MGMT methylation and its prognostic significance in inoperable IDH-wildtype glioblastoma: the MGMT-GBM study.

INTRODUCTION: The methylation of the O6-Methylguanine-DNA Methyltransferase (MGMT) promoter is a valid biomarker for predicting response to therapy with alkylating agents and, independently, prognosis in IDH-wildtype(IDH-w) glioblastoma. We aim to study the impact of its methylation in overall survival of the unresectable IDH-w glioblastoma undergoing biopsy and systemic treatment. METHODS: We collected six-year retrospective (2017-2023) data at a quaternary neurosurgery center for patients undergoing biopsy as the only surgical procedure for an unresectable IDH wildtype glioblastoma. Data was collected from patient records including neuro-oncology multidisciplinary team meeting (MDT) documentation. Patients were grouped into categories according to different types of treatment received after biopsy (no treatment, chemotherapy (CT), radiotherapy (RT), chemoradiotherapy (CRT), chemoradiotherapy with adjuvant temozolomide (CRT with adjuvant TMZ), EORTC-NCIC protocol followed by second line treatment) and according to methylation status (unmethylated (< 5%), borderline methylated (5-15%) and strongly methylated (> 15%)). Survival analysis was performed. RESULTS: 166 glioblastoma IDH wildtype patients were included in the study with mean age of 62.5 years (M: F = 1.5: 1). 70 (49.3%) patients had unmethylated MGMT status (< 5%), 29 (20.4%) patients had borderline methylated MGMT status (5-15%) and 43 (30.2%) patients had methylated MGMT status (> 15%). 36 (25.3%) patients did not receive any treatment post biopsy, 13 (9.1%) received CT only, 27 (19%) RT only, 12 (8.4%) CRT, 33 (23.2%) CRT with adjuvant TMZ, whereas 21 (14.7%) received EORTC-NCIC protocol along with second line treatment. In biopsy only group, there was no notable difference in survival outcomes among the different methylation statuses. For biopsy and any-other-form-of-treatment methylated groups showed a distinct trend of better survival compared to the borderline or unmethylated groups. Overall, methylated patients had better survival as compared to unmethylated or borderline groups. CONCLUSION: Methylated MGMT status are predictors for better overall survival in unresectable IDH wildtype glioblastoma patients undergoing biopsy and treatment regardless of the treatment modality.

Impact of the Lung Microbiota on Development and Progression of Lung Cancer.

The past several years have provided a more profound understanding of the role of microbial species in the lung. The respiratory tract is a delicate ecosystem of bacteria, fungi, parasites, and viruses. Detecting microbial DNA, pathogen-associated molecular patterns (PAMPs), and metabolites in sputum is poised to revolutionize the early diagnosis of lung cancer. The longitudinal monitoring of the lung microbiome holds the potential to predict treatment response and side effects, enabling more personalized and effective treatment options. However, most studies into the lung microbiota have been observational and have not adequately considered the impact of dietary intake and air pollutants. This gap makes it challenging to establish a direct causal relationship between environmental exposure, changes in the composition of the microbiota, lung carcinogenesis, and tumor progression. A holistic understanding of the lung microbiota that considers both diet and air pollutants may pave the way to improved prevention and management strategies for lung cancer.

Molecular characterization and biomarker identification in paediatric B-cell acute lymphoblastic leukaemia.

B-cell acute lymphoblastic leukaemia (B-ALL) is the most prevalent hematologic malignancy in children and a leading cause of mortality. Managing B-ALL remains challenging due to its heterogeneity and relapse risk. This study aimed to delineate the molecular features of paediatric B-ALL and explore the clinical utility of circulating tumour DNA (ctDNA). We analysed 146 patients with paediatric B-ALL who received systemic chemotherapy. The mutational landscape was profiled in bone marrow (BM) and plasma samples using next-generation sequencing. Minimal residual disease (MRD) testing on day 19 of induction therapy evaluated treatment efficacy. RNA sequencing identified gene fusions in 61% of patients, including 37 novel fusions. Specifically, the KMT2A-TRIM29 novel fusion was validated in a boy who responded well to initial therapy but relapsed after 1 year. Elevated mutation counts and maximum variant allele frequency in baseline BM were associated with significantly poorer chemotherapy response (p = 0.0012 and 0.028, respectively). MRD-negative patients exhibited upregulation of immune-related pathways (p < 0.01) and increased CD8+ T cell infiltration (p = 0.047). Baseline plasma ctDNA exhibited high mutational concordance with the paired BM samples and was significantly associated with chemotherapy efficacy. These findings suggest that ctDNA and BM profiling offer promising prognostic insights for paediatric B-ALL management.

Chemotherapy combined with immune checkpoint inhibitors may overcome the detrimental effect of high neutrophil-to-lymphocyte ratio prior to treatment in esophageal cancer patients.

Introduction: Immune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for esophageal cancer (EC). Although ICIs enable long-term survival in some patients, the efficacy of ICIs varies widely among patients. Therefore, predictive biomarkers are necessary for identifying patients who are most likely to benefit from ICIs to improve the efficacy of the treatment. We retrospectively analyzed the outcomes of combination therapy, including nivolumab plus ipilimumab or chemotherapy plus anti-programmed cell death 1 (PD-1) antibodies in our institute to identify biomarkers. Methods: Twenty-seven patients received nivolumab plus ipilimumab, and thirty-six patients received chemotherapy plus anti-PD-1 antibodies were included in this study. We analyzed patient characteristics, efficacy, and safety. Multivariable analysis of biomarkers evaluated the correlation among overall survival (OS), progression-free survival (PFS), and the following variables: body mass index, performance status, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein level, and albumin level before treatment. Results: In multivariable analysis, albumin level was significantly correlated with PFS in the cisplatin plus 5-fluorouracil (CF) plus pembrolizumab group. NLR and albumin level were significantly correlated with OS in the nivolumab plus ipilimumab group. Other variables, including PS, BMI, and CRP did not correlate with any of the outcomes. Conclusions: High NLR in EC patients prior to treatment was significantly less effective for ICIs. In chemotherapy combined with ICIs, NLR before the treatment was not associated with treatment efficacy, suggesting combination chemotherapy may be beneficial for EC patients with high NLR. NLR may be an indicator of immunocompetence in anti-tumor immunity and a convenient predictive biomarker for selecting appropriate treatments including ICIs.

D-dimer as a Predictive Biomarker of Response to Chemotherapy in Patients With Metastatic Breast Cancer.

Background: Tumor-induced coagulation is widely observed in cancer patients. Moreover, it is associated with tumorigenesis, tumor progression and metastasis, by creating a proliferative and proangiogenic microenvironment. Therefore, D-dimer, a fibrin degradation product, correlates with tumor prognosis in several cancer types. Objectives: This study aims to investigate whether D-dimer levels can be a predictive and monitoring indicator for chemotherapy response in metastatic breast cancer (MBC) patients. Design: This was a prospective study. Methods: This study included two groups, 76 patients diagnosed with metastatic breast carcinoma and 25 patients with primary breast carcinoma. Plasma D-dimer levels were measured prospectively before chemotherapy initiation, and after the fourth treatment cycle in MBC patients. D-dimer levels before chemotherapy (D0) were analyzed using Receiver Operating Characteristic (ROC) curves to determine the optimal cut-off baseline values of D0, and to evaluate their discriminatory abilities in predicting response to chemotherapy. Results: In the preliminary response evaluation, the mean level of D-dimer significantly decreased by 0.65 µg/ml in patients with partial response patterns, and by 0.5 µg/ml in patients with stable disease. In the disease progression group, a marked increase was seen in D-dimer levels by 1.2 µg/ml. Analysis of ROC curves showed that D-dimer levels at D0 could discriminate the response to chemotherapy, whereas progressive disease rate correlated with higher levels of D-dimer. Conclusion: D-dimer level in plasma is a useful predictive and monitoring marker of response to chemotherapy in metastatic breast cancer.

Biomarkers in head and neck squamous cell carcinoma: unraveling the path to precision immunotherapy.

Recent strides in understanding the molecular underpinnings of head and neck cancers have sparked considerable interest in identifying precise biomarkers that can enhance prognostication and enable personalized treatment strategies. Immunotherapy has particularly revolutionized the therapeutic landscape for head and neck squamous cell carcinoma, offering new avenues for treatment. This review comprehensively examines the application and limitations of the established and emerging/novel biomarkers for head and neck squamous cell carcinoma. Established biomarkers, including well-characterized genetic mutations, protein expressions, and clinical factors, have been extensively studied and validated in clinical practice. Novel biomarkers identified through molecular analyses, including novel genetic alterations, immune-related markers, and molecular signatures, are currently being investigated and validated in preclinical and clinical settings. Biomarkers hold the potential to deepen our understanding of head and neck squamous cell carcinoma biology and guide therapeutic strategies. The evolving paradigm of predictive biomarkers facilitates the study of individual responses to specific treatments, including targeted therapy and immunotherapy.

The baseline hemoglobin level is a positive biomarker for immunotherapy response and can improve the predictability of tumor mutation burden for immunotherapy response in cancer.

Purpose: Because only a subset of cancer patients can benefit from immunotherapy, identifying predictive biomarkers of ICI therapy response is of utmost importance. Methods: We analyzed the association between hemoglobin (HGB) levels and clinical outcomes in 1,479 ICIs-treated patients across 16 cancer types. We explored the dose-dependent associations between HGB levels and survival and immunotherapy response using the spline-based cox regression analysis. Furthermore, we investigated the associations across subgroups of patients with different clinicopathological characteristics, treatment programs and cancer types using the bootstrap resampling method. Results: HGB levels correlated positively with clinical outcomes in cancer patients receiving immunotherapy but not in those without immunotherapy. Moreover, this association was independent of other clinicopathological characteristics (such as sex, age, tumor stage and tumor mutation burden (TMB)), treatment program and cancer type. Also, this association was independent of the established biomarkers of immunotherapy response, including TMB, PD-L1 expression and microsatellite instability. The combination of TMB and HGB level are more powerful in predicting immunotherapy response than TMB alone. Multi-omics analysis showed that HGB levels correlated positively with antitumor immune signatures and negatively with tumor properties directing antitumor immunosuppression, such as homologous recombination defect, stemness and intratumor heterogeneity. Conclusion: The HGB measure has the potential clinical value as a novel biomarker of immunotherapy response that is easily accessible from clinically routine examination. The combination of TMB and HGB measures have better predictive performance for immunotherapy response than TMB.

Adebrelimab plus chemotherapy and sequential thoracic radiotherapy as first-line therapy for extensive-stage small-cell lung cancer (ES-SCLC): a phase II trial.

Background: This phase II prospective trial aimed to investigate the efficacy and safety of adebrelimab (PD-L1 antibody) plus first-line chemotherapy followed by sequential thoracic radiotherapy (TRT) combined with adebrelimab in extensive-stage small-cell lung cancer (ES-SCLC). Biomarkers associated with potential therapeutic effects were also explored. Methods: Patients with previously untreated ES-SCLC were enrolled at Shandong Cancer Hospital and Institute (Jinan, China). Patients received 4-6 cycles of adebrelimab (20 mg/kg, D1, Q3W) combined with EP/EC (etoposide, 100 mg/m2, D1-3, Q3W and cisplatin, 75 mg/m2, D1, Q3W or carboplatin, AUC = 5, D1, Q3W). Then patients with response sequentially underwent consolidative TRT (≥30 Gy in 10 fractions or ≥50 Gy in 25 fractions, involved-field irradiation), and maintenance adebrelimab until disease progression or intolerable adverse events (AEs). The primary endpoint was overall survival (OS). Genomic and circulating tumour DNA (ctDNA) profiling were also analyzed with tumour tissues and peripheral blood. This trial was registered with ClinicalTrials.gov, NCT04562337. Findings: From October 2020 to April 2023, 67 patients diagnosed with ES-SCLC were enrolled and received at least one dose of study treatment. All patients were included in the efficacy and safety analyses. 45 patients received sequential TRT as planned. The median OS and progression-free survival (PFS) was 21.4 months (95% CI: 17.2-not reached months) and 10.1 months (95% CI: 6.9-15.5 months), respectively. The confirmed objective response rate was 71.6% (48/67, 95% CI: 59.3-82.0%) and disease control rate was 89.6% (60/67, 95% CI: 79.7-95.7%). There were no treatment-related deaths. The most common grade 3 or higher treatment-related adverse events (TRAEs) were hematological toxicities. The incidence of any grade and G3+ pneumonitis was 25% (17/67) and 6% (4/67), respectively. No unexpected adverse events were observed. Patients without co-mutations of TP53/RB1 in both tissue and peripheral blood displayed longer PFS (tissue, P = 0.071; ctDNA, P = 0.060) and OS (tissue, P = 0.032; ctDNA, P = 0.031). Interpretation: Adebrelimab plus chemotherapy and sequential TRT as first-line therapy for ES-SCLC showed promising efficacy and acceptable safety. Funding: This study was funded by the National Natural Science Foundation of China (82172865), Jiangsu Hengrui Pharmaceuticals Co., Ltd. and Amoy Diagnostics Co., Ltd.

Antithetical impacts of deleterious LRP1B mutations in non-squamous and squamous NSCLCs on predicting benefits from immune checkpoint inhibitor alone or with chemotherapy over chemotherapy alone: retrospective analyses of the POPLAR/OAK and CHOICE-01 trials.

In non-small cell lung cancers, the non-squamous and squamous subtypes (nsqNSCLC and sqNSCLC) exhibit disparities in pathophysiology, tumor immunology, and potential genomic correlates affecting responses to immune checkpoint inhibitor (ICI)-based treatments. In our in-house training cohort (n=85), the presence of the LRP1B deleterious mutation (LRP1B-del) was associated with longer and shorter progression-free survival (PFS) on ICIs alone in nsqNSCLCs and sqNSCLCs, respectively (Pinteraction=0.008). These results were validated using a larger public ICI cohort (n=208, Pinteraction<0.001). Multiplex immunofluorescence staining revealed an association between LRP1B-del and increased and decreased numbers of tumor-infiltrating CD8+ T cells in nsqNSCLCs (P=0.040) and sqNSCLCs (P=0.014), respectively. In the POPLAR/OAK cohort, nsqNSCLCs with LRP1B-del demonstrated improved PFS benefits from atezolizumab over docetaxel (hazard ratio (HR) =0.70, P=0.046), whereas this benefit was negligible in those without LRP1B-del (HR=1.05, P=0.64). Conversely, sqNSCLCs without LRP1B-del benefited more from atezolizumab (HR=0.60, P=0.002) than those with LRP1B-del (HR=1.30, P=0.31). Consistent results were observed in the in-house CHOICE-01 cohort, in which nsqNSCLCs with LRP1B-del and sqNSCLCs without LRP1B-del benefited more from toripalimab plus chemotherapy than from chemotherapy alone (Pinteraction=0.008). This multi-cohort study delineates the antithetical impacts of LRP1B-del in nsqNSCLCs and sqNSCLCs on predicting the benefits from ICI alone or with chemotherapy over chemotherapy alone. Our findings highlight the distinct clinical utility of LRP1B-del in guiding treatment choices for nsqNSCLCs and sqNSCLCs, emphasizing the necessity for a detailed analysis based on pathological subtypes when investigating biomarkers for cancer therapeutics.

The emerging HER2 landscape in colorectal cancer: the key to unveil the future treatment algorithm?

Colorectal cancer (CRC) represents a global health threat, standing as the second leading cause of cancer-related death worldwide. Targeted therapies brought new hope for the metastatic stage, which historically bore a very poor prognosis. Human epidermal growth receptor 2 (HER2) overexpression concerns about 5 % of the metastatic CRC (mCRC) patients, including both gene amplifications and point mutations. Albeit its controversial prognostic role, preclinical and clinical data indicate HER2 as a negative predictive biomarker of response to anti-EGFR therapies. Tissue and plasma-based NGS testing, could permit a precise identification of this resistance mechanism both at baseline and during treatment, thus guiding decision-making. Furthermore, promising results come from completed and ongoing randomized trials, testing HER2 as an actionable target. In this review, we discuss the available evidence on HER2 targeting in advanced CRC, analyzing its possible future role in the treatment algorithm.

Prediction of gestational diabetes mellitus by multiple biomarkers at early gestation.

BACKGROUND: It remains unclear which early gestational biomarkers can be used in predicting later development of gestational diabetes mellitus (GDM). We sought to identify the optimal combination of early gestational biomarkers in predicting GDM in machine learning (ML) models. METHODS: This was a nested case-control study including 100 pairs of GDM and euglycemic (control) pregnancies in the Early Life Plan cohort in Shanghai, China. High sensitivity C reactive protein, sex hormone binding globulin, insulin-like growth factor I, IGF binding protein 2 (IGFBP-2), total and high molecular weight adiponectin and glycosylated fibronectin concentrations were measured in serum samples at 11-14 weeks of gestation. Routine first-trimester blood test biomarkers included fasting plasma glucose (FPG), serum lipids and thyroid hormones. Five ML models [stepwise logistic regression, least absolute shrinkage and selection operator (LASSO), random forest, support vector machine and k-nearest neighbor] were employed to predict GDM. The study subjects were randomly split into two sets for model development (training set, n = 70 GDM/control pairs) and validation (testing set: n = 30 GDM/control pairs). Model performance was evaluated by the area under the curve (AUC) in receiver operating characteristics. RESULTS: FPG and IGFBP-2 were consistently selected as predictors of GDM in all ML models. The random forest model including FPG and IGFBP-2 performed the best (AUC 0.80, accuracy 0.72, sensitivity 0.87, specificity 0.57). Adding more predictors did not improve the discriminant power. CONCLUSION: The combination of FPG and IGFBP-2 at early gestation (11-14 weeks) could predict later development of GDM with moderate discriminant power. Further validation studies are warranted to assess the utility of this simple combination model in other independent cohorts.

Mature MUC5AC Expression in Resected Pancreatic Ductal Adenocarcinoma Predicts Treatment Response and Outcomes.

Neoadjuvant therapy (NAT) for early-stage pancreatic ductal adenocarcinoma (PDA) has recently gained prominence. We investigated the clinical significance of mucin 5 AC (MUC5AC), which exists in two major glycoforms, a less-glycosylated immature isoform (IM) and a heavily glycosylated mature isoform (MM), as a biomarker in resected PDA. Immunohistochemistry was performed on 100 resected PDAs to evaluate the expression of the IM and MM of MUC5AC using their respective monoclonal antibodies, CLH2 (NBP2-44455) and 45M1 (ab3649). MUC5AC localization (cytoplasmic, apical, and extra-cellular (EC)) was determined, and the H-scores were calculated. Univariate and multivariate (MVA) Cox regression models were used to estimate progression-free survival (PFS) and overall survival (OS). Of 100 resected PDA patients, 43 received NAT, and 57 were treatment-naïve with upfront surgery (UpS). In the study population (n = 100), IM expression (H-scores for objective response vs. no response vs. UpS = 104 vs. 152 vs. 163, p = 0.01) and MM-MUC5AC detection rates (56% vs. 63% vs. 82%, p = 0.02) were significantly different. In the NAT group, MM-MUC5AC-negative patients had significantly better PFS according to the MVA (Hazard Ratio: 0.2, 95% CI: 0.059-0.766, p = 0.01). Similar results were noted in a FOLFIRINOX sub-group (n = 36). We established an association of MUC5AC expression with treatment response and outcomes.

Clinical applications of radiomics and deep learning in breast and lung cancer: A narrative literature review on current evidence and future perspectives.

Radiomics, analysing quantitative features from medical imaging, has rapidly become an emerging field in translational oncology. Radiomics has been investigated in several neoplastic malignancies as it might allow for a non-invasive tumour characterization and for the identification of predictive and prognostic biomarkers. Over the last few years, evidence has been accumulating regarding potential clinical applications of machine learning in many crucial moments of cancer patients' history. However, the incorporation of radiomics in clinical decision-making process is still limited by low data reproducibility and study variability. Moreover, the need for prospective validations and standardizations is emerging. In this narrative review, we summarize current evidence regarding radiomic applications in high-incidence cancers (breast and lung) for screening, diagnosis, staging, treatment choice, response, and clinical outcome evaluation. We also discuss pro and cons of the radiomic approach, suggesting possible solutions to critical issues which might invalidate radiomics studies and propose future perspectives.

Oncofetal IGF2BP3-mediated control of microRNA structural diversity in the malignancy of early-stage lung adenocarcinoma.

The nature of microRNA (miRNA) dysfunction in carcinogenesis remains controversial because of the complex connection between miRNA structural diversity and biological processes. Here, we found that oncofetal IGF2BP3 regulates the selective production of a subset of 3'-isoforms (3'-isomiRs), including miR-21-5p and Let-7 family, which induces significant changes in their cellular seed occupancy and structural components, establishing a cancer-specific gene expression profile. The D-score, reflecting dominant production of a representative miR-21-5p+C (a 3'-isomiR), discriminated between clinical early-stage lung adenocarcinoma (LUAD) cases with low and high recurrence risks, and was associated with molecular features of cell cycle progression, epithelial-mesenchymal transition pressure, and immune evasion. We found that IGF2BP3 controls the production of miR-21-5p+C by directing the nuclear Drosha complex to select the cleavage site. IGF2BP3 was also involved in the production of 3'-isomiRs of miR-425-5p and miR-454-3p. IGF2BP3-regulated these three miRNAs are suggested to be associated with the regulation of p53, TGF-ß, and TNF pathways in LUAD. Knockdown of IGF2BP3 also induced a selective upregulation of Let-7 3'-isomiRs, leading to increased cellular Let-7 seed occupancy and broad repression of its target genes encoding cell cycle regulators. The D-score is an index that reflects this cellular situation. Our results suggest that the aberrant regulation of miRNA structural diversity is a critical component for controlling cellular networks, thus supporting the establishment of a malignant gene expression profile in early stage LUAD.

Argonaute-2 autoantibodies: a promising biomarker for predicting mortality in HBV-related acute-on-chronic liver failure patients with cirrhosis.

Background & aims: HBV infection initiates autoimmune responses, leading to autoantibody generation. This research explores the role of autoantibodies in HBV-related Acute-on-Chronic Liver Failure (ACLF), offering novel perspectives for clinical management. Method: We applied immunoprecipitation and iTRAQ techniques to screen for autoantibodies in serum from HBV-related cirrhosis patients and conducted detection with conformation- stabilizing ELISA in a cohort of 238 HBV-infected individuals and 49 health controls. Our results were validated in a retrospective cohort comprising 106 ACLF patients and further assessed through immunohistochemical analysis in liver tissues from an additional 10 ACLF cases. Results: Utilizing iTRAQ, we identified Argonaute1-3 autoantibodies (AGO-Abs) in this research. AGO2-Abs notably increased in cirrhosis, decompensation, and further in ACLF, unlike AGO1-Abs and AGO3-Abs. This reflects disease severity correlation. Logistic regression and COX models confirmed AGO2-Abs as independent prognostic indicators for decompensated liver cirrhosis (DLC) and ACLF. In the ROC analysis, AGO2-Abs showed significant diagnostic value for predicting 28- and 90-day mortality (AUROC = 0.853 and 0.854, respectively). Furthermore, combining AGO2-Abs with the Child-Pugh, MELD, and AARC scores significantly improved their predictive accuracy (P < 0.05). Kaplan-Meier analysis showed poorer survival for AGO2-Abs levels above 99.14µg/ml. These findings were supported by a retrospective validation cohort. Additionally, immunohistochemistry revealed band-like AGO2 expression in periportal liver areas, with AGO2-Abs levels correlating with total bilirubin, indicating a potential role in exacerbating liver damage through periportal functions. Conclusions: AGO2-Abs is a robust biomarker for predicting the mortality of patients with HBV-related ACLF.

The Expression Profiles of lncRNAs Are Associated with Neoadjuvant Chemotherapy Resistance in Locally Advanced, Luminal B-Type Breast Cancer.

lncRNAs are noncoding transcripts with tissue and cancer specificity. Particularly, in breast cancer, lncRNAs exhibit subtype-specific expression; they are particularly upregulated in luminal tumors. However, no gene signature-based laboratory tests have been developed for luminal breast cancer identification or the differential diagnosis of luminal tumors, since no luminal A- or B-specific genes have been identified. Particularly, luminal B patients are of clinical interest, since they have the most variable response to neoadjuvant treatment; thus, it is necessary to develop diagnostic and predictive biomarkers for these patients to optimize treatment decision-making and improve treatment quality. In this study, we analyzed the lncRNA expression profiles of breast cancer cell lines and patient tumor samples from RNA-Seq data to identify an lncRNA signature specific for luminal phenotypes. We identified an lncRNA signature consisting of LINC01016, GATA3-AS1, MAPT-IT1, and DSCAM-AS1 that exhibits luminal subtype-specific expression; among these lncRNAs, GATA3-AS1 is associated with the presence of residual disease (Wilcoxon test, p < 0.05), which is related to neoadjuvant chemotherapy resistance in luminal B breast cancer patients. Furthermore, analysis of GATA3-AS1 expression using RNA in situ hybridization (RNA ISH) demonstrated that this lncRNA is detectable in histological slides. Similar to estrogen receptors and Ki67, both commonly detected biomarkers, GATA3-AS1 proves to be a suitable predictive biomarker for clinical application in breast cancer laboratory tests.

Predicting gestational diabetes mellitus risk at 11-13 weeks' gestation: the role of extrachromosomal circular DNA.

BACKGROUND: Gestational diabetes mellitus (GDM) significantly impacts maternal and infant health both immediately and over the long term, yet effective early diagnostic biomarkers are currently lacking. Thus, it is essential to identify early diagnostic biomarkers for GDM risk screening. Extrachromosomal circular DNA (eccDNA), being more stable than linear DNA and involved in disease pathologies, is a viable biomarker candidate for diverse conditions. In this study, eccDNA biomarkers identified for early diagnosis and assessment of GDM risk were explored. METHODS: Using Circle-seq, we identified plasma eccDNA profiles in five pregnant women who later developed GDM and five matched healthy controls at 11-13 weeks of gestation. These profiles were subsequently analyzed through bioinformatics and validated through outward PCR combined with Sanger sequencing. Furthermore, candidate eccDNA was validated by quantitative PCR (qPCR) in a larger cohort of 70 women who developed GDM and 70 normal glucose-tolerant (NGT) subjects. A ROC curve assessed the eccDNA's diagnostic potential for GDM. RESULTS: 2217 eccDNAs were differentially detected between future GDM patients and controls, with 1289 increased and 928 decreased in abundance. KEGG analysis linked eccDNA genes mainly to GDM-related pathways such as Rap1, MAPK, and PI3K-Akt, and Insulin resistance, among others. Validation confirmed a significant decrease in eccDNA PRDM16circle in the plasma of 70 women who developed GDM compared to 70 NGT women, consistent with the eccDNA-seq results. PRDM16circle showed significant diagnostic value in 11-13 weeks of gestation (AUC = 0.941, p < 0.001). CONCLUSIONS: Our study first demonstrats that eccDNAs are aberrantly produced in women who develop GDM, including PRDM16circle, which can predict GDM at an early stage of pregnancy, indicating its potential as a biomarker. TRIAL REGISTRATION: ChiCTR2300075971, http://www.chictr.org.cn . Registered 20 September 2023.

Early circulating tumor DNA changes predict outcomes in head and neck cancer patients under re-radiotherapy.

Local recurrence after radiotherapy is common in locally advanced head and neck cancer (HNC) patients. Re-irradiation can improve local disease control, but disease progression remains frequent. Hence, predictive biomarkers are needed to adapt treatment intensity to the patient's individual risk. We quantified circulating tumor DNA (ctDNA) in sequential plasma samples and correlated ctDNA levels with disease outcome. Ninety four longitudinal plasma samples from 16 locally advanced HNC patients and 57 healthy donors were collected at re-radiotherapy baseline, after 5 and 10 radiation fractions, at irradiation end, and at routine follow-up visits. Plasma DNA was subjected to low coverage whole genome sequencing for copy number variation (CNV) profiling to quantify ctDNA burden. CNV-based ctDNA burden was detected in 8/16 patients and 25/94 plasma samples. Ten additional ctDNA-positive samples were identified by tracking patient-specific CNVs found in earlier sequential plasma samples. ctDNA-positivity after 5 and 10 radiation fractions (both: log-rank, p = .050) as well as at the end of irradiation correlated with short progression-free survival (log-rank, p = .006). Moreover, a pronounced decrease of ctDNA toward re-radiotherapy termination was associated with worse treatment outcome (log-rank, p = .005). Dynamic ctDNA tracking in serial plasma beyond re-radiotherapy reflected treatment response and imminent disease progression. In five patients, molecular progression was detected prior to tumor progression based on clinical imaging. Our findings emphasize that quantifying ctDNA during re-radiotherapy may contribute to disease monitoring and personalization of adjuvant treatment, follow-up intervals, and dose prescription.