion. Immune and cell death related genes were up-regulated in grey matter derived cells. We observed a significant number of up-regulated genes shared between the stress/injury and myelination processes, providing a basis for these features. In contrast to oligodendrocyte lineage cells, no functional or molecular heterogeneity was detected in microglia maintained in vitro, likely reflecting the plasticity of these cells ex vivo. The combined functional and molecular data indicate that grey matter human oligodendrocytes have increased intrinsic capacity to myelinate but also increased injury susceptibility, in part reflecting their being at a stage earlier in the oligodendrocyte lineage.

Biomarker Landscape in RASopathies.

RASopathies are a group of related genetic disorders caused by mutations in genes within the RAS/MAPK signaling pathway. This pathway is crucial for cell division, growth, and differentiation, and its disruption can lead to a variety of developmental and health issues. RASopathies present diverse clinical features and pose significant diagnostic and therapeutic challenges. Studying the landscape of biomarkers in RASopathies has the potential to improve both clinical practices and the understanding of these disorders. This review provides an overview of recent discoveries in RASopathy molecular profiling, which extend beyond traditional gene mutation analysis. mRNAs, non-coding RNAs, protein expression patterns, and post-translational modifications characteristic of RASopathy patients within pivotal signaling pathways such as the RAS/MAPK, PI3K/AKT/mTOR, and Rho/ROCK/LIMK2/cofilin pathways are summarized. Additionally, the field of metabolomics holds potential for uncovering metabolic signatures associated with specific RASopathies, which are crucial for developing precision medicine. Beyond molecular markers, we also examine the role of histological characteristics and non-invasive physiological assessments in identifying potential biomarkers, as they provide evidence of the disease's effects on various systems. Here, we synthesize key findings and illuminate promising avenues for future research in RASopathy biomarker discovery, underscoring rigorous validation and clinical translation.

Closing the gap: prognostic and predictive biomarker validation for personalized care in a Latin American hormone-dependent breast cancer cohort.

BACKGROUND: Several guidelines recommend the use of different classifiers to determine the risk of recurrence (ROR) and treatment decisions in patients with HR+HER2- breast cancer. However, data are still lacking for their usefulness in Latin American (LA) patients. Our aim was to evaluate the comparative prognostic and predictive performance of different ROR classifiers in a real-world LA cohort. METHODS: The Molecular Profile of Breast Cancer Study (MPBCS) is an LA case-cohort study with 5-year follow-up. Stages I and II, clinically node-negative HR+HER2- patients (n = 340) who received adjuvant hormone therapy and/or chemotherapy, were analyzed. Time-dependent receiver-operator characteristic-area under the curve, univariate and multivariate Cox proportional hazards regression (CPHR) models were used to compare the prognostic performance of several risk biomarkers. Multivariate CPHR with interaction models tested the predictive ability of selected risk classifiers. RESULTS: Within this cohort, transcriptomic-based classifiers such as the recurrence score (RS), EndoPredict (EP risk and EPClin), and PAM50-risk of recurrence scores (ROR-S and ROR-PC) presented better prognostic performances for node-negative patients (univariate C-index 0.61-0.68, adjusted C-index 0.77-0.80, adjusted hazard ratios [HR] between high and low risk: 4.06-9.97) than the traditional classifiers Ki67 and Nottingham Prognostic Index (univariate C-index 0.53-0.59, adjusted C-index 0.72-0.75, and adjusted HR 1.85-2.54). RS (and to some extent, EndoPredict) also showed predictive capacity for chemotherapy benefit in node-negative patients (interaction P = .0200 and .0510, respectively). CONCLUSION: In summary, we could prove the clinical validity of most transcriptomic-based risk classifiers and their superiority over clinical and immunohistochemical-based methods in the heterogenous, real-world node-negative HR+HER2- MPBCS cohort.

Molecular Signatures of CB-6644 Inhibition of the RUVBL1/2 Complex in Multiple Myeloma.

Multiple myeloma is the second most hematological cancer. RUVBL1 and RUVBL2 form a subcomplex of many chromatin remodeling complexes implicated in cancer progression. As an inhibitor specific to the RUVBL1/2 complex, CB-6644 exhibits remarkable anti-tumor activity in xenograft models of Burkitt's lymphoma and multiple myeloma (MM). In this work, we defined transcriptional signatures corresponding to CB-6644 treatment in MM cells and determined underlying epigenetic changes in terms of chromatin accessibility. CB-6644 upregulated biological processes related to interferon response and downregulated those linked to cell proliferation in MM cells. Transcriptional regulator inference identified E2Fs as regulators for downregulated genes and MED1 and MYC as regulators for upregulated genes. CB-6644-induced changes in chromatin accessibility occurred mostly in non-promoter regions. Footprinting analysis identified transcription factors implied in modulating chromatin accessibility in response to CB-6644 treatment, including ATF4/CEBP and IRF4. Lastly, integrative analysis of transcription responses to various chemical compounds of the molecular signature genes from public gene expression data identified CB-5083, a p97 inhibitor, as a synergistic candidate with CB-6644 in MM cells, but experimental validation refuted this hypothesis.

Comparing molecular signatures of dissolved organic matter (DOM) in four large freshwater lakes differing in hydrological connectivity to the Changjiang River.

Freshwater lakes serve as active conduits for processing terrestrial dissolved organic matter (DOM), playing a crucial role in global carbon cycle. Little attention has been paid to how hydrological connectivity to a large river would affect the molecular signatures of DOM in lakes. Here, we systematically characterized and compared the molecular signatures of DOM in surface waters of four large freshwater lakes in the middle and lower Changjiang River basin that are directly connected to the river (Lake Dongting and Lake Poyang, referred to as Lakeconnected) or indirectly connected to the river (Lake Chao and Lake Tai, referred to as Lakenonconnected). The DOM in Lakeconnected was found to have similar total organic carbon (TOC)-normalized contents and characteristics of lignin phenols to the DOM in surface waters from the upstream Changjiang river, indicating allochthonous/terrestrial sources from riverine inputs. As indicated by the UV-vis and fluorescence analyses, the DOM in Lakeconnected overall had higher aromaticity and larger average molecular weight as well as stronger allochthonous feature compared to the DOM in Lakenonconnected. Consistently, the FT-ICR MS analysis revealed that the DOM in Lakeconnected had higher molecular diversity, higher unsaturation degree, and larger proportions of highly aromatic compounds. In contrast, the DOM in Lakenonconnected had larger proportions of lipids and peptide-like structures, but lower proportions of aromatic compounds, which could be ascribed to the enhanced autochthonous production and photodegradation due to pollution and eutrophication as well as longer water residence time. The results highlight the strong impacts of the hydrological connectivity to a large river on the molecular signatures of lake DOM. CAPSULE: The hydrological connectivity of the lakes to the Changjiang River has strong impacts on the molecular signatures of lake DOM.

Molecular landscape for risk prediction and personalized therapeutics of castration-resistant prostate cancer: at a glance.

Prostate cancer (PCa) is commonly occurred with high incidence in men worldwide, and many patients will be eventually suffered from the dilemma of castration-resistance with the time of disease progression. Castration-resistant PCa (CRPC) is an advanced subtype of PCa with heterogeneous carcinogenesis, resulting in poor prognosis and difficulties in therapy. Currently, disorders in androgen receptor (AR)-related signaling are widely acknowledged as the leading cause of CRPC development, and some non-AR-based strategies are also proposed for CRPC clinical analyses. The initiation of CRPC is a consequence of abnormal interaction and regulation among molecules and pathways at multi-biological levels. In this study, CRPC-associated genes, RNAs, proteins, and metabolites were manually collected and integrated by a comprehensive literature review, and they were functionally classified and compared based on the role during CRPC evolution, i.e., drivers, suppressors, and biomarkers, etc. Finally, translational perspectives for data-driven and artificial intelligence-powered CRPC systems biology analysis were discussed to highlight the significance of novel molecule-based approaches for CRPC precision medicine and holistic healthcare.

Decoding the molecular concerto: Toxicotranscriptomic evaluation of microplastic and nanoplastic impacts on aquatic organisms.

The pervasive and steadily increasing presence of microplastics/nanoplastics (MPs/NPs) in aquatic environments has raised significant concerns regarding their potential adverse effects on aquatic organisms and their integration into trophic dynamics. This emerging issue has garnered the attention of (eco)toxicologists, promoting the utilization of toxicotranscriptomics to unravel the responses of aquatic organisms not only to MPs/NPs but also to a wide spectrum of environmental pollutants. This review aims to systematically explore the broad repertoire of predicted molecular responses by aquatic organisms, providing valuable intuitions into complex interactions between plastic pollutants and aquatic biota. By synthesizing the latest literature, present analysis sheds light on transcriptomic signatures like gene expression, interconnected pathways and overall molecular mechanisms influenced by various plasticizers. Harmful effects of these contaminants on key genes/protein transcripts associated with crucial pathways lead to abnormal immune response, metabolic response, neural response, apoptosis and DNA damage, growth, development, reproductive abnormalities, detoxification, and oxidative stress in aquatic organisms. However, unique challenge lies in enhancing the fingerprint of MPs/NPs, presenting complicated enigma that requires decoding their specific impact at molecular levels. The exploration endeavors, not only to consolidate existing knowledge, but also to identify critical gaps in understanding, push forward the frontiers of knowledge about transcriptomic signatures of plastic contaminants. Moreover, this appraisal emphasizes the imperative to monitor and mitigate the contamination of commercially important aquatic species by MPs/NPs, highlighting the pivotal role that regulatory frameworks must play in protecting all aquatic ecosystems. This commitment aligns with the broader goal of ensuring the sustainability of aquatic resources and the resilience of ecosystems facing the growing threat of plastic pollutants.

Noncoding RNA landscape and their emerging roles as biomarkers and therapeutic targets in meningioma.

Meningiomas are among the most prevalent primary CNS tumors in adults, accounting for nearly 38% of all brain neoplasms. The World Health Organization (WHO) grade assigned to meningiomas guides medical care in patients and is primarily based on tumor histology and malignancy potential. Although often considered benign, meningiomas with complicated histology, limited accessibility for surgical resection, and/or higher malignancy potential (WHO grade 2 and WHO grade 3) are harder to combat, resulting in significant morbidity. With limited treatment options and no systemic therapies, it is imperative to understand meningioma tumorigenesis at the molecular level and identify novel therapeutic targets. The last decade witnessed considerable progress in understanding the noncoding RNA landscape of meningioma, with microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) emerging as molecular entities of interest. This review aims to highlight the commonly dysregulated miRNAs and lncRNAs in meningioma and their correlation with meningioma progression, malignancy, recurrence, and radioresistance. The role of "key" miRNAs as biomarkers and their therapeutic potential has also been reviewed in detail. Furthermore, current and emerging therapeutic modalities for meningioma have been discussed, with emphasis on the need to identify and subsequently employ clinically relevant miRNAs and lncRNAs as novel therapeutic targets and biomarkers.

Recent developments in the diagnosis of pancreatic neuroendocrine neoplasms.

INTRODUCTION: Pancreatic Neuroendocrine Neoplasms (PanNENs) are characterized by a highly heterogeneous clinical and biological behavior, making their diagnosis challenging. PanNENs diagnostic work-up mainly relies on biochemical markers, pathological examination, and imaging evaluation. The latter includes radiological imaging (i.e. computed tomography [CT] and magnetic resonance imaging [MRI]), functional imaging (i.e. 68Gallium [68 Ga]Ga-DOTA-peptide PET/CT and Fluorine-18 fluorodeoxyglucose [18F]FDG PET/CT), and endoscopic ultrasound (EUS) with its associated procedures. AREAS COVERED: This review provides a comprehensive assessment of the recent advancements in the PanNENs diagnostic field. PubMed and Embase databases were used for the research, performed from inception to October 2023. EXPERT OPINION: A deeper understanding of PanNENs biology, recent technological improvements in imaging modalities, as well as progresses achieved in molecular and cytological assays, are fundamental players for the achievement of early diagnosis and enhanced preoperative characterization of PanNENs. A multimodal diagnostic approach is required for a thorough disease assessment.

Proteomic Insights into Biology of Bipolar Disorder: Implications for Health Complexity and Mortality.

OBJECTIVE: The present study has the following objectives: 1) identify differentially expressed proteins and pathways in blood samples of BD compared to healthy controls by employing high-throughput proteomics and bioinformatics and 2) characterize disease-related molecular signatures through in-depth analysis of the differentially expressed proteins and pathways. METHODS: Blood samples from BD patients (n=10) classified into high (BD+) or poor functioning (BD-), based on functional and cognitive status, and healthy controls (n=5) were analyzed using mass spectrometry-based proteomic analysis. Bioinformatics was performed to detect biological processes, pathways, and diseases related to BD. RESULTS: Eight proteins exclusively characterized the molecular profile of patients with BD+ compared to HC, while 26 altered proteins were observed in the BD- group. These altered proteins were mainly enriched in biological processes related to lipid metabolism, complement system and coagulation cascade, and cardiovascular diseases; all these changes were more prominent in the BD- group. CONCLUSION: These findings may represent systemic alterations that occur with the progression of the illness and a possible link between BD and medical comorbidities. Such comprehensive understanding provides valuable insights for targeted interventions, addressing mental and physical health aspects in subjects with BD. Despite these promising findings, further research is warranted, encompassing larger sample cohorts and incorporating biological validation through molecular biology methods.

Widespread alteration of protein autoinhibition in human cancers.

Autoinhibition is a prevalent allosteric regulatory mechanism in signaling proteins. Reduced autoinhibition underlies the tumorigenic effect of some known cancer drivers, but whether autoinhibition is altered generally in cancer remains elusive. Here, we demonstrate that cancer-associated missense mutations, in-frame insertions/deletions, and fusion breakpoints are enriched within inhibitory allosteric switches (IASs) across all cancer types. Selection for IASs that are recurrently mutated in cancers identifies established and unknown cancer drivers. Recurrent missense mutations in IASs of these drivers are associated with distinct, cancer-specific changes in molecular signaling. For the specific case of PPP3CA, the catalytic subunit of calcineurin, we provide insights into the molecular mechanisms of altered autoinhibition by cancer mutations using biomolecular simulations, and demonstrate that such mutations are associated with transcriptome changes consistent with increased calcineurin signaling. Our integrative study shows that autoinhibition-modulating genetic alterations are positively selected for by cancer cells.

Single-Cell Transcriptome Analysis Reveals Development-Specific Networks at Distinct Synchronized Antral Follicle Sizes in Sheep Oocytes.

The development of the ovarian antral follicle is a complex, highly regulated process. Oocytes orchestrate and coordinate the development of mammalian ovarian follicles, and the rate of follicular development is governed by a developmental program intrinsic to the oocyte. Characterizing oocyte signatures during this dynamic process is critical for understanding oocyte maturation and follicular development. Although the transcriptional signature of sheep oocytes matured in vitro and preovulatory oocytes have been previously described, the transcriptional changes of oocytes in antral follicles have not. Here, we used single-cell transcriptomics (SmartSeq2) to characterize sheep oocytes from small, medium, and large antral follicles. We characterized the transcriptomic landscape of sheep oocytes during antral follicle development, identifying unique features in the transcriptional atlas, stage-specific molecular signatures, oocyte-secreted factors, and transcription factor networks. Notably, we identified the specific expression of 222 genes in the LO, 8 and 6 genes that were stage-specific in the MO and SO, respectively. We also elucidated signaling pathways in each antral follicle size that may reflect oocyte quality and in vitro maturation competency. Additionally, we discovered key biological processes that drive the transition from small to large antral follicles, revealing hub genes involved in follicle recruitment and selection. Thus, our work provides a comprehensive characterization of the single-oocyte transcriptome, filling a gap in the mapping of the molecular landscape of sheep oogenesis. We also provide key insights into the transcriptional regulation of the critical sizes of antral follicular development, which is essential for understanding how the oocyte orchestrates follicular development.

Novel model of pyroptosis-related molecular signatures for prognosis prediction of clear cell renal cell carcinoma patients.

Background: Pyroptosis is a programmed death mode of inflammatory cells, which is closely related to tumor progression and tumor immunity. Clear cell renal cell carcinoma (ccRCC) is the major pathological type of renal cell carcinoma (RCC) with poor prognosis. Many theories have tried to clarify the mechanism in the development of ccRCC, but the role of pyroptosis in ccRCC has not been well described. The main purpose of this study is to explore the role of pyroptosis in ccRCC and establish a novel prognosis prediction model of pyroptosis-related molecular signatures for ccRCC. Methods: In the present study, we made a systematical analysis of the association between ccRCC RNA transcriptome sequencing data from The Cancer Genome Atlas (TCGA) database [which included 529 ccRCC patients who were randomized in a training cohort (n=265) and an internal validation cohort (n=264)] and 40 pyroptosis-related genes (PRGs), from which four genes (CASP9, GSDME, IL1B and TIRAP) were selected to construct a molecular prediction model of PRGs for ccRCC. In addition, a cohort of 114 ccRCC patients from Shanghai Eastern Hepatobiliary Surgery Hospital (EHSH) was used as external data to verify the effectiveness of the model by immunohistochemistry. Moreover, the biological functions of the four PRGs were also verified in ccRCC 786-O and 769-P cells by Western blot (WB), CCK-8 cell proliferation, and Transwell invasion assays. Results: The model was able to differentiate high-risk patients from low-risk patients, and this differentiation was consistent with their clinical survival outcomes. In addition, the four PRGs also affected the ability of cell proliferation and invasion in ccRCC. Conclusion: The prediction model of pyroptosis-related molecular markers developed in this study may prove to be a novel understanding for ccRCC.

Direct image to subtype prediction for brain tumors using deep learning.

Background: Deep Learning (DL) can predict molecular alterations of solid tumors directly from routine histopathology slides. Since the 2021 update of the World Health Organization (WHO) diagnostic criteria, the classification of brain tumors integrates both histopathological and molecular information. We hypothesize that DL can predict molecular alterations as well as WHO subtyping of brain tumors from hematoxylin and eosin-stained histopathology slides. Methods: We used weakly supervised DL and applied it to three large cohorts of brain tumor samples, comprising N = 2845 patients. Results: We found that the key molecular alterations for subtyping, IDH and ATRX, as well as 1p19q codeletion, were predictable from histology with an area under the receiver operating characteristic curve (AUROC) of 0.95, 0.90, and 0.80 in the training cohort, respectively. These findings were upheld in external validation cohorts with AUROCs of 0.90, 0.79, and 0.87 for prediction of IDH, ATRX, and 1p19q codeletion, respectively. Conclusions: In the future, such DL-based implementations could ease diagnostic workflows, particularly for situations in which advanced molecular testing is not readily available.

The causal association between obesity and gastric cancer and shared molecular signatures: a large-scale Mendelian randomization and multi-omics analysis.

Purpose: While observational studies have identified obesity as a potential risk factor for gastric cancer, the causality remains uncertain. This study aimed to evaluate the causal relationship between obesity and gastric cancer and identify the shared molecular signatures linking obesity to gastric cancer. Methods: A two-sample Mendelian randomization (MR) analysis was conducted using the GWAS data of body fat percentage (exposure, n = 331,117) and gastric cancer (outcome, n = 202,308). Bioinformatics and meta-analysis of multi-omics data were performed to identify key molecules mediating the causality. The meta-analysis of the plasma/serum proteome included 1,662 obese and 3,153 gastric cancer patients. Obesity and gastric cancer-associated genes were identified using seven common gene ontology databases. The transcriptomic data were obtained from TCGA and GEO databases. The Bioinformatic findings were clinically validated in plasma from 220 obese and 400 gastric cancer patients across two hospitals. Finally, structural-based virtual screening (SBVS) was performed to explore the potential FDA-approved drugs targeting the identified mediating molecules. Results: The MR analysis revealed a significant causal association between obesity and gastric cancer (IVW, OR = 1.37, 95% CI:1.12-1.69, P = 0.0028), without pleiotropy or heterogeneity. Bioinformatic and meta-analysis of multi-omics data revealed shared TNF, PI3K-AKT, and cytokine signaling dysregulation, with significant upregulation of AKT1, IL-6, and TNF. The clinical study confirmed widespread upregulation of systemic inflammatory markers in the plasma of both diseases. SBVS identified six novel potent AKT1 inhibitors, including the dietary supplement adenosine, representing a potentially preventive drug with low toxicity. Conclusion: Obesity causally increases gastric cancer, likely mediated by persistent AKT1/IL-6/TNF upregulation. As a potential AKT1 inhibitor, adenosine may mitigate the obesity-to-gastric cancer transition. These findings could inform preventive drug development to reduce gastric cancer risk in obesity.

Molecular and optical signatures of photochemical transformation of dissolved organic matter: Nonnegligible role of suspended particulate matter in urban river.

Natural dissolved organic matter (DOM) is one of the Earth's dynamic carbon pools and a key intermediate in the global carbon cycle. Photochemical processes potentially affect DOM composition and activity in surface water. Suspended particulate matter (SPM) is the integral component of slow-moving rivers, and holds the potential for photochemical reactivity. To further investigate the influence of SPM on DOM photochemical transformation, this study conducted experiments comparing samples with and without SPM irradiated under simulated sunlight. Surface water samples from slow-moving urban rivers were collected. DOM optical characteristics and molecular features obtained by Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) were investigated. Photolabile DOM was enriched in unsaturated and highly aromatic terrestrial substances. Photoproduced DOM had low aromaticity and was dominated by saturated aliphatics, protein-like substances, and carbohydrates. Study results indicated that the presence of SPM had a nonnegligible impact on the molecular traits of DOM, such as composition, molecular diversity, photolability, and bioavailability during photochemical reactions. In the environment affected by SPM, molecules containing heteroatoms exhibit higher photosensitivity. SPM promotes the photochemical transformation of a wider range of chemical types of photolabile DOM, particularly nitrogen-containing compounds. This study provides an essential insight into the more precise simulation of photochemical reactions of DOM influenced by SPM occurring in natural rivers, contributing to our understanding of the global carbon cycle from new theoretical perspectives.

Deciphering molecular complexity of HCV-associated lymphoproliferation.

Recent clinical studies demonstrated the achievement of lymphoma responses in patients with Hepatitis C virus-associated indolent lymphoproliferative disorders (LPD) receiving direct-acting antivirals (DAAs) as their sole treatment. However, the molecular mechanisms underlying LPD responses to DAAs are still poorly understood. In their paper the authors provide new molecular insights on this issue, reporting intraclonal diversification and persistence of B-cell clones in most cases, despite viral eradication and beneficial clinical outcome. These provocative data suggest that the achievement of molecular response is probably not required for a 'functional cure' of these patients. Further comprehensive immunogenetic and mutational studies would be fundamental to dissect this biological puzzle and, ultimately, to refine improved treatment strategies in this setting. Commentary on: Mazzaro et al. Persistence of monoclonal B-cell expansion and intraclonal diversification despite virus eradication in patients affected by hepatitis C virus-associated lymphoproliferative disorders. Br J Haematol 2023;203:237-243.

Translational implications of newly characterized pathogenic pathways in systemic lupus erythematosus.

Improved characterization of relevant pathogenic pathways in systemic lupus erythematosus (SLE) has been further delineated over the last decades. This led to the development of targeted treatments including belimumab and anifrolumab, which recently became available in clinics. Therapeutic targets in SLE encompass interferon (IFN) signaling, B-T costimulation including immune checkpoints, and increasing modalities of B lineage targeting, such as chimeric antigen receptor (CAR) T cells directed against CD19 or sequential anti-B cell targeting. Patient profiling based on characterization of underlying molecular abnormalities, often performed through comprehensive omics analyses, has recently been shown to better predict patients' treatment responses and also holds promise to unravel key molecular mechanisms driving SLE. SLE carries two key signatures, namely the IFN and B lineage/plasma cell signatures. Recent advances in SLE treatments clearly indicate that targeting innate and adaptive immunity is successful in such a complex autoimmune disease. Although those signatures may interact at the molecular level and provide the basis for the first selective treatments in SLE, it remains to be clarified whether these distinct treatments show different treatment responses among certain patient subsets. In fact, notwithstanding the remarkable amount of novel clues for innovative SLE treatment, harmonization of big data within tailored treatment strategies will be instrumental to better understand and treat this challenging autoimmune disorder. This review will provide an overview of recent improvements in SLE pathogenesis, related insights by analyses of big data and machine learning as well as technical improvements in conducting clinical trials with the ultimate goal that translational research results in improved patient outcomes.