AHRR and SFRP2 in primary versus recurrent high-grade serous ovarian carcinoma and their prognostic implication

BACKGROUND

The aim of this study was to analyse transcriptomic differences between primary and recurrent high-grade serous ovarian carcinoma (HGSOC) to identify prognostic biomarkers.

METHODS

We analysed 19 paired primary and recurrent HGSOC samples using targeted RNA sequencing. We selected the best candidates using in silico survival and pathway analysis and validated the biomarkers using immunohistochemistry on a cohort of 44 paired samples, an additional cohort of 504 primary HGSOCs and explored their function.

RESULTS

We identified 233 differential expressed genes. Twenty-three showed a significant prognostic value for PFS and OS in silico. Seven markers (AHRR, COL5A2, FABP4, HMGCS2, ITGA5, SFRP2 and WNT9B) were chosen for validation at the protein level. AHRR expression was higher in primary tumours (p < 0.0001) and correlated with better patient survival (p < 0.05). Stromal SFRP2 expression was higher in recurrent samples (p = 0.009) and protein expression in primary tumours was associated with worse patient survival (p = 0.022). In multivariate analysis, tumour AHRR and SFRP2 remained independent prognostic markers. In vitro studies supported the anti-tumorigenic role of AHRR and the oncogenic function of SFRP2.

CONCLUSIONS

Our results underline the relevance of AHRR and SFRP2 proteins in aryl-hydrocarbon receptor and Wnt-signalling, respectively, and might lead to establishing them as biomarkers in HGSOC.

HER2 expression and genOmic characterization of rESected brain metastases from colorectal cancer: the HEROES study

BACKGROUND

Little is known about prognostic factors of brain metastases (BM) from colorectal cancer (CRC). HER2 amplification/overexpression (HER2+) was previously described; its impact on prognosis remains uncertain.

METHODS

In the translational study HEROES, extensive molecular analysis was performed on primary CRC (prCRC) and their matched resected BM by means of NGS comprehensive genomic profiling and HER2 status as assessed by immunohistochemical/ in situ hybridization. Count of tumour-infiltrating lymphocytes (TILs) was also performed.

PRIMARY OBJECTIVE

to describe the molecular landscape of paired BM/prCRC.

SECONDARY OBJECTIVES

to search for new prognostic biomarkers of outcome after BM resection: intracranial-only Progression-Free Survival (BM-iPFS), Progression-Free Survival (BM-PFS), and Overall Survival (BM-OS).

RESULTS

Out of 22 patients having paired samples of prCRC and BM, HER2+ was found on 4 (18%) BM, 3 (75%) of which also HER2+ in matched prCRC. Lower tumour mutation burden (HR 3.08; 95%CI 1.06-8.93; p = 0.0386) and HER2-negative BM (HER2neg) (HR 7.75;95%CI 1.97-30.40; p = 0.0033) were associated with longer BM-iPFS; HER2neg BM (HR 3.44; 95%CI 1.03-11.53; p = 0.0449) and KRASmut BM (HR 0.31; 95%CI 0.12-0.80; p = 0.0153) conferred longer BM-PFS. Longer BM-OS was found in pts with TILs-enriched (≥1.6/HPF) BM (HR 0.11; 95%CI0.01-0.91; p = 0.0403).

CONCLUSIONS

This study shows HER2+ enrichment in both BM and their prCRC. TILs-enriched BM conferred better BM-OS.

Fluoropyrimidine type, patient age, tumour sidedness and mutation status as determinants of benefit in patients with metastatic colorectal cancer treated with EGFR monoclonal antibodies: individual patient data pooled analysis of randomised trials from the ARCAD database

BACKGROUND

KRAS mutations in metastatic colorectal cancer (mCRC) are used as predictive biomarkers to select therapy with EGFR monoclonal antibodies (mAbs). Other factors may be significant determinants of benefit.

METHODS

Individual patient data from randomised trials with a head-to-head comparison between EGFR mAb versus no EGFR mAb (chemotherapy alone or best supportive care) in mCRC, across all lines of therapy, were pooled. Overall survival (OS) and progression-free survival (PFS) were compared between groups. Treatment effects within the predefined KRAS biomarker subsets were estimated by adjusted hazard ratio (HRadj) and 95% confidence interval (CI). EGFR mAb efficacy was measured within the KRAS wild-type subgroup according to BRAF and NRAS mutation status. In both KRAS wild-type and mutant subgroups, additional factors that could impact EGFR mAb efficacy were explored including the type of chemotherapy, line of therapy, age, sex, tumour sidedness and site of metastasis.

RESULTS

5675 patients from 8 studies were included, all with known mCRC KRAS mutation status. OS (HRadj 0.90, 95% CI 0.84-0.98, p = 0.01) and PFS benefit (HRadj 0.73, 95% CI 0.68-0.79, p < 0.001) from EGFR mAbs was observed in the KRAS wild-type group. PFS benefit was seen in patients treated with fluorouracil (HRadj 0.75, 95% CI 0.68-0.82) but not with capecitabine-containing regimens (HRadj 1.04, 95% CI 0.86-1.26) (pinteraction = 0.002). Sidedness also interacted with EGFR mAb efficacy, with survival benefit restricted to left-sided disease (pinteraction = 0.038). PFS benefits differed according to age, with benefits greater in those under 70 (pinteraction = 0.001). The survival benefit was not demonstrated in those patients with mutations found in the KRAS, NRAS or BRAF genes. The presence of liver metastases interacted with EGFR mAb efficacy in patients with KRAS mutant mCRC (pinteraction = 0.004).

CONCLUSION

The benefit provided by EGFR mAbs in KRAS WT mCRC is associated with left-sided primary tumour location, younger patient age and absence of NRAS or BRAF mutations. Survival benefit is observed with fluorouracil but not capecitabine. Exploratory results support further research in KRAS mutant mCRC without liver metastases.

Acute spinal cord injury serum biomarkers in human and rat: a scoping systematic review

STUDY DESIGN

Scoping systematic review.

OBJECTIVES

To summarize the available experimental clinical and animal studies for the identification of all CSF and serum-derived biochemical markers in human and rat SCI models.

SETTING

Tehran, Iran.

METHODS

In this scoping article, we systematically reviewed the electronic databases of PubMed, Scopus, WOS, and CENTRAL to retrieve current literature assessing the levels of different biomarkers in human and rat SCI models.

RESULTS

A total of 19,589 articles were retrieved and 6897 duplicated titles were removed. The remaining 12,692 studies were screened by their title/abstract and 12,636 were removed. The remaining 56 were considered for full-text assessment, and 11 papers did not meet the criteria, and finally, 45 studies were included. 26 studies were human observational studies comprising 1630 patients, and 19 articles studied SCI models in rats, including 832 rats. Upon reviewing the literature, we encountered a remarkable heterogeneity in terms of selected biomarkers, timing, and method of measurement, studied models, extent, and mechanism of injury as well as outcome assessment measures.

CONCLUSIONS

The specific expression and distribution patterns of biomarkers in relation to spinal cord injury (SCI) phases, and their varied concentrations over time, suggest that cerebrospinal fluid (CSF) and blood biomarkers are effective measures for assessing the severity of SCI.

Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis

BACKGROUND

The field of Artificial Intelligence (AI) holds transformative potential in medicine. However, the lack of universal reporting guidelines poses challenges in ensuring the validity and reproducibility of published research studies in this field.

METHODS

Based on a systematic review of academic publications and reporting standards demanded by both international consortia and regulatory stakeholders as well as leading journals in the fields of medicine and medical informatics, 26 reporting guidelines published between 2009 and 2023 were included in this analysis. Guidelines were stratified by breadth (general or specific to medical fields), underlying consensus quality, and target research phase (preclinical, translational, clinical) and subsequently analyzed regarding the overlap and variations in guideline items.

RESULTS

AI reporting guidelines for medical research vary with respect to the quality of the underlying consensus process, breadth, and target research phase. Some guideline items such as reporting of study design and model performance recur across guidelines, whereas other items are specific to particular fields and research stages.

CONCLUSIONS

Our analysis highlights the importance of reporting guidelines in clinical AI research and underscores the need for common standards that address the identified variations and gaps in current guidelines. Overall, this comprehensive overview could help researchers and public stakeholders reinforce quality standards for increased reliability, reproducibility, clinical validity, and public trust in AI research in healthcare. This could facilitate the safe, effective, and ethical translation of AI methods into clinical applications that will ultimately improve patient outcomes.

Enhancing NSCLC recurrence prediction with PET/CT habitat imaging, ctDNA, and integrative radiogenomics-blood insights

While we recognize the prognostic importance of clinicopathological measures and circulating tumor DNA (ctDNA), the independent contribution of quantitative image markers to prognosis in non-small cell lung cancer (NSCLC) remains underexplored. In our multi-institutional study of 394 NSCLC patients, we utilize pre-treatment computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) to establish a habitat imaging framework for assessing regional heterogeneity within individual tumors. This framework identifies three PET/CT subtypes, which maintain prognostic value after adjusting for clinicopathologic risk factors including tumor volume. Additionally, these subtypes complement ctDNA in predicting disease recurrence. Radiogenomics analysis unveil the molecular underpinnings of these imaging subtypes, highlighting downregulation in interferon alpha and gamma pathways in the high-risk subtype. In summary, our study demonstrates that these habitat imaging subtypes effectively stratify NSCLC patients based on their risk levels for disease recurrence after initial curative surgery or radiotherapy, providing valuable insights for personalized treatment approaches.

Quantitative performance assessment of Ultivue multiplex panels in formalin-fixed, paraffin-embedded human and murine tumor specimens

We present a rigorous validation strategy to evaluate the performance of Ultivue multiplex immunofluorescence panels. We have quantified the accuracy and precision of four different multiplex panels (three human and one mouse) in tumor specimens with varying levels of T cell density. Our results show that Ultivue panels are typically accurate wherein the relative difference in cell proportion between a multiplex image and a 1-plex image is less than 20% for a given biomarker. Ultivue panels exhibited relatively high intra-run precision (CV ≤ 25%) and relatively low inter-run precision (CV >> 25%) which can be remedied by using local intensity thresholding to gate biomarker positivity. We also evaluated the reproducibility of cell-cell distance estimates measured from multiplex images which show high intra- and inter-run precision. We introduce a new metric, multiplex labeling efficiency, which can be used to benchmark the overall fidelity of the multiplex data across multiple batch runs. Taken together our results provide a comprehensive characterization of Ultivue panels and offer practical guidelines for analyzing multiplex images.

Research on the toxicological prognostic significance of age-related genes in endometrial cancer unveiling key factors in patient prognosis

This study investigates the influence of aging-related genes on endometrial cancer, a prominent gynecological malignancy with rising incidence and mortality. By analyzing gene expression differences between cancerous and normal endometrial tissues, 42 aging-related genes were identified as differentially expressed. Utilizing the TCGA-UCEC sample, consensus clustering divided the samples into two molecular subgroups, Aging low and Aging high, based on their expression profiles. These subgroups showed distinct prognoses and survival rates, with the Aging high group associated with DNA repair and cell cycle pathways, and the Aging low group showing suppressed metabolic pathways and increased immune cell infiltration, suggesting a potential for better immunotherapy outcomes. Mutation analysis did not find significant differences in mutation frequencies between the groups, but a high Tumor Mutation Burden (TMB) correlated with better prognosis. A risk score model was also developed, showcasing significant prognostic power. Further analysis of the SIX1 gene revealed its overexpression in cancer cells. Drug sensitivity tests indicated that the low-risk group might respond better to chemotherapy. This research underscores the significance of aging-related genes in endometrial cancer, offering insights into their prognostic value and therapeutic potential, which could lead to personalized treatment approaches and enhanced patient management.

Integration of pathologic characteristics, genetic risk and lifestyle exposure for colorectal cancer survival assessment

The development of an effective survival prediction tool is key for reducing colorectal cancer mortality. Here, we apply a three-stage study to devise a polygenic prognostic score (PPS) for stratifying colorectal cancer overall survival. Leveraging two cohorts of 3703 patients, we first perform a genome-wide survival association analysis to develop eight candidate PPSs. Further using an independent cohort with 470 patients, we identify the 287 variants-derived PPS (i.e., PPS287) achieving an optimal prediction performance [hazard ratio (HR) per SD = 1.99, P = 1.76 × 10-8], accompanied by additional tests in two external cohorts, with HRs per SD of 1.90 (P = 3.21 × 10-14; 543 patients) and 1.80 (P = 1.11 × 10-9; 713 patients). Notably, the detrimental impact of pathologic characteristics and genetic risk could be attenuated by a healthy lifestyle, yielding a 7.62% improvement in the 5-year overall survival rate. Therefore, our findings demonstrate the integrated contribution of pathologic characteristics, germline variants, and lifestyle exposure to the prognosis of colorectal cancer patients.

Novel genetic variants of HLA gene associated with Thai Behcet's disease (BD) patients using next generation sequencing technology

Behçet's disease (BD) manifests as an autoimmune disorder featuring recurrent ulcers and multi-organ involvement, influenced by genetic factors associated with both HLA and non-HLA genes, including TNF-α and ERAP1. The study investigated the susceptible alleles of both Class I and II molecules of the HLA gene in 56 Thai BD patients and 192 healthy controls through next-generation sequencing using a PacBio kit. The study assessed 56 BD patients, primarily females (58.9%), revealing diverse manifestations including ocular (41.1%), vascular (35.7%), skin (55.4%), CNS (5.4%), and GI system (10.7%) involvement. This study found associations between BD and HLA-A*26:01:01 (OR 3.285, 95% CI 1.135-9.504, P-value 0.028), HLA-B*39:01:01 (OR 6.176, 95% CI 1.428-26.712, P-value 0.015), HLA-B*51:01:01 (OR 3.033, 95% CI 1.135-8.103, P-value 0.027), HLA-B*51:01:02 (OR 6.176, 95% CI 1.428-26.712, P-value 0.015), HLA-C*14:02:01 (OR 3.485, 95% CI 1.339-9.065, P-value 0.01), HLA-DRB1*14:54:01 (OR 1.924, 95% CI 1.051-3.522, P-value 0.034), and HLA-DQB1*05:03:01 (OR 3.00, 95% CI 1.323-6.798, P-value 0.008). However, after Bonferroni correction none of these alleles were found to be associated with BD. In haplotype analysis, we found a strong linkage disequilibrium in HLA-B*51:01:01, HLA-C*14:02:01 (P-value 0.0, Pc-value 0.02). Regarding the phenotype, a significant association was found between HLA-DRB1*14:54:01 (OR 11.67, 95% CI 2.86-47.57, P-value 0.001) and BD with ocular involvement, apart from this, no distinct phenotype-HLA association was documented. In summary, our study identifies specific HLA associations in BD. Although limited by a small sample size, we acknowledge the need for further investigation into HLA relationships with CNS, GI, and neurological phenotypes in the Thai population.

Plasma brain-derived tau is an amyloid-associated neurodegeneration biomarker in Alzheimer's disease

Staging amyloid-beta (Aβ) pathophysiology according to the intensity of neurodegeneration could identify individuals at risk for cognitive decline in Alzheimer's disease (AD). In blood, phosphorylated tau (p-tau) associates with Aβ pathophysiology but an AD-type neurodegeneration biomarker has been lacking. In this multicenter study (n = 1076), we show that brain-derived tau (BD-tau) in blood increases according to concomitant Aβ ("A") and neurodegeneration ("N") abnormalities (determined using cerebrospinal fluid biomarkers); We used blood-based A/N biomarkers to profile the participants in this study; individuals with blood-based p-tau+/BD-tau+ profiles had the fastest cognitive decline and atrophy rates, irrespective of the baseline cognitive status. Furthermore, BD-tau showed no or much weaker correlations with age, renal function, other comorbidities/risk factors and self-identified race/ethnicity, compared with other blood biomarkers. Here we show that blood-based BD-tau is a biomarker for identifying Aβ-positive individuals at risk of short-term cognitive decline and atrophy, with implications for clinical trials and implementation of anti-Aβ therapies.

A novel flow cytometry panel to identify prognostic markers for steroid-sensitive forms of idiopathic nephrotic syndrome in childhood

Introduction

The clinical evolution of steroid-sensitive forms of pediatric idiopathic nephrotic syndrome (INS) is highly heterogeneous following the standard treatment with prednisone. To date, no prognostic marker has been identified to predict the severity of the disease course starting from the first episode.

Methods

In this monocentric prospective cohort study we set up a reproducible and standardized flow cytometry panel using two sample tubes (one for B-cell and one for T-cell subsets) to extensively characterized the lymphocyte repertoire of INS pediatric patients. A total of 44 children with INS at disease onset were enrolled, sampled before and 3 months after standard induction therapy with prednisone and followed for 12 months to correctly classify their disease based on relapses. Age-matched controls with non immune-mediated renal diseases or with urological disorders were also enrolled. Demographical, clinical, laboratory and immunosuppressive treatment data were registered.

Results

We found that children with INS at disease onset had significantly higher circulating levels of total CD19+ and specific B-cell subsets (transitional, mature-naïve, plasmablasts/plasmacells, CD19+CD27+, unswitched, switched and atypical memory B cells) and reduced circulating levels of Tregs, when compared to age-matched controls. Prednisone therapy restored most B- and T-cell alterations. When patients were subdivided based on disease relapse, relapsing patients had significantly more transitional, CD19+CD27+ memory and in particular unswitched memory B cells at disease onset, which were predictive of a higher risk of relapse in steroid-sensitive patients by logistic regression analysis, irrespective of age. In accordance, B-cell dysregulations resulted mainly associated with steroid-dependence when patients were stratified in different disease severity forms. Of note, Treg levels were reduced independently from the disease subgroup and were not completely normalized by prednisone treatment.

Conclusion

We have set up a novel, reproducible, disease-specific flow cytometry panel that allows a comprehensive characterization of circulating lymphocytes. We found that, at disease onset, relapsing patients had significantly more transitional, CD19+CD27+ memory and unswitched memory B cells and those who are at higher risk of relapse had increased circulating levels of unswitched memory B cells, independently of age. This approach can allow prediction of clinical evolution, monitoring of immunosuppression and tailored treatment in different forms of INS.

Antenatally Detected Thoracic Lesions: Prognosis, Management and Outcome

BACKGROUND

Foetal thoracic lesions are uncommon, with the incidence of 1 in 15,000 live births. Antenatal monitoring of these lesions is required to prognosticate the parents about the postnatal outcome of the lesions and about the well-being of the baby. Foetal ultrasound and magnetic resonance imaging (MRI) are the modalities to detect these lesions and follow-up during pregnancy and postnatally. Congenital pulmonary adenomatoid malformations (CPAM), congenital diaphragmatic hernia (CDH) and bronchopulmonary sequestrations (BPS) are the commonly detected foetal thoracic lesions. Parameters such as congenital cystic adenomatoid malformation (CCAM) volume ratio (CVR) and lung-to-head ratio (LHR) determine the prognosis of these lesions. With this background, we planned to study the prognosis and outcome of antenatally detected thoracic lesions.

MATERIALS AND METHODS

This was a prospective study carried out for 2 years (January 2017 to December 2018). Pregnant females with foetuses diagnosed to have thoracic lesions on the second- and third-trimester ultrasound and foetal MRI were enrolled for the study. CVR and LHR were noted. Outcomes were analysed in terms of the need of termination of pregnancy, foetal or neonatal demise and need of surgery or conservative management.

RESULTS

Of a total of 521 pregnancies, thoracic lesions were detected in 22 (4.22%) cases. Individually, the incidence of each lesion was: CPAM-10 (45.45%), BPS-5 (22.73%), CDH-5 (22.73%) and congenital higher airway obstruction-2 (9.1%). Chromosomal screening was normal in 100% of cases. Follow-up was done for 2 years. Termination of pregnancy was required in 3 (13.64%) cases, postnatal death occurred in 4 (18.2%) cases, surgery was required in three cases of CDH soon after birth and two cases of extralobar BPS at 2 years of age. 10 (45.45%) cases were managed conservatively, who are doing well at 2-year follow-up.

CONCLUSION

CPAMs, BPSs and CDH are the commonly detected antenatal thoracic lesions. Ultrasonography and MRI help detect and prognosticate the parents about the outcomes of these lesions. CVR and LHR with associated congenital malformations are important prognostic markers for these lesions. There is a need of long-term prospective studies to delineate the natural history of these lesions.

Targeting RCC1 to block the human soft-tissue sarcoma by disrupting nucleo-cytoplasmic trafficking of Skp2

Soft-tissue sarcomas (STS) emerges as formidable challenges in clinics due to the complex genetic heterogeneity, high rates of local recurrence and metastasis. Exploring specific targets and biomarkers would benefit the prognosis and treatment of STS. Here, we identified RCC1, a guanine-nucleotide exchange factor for Ran, as an oncogene and a potential intervention target in STS. Bioinformatics analysis indicated that RCC1 is highly expressed and correlated with poor prognosis in STS. Functional studies showed that RCC1 knockdown significantly inhibited the cell cycle transition, proliferation and migration of STS cells in vitro, and the growth of STS xenografts in mice. Mechanistically, we identified Skp2 as a downstream target of RCC1 in STS. Loss of RCC1 substantially diminished Skp2 abundance by compromising its protein stability, resulting in the upregulation of p27Kip1 and G1/S transition arrest. Specifically, RCC1 might facilitate the nucleo-cytoplasmic trafficking of Skp2 via direct interaction. As a result, the cytoplasmic retention of Skp2 would further protect it from ubiquitination and degradation. Notably, recovery of Skp2 expression largely reversed the phenotypes induced by RCC1 knockdown in STS cells. Collectively, this study unveils a novel RCC1-Skp2-p27Kip1 axis in STS oncogenesis, which holds promise for improving prognosis and treatment of this formidable malignancy.

Higher intraocular pressure is associated with slower axial growth in children with non-pathological high myopia

OBJECTIVES

To investigate the association between intraocular pressure (IOP) and axial elongation rate in highly myopic children from the ZOC-BHVI High Myopia Cohort Study.

METHODS

162 eyes of 81 healthy children (baseline spherical equivalent: -6.25 D to -15.50 D) aged 7-12 years with non-pathological high myopia were studied over five biennial visits. The mean (SD) follow-up duration was 5.2 (3.3) years. A linear mixed-effects model (LMM) was used to assess the association between IOP (at time point t-1) and axial elongation rate (annual rate of change in AL from t-1 to t), controlling for a pre-defined set of covariates including sex, age, central corneal thickness, anterior chamber depth and lens thickness (at t-1). LMM was also used to assess the contemporaneous association between IOP and axial length (AL) at t, controlling for the same set of covariates (at t) as before.

RESULTS

Higher IOP was associated with slower axial growth (β = -0.01, 95% CI -0.02 to -0.005, p = 0.001). There was a positive contemporaneous association between IOP and AL (β = 0.03, 95% CI 0.01-0.05, p = 0.004), but this association became progressively less positive with increasing age, as indicated by a negative interaction effect between IOP and age on AL (β = -0.01, 95% CI -0.01 to -0.003, p = 0.001).

CONCLUSIONS

Higher IOP is associated with slower rather than faster axial growth in children with non-pathological high myopia, an association plausibly confounded by the increased influence of ocular compliance on IOP.

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach

BACKGROUND

Accurate estimation of the long-term risk of recurrence in patients with non-metastatic colorectal cancer (CRC) is crucial for clinical management. Histology-based deep learning is expected to provide more abundant information for risk stratification.

METHODS

We developed and validated a weakly supervised deep-learning model for predicting 5-year relapse-free survival (RFS) to stratify patients with different risks based on histological images from three hospitals of 614 cases with non-metastatic CRC. A deep prognostic factor (DL-RRS) was established to stratify patients into high and low-risk group. The areas under the curve (AUCs) were calculated to evaluate the performances of models.

RESULTS

Our proposed model achieves the AUCs of 0.833 (95% CI: 0.736-0.905) and 0.715 (95% CI: 0.647-0.776) on validation cohort and external test cohort, respectively. The 5-year RFS rate was 45.7% for high DL-RRS patients, and 82.5% for low DL-RRS patients respectively in the external test cohort (HR: 3.89, 95% CI: 2.51-6.03, P < 0.001). Adjuvant chemotherapy was associated with improved RFS in Stage II patients with high DL-RRS (HR: 0.15, 95% CI: 0.06-0.38, P < 0.001).

CONCLUSIONS

DL-RRS has a good predictive performance of 5-year recurrence risk in CRC, and will better serve the clinical decision-making.

Soluble lymphocyte activation gene-3 (sLAG3) and CD4/CD8 ratio dynamics as predictive biomarkers in patients undergoing immune checkpoint blockade for solid malignancies

BACKGROUND

The search for biomarkers to identify suitable candidates for immune checkpoint inhibitor (ICI) therapy remains ongoing. We evaluate how soluble levels of the next generation immune checkpoint Lymphocyte Activation Gene-3 (sLAG-3) and its association with circulating T lymphocyte subsets could pose as a novel biomarker to predict outcome to ICI therapy.

METHODS

Circulating levels of sLAG3 were analyzed using multiplex immunoassay in n = 84 patients undergoing ICI therapy for advanced solid cancer, accompanied by flow cytometry analyses of peripheral blood mononuclear cells (PBMCs).

RESULTS

Uni- and multivariate analysis shows that patients with higher sLAG3 concentrations before ICI therapy had a significantly impaired progression-free (PFS) and overall survival (OS) (HRPFS: 1.005 [95%CI: 1.000-1.009], p = 0.039; HROS: 1.006 [95%CI: 1.001-1.011], p = 0.015). The CD4/CD8 cell ratio and its dynamics during therapy were strong predictors of PFS and OS with patients with a decreasing ratio between baseline and after 1-2 cycles having an improved median OS compared to patients with increasing values (p = 0.012, HR: 3.32). An immunological score combining sLAG3 and the CD4/CD8 ratio showed the highest predictive potential (HROS: 10.3).

CONCLUSION

Pending prospective validation, sLAG3 and correlating circulating T-cell subsets can be used as a non-invasive predictive marker to predict outcome to ICI therapy to help identifying ideal ICI candidates in the future.

A novel long non-coding RNA SLNCR1 promotes proliferation, migration, and invasion of melanoma via transcriptionally regulating SOX5

Steroid receptor RNA activator (SRA)-like non-coding RNA (SLNCR1) has been implicated in various tumorigenic processes, but the precise regulatory role in melanoma progression remains uncertain. We performed a comprehensive analysis to investigate the prognostic value of SLNCR1 expression in patients with melanoma by TCGA database and melanoma tissue samples via the Kaplan-Meier method. Subsequently, we conducted qRT-PCR and Fluorescence in Situ Hybridization (FISH) assays to identify SLNCR1 expression levels and localization in tissues and cells, respectively. Loss-of-function assays utilizing shRNAs vectors were used to investigate the potential impact of SLNCR1. Our data showed that SLNCR1 is significantly up-regulated in human malignant melanoma tissues and cell lines and functions as an oncogene. Silencing of SLNCR1 suppressed melanoma cell proliferation, migration, invasion, and inhibited tumorigenesis in a mouse xenograft model. Additionally, we employed bioinformatic predictive analysis, combined with dual-luciferase reporter analysis and functional rescue assays, to elucidate the mechanistic target of the SLNCR1/SOX5 axis in melanoma. Mechanistically, we discovered that SLNCR1 promotes EMT of human melanoma by targeting SOX5, as downregulation of SLNCR1 expression leads to a decrease in SOX5 protein levels and inhibits melanoma tumorigenesis. Our research offers promising insights for more precise diagnosis and treatment of human melanoma.

Fulvestrant and everolimus efficacy after CDK4/6 inhibitor: a prospective study with circulating tumor DNA analysis

In a prospective study (NCT02866149), we assessed the efficacy of fulvestrant and everolimus in CDK4/6i pre-treated mBC patients and circulating tumor DNA (ctDNA) changes throughout therapy. Patients treated with fulvestrant and everolimus had their ctDNA assessed at baseline, after 3-5 weeks and at disease progression. Somatic mutations were identified in archived tumor tissues by targeted NGS and tracked in cell-free DNA by droplet digital PCR. ctDNA detection was then associated with clinicopathological characteristics and patients' progression-free survival (PFS), overall survival (OS) and best overall response (BOR). In the 57 included patients, median PFS and OS were 6.8 (95%CI [5.03-11.5]) and 38.2 (95%CI [30.0-not reached]) months, respectively. In 47 response-evaluable patients, BOR was a partial response or stable disease in 15 (31.9%) and 11 (23.4%) patients, respectively. Among patients with trackable somatic mutation and available plasma sample, N = 33/47 (70.2%) and N = 19/36 (52.8%) had ctDNA detected at baseline and at 3 weeks, respectively. ctDNA detection at baseline and PIK3CA mutation had an adverse prognostic impact on PFS and OS in multivariate analysis. This prospective cohort study documents the efficacy of fulvestrant and everolimus in CDK4/6i-pretreated ER + /HER2- mBC and highlights the clinical validity of early ctDNA changes as pharmacodynamic biomarker.

Genotype-phenotype correlation in PRKN-associated Parkinson's disease

Bi-allelic pathogenic variants in PRKN are the most common cause of autosomal recessive Parkinson's disease (PD). 647 patients with PRKN-PD were included in this international study. The pathogenic variants present were characterised and investigated for their effect on phenotype. Clinical features and progression of PRKN-PD was also assessed. Among 133 variants in index cases (n = 582), there were 58 (43.6%) structural variants, 34 (25.6%) missense, 20 (15%) frameshift, 10 splice site (7.5%%), 9 (6.8%) nonsense and 2 (1.5%) indels. The most frequent variant overall was an exon 3 deletion (n = 145, 12.3%), followed by the p.R275W substitution (n = 117, 10%). Exon3, RING0 protein domain and the ubiquitin-like protein domain were mutational hotspots with 31%, 35.4% and 31.7% of index cases presenting mutations in these regions respectively. The presence of a frameshift or structural variant was associated with a 3.4 ± 1.6 years or a 4.7 ± 1.6 years earlier age at onset of PRKN-PD respectively (p < 0.05). Furthermore, variants located in the N-terminus of the protein, a region enriched with frameshift variants, were associated with an earlier age at onset. The phenotype of PRKN-PD was characterised by slow motor progression, preserved cognition, an excellent motor response to levodopa therapy and later development of motor complications compared to early-onset PD. Non-motor symptoms were however common in PRKN-PD. Our findings on the relationship between the type of variant in PRKN and the phenotype of the disease may have implications for both genetic counselling and the design of precision clinical trials.

Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer

Operable triple-negative breast cancer (TNBC) has a higher risk of recurrence and death compared to other subtypes. Tumor size and nodal status are the primary clinical factors used to guide systemic treatment, while biomarkers of proliferation have not demonstrated value. Recent studies suggest that subsets of TNBC have a favorable prognosis, even without systemic therapy. We evaluated the association of fully automated mitotic spindle hotspot (AMSH) counts with recurrence-free (RFS) and overall survival (OS) in two separate cohorts of patients with early-stage TNBC who did not receive systemic therapy. AMSH counts were obtained from areas with the highest mitotic density in digitized whole slide images processed with a convolutional neural network trained to detect mitoses. In 140 patients from the Mayo Clinic TNBC cohort, AMSH counts were significantly associated with RFS and OS in a multivariable model controlling for nodal status, tumor size, and tumor-infiltrating lymphocytes (TILs) (p < 0.0001). For every 10-point increase in AMSH counts, there was a 16% increase in the risk of an RFS event (HR 1.16, 95% CI 1.08-1.25), and a 7% increase in the risk of death (HR 1.07, 95% CI 1.00-1.14). We corroborated these findings in a separate cohort of systemically untreated TNBC patients from Radboud UMC in the Netherlands. Our findings suggest that AMSH counts offer valuable prognostic information in patients with early-stage TNBC who did not receive systemic therapy, independent of tumor size, nodal status, and TILs. If further validated, AMSH counts could help inform future systemic therapy de-escalation strategies.

ELAVL2 loss promotes aggressive mesenchymal transition in glioblastoma

Glioblastoma (GBM), the most lethal primary brain cancer, exhibits intratumoral heterogeneity and molecular plasticity, posing challenges for effective treatment. Despite this, the regulatory mechanisms underlying such plasticity, particularly mesenchymal (MES) transition, remain poorly understood. In this study, we elucidate the role of the RNA-binding protein ELAVL2 in regulating aggressive MES transformation in GBM. We found that ELAVL2 is most frequently deleted in GBM compared to other cancers and associated with distinct clinical and molecular features. Transcriptomic analysis revealed that ELAVL2-mediated alterations correspond to specific GBM subtype signatures. Notably, ELAVL2 expression negatively correlated with epithelial-to-mesenchymal transition (EMT)-related genes, and its loss promoted MES process and chemo-resistance in GBM cells, whereas ELAVL2 overexpression exerted the opposite effect. Further investigation via tissue microarray analysis demonstrated that high ELAVL2 protein expression confers a favorable survival outcome in GBM patients. Mechanistically, ELAVL2 was shown to directly bind to the transcripts of EMT-inhibitory molecules, SH3GL3 and DNM3, modulating their mRNA stability, potentially through an m6A-dependent mechanism. In summary, our findings identify ELAVL2 as a critical tumor suppressor and mRNA stabilizer that regulates MES transition in GBM, underscoring its role in transcriptomic plasticity and glioma progression.

A multiparameter liquid biopsy approach allows to track melanoma dynamics and identify early treatment resistance

Melanoma heterogeneity is a hurdle in metastatic disease management. Although the advent of targeted therapy has significantly improved patient outcomes, the occurrence of resistance makes monitoring of the tumor genetic landscape mandatory. Liquid biopsy could represent an important biomarker for the real-time tracing of disease evolution. Thus, we aimed to correlate liquid biopsy dynamics with treatment response and progression by devising a multiplatform approach applied to longitudinal melanoma patient monitoring. We conceived an approach that exploits Next Generation Sequencing (NGS) and droplet digital PCR, as well as the FDA-cleared platform CellSearch, to analyze circulating tumor DNA (ctDNA) trend and circulating melanoma cell (CMC) count, together with their customized genetic and copy number variation analysis. The approach was applied to 17 stage IV melanoma patients treated with BRAF/MEK inhibitors, followed for up to 28 months. BRAF mutations were detected in the plasma of 82% of patients. Single nucleotide variants known or suspected to confer resistance were identified in 70% of patients. Moreover, the amount of ctDNA, both at baseline and during response, correlated with the type and duration of the response itself, and the CMC count was confirmed to be a prognostic biomarker. This work provides proof of principle of the power of this approach and paves the way for a validation study aimed at evaluating early ctDNA-guided treatment decisions in stage IV melanoma. The NGS-based molecular profile complemented the analysis of ctDNA trend and, together with CMC analysis, revealed to be useful in capturing tumor evolution.

Deep learning on tertiary lymphoid structures in hematoxylin-eosin predicts cancer prognosis and immunotherapy response

Tertiary lymphoid structures (TLSs) have been associated with favorable immunotherapy responses and prognosis in various cancers. Despite their significance, their quantification using multiplex immunohistochemistry (mIHC) staining of T and B lymphocytes remains labor-intensive, limiting its clinical utility. To address this challenge, we curated a dataset from matched mIHC and H&E whole-slide images (WSIs) and developed a deep learning model for automated segmentation of TLSs. The model achieved Dice coefficients of 0.91 on the internal test set and 0.866 on the external validation set, along with intersection over union (IoU) scores of 0.819 and 0.787, respectively. The TLS ratio, defined as the segmented TLS area over the total tissue area, correlated with B lymphocyte levels and the expression of CXCL13, a chemokine associated with TLS formation, in 6140 patients spanning 16 tumor types from The Cancer Genome Atlas (TCGA). The prognostic models for overall survival indicated that the inclusion of the TLS ratio with TNM staging significantly enhanced the models' discriminative ability, outperforming the traditional models that solely incorporated TNM staging, in 10 out of 15 TCGA tumor types. Furthermore, when applied to biopsied treatment-naïve tumor samples, higher TLS ratios predicted a positive immunotherapy response across multiple cohorts, including specific therapies for esophageal squamous cell carcinoma, non-small cell lung cancer, and stomach adenocarcinoma. In conclusion, our deep learning-based approach offers an automated and reproducible method for TLS segmentation and quantification, highlighting its potential in predicting immunotherapy response and informing cancer prognosis.

Plasma neutrophil gelatinase-associated lipocalin independently predicts dialysis need and mortality in critical COVID-19

Neutrophil gelatinase-associated lipocalin (NGAL) is a novel kidney injury and inflammation biomarker. We investigated whether NGAL could be used to predict continuous renal replacement therapy (CRRT) and mortality in critical coronavirus disease 2019 (COVID-19). This prospective multicenter cohort study included adult COVID-19 patients in six intensive care units (ICUs) in Sweden between May 11, 2020 and May 10, 2021. Blood was sampled at admission, days two and seven in the ICU. The samples were batch analyzed for NGAL, creatinine, and cystatin c after the end of the study period. Initiation of CRRT and 90-day survival were used as dependent variables in regression models. Of 498 included patients, 494 were analyzed regarding CRRT and 399 were analyzed regarding survival. Seventy patients received CRRT and 154 patients did not survive past 90 days. NGAL, in combination with creatinine and cystatin c, predicted the subsequent initiation of CRRT with an area under the curve (AUC) of 0.95. For mortality, NGAL, in combination with age and sex, had an AUC of 0.83. In conclusion, NGAL is a valuable biomarker for predicting subsequent initiation of CRRT and 90-day mortality in critical COVID-19. NGAL should be considered when developing future clinical scoring systems.

Unraveling the role of the circadian clock genes in cervical squamous cell carcinoma and endocervical adenocarcinoma: A prognostic indicator for prognostic, immunotherapy response, and chemotherapy sensitivity

Background: Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) account for a significant proportion of gynecological malignancies and represent a major global health concern. Globally, CESC is ranked as the fourth most common cancer among women. Conventional treatment of this disease has a less favorable prognosis for most patients. However, the discovery of early molecular biomarkers is therefore important for the diagnosis of CESC, as well as for slowing down their progression process. Methods: To identify differentially expressed genes strongly associated with prognosis, univariate Cox proportional hazard analysis and least absolute shrinkage and selection operator (LASSO) regression analysis were used. Using multiple Cox proportional hazard regression, a multifactorial model for prognostic risk assessment was then created. Results: The expression of biological clock-related genes, which varied considerably among distinct subtypes and were associated with significantly diverse prognoses, was used to categorize CESC patients. These findings demonstrate how the nomogram developed based on the 7-CRGs signature may assist physicians in creating more precise, accurate, and successful treatment plans that can aid CESC patients at 1, 3, and 5 years. Conclusions: By using machine learning techniques, we thoroughly investigated the impact of CRGs on the prognosis of CESC patients in this study. By creating a unique nomogram, we were able to accurately predict patient prognosis. At the same time, we showed new perspectives on the development of CESC and its treatment by analyzing the associations of the prognostic model with immunity, enrichment pathways, chemotherapy sensitivity, and so on. This research provides a new direction for clinical treatment.

Physical activity and sleep changes among children during the COVID-19 pandemic

Daily routines, including in-person school and extracurricular activities, are important for maintaining healthy physical activity and sleep habits in children. The COVID-19 pandemic significantly disrupted daily routines as in-person school and activities closed to prevent spread of SARS-CoV-2. We aimed to examine and assess differences in objectively measured physical activity levels and sleep patterns from wearable sensors in children with obesity before, during, and after a period of school and extracurricular activity closures associated with the COVID-19 pandemic. We compared average step count and sleep patterns (using the Mann-Whitney U Test) before and during the pandemic-associated school closures by using data from activity tracker wristbands (Garmin VivoFit 3). Data were collected from 94 children (aged 5-17) with obesity, who were enrolled in a randomized controlled trial testing a community-based lifestyle intervention for a duration of 12-months. During the period that in-person school and extracurricular activities were closed due to the COVID-19 pandemic, children with obesity experienced objectively-measured decreases in physical activity, and sleep duration. From March 15, 2020 to March 31, 2021, corresponding with local school closures, average daily step count decreased by 1655 steps. Sleep onset and wake time were delayed by about an hour and 45 min, respectively, while sleep duration decreased by over 12 min as compared with the pre-closure period. Step counts increased with the resumption of in-person activities. These findings provide objective evidence for parents, clinicians, and public health professionals on the importance of in-person daily activities and routines on health behaviors, particularly for children with pre-existing obesity. Trial Registration: Clinical trial registration: NCT03339440.

Effect of radiotherapy on head and neck cancer tissues in patients receiving radiotherapy: a bioinformatics analysis-based study

Radiotherapy is pivotal in treating head and neck cancers including nasopharyngeal, tongue, hypopharyngeal, larynx, maxillary sinus, parotid gland, and oral cancers. It holds the potential for curative effects and finds application in conjunction with chemotherapy, either as a radical method to preserve organ function or as an adjuvant postoperative treatment. We used bioinformatics analysis to investigate the effects of radiotherapy on head and neck cancer tissues in patients who had received radiotherapy. In this study, the expression and mutation profiles of The Cancer Genome Atlas-Head-Neck Squamous Cell Carcinoma were downloaded from the UCSC-Xena database, categorizing patients into two groups-those receiving radiotherapy and those not receiving radiotherapy. Subsequently, differential expression analysis and gene set enrichment analysis (GSEA) were performed. Following this, single-sample GSEA (ssGSEA) scores related to glucose and lipid metabolism were compared between the two groups. Additionally, immune cell infiltration analysis and single-cell verification were performed. Finally, the mutation profiles of the two groups were compared. The analyses revealed that patients receiving radiotherapy exhibited prolonged survival, enhanced apoptosis in head and neck cancer tissue, and diminished keratinocyte proliferation and migration. A comparison of ssGSEA scores related to glucose and lipid metabolism between the two groups indicated a reduction in glycolysis, tricarboxylic acid cycle activity, and fat synthesis in tissues treated with radiotherapy, suggesting that radiotherapy can effectively inhibit tumour cell energy metabolism. Analyses of immune cell infiltration and single-cell verification suggested decreased infiltration of immune cells post-radiotherapy in head and neck cancer tissues. A comparison of mutation profiles revealed a higher frequency of TP53, TTN, and CDKN2A mutations in patients receiving radiotherapy for head and neck cancer. In conclusion, the bioinformatics analyses delved into the effect of radiotherapy on patients with head and neck carcinoma. This study provides a theoretical framework elucidating the molecular mechanisms underlying radiotherapy's efficacy in treating head and neck cancer and presents scientific recommendations for drug therapy following radiotherapy.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aβ42/Aβ40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers

BACKGROUND

Heavy smokers are at increased risk for cardiovascular disease and may benefit from individualized risk quantification using routine lung cancer screening chest computed tomography. We investigated the prognostic value of deep learning-based automated epicardial adipose tissue quantification and compared it to established cardiovascular risk factors and coronary artery calcium.

METHODS

We investigated the prognostic value of automated epicardial adipose tissue quantification in heavy smokers enrolled in the National Lung Screening Trial and followed for 12.3 (11.9-12.8) years. The epicardial adipose tissue was segmented and quantified on non-ECG-synchronized, non-contrast low-dose chest computed tomography scans using a validated deep-learning algorithm. Multivariable survival regression analyses were then utilized to determine the associations of epicardial adipose tissue volume and density with all-cause and cardiovascular mortality (myocardial infarction and stroke).

RESULTS

Here we show in 24,090 adult heavy smokers (59% men; 61 ± 5 years) that epicardial adipose tissue volume and density are independently associated with all-cause (adjusted hazard ratios: 1.10 and 1.38; P < 0.001) and cardiovascular mortality (adjusted hazard ratios: 1.14 and 1.78; P < 0.001) beyond demographics, clinical risk factors, body habitus, level of education, and coronary artery calcium score.

CONCLUSIONS

Our findings suggest that automated assessment of epicardial adipose tissue from low-dose lung cancer screening images offers prognostic value in heavy smokers, with potential implications for cardiovascular risk stratification in this high-risk population.

A platform-independent AI tumor lineage and site (ATLAS) classifier

Histopathologic diagnosis and classification of cancer plays a critical role in guiding treatment. Advances in next-generation sequencing have ushered in new complementary molecular frameworks. However, existing approaches do not independently assess both site-of-origin (e.g. prostate) and lineage (e.g. adenocarcinoma) and have minimal validation in metastatic disease, where classification is more difficult. Utilizing gradient-boosted machine learning, we developed ATLAS, a pair of separate AI Tumor Lineage and Site-of-origin models from RNA expression data on 8249 tumor samples. We assessed performance independently in 10,376 total tumor samples, including 1490 metastatic samples, achieving an accuracy of 91.4% for cancer site-of-origin and 97.1% for cancer lineage. High confidence predictions (encompassing the majority of cases) were accurate 98-99% of the time in both localized and remarkably even in metastatic samples. We also identified emergent properties of our lineage scores for tumor types on which the model was never trained (zero-shot learning). Adenocarcinoma/sarcoma lineage scores differentiated epithelioid from biphasic/sarcomatoid mesothelioma. Also, predicted lineage de-differentiation identified neuroendocrine/small cell tumors and was associated with poor outcomes across tumor types. Our platform-independent single-sample approach can be easily translated to existing RNA-seq platforms. ATLAS can complement and guide traditional histopathologic assessment in challenging situations and tumors of unknown primary.

Development and validation of prognostic machine learning models for short- and long-term mortality among acutely admitted patients based on blood tests

Several scores predicting mortality at the emergency department have been developed. However, all with shortcomings either simple and applicable in a clinical setting, with poor performance, or advanced, with high performance, but clinically difficult to implement. This study aimed to explore if machine learning algorithms could predict all-cause short- and long-term mortality based on the routine blood test collected at admission.

METHODS

We analyzed data from a retrospective cohort study, including patients > 18 years admitted to the Emergency Department (ED) of Copenhagen University Hospital Hvidovre, Denmark between November 2013 and March 2017. The primary outcomes were 3-, 10-, 30-, and 365-day mortality after admission. PyCaret, an automated machine learning library, was used to evaluate the predictive performance of fifteen machine learning algorithms using the area under the receiver operating characteristic curve (AUC).

RESULTS

Data from 48,841 admissions were analyzed, of these 34,190 (70%) were randomly divided into training data, and 14,651 (30%) were in test data. Eight machine learning algorithms achieved very good to excellent results of AUC on test data in a of range 0.85-0.93. In prediction of short-term mortality, lactate dehydrogenase (LDH), leukocyte counts and differentials, Blood urea nitrogen (BUN) and mean corpuscular hemoglobin concentration (MCHC) were the best predictors, whereas prediction of long-term mortality was favored by age, LDH, soluble urokinase plasminogen activator receptor (suPAR), albumin, and blood urea nitrogen (BUN).

CONCLUSION

The findings suggest that measures of biomarkers taken from one blood sample during admission to the ED can identify patients at high risk of short-and long-term mortality following emergency admissions.

SLC26A9 promotes colorectal tumorigenesis by modulating Wnt/β-catenin signaling

Solute carrier family 26 member 9 (SLC26A9) is a member of the Slc26a family of multifunctional anion transporters that functions as a Cl- channel in parietal cells during acid secretion. We explored the role of SLC26A9 in colorectal cancer (CRC) and its related mechanisms through clinical samples from CRC patients, CRC cell lines and mouse models. We observed that SLC26A9 was expressed at low levels in the cytoplasm of adjacent tissues, polyps and adenomas but was significantly increased in colorectal adenocarcinoma. Moreover, increased levels of SLC26A9 were associated with a high risk of disease and poor prognosis. In addition, downregulation of SLC26A9 in CRC cells induced cell cycle arrest and apoptosis but inhibited cell proliferation and xenograft tumor growth both in vitro and in vivo. Mechanistic analysis revealed that SLC26A9 was colocalized with β-catenin in the nucleus of CRC cells. The translocation of these two proteins from the cytoplasm to the nucleus reflected the activation of Wnt/β-catenin signaling, and promoted the transcription of downstream target proteins, including CyclinD1, c-Myc and Snail, but inhibited the expression of cytochrome C (Cyt-c), cleaved Caspase9, cleaved Caspase3 and apoptosis-inducing factor (AIF). CRC is accompanied by alteration of epithelial mesenchymal transition (EMT) markers. Meanwhile, further studies showed that in SW48 cells, overexpressing SLC26A9 was cocultured with the β-catenin inhibitor XAV-939, β-catenin was downregulated, and EMT was reversed. Our study demonstrated SLC26A9 may be responsible for alterations in the proliferative ability and aggressive potential of CRC by regulating the Wnt/β-catenin signaling pathway.

MicroRNA expression profiling of urine exosomes in children with congenital cytomegalovirus infection

Congenital cytomegalovirus (cCMV) infection can damage the central nervous system in infants; however, its prognosis cannot be predicted from clinical evaluations at the time of birth. Urinary exosomes can be used to analyze neuronal damage in neuronal diseases. To investigate the extent of neuronal damage in patients with cCMV, exosomal miRNA expression in the urine was investigated in cCMV-infected infants and controls. Microarray analysis of miRNA was performed in a cohort of 30 infants, including 11 symptomatic cCMV (ScCMV), 7 asymptomatic cCMV (AScCMV), and one late-onset ScCMV cases, and 11 healthy controls (HC). Hierarchical clustering analysis revealed the distinct expression profile of ScCMV. The patient with late-onset ScCMV was grouped into the ScCMV cluster. Pathway enrichment analysis of the target mRNAs differed significantly between the ScCMV and HC groups; this analysis also revealed that pathways related to brain development were linked to upregulated pathways. Six miRNAs that significantly different between groups (ScCMV vs. HC and ScCMV vs. AScCMV) were selected for digital PCR in another cohort for further validation. Although these six miRNAs seemed insufficient for predicting ScCMV, expression profiles of urine exosomal miRNAs can reveal neurological damage in patients with ScCMV compared to those with AcCMV or healthy infants.

Baseline ctDNA gene alterations as a biomarker of survival after panitumumab and chemotherapy in metastatic colorectal cancer

Certain genetic alterations and right-sided primary tumor location are associated with resistance to anti-epidermal growth factor (EGFR) treatment in metastatic colorectal cancer (mCRC). The phase 3 PARADIGM trial (n = 802) demonstrated longer overall survival with first-line anti-EGFR (panitumumab) versus antivascular endothelial growth factor (bevacizumab) plus modified FOLFOX6 in patients with RAS wild-type mCRC with left-sided primary tumors. This prespecified exploratory biomarker analysis of PARADIGM (n = 733) evaluated the association between circulating tumor DNA (ctDNA) gene alterations and efficacy outcomes, focusing on a broad panel of gene alterations associated with resistance to EGFR inhibition, including KRAS, NRAS, PTEN and extracellular domain EGFR mutations, HER2 and MET amplifications, and ALK, RET and NTRK1 fusions. Overall survival was prolonged with panitumumab plus modified FOLFOX6 versus bevacizumab plus modified FOLFOX6 in patients with ctDNA that lacked gene alterations in the panel (that is, negative hyperselected; median in the overall population: 40.7 versus 34.4 months; hazard ratio, 0.76; 95% confidence interval, 0.62-0.92) but was similar or inferior with panitumumab in patients with ctDNA that contained any gene alteration in the panel (19.2 versus 22.2 months; hazard ratio, 1.13; 95% confidence interval, 0.83-1.53), regardless of tumor sidedness. Negative hyperselection using ctDNA may guide optimal treatment selection in patients with mCRC. ClinicalTrials.gov registrations: NCT02394834 and NCT02394795 .

Digital RNA sequencing using unique molecular identifiers enables ultrasensitive RNA mutation analysis

Mutation analysis is typically performed at the DNA level since most technical approaches are developed for DNA analysis. However, some applications, like transcriptional mutagenesis, RNA editing and gene expression analysis, require RNA analysis. Here, we combine reverse transcription and digital DNA sequencing to enable low error digital RNA sequencing. We evaluate yield, reproducibility, dynamic range and error correction rate for seven different reverse transcription conditions using multiplexed assays. The yield, reproducibility and error rate vary substantially between the specific conditions, where the yield differs 9.9-fold between the best and worst performing condition. Next, we show that error rates similar to DNA sequencing can be achieved for RNA using appropriate reverse transcription conditions, enabling detection of mutant allele frequencies <0.1% at RNA level. We also detect mutations at both DNA and RNA levels in tumor tissue using a breast cancer panel. Finally, we demonstrate that digital RNA sequencing can be applied to liquid biopsies, analyzing cell-free gene transcripts. In conclusion, we demonstrate that digital RNA sequencing is suitable for ultrasensitive RNA mutation analysis, enabling several basic research and clinical applications.

Dutch Pharmacogenetics Working Group (DPWG) guideline for the gene-drug interaction between CYP2D6, CYP3A4 and CYP1A2 and antipsychotics

The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.

Relevance of Comet Assay and Phosphorylated-Hsp90α in Cancer Patients' Peripheral Blood Leukocytes as Tools to Assess Cisplatin-based Chemotherapy Clinical Response and Disease Outcome

Cisplatin (cPt) is a commonly used treatment for solid tumors. The main target of its cytotoxicity is the DNA molecule, which makes the DNA damage response (DDR) crucial for cPt-based chemotherapy. Therefore, it is essential to identify biomarkers that can accurately predict the individual clinical response and prognosis. Our goal was to assess the usefulness of alkaline comet assay and immunocytochemical staining of phosphorylated Hsp90α (p-Hsp90α), γH2AX, and 53BP1 as predictive/prognostic markers. Pre-chemotherapy peripheral blood leukocytes were exposed to cPt in vitro and collected at 0, 24 (T24), and 48 (T48) hr post-drug removal. Healthy subjects were also included. Baseline DNA damage was elevated in cancer patients (variability between individuals was observed). After cPt, patients showed increased γH2AX foci/nucleus (T24 and T48). Both in healthy persons and patients, the nuclear p-Hsp90α and N/C (nuclear/cytoplasmic) ratio augmented (T24), decreasing at T48. Favorable clinical response was associated with high DNA damage and p-Hsp90α N/C ratio following cPt. For the first time, p-Hsp90α significance as a predictive marker is highlighted. Post-cPt-DNA damage was associated with longer disease-free survival and overall survival. Our findings indicate that comet assay and p-Hsp90α (a marker of DDR) would be promising prognostic/predictive tools in cP-treated cancer patients.

Dihydropyrimidine dehydrogenase gene variants for predicting grade 4-5 fluoropyrimidine-induced toxicity: FUSAFE individual patient data meta-analysis

BACKGROUND

Dihydropyrimidine dehydrogenase (DPD) deficiency is the main known cause of life-threatening fluoropyrimidine (FP)-induced toxicities. We conducted a meta-analysis on individual patient data to assess the contribution of deleterious DPYD variants *2A/D949V/*13/HapB3 (recommended by EMA) and clinical factors, for predicting G4-5 toxicity.

METHODS

Study eligibility criteria included recruitment of Caucasian patients without DPD-based FP-dose adjustment. Main endpoint was 12-week haematological or digestive G4-5 toxicity. The value of DPYD variants *2A/p.D949V/*13 merged, HapB3, and MIR27A rs895819 was evaluated using multivariable logistic models (AUC).

RESULTS

Among 25 eligible studies, complete clinical variables and primary endpoint were available in 15 studies (8733 patients). Twelve-week G4-5 toxicity prevalence was 7.3% (641 events). The clinical model included age, sex, body mass index, schedule of FP-administration, concomitant anticancer drugs. Adding *2A/p.D949V/*13 variants (at least one allele, prevalence 2.2%, OR 9.5 [95%CI 6.7-13.5]) significantly improved the model (p < 0.0001). The addition of HapB3 (prevalence 4.0%, 98.6% heterozygous), in spite of significant association with toxicity (OR 1.8 [95%CI 1.2-2.7]), did not improve the model. MIR27A rs895819 was not associated with toxicity, irrespective of DPYD variants.

CONCLUSIONS

FUSAFE meta-analysis highlights the major relevance of DPYD *2A/p.D949V/*13 combined with clinical variables to identify patients at risk of very severe FP-related toxicity.

Associations between lifestyle, health, and clinical characteristics and circulating oxysterols and cholesterol precursors in women diagnosed with breast cancer: a cross-sectional study

Despite increasing evidence that cholesterol precursors and oxysterols, oxidized cholesterol metabolites, play a role in numerous pathological processes and diseases including breast cancer, little is known about correlates of these sterols in women with breast cancer. In this study, 2282 women with breast cancer and blood draw post diagnosis were included and cross-sectional associations between circulating levels of 15 sterols/oxysterols and (a) lifestyle, anthropometric, reproductive characteristics, (b) comorbidities and medication use, and (c) breast cancer tumor and treatment characteristics were calculated using generalized linear models. Obesity was strongly associated with circulating levels of 7-dehydrocholesterol (DC) (body mass index ≥ 30 vs. 18.5-24.9 kg/m2: 51.7% difference) and 7-ketocholesterol (KC) (40.0% difference). After adjustment for BMI, comorbidities such as cardiovascular disease were associated with higher levels of 7-DC (26.1% difference) and lower levels of desmosterol (- 16.4% difference). Breast cancer tumor characteristics including hormone receptor status, tumor stage, and endocrine therapy were associated with lanosterol, 24-DHLan, 7b-HC, and THC (e.g., THC; tumor stage IIIa vs. I: 36.9% difference). Weaker associations were observed for lifestyle characteristics and for any of the other oxysterols. The findings of this study suggest that cholesterol precursors are strongly associated with metabolic factors, while oxysterols are associated with breast cancer tumor characteristics, warranting further investigation into the role of cholesterol precursors and oxysterols in women with breast cancer and other populations.

A Phase II trial of alternating osimertinib and gefitinib therapy in advanced EGFR-T790M positive non-small cell lung cancer: OSCILLATE

In this phase II, single arm trial (ACTRN12617000720314), we investigate if alternating osimertinib and gefitinib would delay the development of resistance to osimertinib in advanced, non-small cell lung cancer (NSCLC) with the epidermal growth factor receptor (EGFR) T790M mutation (n = 47) by modulating selective pressure on resistant clones. The primary endpoint is progression free-survival (PFS) rate at 12 months, and secondary endpoints include: feasibility of alternating therapy, overall response rate (ORR), overall survival (OS), and safety. The 12-month PFS rate is 38% (95% CI 27.5-55), not meeting the pre-specified primary endpoint. Serial circulating tumor DNA (ctDNA) analysis reveals decrease and clearance of the original activating EGFR and EGFR-T790M mutations which are prognostic of clinical outcomes. In 73% of participants, loss of T790M ctDNA is observed at progression and no participants have evidence of the EGFR C797S resistance mutation following the alternating regimen. These findings highlight the challenges of treatment strategies designed to modulate clonal evolution and the clinical importance of resistance mechanisms beyond suppression of selected genetic mutations in driving therapeutic escape to highly potent targeted therapies.

Rare disease research workflow using multilayer networks elucidates the molecular determinants of severity in Congenital Myasthenic Syndromes

Exploring the molecular basis of disease severity in rare disease scenarios is a challenging task provided the limitations on data availability. Causative genes have been described for Congenital Myasthenic Syndromes (CMS), a group of diverse minority neuromuscular junction (NMJ) disorders; yet a molecular explanation for the phenotypic severity differences remains unclear. Here, we present a workflow to explore the functional relationships between CMS causal genes and altered genes from each patient, based on multilayer network community detection analysis of complementary biomedical information provided by relevant data sources, namely protein-protein interactions, pathways and metabolomics. Our results show that CMS severity can be ascribed to the personalized impairment of extracellular matrix components and postsynaptic modulators of acetylcholine receptor (AChR) clustering. This work showcases how coupling multilayer network analysis with personalized -omics information provides molecular explanations to the varying severity of rare diseases; paving the way for sorting out similar cases in other rare diseases.

Prediction of plasma ctDNA fraction and prognostic implications of liquid biopsy in advanced prostate cancer

No consensus strategies exist for prognosticating metastatic castration-resistant prostate cancer (mCRPC). Circulating tumor DNA fraction (ctDNA%) is increasingly reported by commercial and laboratory tests but its utility for risk stratification is unclear. Here, we intersect ctDNA%, treatment outcomes, and clinical characteristics across 738 plasma samples from 491 male mCRPC patients from two randomized multicentre phase II trials and a prospective province-wide blood biobanking program. ctDNA% correlates with serum and radiographic metrics of disease burden and is highest in patients with liver metastases. ctDNA% strongly predicts overall survival, progression-free survival, and treatment response independent of therapeutic context and outperformed established prognostic clinical factors. Recognizing that ctDNA-based biomarker genotyping is limited by low ctDNA% in some patients, we leverage the relationship between clinical prognostic factors and ctDNA% to develop a clinically-interpretable machine-learning tool that predicts whether a patient has sufficient ctDNA% for informative ctDNA genotyping (available online: https://www.ctDNA.org ). Our results affirm ctDNA% as an actionable tool for patient risk stratification and provide a practical framework for optimized biomarker testing.

Zebrafish tumour xenograft models: a prognostic approach to epithelial ovarian cancer

Epithelial ovarian cancer (EOC) is the gynaecological malignancy with highest mortality. Although adjuvant treatment with carboplatin and paclitaxel leads to an objective response in ~80% of these patients, a majority will relapse within two years. Better methods for assessing long-term treatment outcomes are needed. To address this, we established safe and efficacious doses of carboplatin and paclitaxel using IGROV-1 zebrafish-CDX models. Then fluorescently-labelled cell suspensions from 83 tumour biopsies collected at exploratory laparotomy of women with suspected EOC were generated and 37 (45%) were successfully implanted in zebrafish larvae. Among these 19 of 27 pathology-confirmed EOC samples (70%) engrafted. These zebrafish patient-derived tumour xenograft (ZTX) models were treated with carboplatin or paclitaxel and tumour growth/regression and metastatic dissemination were recorded. In a subgroup of nine patients, four ZTX models regressed during carboplatin treatment. All four corresponding patients had >24 months PFS. Furthermore, both ZTX models established from two patients having <24 months PFS failed to regress during carboplatin treatment. Seven of eight models seeding <6 metastatic cells were established from patients having >24 months PFS. In eleven of fourteen patients, FIGO stage I + II or III tumours gave rise to ZTX models seeding <4 or >4 metastatic cells, respectively. In conclusion, ZTX models predicted patients having >24 or <24 months PFS, based on response/no response to carboplatin. Furthermore, high metastatic dissemination in ZTX models correlated to shorter PFS and more advanced disease at diagnosis. These preliminary results suggest that ZTX models could become a useful prognostic tool in EOC treatment planning.

Machine learning reveals diverse cell death patterns in lung adenocarcinoma prognosis and therapy

Cancer cell growth, metastasis, and drug resistance pose significant challenges in the management of lung adenocarcinoma (LUAD). However, there is a deficiency in optimal predictive models capable of accurately forecasting patient prognoses and guiding the selection of targeted treatments. Programmed cell death (PCD) pathways play a pivotal role in the development and progression of various cancers, offering potential as prognostic indicators and drug sensitivity markers for LUAD patients. The development and validation of predictive models were conducted by integrating 13 PCD patterns with comprehensive analysis of bulk RNA, single-cell RNA transcriptomics, and pertinent clinicopathological details derived from TCGA-LUAD and six GEO datasets. Utilizing the machine learning algorithms, we identified ten critical differentially expressed genes associated with PCD in LUAD, namely CHEK2, KRT18, RRM2, GAPDH, MMP1, CHRNA5, TMPRSS4, ITGB4, CD79A, and CTLA4. Subsequently, we conducted a programmed cell death index (PCDI) based on these genes across the aforementioned cohorts and integrated this index with relevant clinical features to develop several prognostic nomograms. Furthermore, we observed a significant correlation between the PCDI and immune features in LUAD, including immune cell infiltration and the expression of immune checkpoint molecules. Additionally, we found that patients with a high PCDI score may exhibit resistance to immunotherapy and standard adjuvant chemotherapy regimens; however, they may benefit from other FDA-supported drugs such as docetaxel and dasatinib. In conclusion, the PCDI holds potential as a prognostic signature and can facilitate personalized treatment for LUAD patients.

Ubiquitin B, Ubiquitin C, and β-Catenin as Promising Diagnostic and Prognostic Tools in Prostate Cancer

Prostate cancer (PC) is a major global public health concern, imposing a significant burden on men and ranking as the second most prevalent malignancy. This study delves into the intricate world of ubiquitination processes and expression regulation, with a specific focus on understanding the roles of ubiquitin B (UBB), ubiquitin C (UBC), and β-Catenin in PC development. We thoroughly analyze the expression profiles of UBB, UBC, and β-Catenin, investigating their interactions and associations with clinical and histopathological data. These findings offer valuable insights into their potential as robust prognostic markers and their significance for patient survival. Our research uncovers the upregulation of UBB and UBC expression in PC tissues, and an even more pronounced expression in lymph node metastases, highlighting their pivotal roles in PC progression. Moreover, we identify a compelling correlation between high UBB and UBC levels and diminished overall survival in PC patients, emphasizing their clinical relevance. Additionally, we observe a significant reduction in membranous β-Catenin expression in PC tissues. Importantly, abnormal β-Catenin expression is strongly associated with shorter survival in PC patients and serves as a significant, independent prognostic factor for patient outcomes. Kaplan-Meier survival analysis indicates that patients with tumors characterized by simultaneous UBB and aberrant β-Catenin expression exhibit the poorest overall survival. These collective insights underline the clinical importance of evaluating UBB, UBC, and β-Catenin as combined prognostic markers in PC.

Construction and optimization of multi-platform precision pathways for precision medicine

In the enduring challenge against disease, advancements in medical technology have empowered clinicians with novel diagnostic platforms. Whilst in some cases, a single test may provide a confident diagnosis, often additional tests are required. However, to strike a balance between diagnostic accuracy and cost-effectiveness, one must rigorously construct the clinical pathways. Here, we developed a framework to build multi-platform precision pathways in an automated, unbiased way, recommending the key steps a clinician would take to reach a diagnosis. We achieve this by developing a confidence score, used to simulate a clinical scenario, where at each stage, either a confident diagnosis is made, or another test is performed. Our framework provides a range of tools to interpret, visualize and compare the pathways, improving communication and enabling their evaluation on accuracy and cost, specific to different contexts. This framework will guide the development of novel diagnostic pathways for different diseases, accelerating the implementation of precision medicine into clinical practice.

S100A8/A9 predicts response to PIM kinase and PD-1/PD-L1 inhibition in triple-negative breast cancer mouse models

BACKGROUND

Understanding why some triple-negative breast cancer (TNBC) patients respond poorly to existing therapies while others respond well remains a challenge. This study aims to understand the potential underlying mechanisms distinguishing early-stage TNBC tumors that respond to clinical intervention from non-responders, as well as to identify clinically viable therapeutic strategies, specifically for TNBC patients who may not benefit from existing therapies.

METHODS

We conducted retrospective bioinformatics analysis of historical gene expression datasets to identify a group of genes whose expression levels in early-stage tumors predict poor clinical outcomes in TNBC. In vitro small-molecule screening, genetic manipulation, and drug treatment in syngeneic mouse models of TNBC were utilized to investigate potential therapeutic strategies and elucidate mechanisms of drug action.

RESULTS

Our bioinformatics analysis reveals a robust association between increased expression of immunosuppressive cytokine S100A8/A9 in early-stage tumors and subsequent disease progression in TNBC. A targeted small-molecule screen identifies PIM kinase inhibitors as capable of decreasing S100A8/A9 expression in multiple cell types, including TNBC and immunosuppressive myeloid cells. Combining PIM inhibition and immune checkpoint blockade induces significant antitumor responses, especially in otherwise resistant S100A8/A9-high PD-1/PD-L1-positive tumors. Notably, serum S100A8/A9 levels mirror those of tumor S100A8/A9 in a syngeneic mouse model of TNBC.

CONCLUSIONS

Our data propose S100A8/A9 as a potential predictive and pharmacodynamic biomarker in clinical trials evaluating combination therapy targeting PIM and immune checkpoints in TNBC. This work encourages the development of S100A8/A9-based liquid biopsy tests for treatment guidance.

Muscle stiffness indicating mission crew health in space

Muscle function is compromised by gravitational unloading in space affecting overall musculoskeletal health. Astronauts perform daily exercise programmes to mitigate these effects but knowing which muscles to target would optimise effectiveness. Accurate inflight assessment to inform exercise programmes is critical due to lack of technologies suitable for spaceflight. Changes in mechanical properties indicate muscle health status and can be measured rapidly and non-invasively using novel technology. A hand-held MyotonPRO device enabled monitoring of muscle health for the first time in spaceflight (> 180 days). Greater/maintained stiffness indicated countermeasures were effective. Tissue stiffness was preserved in the majority of muscles (neck, shoulder, back, thigh) but Tibialis Anterior (foot lever muscle) stiffness decreased inflight vs. preflight (p < 0.0001; mean difference 149 N/m) in all 12 crewmembers. The calf muscles showed opposing effects, Gastrocnemius increasing in stiffness Soleus decreasing. Selective stiffness decrements indicate lack of preservation despite daily inflight countermeasures. This calls for more targeted exercises for lower leg muscles with vital roles as ankle joint stabilizers and in gait. Muscle stiffness is a digital biomarker for risk monitoring during future planetary explorations (Moon, Mars), for healthcare management in challenging environments or clinical disorders in people on Earth, to enable effective tailored exercise programmes.

Multi-dimensional scaling techniques unveiled gain1q&loss13q co-occurrence in Multiple Myeloma patients with specific genomic, transcriptional and adverse clinical features

The complexity of Multiple Myeloma (MM) is driven by several genomic aberrations, interacting with disease-related and/or -unrelated factors and conditioning patients' clinical outcome. Patient's prognosis is hardly predictable, as commonly employed MM risk models do not precisely partition high- from low-risk patients, preventing the reliable recognition of early relapsing/refractory patients. By a dimensionality reduction approach, here we dissect the genomic landscape of a large cohort of newly diagnosed MM patients, modelling all the possible interactions between any MM chromosomal alterations. We highlight the presence of a distinguished cluster of patients in the low-dimensionality space, with unfavorable clinical behavior, whose biology was driven by the co-occurrence of chromosomes 1q CN gain and 13 CN loss. Presence or absence of these alterations define MM patients overexpressing either CCND2 or CCND1, fostering the implementation of biology-based patients' classification models to describe the different MM clinical behaviors.