Genetic algorithms applied to translational strategy in metabolic-dysfunction associated steatohepatitis (MASH). Learning from mouse models.

BACKGROUND & AIMS: We previously identified subsets of patients with metabolic (dysfunction)-associated steatotic liver disease (MASLD) with different metabolic phenotypes. Here, we aimed to refine this classification based on genetic algorithms implemented in a Python package. The use of these genetic algorithms can help scientists to solve problems which cannot be solved with other methods. We present this package and its capabilities with specific problems. The name, PyGenMet, comes from its main goal, solving problems in Python with Genetic Algorithms and Metabolomics data. METHODS: We collected serum from methionine adenosyltransferase 1a knockout (Mat1a-KO) mice, which have chronically low level of hepatic S-adenosylmethionine (SAMe) and the metabolomes of all samples were determined. We also analyzed serum metabolomes of 541 patients with biopsy proven MASLD (182 with simple steatosis and 359 with metabolic (dysfunction)-associated steatohepatitis or MASH) and compared them with the serum metabolomes of this specific MASLD mouse model using Genetic Algorithms in order to select patients with a specific phenotype. RESULTS: By applying genetic algorithms, we have found a subgroup of patients with a lipid profile similar to that observed in the mouse model. When analyzing the two groups of patients, we have seen that patients with a lipid profile reflecting the mouse model characteristics show significant differences in lipoproteins, especially in LDL-4, LDL-5, and LDL-6 associated with atherogenic risk. CONCLUSION: The results show that the application of genetic algorithms to subclassify patients with MASLD (or other metabolic disease) give consistent results and are a good approximation for the treatment of large volumes of data such as those from omics sciences and patient classification.

The Role of Surgery for Stage IV Breast Cancer.

Surgery for the management metastatic breast cancer has traditionally been considered a palliative procedure. However, some retrospective publications indicated that there may be a survival benefit to surgery in the presence of metastatic disease. Recent randomized trials will be reviewed for both management of the intact primary tumor in de novo breast cancer and systemic secondary metastases.

DOMINO trial post hoc analysis: evaluation of the diet effects on symptoms in IBS subtypes.

Background: Irritable bowel syndrome (IBS) is a disorder of gut-brain interaction characterized by recurrent abdominal pain related to defecation and/or associated to a change in bowel habits. According to the stool type, four different IBS subtypes can be recognized, constipation predominant (IBS-C), diarrhea predominant (IBS-D), mixed (IBS-M), and undefined (IBS-U). Patients report that their IBS symptoms are exacerbated by food. Thus, it is important to find a nutritional approach that could be effective in reducing IBS symptoms. Objective: The present work is a post hoc analysis of the previously published DOMINO trial. It aimed to evaluate the effects of a self-instructed FODMAP-lowering diet smartphone application on symptoms and psychosocial aspects in primary care IBS stratifying the results for each IBS subtypes. Design: Post hoc analysis. Methods: Two hundred twenty-two primary care IBS patients followed a FODMAP-lowering diet for 8 weeks with the support of a smartphone application. Two follow-up visits were scheduled after 16 and 24 weeks. IBS-Symptoms Severity Score (IBS-SSS), quality of life (QoL), and adherence and dietary satisfaction were evaluated. Results: After 8 weeks, IBS-SSS improved in all IBS subtypes (p < 0.0001). Physician Health Questiionnaire (PHQ-15) improved only in IBS-D (p = 0.0006), whereas QoL improved both in IBS-D (p = 0.01) and IBS-M (p = 0.005). Conclusion: This post hoc analysis showed that the app is useful in all IBS subtypes; thus, it could be used as an effective tool by both general practitioners and patients to manage symptoms in primary care. Trial registration: Ethical Commission University Hospital of Leuven reference number: S59482. Clinicaltrial.gov reference number: NCT04270487.

What is already known about this subject? The low FODMAP (fermentable oligo-, di-, and monosaccharides and polyols) diet has shown efficacy for controlling IBS (irritable bowel syndrome) symptoms in small controlled trials in tertiary care patients. As this approach requires several visits with an experienced dietitian, it seems less suitable for primary care. What are the new findings? The benefit of the FODMAP lowering app was already present at 4 weeks and persisted during follow-up until 24 weeks. How might it impact on clinical practice in the foreseeable future? Given its superiority to standard first-line pharmacotherapy, and its ease of use, a FODMAP lowering app has the potential to become the preferred first-line treatment for primary care IBS.

COPD Subtypes Are Differentially Associated with Cardiovascular Events and COPD Exacerbations.

BACKGROUND: The coronary artery calcium score (CACS) and ratio of the pulmonary artery to aorta diameters (PA:A ratio) measured from chest CT scans have been established as predictors of cardiovascular events and chronic obstructive pulmonary disease (COPD) exacerbations, respectively. However, little is known about the reciprocal relationship between these predictors and outcomes. Furthermore, the prognostic implications of COPD subtypes on clinical outcomes remain insufficiently characterized. RESEARCH QUESTION: How can these two chest CT-derived parameters predict subsequent cardiovascular events and COPD exacerbations in different COPD subtypes? STUDY DESIGN AND METHODS: Using COPDGene study data, we assessed prospective cardiovascular disease (CVD) and COPD exacerbation risk in COPD subjects (Global Initiative for Chronic Obstructive Lung Disease spirometric grades 2-4), focusing on CACS and PA:A ratio at study enrollment, with logistic regression models. These outcomes were analyzed in three COPD subtypes: 1,042 Non-emphysema-predominant COPD (NEPD; low attenuation area at -950 Hounsfield units [LAA-950]<5%), 1,324 Emphysema-predominant COPD (EPD; LAA-950≥10%), and 465 Intermediate Emphysema COPD (IE; 5≤LAA-950<10%). RESULTS: Our study indicated significantly higher overall risk for cardiovascular events in subjects with higher CACS (≥median; Odds Ratio (OR): 1.61, 95% Confidence Interval (CI)=1.30-2.00) and increased COPD exacerbations in those with higher PA:A ratios (≥1; OR: 1.80, 95% CI=1.46-2.23). Notably, NEPD subjects showed a stronger association between these indicators and clinical events compared to EPD (with CACS/CVD, NEPD vs. EPD, OR 2.02 vs. 1.41; with PA:A ratio/COPD exacerbation, NEPD vs. EPD, OR 2.50 vs. 1.65); the difference in odds ratios between COPD subtypes was statistically significant for CACS/CVD. INTERPRETATION: Two chest CT parameters, CACS and PA:A ratio, hold distinct predictive values for cardiovascular events and COPD exacerbations that are influenced by specific COPD subtypes. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT00608764.

Histopathological, Molecular and Clinical Profiling of Lymphoepithelioma-Like Carcinoma of the Bladder (LELC-B).

Lymphoepithelioma-like urothelial carcinoma of the urinary bladder (LELC-B) is a rare histologic subtype characterized by strong immune cell infiltrates. A better prognosis and favorable response rates to immune-checkpoint inhibitors (ICI) have been described. We aimed to characterize the molecular profiles and immune cell infiltration of LELC-B for a better understanding and its therapeutic implications. We identified eleven muscle-invasive bladder cancer cases with pure and mixed LELC-B. PD-L1 expression and mismatch-repair (MMR) proteins were evaluated using immunohistochemistry. We calculated the tumor-mutational burden (TMB) and characterized mutational profiles using whole exome DNA-sequencing data. Transcriptomic signatures were detected using the NanoString nCounter PanCancer IO360 panel. Multiplex immunofluorescence of tumor microenvironment (PD-L1, PanCK, aSMA, Vimentin, CD45, Ki67) and T-cells (CD4, CD3, PD-1, CD163, CD8, FoxP3) was used to quantify cell populations. All LELC-B cases were highly positive for PD-L1 (median TPS/TC 70%; range 20-100; median CPS 100; range 50-100), MMR-proficient and negative for Epstein-Barr virus infection. Immune cell infiltrates were characterized by high CD8+ T-cell count and high PD-1/PD-L1 expression on immune and tumor cells. LELC-B showed upregulation of signaling pathways involved in immune cell response. Most common mutations were found in chromatin remodeling genes causing epigenetic dysregulation. All LELC-B cases showed high TMB of 39 Mut/Mb (IQR 29-66). In conclusion, LELC-B is a highly immunogenic tumor, showing strong upregulation of PD1/PD-L1 and making ICI a promising treatment option.

Mapping Single-Cell Transcriptomes of Endometrium Reveals Potential Biomarkers in Endometrial Cancer.

Background: The heterogeneity and dynamic changes of endometrial cells have a significant impact on health as they determine the normal function of the endometrium during the menstrual cycle. Dysfunction of the endometrium can lead to the occurrence of various gynecological diseases. Therefore, deconvolution of immune microenvironment that drives transcriptional programs throughout the menstrual cycle is key to understand regulatory biology of endometrium. Methods: Herein, we comprehensively analyzed single-cell transcriptome of 59,397 cells across ten human endometrium samples and revealed the dynamic cellular heterogeneity throughout the menstrual cycle. Results: We identified two perivascular cell subtypes, four epithelial subtypes and four fibroblast cell types in endometrium. Moreover, we inferred the cell type-specific transcription factor (TF) activities and linked critical TFs to transcriptional output of diverse immune cell types, highlighting the importance of transcriptional regulation in endometrium. Dynamic interactions between various types of cells in endometrium contribute to a range of biological pathways regulating differentiation of secretory. Integration of the molecular biomarkers identified in endometrium and bulk transcriptome of 535 endometrial cancers (EC), we revealed five RNA-based molecular subtypes of EC with highly intratumoral heterogeneity and different clinical manifestations. Mechanism analysis uncovered clinically relevant pathways for pathogenesis of EC. Conclusion: In summary, our results revealed the dynamic immune microenvironment of endometrium and provided novel insights into future development of RNA-based treatments for endometriosis and endometrial carcinoma.

Investigating the Role of Inflammatory Response in Polycystic Ovary Syndrome Using Integrated RNA-Seq Analysis.

Background: An important factor in the pathogenesis of polycystic ovary syndrome (PCOS) is chronic low-grade inflammation. However, the exact pathophysiology of PCOS is currently unknown, which makes clinical diagnosis and the development of effective treatments more difficult. We aimed to investigate the role of the inflammatory response in initiating and progressing PCOS. Methods: 13 control granulosa cell samples and 15 granulosa cell samples from patients with PCOS were obtained from the GSE102293, GSE34526, and GSE5850 datasets. The gene set variation analysis (GSVA) method was used to calculate the inflammatory response score. Subsequently, the genes associated with inflammation in the hub were identified using differential expression analysis and weighted gene co-expression network analysis (WGCNA). The findings were confirmed by analysis of independent datasets and examination of clinical samples by qRT-PCR analysis. A consensus cluster analysis was conducted to categorize the PCOS samples into subtypes related to inflammation. Functional enrichment and analysis of immune cell infiltration were conducted to explore the potential mechanisms involved. Additionally, the CMap database was utilized to predict potential drugs, and the results were confirmed through molecular docking. Results: During the training cohort analysis, we identified five distinct genes (TGFBR2, ICAM3, WIPF1, SLC11A1, and NCF2) that could serve as potential diagnostic markers for PCOS. The expression levels of these genes were confirmed through validation in both the test set and clinical samples. In training cohort, two distinct inflammatory patterns (C1 and C2) were identified, and the C2 subtype exhibited activated immune- and inflammation-related pathways. Esmolol was shown to have potential as a drug to treat PCOS and it showed good results for molecular binding at TGFBR2, ICAM3, WIPF1, SLC11A1, and NCF2 proteins. Conclusion: Five diagnostic biomarkers and two inflammation-related molecular types associated with PCOS were identified, and esmolol was a potential drug for PCOS treatment. Our findings provided new diagnostic markers and potential small-molecule drugs for PCOS diagnosis and prevention.

Quantitative EEG in Parkinson's disease: when REM sleep behavior disorder onset really matters.

Parkinson's Disease (PD) body-first subtype is characterized by prodromal autonomic symptoms and REM sleep behavior disorder (RBD), symmetric dopaminergic degeneration, and increased risk of dementia. On the other hand, the PD brain-first subtype has fewer non-motor symptoms and a milder motor phenotype. The temporal relationship between RBD onset and motor symptoms onset may differentiate these two subtypes. We aimed to investigate electrocortical differences between brain-first and body-first PD patients. PD patients with an available routinely collected EEG were retrospectively selected. RBD was diagnosed using the RBD screening questionnaire (≥ 6). According to the onset of RBD patients were classified into PD-RBDpre (RBD onset before motor symptoms) and PD-RBDpost (RBD onset after motor symptoms). Patients without RBD were classified as PD-RBD-. Presence of Mild Cognitive Impairment (MCI) was diagnosed according to the MDS criteria. EEG Spectral analysis was performed in resting state by computing the Power Spectral Density (PSD) of site-specific signal epochs for the common frequency bands (delta, theta, alpha, beta). Thirty-eight PD-RBD-, 14 PD-RBDpre and 31 PD-RBDpost patients were recruited. Comparing both global and site-specific absolute values, we found a significant trend toward beta band reduction going from PD-RBD-, PD-RBDpost and PD-RBDpre. No significant differences were found between PD-RBDpost and PD-RBD- patients. PD-RBDpre patients may represent a different subset of patients as compared to patients without RBD, while patients with later onset have intermediate EEG spectral features. Quantitative EEG may provide new hints in PD subtyping.

Investigation of Choroidal Thickness and Choroidal Vascularity Index in Ocular Rosacea Patients According to Skin Subtypes.

BACKGROUND: To compare the choroidal thickness (CT) and choroidal vascularity index (CVI) values in ocular rosacea (OR) patients across skin subtypes of the disease and healthy controls. METHODS: This prospective study included 90 eyes of 90 mild-moderate OR patients with different skin subtypes (30 phymatous, 30 papulopustular and 30 erythematotelangiectatic) and 30 eyes of 30 age-gender matched healthy volunteers. After obtaining the enhanced depth imaging optical coherence tomography images, the CT was measured at subfoveal, 1500µm nasal and 1500µm temporal to the fovea, and the CVI was calculated using Image J software in the subfoveal, nasal and temporal areas. RESULTS: There was no CT significant difference between OR patients and healthy controls in all regions (p>0.05). CVI values of OR patients were found to be significantly lower in the subfoveal, nasal and temporal regions compared to healthy controls (p=0.02, p=0.01, p=0.01, respectively). No CT difference was detected between the subtypes and healthy controls in all regions (p>0.05). Subfoveal-CVI was significantly lower in the phymatous subtype than the other subtypes and controls (p<0.05), while nasal and temporal-CVI were significantly lower in the phymatous and papulopustular subtypes than the erythematotelangiectatic subtype and controls. CONCLUSION: Our study demonstrated no difference between rosacea skin types and healthy controls in terms of CT. Phymatous and papulopustular subtypes were more likely to be affected by chronic inflammation with having lower CVI in most of the regions. Further studies are needed to investigate the association of inflammatory factors with CVI in OR.

Biological aging of different blood cell types.

Biological age (BA) captures detrimental age-related changes. The best-known and most-used BA indicators include DNA methylation-based epigenetic clocks and telomere length (TL). The most common biological sample material for epidemiological aging studies, whole blood, is composed of different cell types. We aimed to compare differences in BAs between blood cell types and assessed the BA indicators' cell type-specific associations with chronological age (CA). An analysis of DNA methylation-based BA indicators, including TL, methylation level at cg16867657 in ELOVL2, as well as the Hannum, Horvath, DNAmPhenoAge, and DunedinPACE epigenetic clocks, was performed on 428 biological samples of 12 blood cell types. BA values were different in the majority of the pairwise comparisons between cell types, as well as in comparison to whole blood (p < 0.05). DNAmPhenoAge showed the largest cell type differences, up to 44.5 years and DNA methylation-based TL showed the lowest differences. T cells generally had the "youngest" BA values, with differences across subsets, whereas monocytes had the "oldest" values. All BA indicators, except DunedinPACE, strongly correlated with CA within a cell type. Some differences such as DNAmPhenoAge-difference between naïve CD4 + T cells and monocytes were constant regardless of the blood donor's CA (range 20-80 years), while for DunedinPACE they were not. In conclusion, DNA methylation-based indicators of BA exhibit cell type-specific characteristics. Our results have implications for understanding the molecular mechanisms underlying epigenetic clocks and underscore the importance of considering cell composition when utilizing them as indicators for the success of aging interventions.

CT-based radiomics combined with clinical features for invasiveness prediction and pathological subtypes classification of subsolid pulmonary nodules.

Purpose: To construct optimal models for predicting the invasiveness and pathological subtypes of subsolid nodules (SSNs) based on CT radiomics and clinical features. Materials and Methods: This study was a retrospective study involving two centers. A total of 316 patients with 353 SSNs confirmed as atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) were included from January 2019 to February 2023. Models based on CT radiomics and clinical features were constructed for classification of AAH/AIS and MIA, MIA and IAC, as well as lepidic-predominant adenocarcinoma (LPA) and acinar-predominant adenocarcinoma (APA). Receiver operating characteristic (ROC) curve was used to evaluate the model performance. Finally, the nomograms based on the optimal models were established. Results: The nomogram based on the combined model (AAH/AIS versus MIA) consisting of lobulation, the GGN-vessel relationship, diameter, CT value, consolidation tumor ratio (CTR) and rad-score performed the best (AUC=0.841), while age, CT value, CTR and rad-score were the significant features for distinguishing MIA from IAC, the nomogram based on these features performed the best (AUC=0.878). There were no significant differences in clinical features between LPA and APA, while the radiomics model based on rad-score showed good performance for distinguishing LPA from APA (AUC=0.926). Conclusions: The nomograms based on radiomics and clinical features could predict the invasiveness of SSNs accurately. Moreover, radiomics models showed good performance in distinguishing LPA from APA.

The association of magnetic resonance imaging features with five molecular subtypes of breast cancer.

Objective: To identify the association of magnetic resonance imaging (MRI) features with molecular subtypes of breast cancer (BC). Materials and methods: A retrospective study was conducted on 112 invasive BC patients with preoperative breast MRI. The confirmed diagnosis and molecular subtypes of BC were based on the postoperative specimens. MRI features were collected by experienced radiologists. The association of MRI features of each subtype was compared to other molecular subtypes in univariate and multivariate logistic regression analyses. Results: The proportions of luminal A, luminal B HER2-negative, luminal B HER2-positive, HER2-enriched, and triple-negative BC were 14.3 %, 52.7 %, 12.5 %, 10.7 %, and 9.8 %, respectively. Luminal A was associated with hypo-isointensityon T2-weighted images (OR=6.214, 95 % CI: 1.163-33.215) and non-restricted diffusion on DWI-ADC (OR=6.694, 95 % CI: 1.172-38.235). Luminal B HER2-negative was related to the presence of mass (OR=7.245, 95 % CI: 1.760-29.889) and slow/medium initial enhancement pattern (OR=3.654, 95 % CI: 1.588-8.407). There were no associations between MRI features and luminal B HER2-positive. HER2-enriched tended to present as non-mass enhancement lesions (OR=20.498, 95 % CI: 3.145-133.584) with fast uptake in the initial postcontrast phase (OR=9.788, 95 % CI: 1.689-56.740), and distortion (OR=11.471, 95 % CI: 2.250-58.493). Triple-negative were associated with unifocal (OR=7.877, 95 % CI: 1.180-52.589), hyperintensityon T2-weighted images (OR=14.496, 95 % CI: 1.303-161.328), rim-enhanced lesions (OR=18.706, 95 % CI: 1.915-182.764), and surrounding tissue edema (OR=5.768, 95 % CI: 1.040-31.987). Conclusion: Each molecular subtype of BC has distinct features on breast MRI. These characteristics can serve as an adjunct to immunohistochemistry in diagnosing molecular subtypes, particularly in cases, where traditional methods yield equivocal results.

Resting-state functional connectivity of amygdala subregions across different symptom subtypes of obsessive-compulsive disorder patients.

AIM: Obsessive-compulsive disorder (OCD) is a heterogeneous condition characterized by distinct symptom subtypes, each with varying pathophysiologies and treatment responses. Recent research has highlighted the role of the amygdala, a brain region that is central to emotion processing, in these variations. However, the role of amygdala subregions with distinct functions has not yet been fully elucidated. In this study, we aimed to clarify the biological mechanisms underlying OCD subtype heterogeneity by investigating the functional connectivity (FC) of amygdala subregions across distinct OCD symptom subtypes. METHODS: Resting-state functional magnetic resonance images were obtained from 107 medication-free OCD patients and 110 healthy controls (HCs). Using centromedial, basolateral, and superficial subregions of the bilateral amygdala as seed regions, whole-brain FC was compared between OCD patients and HCs and among patients with different OCD symptom subtypes, which included contamination fear and washing, obsessive (i.e., harm due to injury, aggression, sexual, and religious), and compulsive (i.e., symmetry, ordering, counting, and checking) subtypes. RESULTS: Compared to HCs, compulsive-type OCD patients exhibited hypoconnectivity between the left centromedial amygdala (CMA) and bilateral superior frontal gyri. Compared with patients with contamination fear and washing OCD subtypes, patients with compulsive-type OCD showed hypoconnectivity between the left CMA and left frontal cortex. CONCLUSIONS: CMA-frontal cortex hypoconnectivity may contribute to the compulsive presentation of OCD through impaired control of behavioral responses to negative emotions. Our findings underscored the potential significance of the distinct neural underpinnings of different OCD manifestations, which could pave the way for more targeted treatment strategies in the future.

Determination of endometrial cancer molecular subtypes using a whole exome-sequencing based single-method approach.

AIM: Endometrial cancer (EC) is heterogeneous with respect to epidemiology, clinical course, histopathology and tumor biology. Recently, The Cancer Genome Atlas (TCGA) network has identified four molecular subtypes with distinct clinical courses by an integrated multi-omics approach. These subtypes are of critical importance in the clinical management of EC. However, determination of TCGA molecular subtypes requires a complex methodological approach that is resource intensive and difficult to implement in diagnostic routine procedures. In this context, Talhouk et al. reported the precise determination of modified subtypes based on molecular surrogates obtained by a two-method approach comprising immunohistochemistry and DNA-sequence analysis (Proactive Molecular Risk Classifier for Endometrial Cancer; ProMisE). In this study, we aimed to identify EC molecular subtypes in analogy to TCGA and ProMisE applying an innovative whole exome-sequencing (WES) based single-method approach. METHODS: WES was performed in a cohort comprising N = 114 EC patients. WES data were analyzed using the oncology treatment decision support software MH Guide (Molecular Health, Heidelberg, Germany) and EC molecular subtypes in analogy to TCGA and ProMisE were determined. Results from both classifications were compared regarding their prognostic values using overall survival and progression-free survival analyses. RESULTS: Applying a single-method WES-approach, EC molecular subtypes analogue to TCGA and ProMisE were identified in the study cohort. The surrogate marker-analogue classification precisely identified high-risk and low-risk EC, whereas the TCGA-analogue classification failed to obtain significant prognostic values in this regard. CONCLUSION: Our data demonstrate that determination of EC molecular subtypes analogue to TCGA and ProMisE is feasible by using a single-method WES approach. Within our EC cohort, prognostic implications were only reliably provided by applying the surrogate marker-analogue approach. Designation of molecular subtypes in EC will be increasingly important in routine clinical practice. Thus, the single-method WES approach provides an important simple tool to tailor therapeutic decisions in EC.

Current Applications and Future Directions of Circulating Tumor Cells in Colorectal Cancer Recurrence.

The ability to predict or detect colorectal cancer (CRC) recurrence early after surgery enables physicians to apply appropriate treatment plans and different follow-up strategies to improve patient survival. Overall, 30-50% of CRC patients experience cancer recurrence after radical surgery, but current surveillance tools have limitations in the precise and early detection of cancer recurrence. Circulating tumor cells (CTCs) are cancer cells that detach from the primary tumor and enter the bloodstream. These can provide real-time information on disease status. CTCs might become novel markers for predicting CRC recurrence and, more importantly, for making decisions about additional adjuvant chemotherapy. In this review, the clinical application of CTCs as a therapeutic marker for stage II CRC is described. It then discusses the utility of CTCs for monitoring cancer recurrence in advanced rectal cancer patients who undergo neoadjuvant chemoradiotherapy. Finally, it discusses the roles of CTC subtypes and CTCs combined with clinicopathological factors in establishing a multimarker model for predicting CRC recurrence.

Breast Cancer Stem Cells and Tumor Heterogeneity: Characteristics and Therapeutic Strategies.

Breast cancer is one of the most frequently detected malignancies worldwide. It is responsible for more than 15% of all death cases caused by cancer in women. Breast cancer is a heterogeneous disease representing various histological types, molecular characteristics, and clinical profiles. However, all breast cancers are organized in a hierarchy of heterogeneous cell populations, with a small proportion of cancer stem cells (breast cancer stem cells (BCSCs)) playing a putative role in cancer progression, and they are responsible for therapeutic failure. In different molecular subtypes of breast cancer, they present different characteristics, with specific marker profiles, prognoses, and treatments. Recent efforts have focused on tackling the Wnt, Notch, Hedgehog, PI3K/Akt/mTOR, and HER2 signaling pathways. Developing diagnostics and therapeutic strategies enables more efficient elimination of the tumor mass together with the stem cell population. Thus, the knowledge about appropriate therapeutic methods targeting both "normal" breast cancer cells and breast cancer stem cell subpopulations is crucial for success in cancer elimination.

Low progesterone receptor levels in high-grade DCIS correlate with HER2 upregulation and the presence of invasive components.

Objective: In this study, we investigated pivotal molecular markers in human high-grade breast ductal carcinoma in situ (DCIS). Expression status of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth receptor 2 (HER2) was measured among various subtypes (Luminal (Lum) A, LumB HER2-, LumB HER2+, HER2-enriched and triple-negative). Methods: In total, 357 DCIS cases were classified into respective subtypes, according to the 2013 St. Gallen guidelines. Each subtype was categorized into three subcategories: "Pure" (those without an invasive component), "W/invasive" (those with an invasive component), and "All" (the entire group of the given subtype). ER and PR expression were registered as intervals. Equivocal HER2 immunohistochemistry (IHC) cases (2+) were further investigated using dual-color in situ hybridization. Results: The majority of patients (71%) were over the age of 50. We discovered no significant differences in the proportion of age between the "Pure" and "W/invasive" groups. There was no significant difference in ER/PR expression between "Pure" luminal subtypes of DCIS and "W/invasive" cases. We compared the HER2 IHC scores of "0", "1+", and "2+" among LumA and LumB HER2 subtypes and identified no statistically significant differences between "Pure" and "W/invasive" (p = 0.603). ER and PR expression ≥ 50% cutoff value was present in > 90% of all LumA cases. The incidences of cases with ER expression at cutoff values of < 10% and ≥ 50% in LumA were significantly different compared to other luminal subtypes (p < 0.0001). The proportion of cases with PR expression < 20% showed significant differences in the various luminal subtypes. In luminal B subtypes, low PR expression (< 20%) was significantly associated with both strong HER2 expression (3+) and the presence of an invasive component (p = 0.0001 and p = 0.0365, respectively). Conclusions: ER and PR expression at ≥ 50% cutoff values were found in more than 90% of LumA cases. Samples with ER < 10% and ≥ 50% in LumA were significantly different compared to other luminal subtypes (p < 0.0001). Low PR expression in high-grade DCIS was strongly associated with HER2 overexpression (3+) and an invasive component (p = 0.0001 and p = 0.0365, respectively).

Assessing Etiologic Heterogeneity for Multinomial Outcome with Two-Phase Outcome-Dependent Sampling Design.

Etiologic heterogeneity occurs when distinct sets of events or exposures give rise to different subtypes of disease. Inference about subtype-specific exposure effects from two-phase outcome-dependent sampling data requires adjustment for both confounding and the sampling design. Common approaches to inference for these effects do not necessarily appropriately adjust for these sources of bias, or allow for formal comparisons of effects across different subtypes. Herein, using inverse probability weighting (IPW) to fit a multinomial model is shown to yield valid inference with this sampling design for subtype-specific exposure effects and contrasts thereof. The IPW approach is compared to common regression-based methods for assessing exposure effect heterogeneity using simulations. The methods are applied to estimate subtype-specific effects of various exposures on breast cancer risk in the Carolina Breast Cancer Study.

Exploring the Genetic Heterogeneity of Alzheimer's Disease: Evidence for Genetic Subtypes.

Background: Alzheimer's disease (AD) exhibits considerable phenotypic heterogeneity, suggesting the potential existence of subtypes. AD is under substantial genetic influence, thus identifying systematic variation in genetic risk may provide insights into disease origins. Objective: We investigated genetic heterogeneity in AD risk through a multi-step analysis. Methods: We performed principal component analysis (PCA) on AD-associated variants in the UK Biobank (AD cases = 2,739, controls = 5,478) to assess structured genetic heterogeneity. Subsequently, a biclustering algorithm searched for distinct disease-specific genetic signatures among subsets of cases. Replication tests were conducted using the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset (AD cases = 500, controls = 470). We categorized a separate set of ADNI individuals with mild cognitive impairment (MCI; n = 399) into genetic subtypes and examined cognitive, amyloid, and tau trajectories. Results: PCA revealed three distinct clusters ("constellations") driven primarily by different correlation patterns in a region of strong LD surrounding the MAPT locus. Constellations contained a mixture of cases and controls, reflecting disease-relevant but not disease-specific structure. We found two disease-specific biclusters among AD cases. Pathway analysis linked bicluster-associated variants to neuron morphogenesis and outgrowth. Disease-relevant and disease-specific structure replicated in ADNI, and bicluster 2 exhibited increased cerebrospinal fluid p-tau and cognitive decline over time. Conclusions: This study unveils a hierarchical structure of AD genetic risk. Disease-relevant constellations may represent haplotype structure that does not increase risk directly but may alter the relative importance of other genetic risk factors. Biclusters may represent distinct AD genetic subtypes. This structure is replicable and relates to differential pathological accumulation and cognitive decline over time.

Non-genetic heterogeneity and immune subtyping in breast cancer: Implications for immunotherapy and targeted therapeutics.

Breast cancer (BC) is a complex and multifactorial disease, driven by genetic alterations that promote tumor growth and progression. However, recent research has highlighted the importance of non-genetic factors in shaping cancer evolution and influencing therapeutic outcomes. Non-genetic heterogeneity refers to diverse subpopulations of cancer cells within breast tumors, exhibiting distinct phenotypic and functional properties. These subpopulations can arise through various mechanisms, including clonal evolution, genetic changes, epigenetic changes, and reversible phenotypic transitions. Although genetic and epigenetic changes are important points of the pathology of breast cancer yet, the immune system also plays a crucial role in its progression. In clinical management, histologic and molecular classification of BC are used. Immunological subtyping of BC has gained attention in recent years as compared to traditional techniques. Intratumoral heterogeneity revealed by immunological microenvironment (IME) has opened novel opportunities for immunotherapy research. This systematic review is focused on non-genetic variability to identify and interlink immunological subgroups in breast cancer. This review provides a deep understanding of adaptive methods adopted by tumor cells to withstand changes in the tumor microenvironment and selective pressure imposed by medications. These adaptive methods include alterations in drug targets, immune system evasion, activation of survival pathways, and alterations in metabolism. Understanding non-genetic heterogeneity is essential for the development of targeted therapies.