Artificial intelligence in pathologic diagnosis, prognosis and prediction of prostate cancer.

Histopathology, which is the gold-standard for prostate cancer diagnosis, faces significant challenges. With prostate cancer ranking among the most common cancers in the United States and worldwide, pathologists experience an increased number for prostate biopsies. At the same time, precise pathological assessment and classification are necessary for risk stratification and treatment decisions in prostate cancer care, adding to the challenge to pathologists. Recent advancement in digital pathology makes artificial intelligence and learning tools adopted in histopathology feasible. In this review, we introduce the concept of AI and its various techniques in the field of histopathology. We summarize the clinical applications of AI pathology for prostate cancer, including pathological diagnosis, grading, prognosis evaluation, and treatment options. We also discuss how AI applications can be integrated into the routine pathology workflow. With these rapid advancements, it is evident that AI applications in prostate cancer go beyond the initial goal of being tools for diagnosis and grading. Instead, pathologists can provide additional information to improve long-term patient outcomes by assessing detailed histopathologic features at pixel level using digital pathology and AI. Our review not only provides a comprehensive summary of the existing research but also offers insights for future advancements.

Advancing quantitative PCR with color cycle multiplex amplification.

Quantitative PCR (qPCR) is the gold standard for detection and quantitation of known DNA targets, but the scarcity of spectrally distinct fluorophores and filter sets limits the number of detectable targets. Here, we introduce color cycle multiplex amplification (CCMA) to significantly increase the number of detectable DNA targets in a single qPCR reaction using standard instrumentation. In CCMA, presence of one DNA target species results in a pre-programmed pattern of fluorescence increases. This pattern is distinguished by cycle thresholds (Cts) through rationally designed delays in amplification. For example, we design an assay wherein Staphylococcus aureus sequentially induces FAM, then Cy5.5, then ROX fluorescence increases with more than 3 cycles between each signal. CCMA offers notably higher potential for multiplexing because it uses fluorescence permutation rather than combination. With 4 distinct fluorescence colors, CCMA theoretically allows the detection of up to 136 distinct DNA target sequences using fluorescence permutation. Experimentally, we demonstrated a single-tube qPCR assay screening 21 sepsis-related bacterial DNA targets in samples of blood, sputum, pleural effusion and bronchoalveolar lavage fluid, with 89% clinical sensitivity and 100% clinical specificity, showing its potential as a powerful tool for advanced quantitative screening in molecular diagnostics.

Protein-truncating variant in APOL3 increases chronic kidney disease risk in epistasis with APOL1 risk alleles.

BACKGROUND: Two coding alleles within the APOL1 gene, G1 and G2, found almost exclusively in individuals genetically similar to West African populations, contribute substantially to the pathogenesis of chronic kidney disease (CKD). The APOL gene cluster on chromosome 22 contains a total of six APOL genes that have arisen as a result of gene duplication. METHODS: Using a genome-first approach in the Penn Medicine Biobank, we identified 62 protein-altering variants in the six APOL genes with a minor allele frequency > 0.1% in a population of participants genetically similar to African reference populations and performed population-specific phenome-wide association studies. RESULTS: We identified rs1108978, a stop-gain variant in APOL3 (p.Q58*), to be significantly associated with increased CKD risk, even after conditioning on APOL1 G1/G2 carrier status. These findings were replicated in the Veterans Affairs Million Veteran Program and the All of Us Research Program. APOL3 p.Q58* was also significantly associated with a number of quantitative traits linked to CKD including decreased kidney volume. This truncating variant contributed the most risk for CKD in patients monoallelic for APOL1 G1/G2, suggesting an epistatic interaction and a potential protective effect of wild-type APOL3 against APOL1-induced kidney disease. CONCLUSION: This study demonstrates the utility of targeting population-specific variants in a genome-first approach, even in the context of well-studied gene-disease relationships. FUNDING: National Heart, Lung, and Blood Institute (F30HL172382, R01HL169378, R01HL169458), Doris Duke Foundation (grant 2023-0224), National Institute of Biomedical Imaging and Bioengineering (P41EB029460), National Center for Advancing Translational Sciences (UL1-TR-001878).

Implementation of Digital Pathology and Artificial Intelligence in Routine Pathology Practice.

The advent of affordable technology has significantly influenced the practice of digital pathology, leading to its growing adoption within the pathology community. This review article aimed to outline the latest developments in digital pathology, the cutting-edge advancements in artificial intelligence (AI) applications within this field, and the pertinent United States regulatory frameworks. The content is based on a thorough analysis of original research articles and official United States Federal guidelines. Findings from our review indicate that several Food and Drug Administration-approved digital scanners and image management systems are establishing a solid foundation for the seamless integration of advanced technologies into everyday pathology workflows, which may reduce device and operational costs in the future. AI is particularly transforming the way morphologic diagnoses are automated, notably in cancers like prostate and colorectal, within screening initiatives, albeit challenges such as data privacy issues and algorithmic biases remain. The regulatory environment, shaped by standards from the Food and Drug Administration, Centers for Medicare & Medicaid Services/Clinical Laboratory Improvement Amendments, and College of American Pathologists, is evolving to accommodate these innovations while ensuring safety and reliability. Centers for Medicare & Medicaid Services/Clinical Laboratory Improvement Amendments have issued policies to allow pathologists to review and render diagnoses using digital pathology remotely. Moreover, the introduction of new digital pathology Current Procedural Terminology codes designed to complement existing pathology Current Procedural Terminology codes is facilitating reimbursement processes. Overall, these advancements are heralding a new era in pathology that promises enhanced diagnostic precision and efficiency through digital and AI technologies, potentially improving patient care as well as bolstering educational and research activities.

The Liquid Biopsy Consortium: Challenges and opportunities for early cancer detection and monitoring.

The emerging field of liquid biopsy stands at the forefront of novel diagnostic strategies for cancer and other diseases. Liquid biopsy allows minimally invasive molecular characterization of cancers for diagnosis, patient stratification to therapy, and longitudinal monitoring. Liquid biopsy strategies include detection and monitoring of circulating tumor cells, cell-free DNA, and extracellular vesicles. In this review, we address the current understanding and the role of existing liquid-biopsy-based modalities in cancer diagnostics and monitoring. We specifically focus on the technical and clinical challenges associated with liquid biopsy and biomarker development being addressed by the Liquid Biopsy Consortium, established through the National Cancer Institute. The Liquid Biopsy Consortium has developed new methods/assays and validated existing methods/technologies to capture and characterize tumor-derived circulating cargo, as well as addressed existing challenges and provided recommendations for advancing biomarker assays.

Common- and rare-variant genetic architecture of heart failure across the allele frequency spectrum.

Heart failure (HF) is a complex trait, influenced by environmental and genetic factors, that affects over 30 million individuals worldwide. Historically, the genetics of HF have been studied in Mendelian forms of disease, where rare genetic variants have been linked to familial cardiomyopathies. More recently, genome-wide association studies (GWAS) have successfully identified common genetic variants associated with risk of HF. However, the relative importance of genetic variants across the allele-frequency spectrum remains incompletely characterized. Here, we report the results of common- and rare-variant association studies of all-cause heart failure, applying recently developed methods to quantify the heritability of HF attributable to different classes of genetic variation. We combine GWAS data across multiple populations including 207,346 individuals with HF and 2,151,210 without, identifying 176 risk loci at genome-wide significance (p < 5×10-8). Signals at newly identified common-variant loci include coding variants in Mendelian cardiomyopathy genes (MYBPC3, BAG3), as well as regulators of lipoprotein (LPL) and glucose metabolism (GIPR, GLP1R), and are enriched in cardiac, muscle, nerve, and vascular tissues, as well as myocyte and adipocyte cell types. Gene burden studies across three biobanks (PMBB, UKB, AOU) including 27,208 individuals with HF and 349,126 without uncover exome-wide significant (p < 3.15×10-6) associations for HF and rare predicted loss-of-function (pLoF) variants in TTN, MYBPC3, FLNC, and BAG3. Total burden heritability of rare coding variants (2.2%, 95% CI 0.99-3.5%) is highly concentrated in a small set of Mendelian cardiomyopathy genes, and is lower than heritability attributable to common variants (4.3%, 95% CI 3.9-4.7%) which is more diffusely spread throughout the genome. Finally, we demonstrate that common-variant background, in the form of a polygenic risk score (PRS), significantly modifies the risk of HF among carriers of pathogenic truncating variants in the Mendelian cardiomyopathy gene TTN. These findings suggest a significant polygenic component to HF exists that is not captured by current clinical genetic testing.

Whole genome sequence analysis of blood lipid levels in >66,000 individuals.

Blood lipids are heritable modifiable causal factors for coronary artery disease. Despite well-described monogenic and polygenic bases of dyslipidemia, limitations remain in discovery of lipid-associated alleles using whole genome sequencing (WGS), partly due to limited sample sizes, ancestral diversity, and interpretation of clinical significance. Among 66,329 ancestrally diverse (56% non-European) participants, we associate 428M variants from deep-coverage WGS with lipid levels; ~400M variants were not assessed in prior lipids genetic analyses. We find multiple lipid-related genes strongly associated with blood lipids through analysis of common and rare coding variants. We discover several associated rare non-coding variants, largely at Mendelian lipid genes. Notably, we observe rare LDLR intronic variants associated with markedly increased LDL-C, similar to rare LDLR exonic variants. In conclusion, we conducted a systematic whole genome scan for blood lipids expanding the alleles linked to lipids for multiple ancestries and characterize a clinically-relevant rare non-coding variant model for lipids.

High-Throughput Variant Detection Using a Color-Mixing Strategy.

Many diseases are related to multiple genetic alterations within a single gene. Probing for highly multiple (>10) variants in a single quantitative PCR tube is impossible because of a limited number of fluorescence channels and the limited ability to test one variant per channel, increasing the need for tubes. Herein, a novel color-mixing strategy was experimentally validated that uses fluorescence combinations as digital color codes to probe multiple variants simultaneously. The color-mixing strategy relies on a simple intratube assay that can probe for 15 variants as part of an intertube assay that can probe for an exponentially increased number of variants. This strategy is achieved by using multiplex double-stranded toehold probes modified with fluorophores and quenchers; the probes are designed to be quenched or remain luminous after binding to wild-type or variant templates. The color-mixing strategy was used to probe for 21 pathogenic variants in thalassemia and to distinguish between heterozygous and homozygous variants in six tubes, with a specificity of 99% and a sensitivity of 94%. To support tuberculosis diagnosis, the same strategy was applied to simultaneously probe in Mycobacterium tuberculosis for rifampicin-resistance mutations occurring within one 81-bp region and one 48-bp region in the rpoB gene, plus five isoniazid-resistance mutations in the inhA and katG genes.

Invasive brain tissue oxygen and intracranial pressure (ICP) monitoring versus ICP-only monitoring in pediatric severe traumatic brain injury.

OBJECTIVE: Severe traumatic brain injury (TBI) is a leading cause of disability and death in the pediatric population. While intracranial pressure (ICP) monitoring is the gold standard in acute neurocritical care following pediatric severe TBI, brain tissue oxygen tension (PbtO2) monitoring may also help limit secondary brain injury and improve outcomes. The authors hypothesized that pediatric patients with severe TBI and ICP + PbtO2 monitoring and treatment would have better outcomes than those who underwent ICP-only monitoring and treatment. METHODS: Patients ≤ 18 years of age with severe TBI who received ICP ± PbtO2 monitoring at a quaternary children's hospital between 1998 and 2021 were retrospectively reviewed. The relationships between conventional measurements of TBI were evaluated, i.e., ICP, cerebral perfusion pressure (CPP), and PbtO2. Differences were analyzed between patients with ICP + PbtO2 versus ICP-only monitoring on hospital and pediatric intensive care unit (PICU) length of stay (LOS), length of intubation, Pediatric Intensity Level of Therapy scale score, and functional outcome using the Glasgow Outcome Score-Extended (GOS-E) scale at 6 months postinjury. RESULTS: Forty-nine patients, including 19 with ICP + PbtO2 and 30 with ICP only, were analyzed. There was a weak negative association between ICP and PbtO2 (ß = -0.04). Conversely, there was a strong positive correlation between CPP ≥ 40 mm Hg and PbtO2 ≥ 15 and ≥ 20 mm Hg (ß = 0.30 and ß = 0.29, p < 0.001, respectively). An increased number of events of cerebral PbtO2 < 15 mm Hg or < 20 mm Hg were associated with longer hospital (p = 0.01 and p = 0.022, respectively) and PICU (p = 0.015 and p = 0.007, respectively) LOS, increased duration of mechanical ventilation (p = 0.015 when PbtO2 < 15 mm Hg), and an unfavorable 6-month GOS-E score (p = 0.045 and p = 0.022, respectively). An increased number of intracranial hypertension episodes (ICP ≥ 20 mm Hg) were associated with longer hospital (p = 0.007) and PICU (p < 0.001) LOS and longer duration of mechanical ventilation (p < 0.001). Lower minimum hourly and average daily ICP values predicted favorable GOS-E scores (p < 0.001 for both). Patients with ICP + PbtO2 monitoring experienced longer PICU LOS (p = 0.018) compared to patients with ICP-only monitoring, with no significant GOS-E score difference between groups (p = 0.733). CONCLUSIONS: An increased number of cerebral hypoxic episodes and an increased number of intracranial hypertension episodes resulted in longer hospital LOS and longer duration of mechanical ventilator support. An increased number of cerebral hypoxic episodes also correlated with less favorable functional outcomes. In contrast, lower minimum hourly and average daily ICP values, but not the number of intracranial hypertension episodes, were associated with more favorable functional outcomes. There was a weak correlation between ICP and PbtO2, supporting the importance of multimodal invasive neuromonitoring in pediatric severe TBI.

Early Rooming Triage: Accuracy and Demographic Factors Associated with Clinical Acuity.

INTRODUCTION: Early rooming triage increases patient throughput and satisfaction by rapidly assigning patients to a definitive care area, without using vital signs or detailed chart review. Despite these operational benefits, the clinical accuracy of early rooming triage is not well known. We sought to measure the accuracy of early rooming triage and uncover additional patient characteristics that can assist triage. METHODS: We conducted a single-center, retrospective population study of walk-in emergency department (ED) patients presenting to the ED via an early rooming triage system, examining triage accuracy and demographic factor correlation with higher acuity ED outcomes. RESULTS: Among all patients included from the three-year study period (N = 238,457), early rooming triage was highly sensitive (0.89) and less specific (0.61) for predicting which patients would have a severe outcome in the ED. Patients triaged to the lowest acuity area of the ED experienced severe outcomes in 4.39% of cases, while patients triaged to the highest acuity area of the ED experienced severe outcomes in 65.9% of cases. An age of greater than 43 years (odds ratio [OR] 3.48, 95% confidence interval: 3.40, 3.57) or patient's home address farther from the ED ([OR] 2.23 to 3.08) were highly correlated with severe outcomes. Multivariable models incorporating triage team judgment were robust for predicting severe outcomes at triage, with an area under the receiver operating characteristic of 0.82. CONCLUSION: Early rooming workflows are appropriately sensitive for ED triage. Consideration of demographic factors, automated or otherwise, can augment ED processes to provide optimal triage.

Clinically translatable cytokine delivery platform for eradication of intraperitoneal tumors.

Proinflammatory cytokines have been approved by the Food and Drug Administration for the treatment of metastatic melanoma and renal carcinoma. However, effective cytokine therapy requires high-dose infusions that can result in antidrug antibodies and/or systemic side effects that limit long-term benefits. To overcome these limitations, we developed a clinically translatable cytokine delivery platform composed of polymer-encapsulated human ARPE-19 (RPE) cells that produce natural cytokines. Tumor-adjacent administration of these capsules demonstrated predictable dose modulation with spatial and temporal control and enabled peritoneal cancer immunotherapy without systemic toxicities. Interleukin-2 (IL2)-producing cytokine factory treatment eradicated peritoneal tumors in ovarian and colorectal mouse models. Furthermore, computational pharmacokinetic modeling predicts clinical translatability to humans. Notably, this platform elicited T cell responses in NHPs, consistent with reported biomarkers of treatment efficacy without toxicity. Combined, our findings demonstrate the safety and efficacy of IL2 cytokine factories in preclinical animal models and provide rationale for future clinical testing in humans.

Artificial intelligence and computational pathology.

Data processing and learning has become a spearhead for the advancement of medicine, with pathology and laboratory medicine has no exception. The incorporation of scientific research through clinical informatics, including genomics, proteomics, bioinformatics, and biostatistics, into clinical practice unlocks innovative approaches for patient care. Computational pathology is burgeoning subspecialty in pathology that promises a better-integrated solution to whole-slide images, multi-omics data, and clinical informatics. However, computational pathology faces several challenges, including the ability to integrate raw data from different sources, limitation of hardware processing capacity, and a lack of specific training programs, as well as issues on ethics and larger societal acceptable practices that are still solidifying. The establishment of the entire industry of computational pathology requires far-reaching changes of the three essential elements connecting patients and doctors: the local laboratory, the scan center, and the central cloud hub/portal for data processing and retrieval. Computational pathology, unlocked through information integration and advanced digital communication networks, has the potential to improve clinical workflow efficiency, diagnostic quality, and ultimately create personalized diagnosis and treatment plans for patients. This review describes clinical perspectives and discusses the statistical methods, clinical applications, potential obstacles, and future directions of computational pathology.

Low-level parental somatic mosaic SNVs in exomes from a large cohort of trios with diverse suspected Mendelian conditions.

PURPOSE: The goal of this study was to assess the scale of low-level parental mosaicism in exome sequencing (ES) databases. METHODS: We analyzed approximately 2000 family trio ES data sets from the Baylor-Hopkins Center for Mendelian Genomics (BHCMG) and Baylor Genetics (BG). Among apparent de novo single-nucleotide variants identified in the affected probands, we selected rare unique variants with variant allele fraction (VAF) between 30% and 70% in the probands and lower than 10% in one of the parents. RESULTS: Of 102 candidate mosaic variants validated using amplicon-based next-generation sequencing, droplet digital polymerase chain reaction, or blocker displacement amplification, 27 (26.4%) were confirmed to be low- (VAF between 1% and 10%) or very low (VAF <1%) level mosaic. Detection precision in parental samples with two or more alternate reads was 63.6% (BHCMG) and 43.6% (BG). In nine investigated individuals, we observed variability of mosaic ratios among blood, saliva, fibroblast, buccal, hair, and urine samples. CONCLUSION: Our computational pipeline enables robust discrimination between true and false positive candidate mosaic variants and efficient detection of low-level mosaicism in ES samples. We confirm that the presence of two or more alternate reads in the parental sample is a reliable predictor of low-level parental somatic mosaicism.

Highly Sensitive Blocker Displacement Amplification and Droplet Digital PCR Reveal Low-Level Parental FOXF1 Somatic Mosaicism in Families with Alveolar Capillary Dysplasia with Misalignment of Pulmonary Veins.

Detection of low-level somatic mosaicism [alternate allele fraction (AAF) ≤ 10%] in parents of affected individuals with the apparent de novo pathogenic variants enables more accurate estimate of recurrence risk. To date, only a few systematic analyses of low-level parental somatic mosaicism have been performed. Herein, highly sensitive blocker displacement amplification, droplet digital PCR, quantitative PCR, long-range PCR, and array comparative genomic hybridization were applied in families with alveolar capillary dysplasia with misalignment of pulmonary veins. We screened 18 unrelated families with the FOXF1 variant previously determined to be apparent de novo (n = 14), of unknown parental origin (n = 1), or inherited from a parent suspected to be somatic and/or germline mosaic (n = 3). We identified four (22%) families with FOXF1 parental somatic mosaic single-nucleotide variants (n = 3) and copy number variant deletion (n = 1) detected in parental blood samples and an AAF ranging between 0.03% and 19%. In one family, mosaic allele ratio in tissues originating from three germ layers ranged between <0.03% and 0.65%. Because the ratio of parental somatic mosaicism have significant implications for the recurrence risk, this study further implies the importance of a systematic screening of parental samples for low-level and very-low-level (AAF ≤ 1%) somatic mosaicism using methods that are more sensitive than those routinely applied in diagnostics.

Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival.

BACKGROUND: Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses. METHODS: Tissue microarrays were used to measure expression of nine GC-associated proteins in GC tissue and normal gastric tissue samples. Hierarchical cluster analysis of microarray data and feature selection for factors associated with survival were performed. Based on these data, prognostic scoring models were established to predict clinical outcomes. Finally, ingenuity pathway analysis (IPA) was used to identify a biological GC network. RESULTS: Eight proteins were upregulated in GC tissues versus normal gastric tissues. Hierarchical cluster analysis and feature selection showed that overall survival was worse in cyclin dependent kinase (CDK)2, Akt1, X-linked inhibitor of apoptosis protein (XIAP), Notch4, and phosphorylated (p)-protein kinase C (PKC) α/ß2 immunopositive patients than in patients that were immunonegative for these proteins. Risk score models based on these five proteins and clinicopathological characteristics were established to determine prognoses of GC patients. These proteins were found to be involved in cancer related-signaling pathways and upstream regulators were identified. CONCLUSION: This study identified proteins that can be used as clinical biomarkers and established a risk score model based on these proteins and clinicopathological characteristics to assess GC prognosis.

A recurrent 8 bp frameshifting indel in FOXF1 defines a novel mutation hotspot associated with alveolar capillary dysplasia with misalignment of pulmonary veins.

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a rare lethal lung developmental disease. Affected infants manifest with severe respiratory distress and refractory pulmonary hypertension and uniformly die in the first month of life. Heterozygous point mutations or copy-number variant deletions involving FOXF1 and/or its upstream lung-specific enhancer on 16q24.1 have been identified in the vast majority of ACDMPV patients. We have previously described two unrelated families with a de novo pathogenic frameshift variant c.691_698del (p.Ala231Argfs*61) in the exon 1 of FOXF1. Here, we present a third unrelated ACDMPV family with the same de novo variant and propose that a direct tandem repeat of eight consecutive nucleotides GCGGCGGC within the ~4 kb CpG island in FOXF1 exon 1 is a novel mutation hotspot causative for ACDMPV.

Repeated craniotomies for intracranial tumors: is the risk increased? Pooled analysis of two prospective, institutional registries of complications and outcomes.

PURPOSE: Deciding whether to re-operate patients with intracranial tumor recurrence or remnant is challenging, as the data on safety of repeated procedures is limited. This study set out to evaluate the risks for morbidity, mortality, and complications after repeated operations, and to compare those to primary operations. METHODS: Retrospective observational two-center study on consecutive patients undergoing microsurgical tumor resection. The data derived from independent, prospective institutional registries. The primary endpoint was morbidity at 3 months (M3), defined as significant decrease on the Karnofsky Performance Scale (KPS). Secondary endpoints were mortality, rate and severity of complications according to the Clavien-Dindo Grade (CDG). RESULTS: 463/2403 (19.3%) were repeated procedures. Morbidity at M3 occurred in n = 290 patients (12.1%). In univariable analysis, patients undergoing repeated surgery were 98% as likely as patients undergoing primary surgery to experience morbidity (OR 0.98, 95% CI 0.72-1.34, p = 0.889). In multivariable analysis adjusted for age, sex, tumor size, histology and posterior fossa location, the relationship remained stable (aOR 1.25, 95% CI 0.90-1.73, p = 0.186). Mortality was n = 10 (0.4%) at discharge and n = 95 (4.0%) at M3, without group differences. At least one complication occurred in n = 855, and the rate (35.5% vs. 35.9%, p = 0.892) and severity (CDG; p = 0.520) was similar after primary and repeated procedures. Results were reproduced in subgroup analyses for meningiomas, gliomas and cerebral metastases. CONCLUSIONS: Repeated surgery for intracranial tumors does not increase the risk of morbidity. Mortality, and both the rate and severity of complications are comparable to primary operations. This information is of value for patient counseling and the informed consent process.

Protein expression profiles and clinicopathologic characteristics associate with gastric cancer survival

BACKGROUND: Prognosis remains one of most crucial determinants of gastric cancer (GC) treatment, but current methods do not predict prognosis accurately. Identification of additional biomarkers is urgently required to identify patients at risk of poor prognoses. METHODS: Tissue microarrays were used to measure expression of nine GC-associated proteins in GC tissue and normal gastric tissue samples. Hierarchical cluster analysis of microarray data and feature selection for factors associated with survival were performed. Based on these data, prognostic scoring models were established to predict clinical outcomes. Finally, ingenuity pathway analysis (IPA) was used to identify a biological GC network. RESULTS: Eight proteins were upregulated in GC tissues versus normal gastric tissues. Hierarchical cluster analysis and feature selection showed that overall survival was worse in cyclin dependent kinase (CDK)2, Akt1, X-linked inhibitor of apoptosis protein (XIAP), Notch4, and phosphorylated (p)-protein kinase C (PKC) α/ß2 immunopositive patients than in patients that were immunonegative for these proteins. Risk score models based on these five proteins and clinicopathological characteristics were established to determine prognoses of GC patients. These proteins were found to be involved in cancer related-signaling pathways and upstream regulators were identified. CONCLUSION: This study identified proteins that can be used as clinical biomarkers and established a risk score model based on these proteins and clinicopathological characteristics to assess GC prognosis.

The expression of serum sEGFR, sFlt-1, sEndoglin and PLGF in preeclampsia.

The objective of this study was to investigate soluble epidermal growth factor receptor (sEGFR), soluble vascular endothelial growth factor receptor 1 (sFlt-1), soluble endoglin (sEndoglin) and placenta growth factor (PLGF) concentrations in normotensive, preterm and term preeclamptic pregnancies' serum and thus to specify the clinical utility of these biochemical markers in monitoring severity and intrauterine growth retardation of preterm preeclampsia. 172 pregnant women were divided into the following groups: preterm preeclampsia, preterm control, term preeclampsia and term control. Preterm preeclampsia patients were stratified with severe feature (n = 50) and without severe feature (n = 22). sEGFR, sEndoglin and PLGF were assessed using Luminex multiplex immunoassay, whilesFlt-1 was assessed using ELISA. sEGFR was significantly lower in preterm preeclampsia than matched control (p < 0.001) and mildly lower in term preeclampsia than matched control (p < 0.01). On contrary, sFlt-1 was significantly higher in preterm preeclampsia than matched control (p < 0.001) and mildly higher in term preeclampsia than matched control (p < 0.01). sFlt-1, sFlt-1/sEGFR and sFlt-1/PLGF were positively correlated with the severity of preterm preeclampsia (P < 0.001, R value ≥ 0.6), especially sFlt-1/sEGFR had the highest R value (R value = 0.711) among them. Furthermore, sEndoglin and the ratio of sEndoglin/sEGFR were associated with neonatal birth weight small for gestational age (SGA, n = 25) in preterm preeclampsia group. CONCLUSIONS: The ratio of sFlt-1/sEGFR could be used as a novel candidate biochemical marker in monitoring the severity of preterm preeclampsia. sEndoglin and sEGFR may be involved in the pathogenesis of SGA in preterm preelampsia.