An unbiased approach of molecular characterization of the endometrium: toward defining endometrial-based infertility.

Infertility is a complex condition affecting millions of couples worldwide. The current definition of infertility, based on clinical criteria, fails to account for the molecular and cellular changes that may occur during the development of infertility. Recent advancements in sequencing technology and single-cell analysis offer new opportunities to gain a deeper understanding of these changes. The endometrium has a potential role in infertility and has been extensively studied to identify gene expression profiles associated with (impaired) endometrial receptivity. However, limited overlap among studies hampers the identification of relevant downstream pathways that could play a role in the development of endometrial-related infertility. To address these challenges, we propose sequencing the endometrial transcriptome of healthy and infertile women at the single-cell level to consistently identify molecular signatures. Establishing consensus on physiological patterns in endometrial samples can aid in identifying deviations in infertile patients. A similar strategy has been used with great success in cancer research. However, large collaborative initiatives, international uniform protocols of sample collection and processing are crucial to ensure reliability and reproducibility. Overall, the proposed approach holds promise for an objective and accurate classification of endometrial-based infertility and has the potential to improve diagnosis and treatment outcomes.

WONOEP 2022: Neurotechnology for the diagnosis of epilepsy.

Epilepsy's myriad causes and clinical presentations ensure that accurate diagnoses and targeted treatments remain a challenge. Advanced neurotechnologies are needed to better characterize individual patients across multiple modalities and analytical techniques. At the XVIth Workshop on Neurobiology of Epilepsy: Early Onset Epilepsies: Neurobiology and Novel Therapeutic Strategies (WONOEP 2022), the session on "advanced tools" highlighted a range of approaches, from molecular phenotyping of genetic epilepsy models and resected tissue samples to imaging-guided localization of epileptogenic tissue for surgical resection of focal malformations. These tools integrate cutting edge research, clinical data acquisition, and advanced computational methods to leverage the rich information contained within increasingly large datasets. A number of common challenges and opportunities emerged, including the need for multidisciplinary collaboration, multimodal integration, potential ethical challenges, and the multistage path to clinical translation. Despite these challenges, advanced epilepsy neurotechnologies offer the potential to improve our understanding of the underlying causes of epilepsy and our capacity to provide patient-specific treatment.

Stratification of asthma by lipidomic profiling of induced sputum supernatant.

BACKGROUND: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. OBJECTIVE: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. METHODS: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. RESULTS: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. CONCLUSION: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.

Metabolic changes and retinal remodeling in Heterozygous CRX mutant cats (CRXRDY/+).

CRX is a transcription factor essential for normal photoreceptor development and survival. The CRXRdy cat has a naturally occurring truncating mutation in CRX and is a large animal model for dominant Leber congenital amaurosis. This study investigated retinal remodeling that occurs as photoreceptors degenerate. CRXRdy/+ cats from 6 weeks to 10 years of age were investigated. In vivo structural changes of retinas were analyzed by fundus examination, confocal scanning laser ophthalmoscopy and spectral domain optical coherence tomography. Histologic analyses included immunohistochemistry for computational molecular phenotyping with macromolecules and small molecules. Affected cats had a cone-led photoreceptor degeneration starting in the area centralis. Initially there was preservation of inner retinal cells such as bipolar, amacrine and horizontal cells but with time migration of the deafferented neurons occurred. Early in the process of degeneration glial activation occurs ultimately resulting in formation of a glial seal. With progression the macula-equivalent area centralis developed severe atrophy including loss of retinal pigmentary epithelium. Microneuroma formation occured in advanced stages as more marked retinal remodeling occurred. This study indicates that retinal degeneration in the CrxRdy/+ cat retina follows the progressive, phased revision of retina that have been previously described for retinal remodeling. These findings suggest that therapy dependent on targeting inner retinal cells may be useful in young adults with preserved inner retinas prior to advanced stages of retinal remodeling and neuronal cell loss.

Genetic profiles of transcriptomic clusters of childhood asthma determine specific severe subtype.

BACKGROUND: Previous studies have defined transcriptomic subtypes of adult asthma using samples of induced sputum and bronchial epithelium; however, those procedures are not readily applicable in the clinic, especially for childhood asthma. OBJECTIVE: We aim to dissect the transcriptomic clusters of childhood asthma using highly variably expressed genes of peripheral blood mononuclear cells (PBMC) among patients. METHODS: Gene expression of PBMC from 133 asthmatic children and 11 healthy controls was measured with Illumina microarrays. We applied the k-means clustering algorithm of 2048 genes to assign asthmatic children into clusters. Genes with differential expression between asthma clusters and healthy controls were used to investigate whether they could identify severe asthma of children and adults. RESULTS: We identified 3 asthma clusters with distinct inflammatory profiles in peripheral blood. Cluster 1 had the highest eosinophil count. Cluster 2 showed lower counts of both eosinophils and neutrophils. Cluster 3 had the highest neutrophil count and the poorest treatment control. Compared with other patients, Cluster 3 exhibited a unique gene expression pattern which was associated with changes in the glucocorticoid signalling and activation of the T helper 1/T helper 17 (TH 1/TH 17) immune pathways. In the validation studies, an 84-gene signature could identify severe asthma in children on leucocytes, as well as severe asthma in adults on CD8+ T cells. CONCLUSIONS AND CLINICAL RELEVANCE: Gene expression profiling of PBMC is useful for the identification of TH 1/TH 17-mediated asthma with poor treatment control. PBMC and CD8+ T cells could be important targets for the investigation and identification of severe asthma.

Ethical, legal and social implications of forensic molecular phenotyping in South Africa.

Conventional forensic DNA analysis involves a matching principle, which compares DNA profiles from evidential samples to those from reference samples of known origin. In casework, however, the accessibility to a reference sample is not guaranteed which limits the use of DNA as an investigative tool. This has led to the development of phenotype prediction, which uses SNP analysis to estimate the physical appearance of the sample donor. Physical traits, such as eye, hair and skin colour, have been associated with certain alleles within specific genes involved in the melanogenesis pathways. These genetic markers are also associated with ancestry and their trait prediction ability has mainly been assessed in European and North American populations. This has prompted research investigating the discriminatory power of these markers in other populations, especially those exhibiting admixture. South Africa is well known for its diversity, and the viability of these particular SNPs still needs to be assessed within this population. South African law currently restricts the use of DNA for molecular phenotyping, and there are also numerous ethical and social considerations, all of which are discussed.

Multiplexed MRM-based assays for the quantitation of proteins in mouse plasma and heart tissue.

The mouse is the most commonly used laboratory animal, with more than 14 million mice being used for research each year in North America alone. The number and diversity of mouse models is increasing rapidly through genetic engineering strategies, but detailed characterization of these models is still challenging because most phenotypic information is derived from time-consuming histological and biochemical analyses. To expand the biochemists' toolkit, we generated a set of targeted proteomic assays for mouse plasma and heart tissue, utilizing bottom-up LC/MRM-MS with isotope-labeled peptides as internal standards. Protein quantitation was performed using reverse standard curves, with LC-MS platform and curve performance evaluated by quality control standards. The assays comprising the final panel (101 peptides for 81 proteins in plasma; 227 peptides for 159 proteins in heart tissue) have been rigorously developed under a fit-for-purpose approach and utilize stable-isotope labeled peptides for every analyte to provide high-quality, precise relative quantitation. In addition, the peptides have been tested to be interference-free and the assay is highly multiplexed, with reproducibly determined protein concentrations spanning >4 orders of magnitude. The developed assays have been used in a small pilot study to demonstrate their application to molecular phenotyping or biomarker discovery/verification studies.

Molecular phenotyping of maternally mediated parallel adaptive divergence within Rana arvalis and Rana temporaria.

When similar selection acts on the same traits in multiple species or populations, parallel evolution can result in similar phenotypic changes, yet the underlying molecular architecture of parallel phenotypic divergence can be variable. Maternal effects can influence evolution at ecological timescales and facilitate local adaptation, but their contribution to parallel adaptive divergence is unclear. In this study, we (i) tested for variation in embryonic acid tolerance in a common garden experiment and (ii) used molecular phenotyping of egg coats to investigate the molecular basis of maternally mediated parallel adaptive divergence in two amphibian species (Rana arvalis and Rana temporaria). Our results on three R. arvalis and two R. temporaria populations show that adaptive divergence in embryonic acid tolerance is mediated via maternally derived egg coats in both species. We find extensive polymorphism in egg jelly coat glycoproteins within both species and that acid-tolerant clutches have more negatively charged egg jelly - indicating that the glycosylation status of the jelly coat proteins is under divergent selection in acidified environments, likely due to its impact on jelly water balance. Overall, these data provide evidence for parallel mechanisms of adaptive divergence in two species. Our study highlights the importance of studying intraspecific molecular variation in egg coats and, specifically, their glycoproteins, to increase understanding of underlying forces maintaining variation in jelly coats.

Müller cell metabolic chaos during retinal degeneration.

Müller cells play a critical role in retinal metabolism and are among the first cells to demonstrate metabolic changes in retinal stress or disease. The timing, extent, regulation, and impacts of these changes are not yet known. We evaluated metabolic phenotypes of Müller cells in the degenerating retina. Retinas harvested from wild-type (WT) and rhodopsin Tg P347L rabbits were fixed in mixed aldehydes and resin embedded for computational molecular phenotyping (CMP). CMP facilitates small molecule fingerprinting of every cell in the retina, allowing evaluation of metabolite levels in single cells. CMP revealed signature variations in metabolite levels across Müller cells from TgP347L retina. In brief, neighboring Müller cells demonstrated variability in taurine, glutamate, glutamine, glutathione, glutamine synthetase (GS), and CRALBP. This variability showed no correlation across metabolites, implying the changes are functionally chaotic rather than simply heterogeneous. The inability of any clustering algorithm to classify Müller cell as a single class in the TgP347L retina is a formal proof of metabolic variability in the present in degenerating retina. Although retinal degeneration is certainly the trigger, Müller cell metabolic alterations are not a coherent response to the microenvironment. And while GS is believed to be the primary enzyme responsible for the conversion of glutamate to glutamine in the retina, alternative pathways appear to be unmasked in degenerating retina. Somehow, long term remodeling involves loss of Müller cell coordination and identity, which has negative implications for therapeutic interventions that target neurons alone.

Retinal remodeling in human retinitis pigmentosa.

Retinitis Pigmentosa (RP) in the human is a progressive, currently irreversible neural degenerative disease usually caused by gene defects that disrupt the function or architecture of the photoreceptors. While RP can initially be a disease of photoreceptors, there is increasing evidence that the inner retina becomes progressively disorganized as the outer retina degenerates. These alterations have been extensively described in animal models, but remodeling in humans has not been as well characterized. This study, using computational molecular phenotyping (CMP) seeks to advance our understanding of the retinal remodeling process in humans. We describe cone mediated preservation of overall topology, retinal reprogramming in the earliest stages of the disease in retinal bipolar cells, and alterations in both small molecule and protein signatures of neurons and glia. Furthermore, while Müller glia appear to be some of the last cells left in the degenerate retina, they are also one of the first cell classes in the neural retina to respond to stress which may reveal mechanisms related to remodeling and cell death in other retinal cell classes. Also fundamentally important is the finding that retinal network topologies are altered. Our results suggest interventions that presume substantial preservation of the neural retina will likely fail in late stages of the disease. Even early intervention offers no guarantee that the interventions will be immune to progressive remodeling. Fundamental work in the biology and mechanisms of disease progression are needed to support vision rescue strategies.

Insect Adhesion Secretions: Similarities and Dissimilarities in Hydrocarbon Profiles of Tarsi and Corresponding Tibiae.

Spatially controlled in vivo sampling by contact solid phase microextraction with a non-coated silica fiber combined with gas chromatography-mass spectrometry (GC-MS) was utilized for hydrocarbon profiling in tarsal adhesion secretions of four insect species (Nicrophorus vespilloides, Nicrophorus nepalensis, Sagra femorata, and Gromphadorhina portentosa) by using distinct adhesion systems, viz. hairy or smooth tarsi. For comparison, corresponding samples from tibiae, representing the general cuticular hydrocarbon profile, were analyzed to enable the statistical inference of active molecular adhesion principles in tarsal secretions possibly contributed by specific hydrocarbons. n-Alkanes, monomethyl and dimethyl alkanes, alkenes, alkadienes, and one aldehyde were detected. Multivariate statistical analysis (principal component and orthogonal partial least square discriminant analyses) gave insights into distinctive molecular features among the various insect species and between tarsus and tibia samples. In general, corresponding hydrocarbon profiles in tarsus and tibia samples largely resembled each other, both qualitatively and in relative abundances as well. However, several specific hydrocarbons showed significantly different relative abundances between corresponding tarsus and tibia samples, thus indicating that such differences of specific hydrocarbons in the complex mixtures might constitute a delicate mechanism for fine-tuning the reversible attachment performances in tarsal adhesive fluids that are composed of substances originating from the same pool as cuticular hydrocarbons. Caused by melting point depression, the multicomponent tarsal adhesion secretion, made up of straight chain alkanes, methyl alkanes, and alkenes will have a semi-solid, grease-like consistency, which might provide the basis for a good reversible attachment performance.

From Data Mining of Public Sources to Clinical Decision Support in Personalized Medicine.

Personalized medicine enables precise tumor treatment for a patient's molecular genetic profile. To devise optimal targeted treatment plans for patients in a molecular tumor board, physicians must consider alterations on gene- and proteins levels but also cancer cell phenotypes. Machine learning can uncover buried patterns, extract pivotal information, and unveil corresponding insights from available data. Publicly available datasets provide the amounts of data necessary. This work outlines the efficacy of various machine learning algorithms which could eventually serve as clinical decision support in a precision oncology setting. Leveraging algorithms including Random Forest, Decision tree, XGBoost, Logistic regression, Gaussian Naive Bayes, k nearest neighbor, and AdaBoost, we conducted two experiments for the breast invasive carcinoma dataset. Incorporated data includes patient-, molecular- and treatment data. The aim of the investigation was to predict medication treatment or type of treatment based on genetic profile. After preprocessing and application of ML algorithms, the first results were promising. Multiple factors challenge application in clinical care settings without carefully considering the limitations.

Molecular phenotyping of malignant canine mammary tumours: Detection of high-risk group and its relationship with clinicomolecular characteristics.

Canine mammary gland tumours (CMTs) constitute the most common cancer in female dogs and comprise approximately 50% of all canine cancers. With the advent of high-throughput technologies such as microarray and next-generation sequencing, the molecular phenotyping (classification) of various cancers has been extensively developed. The present study used a canine RNA-sequencing dataset, namely GSE119810, to classify 113 malignant CMTs and 64 matched normal samples via an unsupervised hierarchical algorithm with a view to evaluating the association between the resulting subtypes (clusters) (n = 4) and clinical and molecular characteristics. Finally, a molecular classifier was developed, and it detected 1 high-risk molecular subtype in the training dataset (GSE119810) and 2 independent validation datasets (GSE20718 and GSE22516). Our results revealed four molecular subtypes (C2-C5) in malignant CMTs. Furthermore, the normal samples constituted a distinct group in the clustering analysis. Marked significant associations were observed between the molecular subtypes (especially C5) and clinical/molecular features, including positive lymphatic invasion, high tumour grades, histopathology diagnoses, short survival and high TP53 mutation rates (ps <.05). The high-risk subtype (C5) was further characterized through the development of a cell cycle-based gene signature, which comprised 37 proliferation-related genes according to the support vector machine algorithm. This signature identified the high-risk group in both training and validation datasets (ps <.001). In the validation analysis, our potential classifier robustly predicted patients with positive lymphatic invasion, metastases and short survival.

Increased Alveolar Epithelial Damage Markers and Inflammasome-Regulated Cytokines Are Associated with Pulmonary Superinfection in ARDS.

Acute respiratory distress syndrome (ARDS) is a life-threatening form of respiratory failure defined by dysregulated immune homeostasis and alveolar epithelial and endothelial damage. Up to 40% of ARDS patients develop pulmonary superinfections, contributing to poor prognosis and increasing mortality. Understanding what renders ARDS patients highly susceptible to pulmonary superinfections is therefore essential. We hypothesized that ARDS patients who develop pulmonary superinfections display a distinct pulmonary injury and pro-inflammatory response pattern. Serum and BALF samples from 52 patients were collected simultaneously within 24 h of ARDS onset. The incidence of pulmonary superinfections was determined retrospectively, and the patients were classified accordingly. Serum concentrations of the epithelial markers soluble receptor for advanced glycation end-products (sRAGE) and surfactant protein D (SP-D) and the endothelial markers vascular endothelial growth factor (VEGF) and angiopoetin-2 (Ang-2) as well as bronchoalveolar lavage fluid concentrations of the pro-inflammatory cytokines interleukin 1ß (IL-1ß), interleukin 18 (IL-18), interleukin 6 (IL-6), and tumor necrosis factor-alpha (TNF-a) were analyzed via multiplex immunoassay. Inflammasome-regulated cytokine IL-18 and the epithelial damage markers SP-D and sRAGE were significantly increased in ARDS patients who developed pulmonary superinfections. In contrast, endothelial markers and inflammasome-independent cytokines did not differ between the groups. The current findings reveal a distinct biomarker pattern that indicates inflammasome activation and alveolar epithelial injury. This pattern may potentially be used in future studies to identify high-risk patients, enabling targeted preventive strategies and personalized treatment approaches.

Raman Microspectroscopy Identifies Biochemical Activation Fingerprints in THP-1- and PBMC-Derived Macrophages.

(1) The monocytic leukemia cell line THP-1 and primary monocyte-derived macrophages (MDMs) are popular in vitro model systems to study human innate immunity, wound healing, and tissue regeneration. However, both cell types differ significantly in their origin and response to activation stimuli. (2) Resting THP-1 and MDMs were stimulated with lipopolysaccharide (LPS) and interferon γ (IFNγ) and analyzed by Raman microspectroscopy (RM) before and 48 h after activation. Raman data were subsequently analyzed using principal component analysis. (3) We were able to resolve and analyze the spatial distribution and molecular composition of proteins, nucleic acids, and lipids in resting and activated THP-1 and MDMs. Our findings reveal that proinflammatory activation-induced significant spectral alterations at protein and phospholipid levels in THP-1. In MDMs, we identified that nucleic acid and non-membrane-associated intracellular lipid composition were also affected. (4) Our results show that it is crucial to carefully choose the right cell type for an in vitro model as the nature of the cells itself may impact immune cell polarization or activation results. Moreover, we demonstrated that RM is a sensitive tool for investigating cell-specific responses to activation stimuli and monitoring molecular changes in subcellular structures.

Identification and Characterization of Marine Microorganisms by Tandem Mass Spectrometry Proteotyping.

The vast majority of marine microorganisms and their functions are yet to be explored. The considerable diversity they encompass is an endless source of knowledge and wealth that can be valued on an industrial scale, emphasizing the need to develop rapid and efficient identification and characterization techniques. In this study, we identified 26 microbial isolates from coastal water of the NW Mediterranean Sea, using phylopeptidomics, a cutting-edge tandem mass spectrometry proteotyping technique. Taxonomical identification at the species level was successfully conducted for all isolates. The presence of strains belonging to the newly described Balneolaeota phylum, yet uncharacterized at the proteomics scale, was noted. The very first proteomics-based investigation of a representative of the Balneolaeota phylum, Balneola vulgaris, is proposed, demonstrating the use of our proteotyping workflow for the rapid identification and in-depth molecular characterization, in a single MS/MS analytical run. Tandem mass spectrometry proteotyping is a valuable asset for culturomic programs as the methodology is able to quickly classify the most atypical isolates.

Genetic Architecture of Untargeted Lipidomics in Cardiometabolic-Disease Patients Combines Strong Polygenic Control and Pleiotropy.

Analysis of the genetic control of small metabolites provides powerful information on the regulation of the endpoints of genome expression. We carried out untargeted liquid chromatography−high-resolution mass spectrometry in 273 individuals characterized for pathophysiological elements of the cardiometabolic syndrome. We quantified 3013 serum lipidomic features, which we used in both genome-wide association studies (GWAS), using a panel of over 2.5 M imputed single-nucleotide polymorphisms (SNPs), and metabolome-wide association studies (MWAS) with phenotypes. Genetic analyses showed that 926 SNPs at 551 genetic loci significantly (q-value < 10−8) regulate the abundance of 74 lipidomic features in the group, with evidence of monogenic control for only 22 of these. In addition to this strong polygenic control of serum lipids, our results underscore instances of pleiotropy, when a single genetic locus controls the abundance of several distinct lipid features. Using the LIPID MAPS database, we assigned putative lipids, predominantly fatty acyls and sterol lipids, to 77% of the lipidome signals mapped to the genome. We identified significant correlations between lipids and clinical and biochemical phenotypes. These results demonstrate the power of untargeted lipidomic profiling for high-density quantitative molecular phenotyping in human-genetic studies and illustrate the complex genetic control of lipid metabolism.

Optimization of the TeraTox Assay for Preclinical Teratogenicity Assessment.

Current animal-free methods to assess teratogenicity of drugs under development still deliver high numbers of false negatives. To improve the sensitivity of human teratogenicity prediction, we characterized the TeraTox test, a newly developed multilineage differentiation assay using 3D human-induced pluripotent stem cells. TeraTox produces primary output concentration-dependent cytotoxicity and altered gene expression induced by each test compound. These data are fed into an interpretable machine-learning model to perform prediction, which relates to the concentration-dependent human teratogenicity potential of drug candidates. We applied TeraTox to profile 33 approved pharmaceuticals and 12 proprietary drug candidates with known in vivo data. Comparing TeraTox predictions with known human or animal toxicity, we report an accuracy of 69% (specificity: 53%, sensitivity: 79%). TeraTox performed better than 2 quantitative structure-activity relationship models and had a higher sensitivity than the murine embryonic stem cell test (accuracy: 58%, specificity: 76%, and sensitivity: 46%) run in the same laboratory. The overall prediction accuracy could be further improved by combining TeraTox and mouse embryonic stem cell test results. Furthermore, patterns of altered gene expression revealed by TeraTox may help grouping toxicologically similar compounds and possibly deducing common modes of action. The TeraTox assay and the dataset described here therefore represent a new tool and a valuable resource for drug teratogenicity assessment.

Dynamic and adaptive cancer stem cell population admixture in colorectal neoplasia.

Intestinal homeostasis is underpinned by LGR5+ve crypt-base columnar stem cells (CBCs), but following injury, dedifferentiation results in the emergence of LGR5-ve regenerative stem cell populations (RSCs), characterized by fetal transcriptional profiles. Neoplasia hijacks regenerative signaling, so we assessed the distribution of CBCs and RSCs in mouse and human intestinal tumors. Using combined molecular-morphological analysis, we demonstrate variable expression of stem cell markers across a range of lesions. The degree of CBC-RSC admixture was associated with both epithelial mutation and microenvironmental signaling disruption and could be mapped across disease molecular subtypes. The CBC-RSC equilibrium was adaptive, with a dynamic response to acute selective pressure, and adaptability was associated with chemoresistance. We propose a fitness landscape model where individual tumors have equilibrated stem cell population distributions along a CBC-RSC phenotypic axis. Cellular plasticity is represented by position shift along this axis and is influenced by cell-intrinsic, extrinsic, and therapeutic selective pressures.

Applying Molecular Phenotyping Tools to Explore Sugarcane Carbon Potential.

Sugarcane (Saccharum spp.), a C4 grass, has a peculiar feature: it accumulates, gradient-wise, large amounts of carbon (C) as sucrose in its culms through a complex pathway. Apart from being a sustainable crop concerning C efficiency and bioenergetic yield per hectare, sugarcane is used as feedstock for producing ethanol, sugar, high-value compounds, and products (e.g., polymers and succinate), and bioelectricity, earning the title of the world's leading biomass crop. Commercial cultivars, hybrids bearing high levels of polyploidy, and aneuploidy, are selected from a large number of crosses among suitable parental genotypes followed by the cloning of superior individuals among the progeny. Traditionally, these classical breeding strategies have been favoring the selection of cultivars with high sucrose content and resistance to environmental stresses. A current paradigm change in sugarcane breeding programs aims to alter the balance of C partitioning as a means to provide more plasticity in the sustainable use of this biomass for metabolic engineering and green chemistry. The recently available sugarcane genetic assemblies powered by data science provide exciting perspectives to increase biomass, as the current sugarcane yield is roughly 20% of its predicted potential. Nowadays, several molecular phenotyping tools can be applied to meet the predicted sugarcane C potential, mainly targeting two competing pathways: sucrose production/storage and biomass accumulation. Here we discuss how molecular phenotyping can be a powerful tool to assist breeding programs and which strategies could be adopted depending on the desired final products. We also tackle the advances in genetic markers and mapping as well as how functional genomics and genetic transformation might be able to improve yield and saccharification rates. Finally, we review how "omics" advances are promising to speed up plant breeding and reach the unexplored potential of sugarcane in terms of sucrose and biomass production.