Molecular Classification of Endometrial Cancers Using an Integrative DNA Sequencing Panel.

BACKGROUND AND OBJECTIVES: Adoption of molecular classification in endometrial cancer (EC) into clinical practice remains challenging due to complexity in coordination of multiple assays. We aimed to develop a simple molecular technique to classify ECs into four subgroups using our custom-designed targeted sequencing panel. METHODS: Patients with newly diagnosed ECs were prospectively recruited from three cancer centres in Ontario, Canada. Using our panel, 181 ECs were sequenced. Variants were analysed for pathogenicity and clinicopathologic information was collected through medical records retrospectively. RESULTS: Of 181, 86 (48%) were mismatch repair deficient (MMRd), of which 62 (72%) harboured MLH1 promoter methylation and 24 (28%) had pathogenic variants in MMR genes. Of single classifiers, three (1.8%) had pathogenic POLE (POLEmut), 15 (9%) had TP53 mutations (p53abn) and 61 (37%) had no specific molecular profile subtype (NSMP). Sixteen (9%) had more than one molecular classifying feature, with eight (4%) MMRd-p53abn, six (3%) POLEmut-MMRd, one (0.5%) POLEmut-MMRd-p53abn and one (0.5%) POLEmut-p53abn. When MMRd group was further subclassified according to mechanism of MMR loss, MLH1 promoter methylated group had worse outcomes than those with somatic MMR pathogenic variants. CONCLUSIONS: Our panel can classify ECs into four subgroups through a simplified process and can be implemented reflexively in clinical practice.

[Correlations of Ultrasound Features With Gene Mutations and Pathologic Subtypes in Papillary Thyroid Carcinoma].

The prognosis of papillary thyroid carcinoma (PTC) is highly dependent on gene mutations and pathologic features.The common gene mutations in PTC include BRAF V600E,RET/PTC rearrangement,and RAS mutations.These mutations have been suggested to be associated with an increased risk of recurrence,poorer efficacy of postoperative radioactive iodine therapy,and reduced survival.The pathologic subtypes of PTC include classic,follicular,tall cell,hobnail,columnar cell,diffuse sclerosing,solid/trabecular,oncocytic,Warthin-like,clear cell,and spindle cell subtypes,which have different aggressiveness and linked with varied clinical prognosis.Therefore,detecting the gene mutations and pathologic subtypes of PTC is of great importance for therapeutic regimen selection and prognosis evaluation.Ultrasound imaging with non-invasiveness,convenience,and high resolution has become the primary examination method for the diagnosis and treatment of thyroid cancer.This paper reviews the correlations of gene mutations and pathologic subtypes with the ultrasound features of PTC,aiming to give new insights into the application of ultrasound imaging in predicting gene mutations and pathologic subtypes of PTC before surgery as well as provide new ideas for accurate assessment of preoperative prognosis.

MFAP3L predicts tumor microenvironment status, molecular subtypes and clinical benefit in patients with bladder cancer.

Bladder cancer (BLCA), ranking as the tenth most prevalent malignancy globally, imposes a substantial public health and socio-economic challenge. Despite ongoing efforts by urologists to identify novel molecular subtypes and treatment paradigms, the intrinsic heterogeneity of BLCA continues to obstruct the efficacy of current diagnostic and therapeutic evaluations, leaving a gap in the comprehensive management of BLCA. This necessitates an in-depth investigation into the BLCA tumor microenvironment (TME) to identify pivotal molecules like MFAP3L. Our research concentrated on MFAP3L, commencing with a pan-cancer analysis of its immune profile. We discovered that MFAP3L exhibits a significant negative correlation with numerous immune components and markers in BLCA, a trend not observed in other cancer types. Within the TCGA-BLCA cohort, patients were classified into High-MFAP3L and Low-MFAP3L groups according to their MFAP3L transcript levels. Our exploration into the BLCA TME delved into immune infiltration, molecular subtype patterns, and treatment preferences within these MFAP3L groups. High MFAP3L expression was linked to favorable prognoses, luminal subtypes, and low immune infiltration, inversely associated with various immune molecules and characteristics. Additionally, high MFAP3L expressors exhibited diminished immune checkpoint levels, suggesting enhanced immunotherapy tolerance and sensitivity to oncogenic pathway targeting. Conversely, low MFAP3L expression correlated with poor outcomes, basal subtypes, increased immune infiltration, and heightened gene mutation rates, alongside sensitivity to radiotherapy, EGFR-targeted treatments, and immunotherapy. Hence, MFAP3L emerges as a critical yet underexplored gene in BLCA, offering insights into immune status within the TME and aiding in molecular subtyping and therapeutic decision-making.

The efficacy of immunotherapy in non-small cell lung cancer with KRAS mutation: a systematic review and meta-analysis.

PURPOSE: The KRAS mutation is highly prevalent in NSCLC and is associated with poor efficacy of immunotherapy. Nevertheless, the impact of KRAS mutation, mutation subtypes, and co-mutations on the effectiveness of immunotherapy remains uncertain. This study aimed to assess the influence of the KRAS mutation on the effectiveness of immunotherapy in NSCLC, specifically examining different subtypes of KRAS mutations and co-mutations. METHODS: We performed an extensive search of multiple databases, covering the period from January 1, 2000, to December 5, 2023. A total of 24 articles met our inclusion criteria and were included in this study. A comparative analysis assessed the influence of different subgroups, including KRAS mutation, KRAS wild-type, KRAS G12C mutation, KRAS G12D mutation, and KRAS with co-mutations in NSCLC with immunotherapy. The study outcomes include HR, with corresponding 95% CI and P-values for OS and PFS using Review Manager 5.4 software for the meta-analysis. RESULT: The KRAS mutation appears to have a more beneficial impact on OS (HR 0.54 [95% CI: 0.41-0.71]; P < 0.00001) and PFS (HR 0.63 [95% CI: 0.53-0.76]; P < 0.00001) in NSCLC patients receiving immunotherapy compared to those without immunotherapy. The presence of KRASG12C mutation has been found to have a positive impact on PFS (HR 0.39 [95% CI: 0.25-0.62]; P < 0.0001) in NSCLC patients who undergo immunotherapy, compared to those who did not receive immunotherapy. KRAS non-G12D mutation is considerably associated with longer OS (HR 1.52 [95% CI: 1.10-2.10]; P = 0.01). The clinical benefit in OS between patients without STK11 co-mutation and those who have KRAS mutation with STK11 is significant (HR 1.46 [95% CI: 1.10-1.93]; P = 0.008). Comparing the impact of OS patients without KEAP1/NFE2L2 mutation to those with KRAS and KEAP1/NFE2L2 co-mutations showed a significant impact (HR 1.89 [95% CI: 1.33-2.68]; P = 0.0004). CONCLUSION: The KRAS mutation and KRAS G12C mutation confer benefits that impact OS and PFS in NSCLC patients treated with immunotherapy. However, the KRAS G12D mutation negatively impacts OS compared to the KRAS non-G12D mutation. Furthermore, KRAS co-mutations involving STK11 and KEAP1/NFE2L2 are associated with a negative impact on the efficacy of immunotherapy in NSCLC patients.

Immune Subtypes and Characteristics of Endometrial Cancer Based on Immunogenes.

Purpose: The aim of this study was to explore the immune subtypes of endometrial cancer (EC) and its characteristics by immunogenes from the perspective of multidimensional genomics (multi-omics). Patients and Methods: Immune subtypes were carried out using an unsupervised non-negative matrix factorization clustering (NMF) method and their characteristics were analysed. Key genes were identified using random forest analysis. A predictive model for immune subtypes and their clinical prognosis were constructed. The relationship between immune subtypes and molecular subtypes was investigated. Results: Two immune subtypes C1 and C2 were available. C2 patients were younger, less graded, had significantly higher immune cell infiltration, immune checkpoint expression, tumor neoantigens, tumor mutation load than C1 (P<005). S100A9, CD3D, CD3E, HLA-DRB1 and IL2RB were the key genes with significant survival outcomes. S100A9 expression was lower in C2 than C1, and IL2RB, HLA-DRB1, CD3E and CD3D expression was higher than C1 (P<0.05). The predictive accuracy of five key genes for immune subtypes was good, with a Receiver operating characteristic of 0.941. The incidence of TP53abn type in C2 was significantly lower than that of C1, and the incidence of POLE type was significantly higher than that of C1 (P<0.0001). Conclusion: EC can be divided into two immune subtypes based on immunogenes. Low expression of S100A9 and high expression of IL2RB, HLA-DRB1, CD3E, and CD3D suggest sensitivity to immunotherapy and a good prognosis.

The prognostic significance of MYC/BCL2 double expression in DLBCL in the genetic classification era.

Double expression (DE) is a World Health Organization-recognized adverse prognostic factor in diffuse large B-cell lymphoma (DLBCL). However, the prognostic value of DE in the genetic subtyping era and potential mechanisms remain to be explored. We enrolled 246 DLBCL patients diagnosed between December 2021 and September 2023 in a Jiangsu Province Hospital cohort and included 930 DLBCL patients from three published studies in an external cohort. Double-expression DLBCL (DEL) in the external cohort was mainly distributed in the OTHER subtype (42.0%), EZB subtype (28.3%), and MCD subtype (15.0%), whereas the MCD subtype exhibited the highest ratio of DEL. DEL was significantly related to unfavorable overall survival (OS) and progression-free survival (PFS) in DLBCL, but only in EZB and OTHER subtypes that DEL retained remarkably adverse impacts on survivals compared to non-DEL. We explored the prognostic value of clinical and genetic parameters in DEL patients and found only ST2 showed better OS than A53 in DEL patients, whereas the other subtypes showed no significant difference. DEL showed similarities with the MCD subtype in mutation profiles. Furthermore, RNA-sequencing analyses exhibited upregulation in tumor proliferation-related pathways in DEL patients, but downregulation in extracellular matrix organization, T-cell activation and proliferation, type II interferon production, and pathways associated with cell death might contribute to the poor outcomes of DEL patients.

Combination of grade and spread through air spaces (STAS) predicts recurrence in early stage lung adenocarcinoma: a retrospective cohort study.

Adenocarcinomas, a common subtype of lung cancer, exhibit diverse histological patterns. In 2020, The International Association for the Study of Lung Cancer (IASLC) introduced a grading system emphasizing high-grade components, which has shown prognostic value. Spread through air spaces (STAS) is recognized as a prognostic feature increasing the risk of recurrence in lung cancer. This study evaluates the combination of STAS status and the IASLC-grading system in surgically resected Stage I lung adenocarcinomas. This study is a retrospective analysis of 123 patients with Stage I lung adenocarcinoma who underwent lobectomy between 2011 and 2019. Histological patterns were assessed according to the IASLC criteria, and STAS status was documented. Patients were categorized based on their IASLC Grade and STAS status. Statistical analyses included Kaplan-Meier survival estimates, Cox proportional hazards models, and comparisons using Chi-square and t-tests. The cohort comprised 43 females and 80 males with a mean age of 61.8 ± 7.6 years. STAS positivity was noted in 52.8% of patients. STAS positivity correlated significantly with Grade 3 tumors (p < 0.001). The 5-year recurrence-free survival was significantly lower in STAS-positive patients (70.7% vs. 88.7%, p = 0.026). Patients with Grade 3 and STAS positivity had significantly lower recurrence-free survival compared to other groups (p = 0.002). Grade 3 and STAS positivity were independent predictors of poor recurrence-free survival in multivariate analysis. IASLC Grade 3 tumors and STAS positivity are independent prognostic factors for poor recurrence-free survival in Stage I lung adenocarcinomas. Adjuvant treatment strategies should be considered for patients with these characteristics to improve outcomes.

Integrative Analysis of ATAC-Seq and RNA-Seq through Machine Learning Identifies 10 Signature Genes for Breast Cancer Intrinsic Subtypes.

Breast cancer is a heterogeneous disease composed of various biologically distinct subtypes, each characterized by unique molecular features. Its formation and progression involve a complex, multistep process that includes the accumulation of numerous genetic and epigenetic alterations. Although integrating RNA-seq transcriptome data with ATAC-seq epigenetic information provides a more comprehensive understanding of gene regulation and its impact across different conditions, no classification model has yet been developed for breast cancer intrinsic subtypes based on such integrative analyses. In this study, we employed machine learning algorithms to predict intrinsic subtypes through the integrative analysis of ATAC-seq and RNA-seq data. We identified 10 signature genes (CDH3, ERBB2, TYMS, GREB1, OSR1, MYBL2, FAM83D, ESR1, FOXC1, and NAT1) using recursive feature elimination with cross-validation (RFECV) and a support vector machine (SVM) based on SHAP (SHapley Additive exPlanations) feature importance. Furthermore, we found that these genes were primarily associated with immune responses, hormone signaling, cancer progression, and cellular proliferation.

Nomogram predicts cervical lymph node metastasis of pathological subtypes of papillary thyroid carcinoma.

BACKGROUND: Pathological subtypes of papillary thyroid carcinoma (PTC) are important factors in thyroid cancer. Some rare subtypes exhibit extensive lymph node metastasis. These pathological subtypes should receive more attention in clinical practice. METHODS: Patients with different pathological subtypes of PTC were selected from the SEER database. Logistic regression, random forest, and bootstrap aggregating (bagging) methods were employed to screen for risk factors associated with cervical lymph node metastasis in the training cohort. A nomogram was established based on the model with the largest area under the curve (AUC) and evaluated using calibration curves. Decision curve analysis (DCA) was used to evaluate the clinical benefit to patients. The nomogram was validated in depth by 200 iterations of tenfold cross-validation. RESULTS: A total of 7,882 patients were included in the analysis, with 5,516 patients in the training group and 2,366 patients in the testing group. The logistic regression model achieved the highest AUC of 0.7396. Sex, age, race, extension (extrathyroidal extension), pathological type, and primary tumour size were identified as independent risk factors for cervical lymph node metastasis (p < 0.05). The calibration curve indicated that the model was well calibrated. DCA indicated that the nomogram model had good clinical practicability. CONCLUSION: In clinical practice, it is important to consider the pathological subtypes of PTC. The established nomogram can serve as a predictive tool for assessing cervical lymph node metastasis.

Ruhao Dashi granules exert therapeutic effects on H1N1 influenza virus infection by altering intestinal microflora composition.

Objective: Antiviral medications for influenza could be ineffective due to the emergence of resistant influenza virus strains. Ruhao Dashi (RHDS) granules possess anti-inflammatory and antibacterial effects. The present study aimed to determine the efficacy of RHDS granules in treating influenza-infected mice and the mechanism underlying this treatment as well as its effect on the intestinal flora composition of the infected mice. Methods: The HPLC-UV method was used to identify the active components of RHDS granules. ICR mice were infected with influenza A virus (IAV) H1N1 subtype through a nasal drip. After the influenza mice model was successfully established, the pathological changes in the lungs were observed for 5 days after gavage treatment with 0.9% sterile saline and low, medium, and high doses (0.07, 0.14, and 0.28 g/mL, respectively) of RHDS granules. The serum levels of the cytokines IL-6 and TNF-α and sIgA were detected by ELISA. Real-time fluorescence quantitative PCR and western blotting assay were performed to determine the expression levels of the tight junction (TJ) proteins claudin-1, occludin, and zonula occludens-1 (ZO-1) in colon tissues. Furthermore, 16S rRNA gene sequencing of feces samples was conducted to assess the effect of RHDS granules on the gut microbiota. Results: RHDS granules exerted a protective effect on the lung tissues of IAV-infected mice; moreover, the granules reduced the synthesis of proinflammatory cytokines and increased the relative expression levels of claudin-1, occludin, and ZO-1 in colon tissues. Furthermore, RHDS granule treatment increased the relative abundance of Lactobacillus, Akkermansia, and Faecalibaculum and decreased the relative abundance of Muribaculaceae; thus, RHDS granules could stabilize the intestinal microbiota to some extent. Conclusion: RHDS granules exert a therapeutic effect on IAV-infected mice probably by modifying the structural composition of their intestinal microbiota.

iSubGen generates integrative disease subtypes by pairwise similarity assessment.

There are myriad types of biomedical data-molecular, clinical images, and others. When a group of patients with the same underlying disease exhibits similarities across multiple types of data, this is called a subtype. Existing subtyping approaches struggle to handle diverse data types with missing information. To improve subtype discovery, we exploited changes in the correlation-structure between different data types to create iSubGen, an algorithm for integrative subtype generation. iSubGen can accommodate any feature that can be compared with a similarity metric to create subtypes versatilely. It can combine arbitrary data types for subtype discovery, such as merging genetic, transcriptomic, proteomic, and pathway data. iSubGen recapitulates known subtypes across multiple cancers even with substantial missing data and identifies subtypes with distinct clinical behaviors. It performs equally with or superior to other subtyping methods, offering greater stability and robustness to missing data and flexibility to new data types. It is available at https://cran.r-project.org/web/packages/iSubGen.

Evolution of Influenza A(H3N2) Viruses in Bhutan for Two Consecutive Years, 2022 and 2023.

BACKGROUND: Influenza A viruses pose a significant public health threat globally and are characterized by rapid evolution of the hemagglutinin (HA) gene causing seasonal epidemics. The aim of this study was to investigate the evolutionary dynamics of A(H3N2) circulating in Bhutan during 2022 and 2023. METHODS: We analysed 166 whole-genome sequences of influenza A(H3N2) from Bhutan, obtained from the GISAID database. We employed a Bayesian Markov Chain Monte Carlo (MCMC) framework, with a curated global dataset of HA sequences from regions with significant migration links to Bhutan. Phylogenetic, temporal, and phylogeographic analyses were conducted to elucidate the evolutionary dynamics and spatial dissemination of the viruses. RESULTS: Our phylogenetic analysis identified the circulation of influenza A(H3N2) Clade 3C.2a1b.2a.2 in Bhutan during 2022 and 2023, with viruses further classified into three subclades: 2a.3 (39/166), 2a.3a.1 (58/166) and 2a.3b (69/166). The TMRCA estimates suggest that these viral lineages originated approximately 1.93 years prior to their detection. Phylogeographic analysis indicates introductions from the United States in 2022 and Australia in 2023. The mean evolutionary rate across all gene segments was calculated to be 4.42 × 10-3 substitutions per site per year (95% HPD: 3.19 × 10-3 to 5.84 × 10-3), with evidence of purifying selection and limited genetic diversity. Furthermore, reassortment events were rare, with an estimated rate of 0.045 events per lineage per year. CONCLUSION: Our findings show that primary forces shaping the local evolution of the influenza A(H3N2) in Bhutan are largely stochastic, with only sporadic instances of adaptive change, and thus underscore the importance of continuous surveillance to mitigate the impact of evolving strains.

Post-operative delirium in different age groups and subtypes: a systematic review of case reports.

Aims: To explore the clinical presentations and outcomes among different ages and subtypes of post-operative delirium patients. Design: Systematic review of Published Cases. Methods and data sources: We comprehensively searched PubMed, EMBASE, and MEDLINE for published case reports of post-operative delirium up to April 2023. The systematic review has been registered with PROSPERO. Two researchers independently conducted unblinded reviews of the full-text articles. Results: This study included 116 patients with post-operative delirium. Compared to post-operative delirium patients aged 65 and above, those between 18 and 65 years old have lower rates of a history of hypertension, cardiovascular disease and urinary system disorder comorbidities, as well as higher usage rates of fentanyl analogs and lorazepam. Additionally, these patients exhibit lower incidences of anemia and renal failure, along with a lower mortality rate. Compared to post-operative delirium patients aged 65 and above, those under 18 years old have a higher rate of fentanyl analog usage and a higher incidence of post-operative delirium following neurological surgeries. Among the hypoactive, hyperactive, and mixed subtypes, the reasons for surgery, such as cardiovascular diseases, reproductive system diseases, and neurological disorders, significantly varied among these three subtypes. Furthermore, substance abuse history and medication usage patterns also significantly varied among these three subtypes. Conclusions: Our investigation has revealed noteworthy insights into post-operative delirium in different patient populations. Notably, age emerged as a pivotal factor. Compared to elderly patients (≥65 years), those aged 18 to 65 demonstrate better prognosis. Additionally, patients younger than 18 years with post-operative delirium have a higher incidence of delirium following neurosurgical procedures compared to those elderly patients. Additionally, a strong association was found between a history of substance abuse and hyperactive delirium. Variations in drug use patterns were observed across different subtypes. Importantly, post-operative delirium patients younger than 18 years, as well as those aged 18 to 65 with mixed-subtype delirium, exhibited similar high mortality rates as elderly patients. This underscores the need for increased attention to post-operative delirium patients under 65 and highlights the necessity of rapid identification and early intervention for these populations at risk of poor outcomes. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023473383, Identifier [Registration ID: CRD 42023473383].

[Efficacy and safety analysis of the OR-CHOP regimen for the treatment of MCD subtype diffuse large B cell lymphoma in the real-world setting].

Objective: To investigate the efficacy and safety of orelabrutinib combined with R-CHOP in the treatment of MCD subtype diffuse large B cell lymphoma (DLBCL) . Methods: Twenty-three MCD subtype patients whose gene-subtype classification was based on baseline tumor tissue and/or baseline plasma using the LymphGen algorithm from June 2022 to June 2023 in the First Affiliated Hospital of Nanjing Medical University were retrospectively enrolled in the analysis. All patients were treated with R-CHOP or R-miniCHOP in Course 1, OR-CHOP or OR-miniCHOP (21 days for one course) in Courses 2-6, and R-monotherapy in Courses 7-8. Results: Of the 23 patients, the median age was 58 years (range: 30-81 years), and 11 (47.8% ) aged >60 years. Fifteen cases (65.2% ) had international prognostic index (IPI) scores of 3 to 5. The top 10 mutated genes in the gDNA tissues were PIM1 (78.3% ), MYD88 (69.6% ), ETV6 (43.5% ), BTG1 (39.1% ), CD79B (43.5% ), HIST1H1E (39.1% ), BTG2 (34.8% ), KMT2D (30.4% ), CD58 (26.1% ), and CDKN2B (21.7% ). The consistency rate of the tissue and plasma mutations was 80%, while the baseline plasma ctDNA burden was closely correlated with the LDH levels and IPI scores (P<0.05). All patients received 5 courses of OR-CHOP regimens. The mid-term (after 3 courses) evaluation showed that the overall response rate (ORR) was 100% (23/23), with 22 patients (95.65% ) achieving complete remission (CR), and 1 patient (4.35% ) achieving partial remission (PR). The ORR after the end of treatment (EOT) was 95.65% (22/23). Moreover, 21 patients (91.30% ) obtained CR, 1 patient (4.35% ) obtained PR, and 1 patient (4.35% ) obtained progression disease (PD). Of the 21 patients who had the dynamic EOT-ctDNA burden, only four patients (19.0% ) did not achieve EOT-ctDNA clearance, while the other 17 patients (81.0% ) achieved EOT-ctDNA clearance. The median follow-up time was 20.8 (15.3-30.0) months, while the median progression-free survival (PFS) and overall survival (OS) were not reached. The 2-year PFS rate was 71.8% (95% CI 54.7% -94.2% ), while the 2-year OS rate was 91.3% (95% CI 80.5% -100.0% ). Furthermore, the OR-CHOP regimen was generally well tolerated during clinical use, with hematological toxicity being the main adverse effect. Conclusion: This study revealed that the OR-CHOP regimen can be used as an effective and safe first-line treatment for MCD subtype DLBCL.

The impact of physical activity on progression-free and overall survival in metastatic breast cancer based on molecular subtype.

BACKGROUND: Although adequate physical activity has been shown to be beneficial in early breast cancer, evidence in metastatic breast cancer is sparse and contradictory, which could be related to distinct effects of physical activity on the different molecular cancer subtypes. Therefore, we here evaluated the effect of physical activity on progression-free and overall survival (PFS, OS) in metastatic breast cancer, specifically looking at molecular subtypes. METHODS: International Physical Activity Questionnaire (IPAQ) questionnaires, filled out by patients enrolled in the prospective PRAEGNANT registry (NCT02338167; n = 1,270) were used to calculate metabolic equivalent task (MET) minutes, which were subsequently categorized into low (n = 138), moderate (n = 995) or high IPAQ categories (n = 137). Cox regression analyses were used to evaluate the impact of IPAQ categories and its interaction with molecular subtypes on PFS and OS. RESULTS: Patient and tumor characteristics were equally distributed across IPAQ categories. HER2pos, HRpos and TNBC were present in 23.1%, 65.7% and 11.2% of patients, respectively. IPAQ scores did not have an impact on PFS and OS in addition to established prognostic factors, either overall or in particular molecular subtypes (PFS: p = 0.33 and OS: p = 0.08, likelihood ratio test). Exploratory analyses showed higher overall survival rates for high IPAQ categories compared to low/moderate IPAQ categories in luminal B-like breast cancer. CONCLUSIONS: Self-reported physical activity using the IPAQ questionnaire did not significantly affect PFS or OS in patients suffering from metastatic breast cancer. Nevertheless, some hypothesis-generating differences between molecular subtypes could be observed, which may be interesting to evaluate further.

Single-cell transcriptional atlas of human breast cancers and model systems.

BACKGROUND: Breast cancer's complex transcriptional landscape requires an improved understanding of cellular diversity to identify effective treatments. The study of genetic variations among breast cancer subtypes at single-cell resolution has potential to deepen our insights into cancer progression. METHODS: In this study, we amalgamate single-cell RNA sequencing data from patient tumours and matched lymph metastasis, reduction mammoplasties, breast cancer patient-derived xenografts (PDXs), PDX-derived organoids (PDXOs), and cell lines resulting in a diverse dataset of 117 samples with 506 719 total cells. These samples encompass hormone receptor positive (HR+), human epidermal growth factor receptor 2 positive (HER2+), and triple-negative breast cancer (TNBC) subtypes, including isogenic model pairs. Herein, we delineated similarities and distinctions across models and patient samples and explore therapeutic drug efficacy based on subtype proportions. RESULTS: PDX models more closely resemble patient samples in terms of tumour heterogeneity and cell cycle characteristics when compared with TNBC cell lines. Acquired drug resistance was associated with an increase in basal-like cell proportions within TNBC PDX tumours as defined with SCSubtype and TNBCtype cell typing predictors. All patient samples contained a mixture of subtypes; compared to primary tumours HR+ lymph node metastases had lower proportions of HER2-Enriched cells. PDXOs exhibited differences in metabolic-related transcripts compared to PDX tumours. Correlative analyses of cytotoxic drugs on PDX cells identified therapeutic efficacy was based on subtype proportion. CONCLUSIONS: We present a substantial multimodel dataset, a dynamic approach to cell-wise sample annotation, and a comprehensive interrogation of models within systems of human breast cancer. This analysis and reference will facilitate informed decision-making in preclinical research and therapeutic development through its elucidation of model limitations, subtype-specific insights and novel targetable pathways. KEY POINTS: Patient-derived xenografts models more closely resemble patient samples in tumour heterogeneity and cell cycle characteristics when compared with cell lines. 3D organoid models exhibit differences in metabolic profiles compared to their in vivo counterparts. A valuable multimodel reference dataset that can be useful in elucidating model differences and novel targetable pathways.

No Evidence for Endocannabinoid-Induced G Protein Subtype Selectivity at Human and Rodent Cannabinoid CB1 Receptors.

Introduction: The endocannabinoid system (ECS) is a widespread neurotransmitter system. A key characteristic of the ECS is that there are multiple endogenous ligands (endocannabinoids). Of these, the most extensively studied are arachidonoyl ethanolamide (AEA) and 2-arachidonoyl-glycerol (2-AG), both act as agonists at the cannabinoid CB1 receptor. In humans, three CB1 variants have been identified: hCB1, considered the most abundant G protein-coupled receptor in the brain, alongside the less abundant and studied variants, hCB1a and hCB1b. CB1 exhibits a preference for coupling with inhibitory Gi/o proteins, although its interactions with specific members of the Gi/o family remain poorly characterized. This study aimed to compare the AEA and 2-AG-induced activation of various G protein subtypes at CB1. Furthermore, we compared the response of human CB1 (hCB1, hCB1a, hCB1b) and explored species differences by examining rodent receptors (mCB1, rCB1). Materials and Methods: Activation of individual G protein subtypes in HEK293 cells transiently expressing CB1 was measured with G protein dissociation assay utilizing TRUPATH biosensors. The performance of the TRUPATH biosensors was evaluated using Z-factor analysis. Pathway potencies and efficacies were analyzed using the operational analysis of bias to determine G protein subtype selectivity for AEA and 2-AG. Results: Initial screening of TRUPATH biosensors performance revealed variable sensitivities within our system. Based on the biosensor performance, the G protein subtypes pursued for further characterization were Gi1, Gi3, GoA, GoB, GZ, G12, and G13. Across all pathways, AEA demonstrated partial agonism, whereas 2-AG exhibited full or high-efficacy agonism. Notably, we provide direct evidence that the hCB1 receptor couples to G12 and G13 proteins. Our findings do not indicate any evidence of G protein subtype selectivity. Similar observations were made across the human receptor variants (hCB1, hCB1a, hCB1b), as well as at mCB1 and rCB1. Discussion: There was no evidence suggesting G protein subtype selectivity for AEA and 2-AG at CB1, and this finding remained consistent across human receptor variants and different species.

Ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer.

Purpose: Accurate preoperative identification of Human epidermal growth factor receptor 2 (HER2) low expression breast cancer (BC) is critical for clinical decision-making. Our aim was to use machine learning methods to develop and validate an ultrasound-based radiomics nomogram for predicting HER2-low expression in BC. Methods: In this retrospective study, 222 patients (108 HER2-0 expression and 114 HER2-low expression) with BC were included. The enrolled patients were randomly divided into a training cohort and a test cohort with a ratio of 8:2. The tumor region of interest was manually delineated from ultrasound image, and radiomics features were subsequently extracted. The features underwent dimension reduction using the least absolute shrinkage and selection operator (LASSO) algorithm, and rad-score were calculated. Five machine learning algorithms were applied for training, and the algorithm demonstrating the best performance was selected to construct a radiomics (USR) model. Clinical risk factors were integrated with rad-score to construct the prediction model, and a nomogram was plotted. The performance of the nomogram was assessed using receiver operating characteristic curve and decision curve analysis. Results: A total of 480 radiomics features were extracted, out of which 11 were screened out. The majority of the extracted features were wavelet features. Subsequently, the USR model was established, and rad-scores were computed. The nomogram, incorporating rad-score, tumor shape, border, and microcalcification, achieved the best performance in both the training cohort (AUC 0.89; 95%CI 0.836-0.936) and the test cohort (AUC 0.84; 95%CI 0.722-0.958), outperforming both the USR model and clinical model. The calibration curves showed satisfactory consistency, and DCA confirmed the clinical utility of the nomogram. Conclusion: The nomogram model based on ultrasound radiomics exhibited high prediction value for HER2-low BC.

Development, study, and comparison of models of cross-immunity to the influenza virus using statistical methods and machine learning.

INTRODUCTION: The World Health Organization considers the values of antibody titers in the hemagglutination inhibition assay as one of the most important criteria for assessing successful vaccination. Mathematical modeling of cross-immunity allows for identification on a real-time basis of new antigenic variants, which is of paramount importance for human health. MATERIALS AND METHODS: This study uses statistical methods and machine learning techniques from simple to complex: logistic regression model, random forest method, and gradient boosting. The calculations used the AAindex matrices in parallel to the Hamming distance. The calculations were carried out with different types and values of antigenic escape thresholds, on four data sets. The results were compared using common binary classification metrics. RESULTS: Significant differentiation is shown depending on the data sets used. The best results were demonstrated by all three models for the forecast autumn season of 2022, which were preliminary trained on the February season of the same year (Auroc 0.934; 0.958; 0.956, respectively). The lowest results were obtained for the entire forecast year 2023, they were set up on data from two seasons of 2022 (Aucroc 0.614; 0.658; 0.775). The dependence of the results on the types of thresholds used and their values turned out to be insignificant. The additional use of AAindex matrices did not significantly improve the results of the models without introducing significant deterioration. CONCLUSION: More complex models show better results. When developing cross-immunity models, testing on a variety of data sets is important to make strong claims about their prognostic robustness.

First detection of influenza A virus subtypes H1N1 and H3N8 in the Antarctic region: King George Island, 2023.

RELEVANCE: Influenza A virus is characterized by a segmented single-stranded RNA genome. Such organization of the virus genome determines the possibility of reassortment, which can lead to the emergence of new virus variants. The main natural reservoir of most influenza A virus subtypes are wild waterfowl. Seasonal migrations gather waterfowl from all major migration routes to nesting areas near the northern and southern polar circles. This makes intercontinental spread of influenza A viruses possible. Objective ‒ to conduct molecular genetic monitoring and study the phylogenetic relationships of influenza A virus variants circulating in Antarctica in 2023. MATERIALS AND METHODS: We studied 84 samples of biological material obtained from birds and marine mammals in April‒May 2023 in coastal areas of Antarctica. For 3 samples, sequencing was performed on the Miseq, Illumina platform and phylogenetic analysis of the obtained nucleotide sequences of the influenza A virus genomes was performed. RESULTS: The circulation of avian influenza virus in the Antarctic region was confirmed. Heterogeneity of the pool of circulating variants of the influenza A virus (H3N8, H1N1) was revealed. Full-length genomes of the avian influenza virus were sequenced and posted in the GISAID database (EPI_ISL_19032103, 19174530, 19174467). CONCLUSION: The study of the genetic diversity of influenza A viruses circulating in the polar regions of the Earth and the identification of the conditions for the emergence of new genetic variants is a relevant task for the development of measures to prevent biological threats.