Citations

Introduction: Dysfunction of pelvic floor muscles (PFMs) can limit physical activity and health. Current screening methods are invasive or expensive, although transabdominal ultrasound (TAUS) is gaining popularity. PFM contraction causes bladder base displacement (BBD) and magnitude reflects PFM function; however, manual image analysis is labor-intensive. Artificial intelligence (AI)–assisted TAUS may offer more efficient and feasible solutions. This study compared standard analysis of BBD to measurement with AI-assisted TAUS to assess reliability and validity. Methods: A total of 20 healthy female participants (26.4 ± 8.5 years) performed 6 repeated Kegel contractions after following a bladder-filling protocol. A curvilinear transducer was placed between the anterior superior iliac spines with the probe placed transversely and then angled inferiorly toward the bladder. The Clarius Bladder AI tool automatically measured distance from bladder apex to base. Images were also saved without an AI overlay and measured manually using ImageJ. Results: Average BBD values were equivalent (manual 0.7 ± 0.5 cm; AI-assisted 0.7 ± 0.6 cm, 90% confidence interval: −0.09 to 0.04 [ P < .05]). Measures were highly related ( r = 0.97, intraclass correlation coefficients [ICC 3,k ] = 0.98) and showed good agreement (95% limits of agreement: −0.33 to 0.28 cm). Test–retest reliability was excellent for both manual (ICC 3,k = 0.94, standard error of measurement [SEM]: 0.12 cm) and AI-assisted measures (ICC 3,k = 0.94, SEM = 0.14 cm). Discussion: No systematic differences were shown between methods, which were highly related. The Clarius AI-assisted bladder tool provided valid, reliable BBD measures consistent with traditional methods. The small SEM supports clinical application for PFM assessment. Conclusion: AI-assisted TAUS appears to be an efficient noninvasive method for assessing PFM function and may be applied easily in various clinical and research settings.

Abstract BRCA-associated homologous recombination deficiency (HRD) is present in ~ 50% of high-grade serous carcinomas (HGSC) and predicts sensitivity to platinum-based therapy. However, there is little understanding of why some patients with BRCA-deficient tumors experience unexpectedly poor outcomes. We profiled 154 tumors, enriched for patients with BRCA-deficient tumors that experienced short overall survival (≤ 3 years, n = 42), using whole-genome, transcriptome, and methylation analyses. All but one BRCA-deficient tumor exceeded an accepted HRD genomic scarring threshold. However, patients with BRCA1-deficient HGSC with a more elevated HRD score survived significantly longer. Patients with BRCA2-deficient HGSC and loss of NF1 survived twice as long as those without NF1 loss, whereas PIK3CA or RAD21 amplification defined BRCA2-deficient HGSC with exceptionally short survival. BRCA1-deficient tumors in short survivors had evidence of immunosuppressive c-kit signaling and EMT. In a large HGSC cohort (n = 1,389) including 282 individuals with pathogenic germline BRCA variants (gBRCApv), the location of the mutation within functional domains stratified clinical outcomes. Notably, residual disease after primary surgery had limited prognostic effect in gBRCApv-carriers compared to non-carriers. Our findings indicate that tumor HR proficiency in the context of therapy response and survival is not a binary property, and highlight genomic and immune modifiers of outcomes in BRCA-deficient HGSC.

Introduction: Sickle cell disease (SCD) is prevalent in sub-Saharan Africa. Phenotypic diversity in patients with similar SCD genotypes may result from genetic and environmental factors. Nigeria has the highest SCD prevalence, with homozygous SCD (HbSS) being the most severe form. Stroke affects about 11% of children under 20 years with SCD (Ohene-Frempong, Weiner, et al. 1998), primarily ischemic, involving medium to large intracranial arteries. Specific single nucleotide polymorphisms have been linked to ischemic stroke risk in some populations. (Earley, Kelly et al. 2023). This study aimed to identify genetic factors associated with early-age large-vessel stroke in SCD using whole-exome sequencing (WES) in a Nigerian cohort. Methods: The protocol was approved by the IRBs of TJU, Nemours, and 3 Nigerian sites. Subjects with SCD who experienced large vessel stroke early in life (16 years or less) were enrolled, along with controls (SCD patients without stroke). Subjects were recruited from 3SCD clinics in Kano Metropolis, Nigeria. Inclusion criteria were confirmed SCD diagnosis (SS and Sβ0 thalassemia genotypes), abnormal transcranial doppler (TCD) measurements, and clinical evidence of stroke confirmed by MRI by age 16. Controls included SCD patients (SS and Sβ0) aged 16-26 years without clinical stroke and at least one normal TCD. All cases underwent Magnetic Resonance Angiography (MRA) to establish arteriopathy. Immediate family members of subjects &gt;16 years (siblings and parents) were used per best practice trio analysis to annotate variants with appropriate Mendelian inheritance patterns. WES was performed using SureSelect XT HS (Agilent) and Human All Exon V7 Rev B capture probes for library preparation on all samples. Libraries were sequenced on a NextSeq 550 to 50M paired-end 150bp reads. Variants were called using the GATK suite of algorithms following best practice guidelines and annotated using the VarSeq algorithm, including AlphaMissense annotations. Results: The control group had a median age of 21 years, and the stroke group had a median age of 9 years. The stroke group had a higher proportion of males (60%) compared to controls (30%) (p &lt; 0.05). Fifty percent of the stroke group and 73% of the controls had a history of acute chest syndrome. History of avascular necrosis (7.5%), heart disease (2.5%), and splenic sequestration (1.3%) were present only in controls. Malaria (1.3%), sepsis (2.5%), and hand-foot syndrome (59%) affected the stroke group. History of priapism (6.3%) and leg ulcers (10%) had similar rates in both groups. Using AlphaMissense annotations, nine genes were identified to have more damaging mutations in the stroke cohort compared to the control cohort (odds ratio &gt; 1 and p &lt; 0.05). Pathway enrichment analysis utilizing genes prioritized with an odds ratio &gt; 1 identified cadherin signaling, cellular junction/adhesion, and WNT signaling as significant (p &lt; 0.05). The role of cellular adhesion has been previously described in SCD stroke subjects (Oni, Brito et al. 2024). The genes that we found that showed significance in our analysis include ADAMTSL2, ADCY9, OR3A1, OR3A2, XRRA1, ABTB2, CLDN18, CPNE7, EIF3A, SLC7A6, UBA7, PDE6A, GLOD5, and PCDHA1. Conclusion: Genes in the ADCY9 and ADAMSL2 families have been reported in previous studies to be associated with ischemic stroke. Though the small sample size limits this study, it offers preliminary insights into the genetic and clinical determinants of stroke in SCD patients in Northern Nigeria. The identified candidate genes potentially hold biological significance for the stroke phenotype; however, additional research with a larger sample size is required to validate these associations. These findings underscore the need for further whole-exome sequencing studies in Nigerian patients with the stroke/arteriopathy phenotype, which may augment our understanding of this severe complication. An in-depth examination of the genetic modifiers associated with stroke in SCD could lead to enhanced predictive models and targeted preventive interventions, reducing the burden of stroke in affected individuals. Our team has identified additional datasets in the United States to help validate molecular signatures of interest, inspiring us to continue our work in this important field.

Abstract Patients with head and neck squamous cell carcinomas (HNSCC) often have poor outcomes due to suboptimal risk management and treatment strategies; yet integrating novel prognostic biomarkers into clinical practice is challenging. Here, we report the presence of multinucleated giant cells (MGC)—a type of macrophages—in tumors from patients with HNSCC, which are associated with a favorable prognosis in treatment-naive and preoperative chemotherapy–treated patients. Importantly, MGC density increased in tumors following preoperative therapy, suggesting a role of these cells in the antitumoral response. To enable clinical translation of MGC density as a prognostic marker, we developed a deep-learning model to automate its quantification on routinely stained pathological whole slide images. Finally, we used spatial transcriptomic and proteomic approaches to describe the MGC-related tumor microenvironment and observed an increase in central memory CD4 T cells. We defined an MGC-specific signature resembling to TREM2-expressing mononuclear tumor-associated macrophages, which colocalized in keratin tumor niches. Significance: Novel individual biomarkers are needed to guide therapeutic decisions for patients with head and neck cancer. We report for the first time, granulomas of TREM2-expressing multinucleated giant macrophages in keratin-rich tumor niches, as a biomarker of favorable prognosis and developed a deep-learning model to automate its quantification on routinely stained pathological slides.

Abstract Recent advances in the field of immuno‐oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high‐throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi‐marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Abstract Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector‐based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well‐described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

AbstractThe clinical significance of the tumor‐immune interaction in breast cancer is now established, and tumor‐infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple‐negative (estrogen receptor, progesterone receptor, and HER2‐negative) breast cancer and HER2‐positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state‐of‐the‐art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false‐positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in‐depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple‐negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

We conducted a retrospective/prospective worldwide study on patients with neuroendocrine neoplasms (NENs) and a molecularly proven SARS-CoV-2 positivity. Preliminary results regarding 85 patients of the INTENSIVE study have been published in 2021. Now we are reporting the 2-year analysis.Here, we are reporting data from consecutive patients enrolled between 1 June 2020, and 31 May 2022. Among the 118 contacted centers, 25 were active to enroll and 19 actively recruiting at the time of data cut-off for a total of 280 patients enrolled. SARS-CoV-2 positivity occurred in 47.5% of patients in 2020, 35.1% in 2021, and 17.4% in 2022. The median age for COVID-19 diagnosis was 60 years. Well-differentiated tumors, non-functioning, metastatic stage, and gastroenteropancreatic (GEP) primary sites represented most of the NENs. COVID-19-related pneumonia occurred in 22.8% of the total, with 61.3% of them requiring hospitalization; 11 patients (3.9%) needed sub-intensive or intensive care unit therapies and 14 patients died (5%), in 11 cases (3.9%) directly related to COVID-19. Diabetes mellitus and age at COVID-19 diagnosis > 70 years were significantly associated with COVID-19 mortality, whereas thoracic primary site with COVID-19 morbidity. A significant decrease in both hospitalization and pneumonia occurred in 2022 vs 2020. In our largest series of NEN patients with COVID-19, the NEN population is similar to the general population of patients with NEN regardless of COVID-19. However, older age, non-GEP primary sites and diabetes mellitus should be carefully considered for increased COVID-19 morbidity and mortality. Relevant information could be derived by integrating our results with NENs patients included in other cancer patients with COVID-19 registries.

AbstractBackgroundCyclin E1 (CCNE1) is a potential predictive marker and therapeutic target in tubo‐ovarian high‐grade serous carcinoma (HGSC). Smaller studies have revealed unfavorable associations for CCNE1 amplification and CCNE1 overexpression with survival, but to date no large‐scale, histotype‐specific validation has been performed. The hypothesis was that high‐level amplification of CCNE1 and CCNE1 overexpression, as well as a combination of the two, are linked to shorter overall survival in HGSC.MethodsWithin the Ovarian Tumor Tissue Analysis consortium, amplification status and protein level in 3029 HGSC cases and mRNA expression in 2419 samples were investigated.ResultsHigh‐level amplification (>8 copies by chromogenic in situ hybridization) was found in 8.6% of HGSC and overexpression (>60% with at least 5% demonstrating strong intensity by immunohistochemistry) was found in 22.4%. CCNE1 high‐level amplification and overexpression both were linked to shorter overall survival in multivariate survival analysis adjusted for age and stage, with hazard stratification by study (hazard ratio [HR], 1.26; 95% CI, 1.08‐1.47, p = .034, and HR, 1.18; 95% CI, 1.05‐1.32, p = .015, respectively). This was also true for cases with combined high‐level amplification/overexpression (HR, 1.26; 95% CI, 1.09‐1.47, p = .033). CCNE1 mRNA expression was not associated with overall survival (HR, 1.00 per 1‐SD increase; 95% CI, 0.94‐1.06; p = .58). CCNE1 high‐level amplification is mutually exclusive with the presence of germline BRCA1/2 pathogenic variants and shows an inverse association to RB1 loss.ConclusionThis study provides large‐scale validation that CCNE1 high‐level amplification is associated with shorter survival, supporting its utility as a prognostic biomarker in HGSC.

PURPOSE This randomized, open-label trial compared the efficacy and safety of adjuvant nab-paclitaxel + gemcitabine with those of gemcitabine for resected pancreatic ductal adenocarcinoma (ClinicalTrials.gov identifier: NCT01964430 ). METHODS We assigned 866 treatment-naive patients with pancreatic ductal adenocarcinoma to nab-paclitaxel (125 mg/m 2 ) + gemcitabine (1,000 mg/m 2 ) or gemcitabine alone to one 30-40 infusion on days 1, 8, and 15 of six 28-day cycles. The primary end point was independently assessed disease-free survival (DFS). Additional end points included investigator-assessed DFS, overall survival (OS), and safety. RESULTS Two hundred eighty-seven of 432 patients and 310 of 434 patients completed nab-paclitaxel + gemcitabine and gemcitabine treatment, respectively. At primary data cutoff (December 31, 2018; median follow-up, 38.5 [interquartile range [IQR], 33.8-43 months), the median independently assessed DFS was 19.4 ( nab-paclitaxel + gemcitabine) versus 18.8 months (gemcitabine; hazard ratio [HR], 0.88; 95% CI, 0.729 to 1.063; P = .18). The median investigator-assessed DFS was 16.6 (IQR, 8.4-47.0) and 13.7 (IQR, 8.3-44.1) months, respectively (HR, 0.82; 95% CI, 0.694 to 0.965; P = .02). The median OS (427 events; 68% mature) was 40.5 (IQR, 20.7 to not reached) and 36.2 (IQR, 17.7-53.3) months, respectively (HR, 0.82; 95% CI, 0.680 to 0.996; P = .045). At a 16-month follow-up (cutoff, April 3, 2020; median follow-up, 51.4 months [IQR, 47.0-57.0]), the median OS (511 events; 81% mature) was 41.8 ( nab-paclitaxel + gemcitabine) versus 37.7 months (gemcitabine; HR, 0.82; 95% CI, 0.687 to 0.973; P = .0232). At the 5-year follow-up (cutoff, April 9, 2021; median follow-up, 63.2 months [IQR, 60.1-68.7]), the median OS (555 events; 88% mature) was 41.8 versus 37.7 months, respectively (HR, 0.80; 95% CI, 0.678 to 0.947; P = .0091). Eighty-six percent ( nab-paclitaxel + gemcitabine) and 68% (gemcitabine) of patients experienced grade ≥ 3 treatment-emergent adverse events. Two patients per study arm died of treatment-emergent adverse events. CONCLUSION The primary end point (independently assessed DFS) was not met despite favorable OS seen with nab-paclitaxel + gemcitabine.