Establishing Criteria for Tumor Necrosis as Prognostic Indicator in Colorectal Cancer.

Tumor necrosis has been reported to represent an independent prognostic factor in colorectal cancer, but its evaluation methods have not been described in sufficient detail to introduce tumor necrosis evaluation into clinical use. To study the potential of tumor necrosis as a prognostic indicator in colorectal cancer, criteria for 3 methods for its evaluation were defined: the average percentage method (tumor necrosis percentage of the whole tumor), the hotspot method (tumor necrosis percentage in a single hotspot), and the linear method (the diameter of the single largest necrotic focus). Cox regression models were used to calculate cancer-specific mortality hazard ratios (HRs) for tumor necrosis categories in 2 colorectal cancer cohorts with more than 1800 cases. For reproducibility assessment, 30 cases were evaluated by 9 investigators, and Spearman's rank correlation coefficients and Cohen's kappa coefficients were calculated. We found that all 3 methods predicted colorectal cancer-specific survival independent of other prognostic parameters, including disease stage, lymphovascular invasion, and tumor budding. The greatest multivariable HRs were observed for the average percentage method (cohort 1: HR for ≥ 40% vs. <3% 3.03, 95% CI, 1.93-4.78; cohort 2: HR for ≥ 40% vs. < 3% 2.97; 95% CI, 1.63-5.40). All 3 methods had high reproducibility, with the linear method showing the highest mean Spearman's correlation coefficient (0.91) and Cohen's kappa (0.70). In conclusion, detailed criteria for tumor necrosis evaluation were established. All 3 methods showed good reproducibility and predictive ability. The findings pave the way for the use of tumor necrosis as a prognostic factor in colorectal cancer.

AI-algorithm training and validation for identification of endometrial CD138+ cells in infertility-associated conditions; polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF).

Background: Endometrial CD138+ plasma cells serve as a diagnostic biomarker for endometrial inflammation, and their elevated occurrence correlates positively with adverse pregnancy outcomes. Infertility-related conditions like polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) are closely associated with systemic and local chronic inflammatory status, wherein endometrial CD138+ plasma cell accumulation could also contribute to endometrial pathology. Current methods for quantifying CD138+ cells typically involve laborious and time-consuming microscopic assessments of only a few random areas from a slide. These methods have limitations in accurately representing the entire slide and are susceptible to significant biases arising from intra- and interobserver variations. Implementing artificial intelligence (AI) for CD138+ cell identification could enhance the accuracy, reproducibility, and reliability of analysis. Methods: Here, an AI algorithm was developed to identify CD138+ plasma cells within endometrial tissue. The AI model comprised two layers of convolutional neural networks (CNNs). CNN1 was trained to segment epithelium and stroma across 28,363 mm2 (2.56 mm2 of epithelium and 24.87 mm2 of stroma), while CNN2 was trained to distinguish stromal cells based on CD138 staining, encompassing 7345 cells in the object layers (6942 CD138- cells and 403 CD138+ cells). The training and performance of the AI model were validated by three experienced pathologists. We collected 193 endometrial tissues from healthy controls (n = 73), women with PCOS (n = 91), and RIF patients (n = 29) and compared the CD138+ cell percentages based on cycle phases, ovulation status, and endometrial receptivity utilizing the AI model. Results: The AI algorithm consistently and reliably distinguished CD138- and CD138+ cells, with total error rates of 6.32% and 3.23%, respectively. During the training validation, there was a complete agreement between the decisions made by the pathologists and the AI algorithm, while the performance validation demonstrated excellent accuracy between the AI and human evaluation methods (intraclass correlation; 0.76, 95% confidence intervals; 0.36-0.93, p = 0.002) and a positive correlation (Spearman's rank correlation coefficient: 0.79, p < 0.01). In the AI analysis, the AI model revealed higher CD138+ cell percentages in the proliferative phase (PE) endometrium compared to the secretory phase or anovulatory PCOS endometrium, irrespective of PCOS diagnosis. Interestingly, CD138+ percentages differed according to PCOS phenotype in the PE (p = 0.03). On the other hand, the receptivity status had no impact on the cell percentages in RIF samples. Conclusion: Our findings emphasize the potential and accuracy of the AI algorithm in detecting endometrial CD138+ plasma cells, offering distinct advantages over manual inspection, such as rapid analysis of whole slide images, reduction of intra- and interobserver variations, sparing the valuable time of trained specialists, and consistent productivity. This supports the application of AI technology to help clinical decision-making, for example, in understanding endometrial cycle phase-related dynamics, as well as different reproductive disorders.

Dynamic changes in AI-based analysis of endometrial cellular composition: Analysis of PCOS and RIF endometrium.

Background: The human endometrium undergoes a monthly cycle of tissue growth and degeneration. During the mid-secretory phase, the endometrium establishes an optimal niche for embryo implantation by regulating cellular composition (e.g., epithelial and stromal cells) and differentiation. Impaired endometrial development observed in conditions such as polycystic ovary syndrome (PCOS) and recurrent implantation failure (RIF) contributes to infertility. Surprisingly, despite the importance of the endometrial lining properly developing prior to pregnancy, precise measures of endometrial cellular composition in these two infertility-associated conditions are entirely lacking. Additionally, current methods for measuring the epithelial and stromal area have limitations, including intra- and inter-observer variability and efficiency. Methods: We utilized a deep-learning artificial intelligence (AI) model, created on a cloud-based platform and developed in our previous study. The AI model underwent training to segment both areas populated by epithelial and stromal endometrial cells. During the training step, a total of 28.36 mm2 areas were annotated, comprising 2.56 mm2 of epithelium and 24.87 mm2 of stroma. Two experienced pathologists validated the performance of the AI model. 73 endometrial samples from healthy control women were included in the sample set to establish cycle phase-dependent dynamics of the endometrial epithelial-to-stroma ratio from the proliferative (PE) to secretory (SE) phases. In addition, 91 samples from PCOS cases, accounting for the presence or absence of ovulation and representing all menstrual cycle phases, and 29 samples from RIF patients on day 5 after progesterone administration in the hormone replacement treatment cycle were also included and analyzed in terms of cellular composition. Results: Our AI model exhibited reliable and reproducible performance in delineating epithelial and stromal compartments, achieving an accuracy of 92.40% and 99.23%, respectively. Moreover, the performance of the AI model was comparable to the pathologists' assessment, with F1 scores exceeding 82% for the epithelium and >96% for the stroma. Next, we compared the endometrial epithelial-to-stromal ratio during the menstrual cycle in women with PCOS and in relation to endometrial receptivity status in RIF patients. The ovulatory PCOS endometrium exhibited epithelial cell proportions similar to those of control and healthy women's samples in every cycle phase, from the PE to the late SE, correlating with progesterone levels (control SE, r2 = 0.64, FDR < 0.001; PCOS SE, r2 = 0.52, FDR < 0.001). The mid-SE endometrium showed the highest epithelial percentage compared to both the early and late SE endometrium in both healthy women and PCOS patients. Anovulatory PCOS cases showed epithelial cellular fractions comparable to those of PCOS cases in the PE (Anovulatory, 14.54%; PCOS PE, 15.56%, p = 1.00). We did not observe significant differences in the epithelial-to-stroma ratio in the hormone-induced endometrium in RIF patients with different receptivity statuses. Conclusion: The AI model rapidly and accurately identifies endometrial histology features by calculating areas occupied by epithelial and stromal cells. The AI model demonstrates changes in epithelial cellular proportions according to the menstrual cycle phase and reveals no changes in epithelial cellular proportions based on PCOS and RIF conditions. In conclusion, the AI model can potentially improve endometrial histology assessment by accelerating the analysis of the cellular composition of the tissue and by ensuring maximal objectivity for research and clinical purposes.

Whole-exome sequencing reveals candidate high-risk susceptibility genes for endometriosis.

BACKGROUND: Endometriosis is a common, chronic disease among fertile-aged women. Disease course may be highly invasive, requiring extensive surgery. The etiology of endometriosis remains elusive, though a high level of heritability is well established. Several low-penetrance predisposing loci have been identified, but high-risk susceptibility remains undetermined. Endometriosis is known to increase the risk of epithelial ovarian cancers, especially of endometrioid and clear cell types. Here, we have analyzed a Finnish family where four women have been diagnosed with surgically verified, severely symptomatic endometriosis and two of the patients also with high-grade serous carcinoma. RESULTS: Whole-exome sequencing revealed three rare candidate predisposing variants segregating with endometriosis. The variants were c.1238C>T, p.(Pro413Leu) in FGFR4, c.5065C>T, p.(Arg1689Trp) in NALCN, and c.2086G>A, p.(Val696Met) in NAV2. The only variant predicted deleterious by in silico tools was the one in FGFR4. Further screening of the variants in 92 Finnish endometriosis and in 19 endometriosis-ovarian cancer patients did not reveal additional carriers. Histopathology, positive p53 immunostaining, and genetic analysis supported the high-grade serous subtype of the two tumors in the family. CONCLUSIONS: Here, we provide FGFR4, NALCN, and NAV2 as novel high-risk candidate genes for familial endometriosis. Our results also support the association of endometriosis with high-grade serous carcinoma. Further studies are required to validate the findings and to reveal the exact pathogenesis mechanisms of endometriosis. Elucidating the genetic background of endometriosis defines the etiology of the disease and provides opportunities for expedited diagnostics and personalized treatments.

Programmed death-ligand 1 and tumor-infiltrating lymphocytes (TILs) - low TIL density may predict poorer long-term prognosis in T1 laryngeal cancer.

We evaluated the prognostic role of programmed death-ligand 1 (PD-L1) and tumor-infiltrating lymphocytes (TILs) in T1 glottic laryngeal squamous cell carcinoma (LSCC). T1 glottic LSCC patients (n = 174) treated at five Finnish university hospitals between 2003 and 2013 were included. Tissue microarray (TMA) blocks were used for PD-L1 immunohistochemistry. TILs were scored from intratumoral and stromal regions in whole tissue sections. Of 174 patients, 92 (53%) had negative, 66 (38%) intermediate, and 16 (9%) high PD-L1 levels. Of 80 patients whose TILs were analyzed, 50 (63%) had low and 30 (38%) high stromal TIL density. Patients with a local recurrence or a new primary tumor of the larynx had lower TIL density than had other patients (p = 0.047). High PD-L1 expression with low stromal TIL density was associated with inferior 5-year disease-specific survival (85% vs. 100%, p = 0.02). In conclusion, in patients treated for T1 glottic LSCC, low stromal TIL density was associated with local recurrences and new primary tumors of the larynx. High PD-L1 expression with low stromal TIL density may be associated with worse survival in T1 glottic LSCC.

Absence of NC14A Domain of COLXVII/BP180 in Mice Results in IL-17‒Associated Skin Inflammation.

The deletion of exon 18 from Col17a1 in transgenic ΔNC14A mice results in the absence of the NC14A domain. NC14A corresponds to the human NC16A domain, the immunodominant epitope in bullous pemphigoid. Before the age of 1 year, 84% of ΔNC14A mice have developed severe itch and skin erosion. Further characterization of mice with mutated CoLXVII (Bp180) revealed acanthosis; subepidermal blistering; and inflammatory cell infiltrates, especially neutrophils, eosinophils, and mast cells in the lesional skin. Direct immunofluorescence analysis detected linear complement C3, IgG, and/or IgA deposition in the dermo‒epidermal junction of symptomatic ΔNC14A mice. Elevated gene expression of IL-17‒associated cytokines was detected in the lesional skin. An increased proportion of dendritic cells, myeloid-derived suppressor cells, and NK cells and a decrease of T cells were found in both the spleen and lymph nodes of symptomatic ΔNC14A mice. The proportions of B cells and regulatory T cells were increased in lymph nodes. An 8-week treatment with an anti‒IL-17A decreased the expression of Il6, Il23a, and Cxcl1 in the nonlesional skin. Our results suggest that the absence of the NC14A domain of CoLXVII in mice causes an autoimmune response against the cutaneous basement membrane and manifests as an IL-17‒associated inflammation in the skin.

Presence of distinctive microbiome in the first-pass meconium of newborn infants.

We critically evaluated the fetal microbiome concept in 44 neonates with placenta, amniotic fluid, and first-pass meconium samples. Placental histology showed no signs of inflammation. Meconium samples were more often bacterial culture positive after vaginal delivery. In next-generation sequencing of the bacterial 16S gene, before and after removal of extracellular and PCR contaminant DNA, the median number of reads was low in placenta (48) and amniotic fluid (46) and high in meconium samples (14,556 C-section, 24,860 vaginal). In electron microscopy, meconium samples showed extracellular vesicles. Utilizing the analysis of composition of microbiomes (ANCOM) against water, meconium samples had a higher relative abundance of Firmicutes, Lactobacillus, Streptococcus, and Escherichia-Shigella. Our results did not support the existence of the placenta and amniotic fluid microbiota in healthy pregnancies. The first-pass meconium samples, formed in utero, appeared to harbor a microbiome that may be explained by perinatal colonization or intrauterine colonization via bacterial extracellular vesicles.

RhoG deficiency abrogates cytotoxicity of human lymphocytes and causes hemophagocytic lymphohistiocytosis.

Exocytosis of cytotoxic granules (CG) by lymphocytes is required for the elimination of infected and malignant cells. Impairments in this process underly a group of diseases with dramatic hyperferritinemic inflammation termed hemophagocytic lymphohistiocytosis (HLH). Although genetic and functional studies of HLH have identified proteins controlling distinct steps of CG exocytosis, the molecular mechanisms that spatiotemporally coordinate CG release remain partially elusive. We studied a patient exhibiting characteristic clinical features of HLH associated with markedly impaired cytotoxic T lymphocyte (CTL) and natural killer (NK) cell exocytosis functions, who beared biallelic deleterious mutations in the gene encoding the small GTPase RhoG. Experimental ablation of RHOG in a model cell line and primary CTLs from healthy individuals uncovered a hitherto unappreciated role of RhoG in retaining CGs in the vicinity of the plasma membrane (PM), a fundamental prerequisite for CG exocytotic release. We discovered that RhoG engages in a protein-protein interaction with Munc13-4, an exocytosis protein essential for CG fusion with the PM. We show that this interaction is critical for docking of Munc13-4+ CGs to the PM and subsequent membrane fusion and release of CG content. Thus, our study illuminates RhoG as a novel essential regulator of human lymphocyte cytotoxicity and provides the molecular pathomechanism behind the identified here and previously unreported genetically determined form of HLH.

Autoantibodies Against the Immunodominant Bullous Pemphigoid Epitopes Are Rare in Patients With Dermatitis Herpetiformis and Coeliac Disease.

Dermatitis herpetiformis (DH) is an extraintestinal manifestation of coeliac disease (CD). Patients with DH have an elevated risk of development of another autoimmune blistering skin disease, bullous pemphigoid (BP). In this study we investigated whether patients with DH and CD (mean age for both 49 years) have circulating autoantibodies against BP180, the major BP autoantigen. ELISA tests showed that only a few DH (3/46) and CD (2/43) patients had BP180-NC16A IgG autoantibodies. Immunoblotting found that more than half of the DH samples contained IgG autoantibodies against full-length BP180. Epitope mapping with 13 fusion proteins covering the BP180 polypeptide revealed that in DH and CD patients, IgG autoantibodies did not target the NC16A or other epitopes typical of BP but recognized other intracellular and mid-extracellular regions of BP180. None of the analyzed DH and CD patients with either ELISA or immunoblotting positivity had IgG or IgA reactivity against the cutaneous basement membrane in indirect immunofluorescence analysis or skin symptoms characteristic of BP. Although only a minority of middle-aged DH patients had IgG autoantibodies against the immunodominant epitopes of BP180, our results do not exclude the possibility that intermolecular epitope spreading could explain the switch from DH to BP in elderly patients.

Gliptin-associated Bullous Pemphigoid and the Expression of Dipeptidyl Peptidase-4/CD26 in Bullous Pemphigoid.

Dipeptidyl peptidase-4 inhibitors (DPP-4i or gliptins) increase the risk of developing bullous pemphigoid (BP). To clarify, whether gliptin-associated BP has special features, we analyzed the clinical, histopathological and immunological features of 27 BP patients, 10 of which previously used gliptin medication. Compared to those who had not previously received gliptins, subjects who had, showed higher BP180-NC16A ELISA (enzyme-linked immunosorbent assay) values, fewer neurological co-morbidities and shorter time to remission, but differences were not statistically significant. The HLA-DQB1*03:01 allele was more commonly present among the BP patients than the control population, but was not more common in those with gliptin history. To determine the effect of gliptins on the expression of the DPP-4/CD-26 protein we performed immunohistochemistry, which showed that the skin expression of DPP-4/CD-26 was increased in BP patients, but not affected by prior gliptin treatment. We conclude that DPP-4i medication is common among BP patients and prior gliptin treatment may be associated with some specific features.

BP180 Autoantibodies Target Different Epitopes in Multiple Sclerosis or Alzheimer's Disease than in Bullous Pemphigoid.

Neurologic patients have an increased risk for bullous pemphigoid (BP), in which autoantibodies target BP180, a cutaneous basement membrane protein also expressed in the brain. Here we show that 53.6% of sera from patients with multiple sclerosis (MS) (n = 56) had IgG reactivity against full-length BP180 in immunoblotting, while in BP180 non-collagenous 16A ELISA (n = 143), only 7.7% of MS samples studied were positive. Epitope mapping with 13 fusion proteins covering the entire BP180 polypeptide revealed that in MS and Alzheimer's disease (AD) patients, IgG autoantibodies target regions located in the intracellular and mid-extracellular parts of BP180, but not the well-known BP epitopes located in the non-collagenous 16A domain and the distal part of extracellular domain. In indirect immunofluorescence analysis, 8.1% of MS sera recognized the cutaneous basement membrane and in full-length BP180 ELISA analysis, 7.5% MS and AD sera were positive, indicating that these autoantibodies rarely recognize BP180 in its native conformation. Thus, in MS and AD patients, BP180 autoantibodies have a different epitope profile than in patients with BP, and seldom bind to native BP180. This explains the inability of these autoantibodies to cause skin symptoms. Our results suggest that the autoantibodies against BP180 alone are not sufficient to induce BP in MS and AD patients.