Malignant Samples Research Articles

Liquid-based Cytological Features of Adenocarcinoma Not Otherwise Specified, Extrauterine Adenocarcinoma, and Other Malignant Neoplasms of The Uterine Cervix: A 5-year Single-institutional Experience With 30 Consecutive Patients.

The adenocarcinoma (ADC) and other malignant neoplasm (OMN) terminologies of The Bethesda System represent various histological types of uterine and extrauterine malignancies. This study aimed to clarify the incidences of ADC not otherwise specified (ADC-NOS), ADC extrauterine (ADC-EXT), and OMN in our institution and describe their characteristic cytomorphological features. We searched the database to identify all patients diagnosed with carcinoma, including those diagnosed through cervical liquid-based cytology (LBC), between January 2019 and December 2023. The electronic medical records and all available slides were reviewed. Overall, 30 of the 149,197 (0.02%) patients were diagnosed with ADC-NOS, ADC-EXT, and OMN. All three groups included various histological types of both gynecological and non-gynecological origin. More than two-thirds (23/30; 76.7%) were of uterine origin, but seven patients had metastatic carcinoma of extrauterine organ origin, including the ovary, lung, stomach, breast, colon, urethra, and pancreas. In all patients, the cytological features were concordant with the histological features. In LBC, ADC-NOS does not only encompass uterine cervical tumors, but also various types of extrauterine malignancies. ADC-EXT and OMN also represent both extrauterine and uterine tumors. Awareness of the morphological features observed in LBC samples of non-gynecological malignancies may be helpful in obtaining the correct diagnosis.

Low SMARCD3 expression is associated with poor prognosis in patients with prostate cancer.

SWI/SNF complexes represent a family of multi-subunit chromatin remodelers that are affected by alterations in >20% of human tumors. While mutations of SWI/SNF genes are relatively uncommon in prostate cancer (PCa), the literature suggests that deregulation of various subunits plays a role in prostate tumorigenesis. To assess SWI/SNF functions in a clinical context, we studied the mutually exclusive, paralogue accessory subunits SMARCD1, SMARCD2, and SMARCD3 that are included in every known complex and are sought to confer specificity. Performing immunohistochemistry (IHC), the protein levels of the SMARCD family members were measured using a tissue microarray (TMA) comprising malignant samples and matching healthy tissue of non-metastatic PCa patients (n = 168). Moreover, IHC was performed in castration-resistant tumors (n = 9) and lymph node metastases (n = 22). To assess their potential role as molecular biomarkers, SMARCD1 and SMARCD3 protein levels were correlated with clinical parameters such as T stage, Gleason score, biochemical recurrence, and progression-free survival. SMARCD1 protein levels in non-metastatic primary tumors, lymph node metastases, and castration-resistant samples were significantly higher than in benign tissues. Likewise, SMARCD3 protein expression was elevated in tumor tissue and especially lymph node metastases compared to benign samples. While SMARCD1 levels in primary tumors did not exhibit significant associations with any of the tested clinical parameters, SMARCD3 exhibited an inverse correlation with pre-operative PSA levels. Moreover, low SMARCD3 expression was associated with progression to metastasis. In congruence with previous literature, our results implicate that both SMARCD1 and SMARCD3 may exhibit relevant functions in the context of prostate tumorigenesis. Moreover, our approach suggests a potential role of SMARCD3 as a novel prognostic marker in clinically non-metastatic PCa.

Differential Urinary Microbiome and Its Metabolic Footprint in Bladder Cancer Patients Following BCG Treatment.

Recent studies have identified a urinary microbiome, dispelling the myth of urine sterility. Intravesical bacillus Calmette-Guérin (BCG) therapy is the preferred treatment for intermediate to high-risk non-muscle-invasive bladder cancer (BCa), although resistance occurs in 30-50% of cases. Progression to muscle-invasive cancer necessitates radical cystectomy. Our research uses 16S rRNA gene sequencing to investigate how the urinary microbiome influences BCa and its response to BCG therapy. Urine samples were collected via urethral catheterization from patients with benign conditions and non-muscle-invasive BCa, all of whom underwent BCG therapy. We utilized 16S rRNA gene sequencing to analyze the bacterial profiles and metabolic pathways in these samples. These pathways were validated using a real metabolite dataset, and we developed predictive models for malignancy and BCG response. In this study, 87 patients participated, including 29 with benign diseases and 58 with BCa. We noted distinct bacterial compositions between benign and malignant samples, indicating the potential role of the toluene degradation pathway in mitigating BCa development. Responders to BCG had differing microbial compositions and higher quinolone synthesis than non-responders, with two Bifidobacterium species being prevalent among responders, associated with prolonged recurrence-free survival. Additionally, we developed highly accurate predictive models for malignancy and BCG response. Our study delved into the mechanisms behind malignancy and BCG responses by focusing on the urinary microbiome and metabolic pathways. We pinpointed specific beneficial microbes and developed clinical models to predict malignancy and BCG therapy outcomes. These models can track recurrence and facilitate early predictions of treatment responses.

8109 Cancer-Associated Fibroblasts Correlate with Aggressive Thyroid Cancer Behavior: Insights from Four Large Patient Cohorts

Abstract Disclosure: M.A. Loberg: None. X. George: None. P.J. Courtney: None. H.C. Eric: None. A. Golding: None. B. David: None. M. Alshalalfa: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. Y. Hao: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. J.P. Klopper: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc. R.T. Kloos: Employee; Self; Veracyte, Inc.. Stock Owner; Self; Veracyte, Inc.. V. Weiss: None. Thyroid tumor molecular analysis often utilizes fine-needle aspirate (FNA) samples to predict malignancy with high sensitivity. An outstanding question is if molecular sequencing can provide prognostic information to predict disease aggression, potentially informing management. Recently, the composition of the tumor microenvironment, in particular the presence of tumor-promoting fibroblasts, has been associated with aggressive thyroid cancer. However, fibroblast gene expression has not previously been analyzed in thyroid tumor FNA samples. In this work, we detect cancer-associated fibroblast (CAF) gene signatures across 4 distinct bulk RNA sequencing cohorts and confirm detection in FNA samples. Associations between CAF gene signatures and tumor characteristics were explored in: Afirma Genomic Sequencing Classifier (GSC) cohort from FNA (n=47,695), a Memorial Healthcare System (MHS) retrospective FNA cohort with pathology outcome data (n=318), TCGA papillary thyroid cancers (n=496), and a Vanderbilt University Medical Center-University of Washington (VUMC-UW) resection cohort (n=312). Published breast CAF gene sets were used to generate normal fibroblast and CAF subtype scores. Novel thyroid cancer specific CAF gene sets were generated from thyroid cancer single-cell RNA sequencing data. Scores for each gene set were calculated as the average Z-score. Across all cohorts, multiple CAF subsets were enriched in samples with BRAFV600E and papillary histology. The strongest enrichment was in an SFRP2+ CAF subset identified in thyroid cancer single-cell sequencing data. In Afirma GSC FNA samples, SFRP2+ CAFs were enriched in GSC-suspicious and Bethesda V/VI relative to GSC-benign nodules (Wilcoxon p value < 2e-[1]6 for all). In TCGA, SFRP2+ CAFs were associated with extrathyroidal extension, advanced disease stage, and aggressive histology. In the MHS cohort of 318 malignant FNA samples, SFRP2+ CAFs were significantly higher in patients with vascular invasion or lymph node metastasis (LNM) (OR:2.75 [95% CI 1.63-4.75], p=4e-5). In the VUMC-UW cohort, SFRP2+ CAFs were associated with shorter progression-free survival (PFS) (p=0.0033). In summary we created a novel thyroid cancer-specific CAF gene signature that is elevated in BRAFV600E+ and aggressive thyroid cancers across multiple large patient cohorts. We also demonstrated the ability to detect these CAF signatures in thyroid FNAs using the Afirma GSC molecular testing platform, with enrichment in suspicious and malignant samples. Amongst the CAF scores tested, thyroid-specific CAF subsets had the highest prognostic potential, and SFRP2+ CAFs, specifically, were associated with shorter PFS, tumor invasion and LNM. Together, these results highlight the potential of interrogating the thyroid tumor stroma in FNA using RNA-based assays to inform prognosis and possibly management. Presentation: 6/3/2024

B-314 Utility of he4 in differential diagnosis of pleural effusions

Abstract Background The usefulness of tumor markers in the differential diagnosis of cancer in patients with pleural effusions (PE) remains controversial. Few studies have reported the measurement of human epididymal protein 4 (HE4) in pleural fluid. HE4 is a tumor marker associated with different types of cancer. An elevated serum concentration has been observed in ovarian and lung cancers. Other benign pathologies can increase HE4 levels, which can be detect with different laboratory tests identified with adenosine deaminase (ADA), C-reactive protein (CRP), % polynuclear cell count (%PMN) and glomerular filtration rate (GFR) can be used in order to detect possible false positives. The objective of this study was to assess the diagnostic usefulness of HE4 in malignant pleural effusions by comparing HE4 concentrations between benign and malignant samples, while considering the causes of HE4 false positives. Methods HE4, ADA, differential leukocyte count, CRP and GFR concentrations were determined in 238 pleural effusion samples. Diagnostic efficacy analysis using receiver operating curves (ROC) identified the ability of HE4 to detect malignancy, searching for cut-off points with 100% specificity. Results HE4 concentrations showed significant differences (P<0.01) between malignant (median 1065pmol/L) and benign (median 699pmol/L) pleural effusions. Significant differences (P<0.01) were found in HE4 concentrations for gynecological and lung cancer origin (median 7397 pmol/L and 5150 pmol/L respectively) and other malignant pleural effusions (median 1065 pmol/L). Patients with benign diseases with renal failure showed a higher HE4 concentration (median 964pmol/L) than in patients without these pathologies (median 696pmol/L) identified with GFR<30 mL/min. No differences were demonstrated in HE4 concentration levels using ADA, differential leukocyte count or CRP, so only glomerular filtration rate was considered cause of false positives. A sensitivity of 23% was obtained for HE4, with a cut-off point of 3050pmol/L and a specificity of 100% for the whole group. In the potential false positive group, the sensitivity of HE4 was 28% with a cutoff point of 3050 pmol/L with a specificity of 100%. In the group without potential false positives, we obtained a sensitivity of 30% with a specificity of 100% for a cutoff point of 1992pmol/L. When we used a specific cut-off point for each group, we obtained a sensitivity of 38% with a specificity of 100%. Conclusions HE4 levels are higher in malignant pleural effusions compared to other pathologies. HE4 levels allow the identification of malignant pleural effusions with moderate sensitivity and maximum specificity. HE4 levels can differentiate between tumors of gynecological or lung origin and others. Glomerular filtration rate (GFR<30 mL/min) was considered the main cause of false positives. If we identify possible false positives, we can use specific cut-offs and improve sensitivity up to 38% with maximum specificity compared to using a single cut-off for all effusions.

Single-cell characterization of differentiation trajectories and drug resistance features in gastric cancer with peritoneal metastasis.

Gastric cancer patients with peritoneal metastasis (GCPM) experience a rapidly deteriorating clinical trajectory characterized by therapeutic resistance and dismal survival, particularly following the development of malignant ascites. However, the intricate dynamics within the peritoneal microenvironment (PME) during the treatment process remain largely unknown. Matched samples from primary tumours (PT), peritoneal metastases (PM), and paired pre-treatment and post-chemo/immunotherapy (anti-PD-1/PD-L1) progression malignant ascites samples, were collected from 48 patients. These samples were subjected to single-cell RNA sequencing (n=30), multiplex immunofluorescence (n=30), and spatial transcriptomics (n=3). Furthermore, post hoc analyses of a phase 1 clinical trial (n=20, NCT03710265) and an in-house immunotherapy cohort (n=499) were conducted to validate the findings. Tracing the evolutionary trajectory of epithelial cells unveiled the terminally differentially MUC1+ cancer cells with a high epithelial-to-mesenchymal transition potential, and they demonstrated spatial proximity with fibroblasts and endothelial cells, correlating with poor prognosis. A significant expansion of macrophage infiltrates, which exhibited the highest proangiogenic activity, was observed in the ascites compared with PT and PM. Besides, higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T-lymphocyte infiltrates in therapeutic failure cases, potentially mediated by the LGALS9-CD45 and SPP1-CD44 ligand-receptor interactions. In the chemoresistant group, intimate interactions between C1Q+ macrophages and fibroblasts through the complement activation pathway were found. In the group demonstrating immunoresistance, heightened TGF-β production activity was detected in MUC1+ cancer cells, and they were skewed to interplay with C1Q+ macrophages through the GDF15-TGF-βR2 axis. Ultimately, post hoc analyses indicated that co-targeting TGF-β and PDL1 pathways may confer superior clinical benefits than sole anti-PD-1/PD-L1 therapy for patients presenting with GCPM at the time of diagnosis. Our findings elucidated the cellular differentiation trajectories and crucial drug resistance features within PME, facilitating the exploration of effective targets for GCPM treatment. MUC1+ cancer cells with a high epithelial-to-mesenchymal transition potential and exhibiting spatial proximity to fibroblasts and endothelial cells constitute the driving force of gastric cancer peritoneal metastasis (GCPM). Higher C1Q+ macrophage infiltrates correlated with significantly lower GZMA+ T-lymphocyte infiltrates within the peritoneal microenvironment in therapeutic failure cases. Co-targeting TGF-β and PDL1 pathways may confer superior clinical benefits than sole anti-PD-1/PD-L1 therapy for patients presenting with GCPM at diagnosis.

Integrated multiomics revealed adenosine signaling predict immunotherapy response and regulate tumor ecosystem of melanoma

Extracellular adenosine is extensively involved in regulating the tumor microenvironment. Given the disappointing results of adenosine-targeted therapy trials, personalized treatment might be necessary, tailored to the microenvironment status of individual patients. Here, we introduce the adenosine signaling score (ADO-score) model using non-negative matrix fraction identified patient subtypes using publicly available melanoma dataset, which aimed to profile adenosine signaling-related genes and construct a model to predict prognosis. We analyzed 580 malignant melanoma samples and demonstrated its robust value for prognosis. Further investigation in immune checkpoint inhibitor dataset suggests its potential as a stratified factor of immune checkpoint inhibitor efficacy. We validated the power of the ADO-score at the protein level immunofluorescence in a melanoma cohort from Xiangya Hospital. More importantly, single-cell and spatial transcriptomic data highlighted the cell-specific expression patterns of adenosine signaling-related genes and the existence of adenosine signaling-mediated crosstalk between tumor cells and immune cells in melanoma. Our study reveals a robust connection between adenosine signaling and clinical benefits in melanoma patients and proposes a universally applicable adenosine signaling model, the ADO-score, in gene expression profiles and histological sections. This model enables us to more precisely and conveniently select patients who are likely to benefit from immunotherapy.

Non-Invasive Endometrial Cancer Screening through Urinary Fluorescent Metabolome Profile Monitoring and Machine Learning Algorithms.

Endometrial cancer is becoming increasingly common, highlighting the need for improved diagnostic methods that are both effective and non-invasive. This study investigates the use of urinary fluorescence spectroscopy as a potential diagnostic tool for endometrial cancer. Urine samples were collected from endometrial cancer patients (n = 77), patients with benign uterine tumors (n = 23), and control gynecological patients attending regular checkups or follow-ups (n = 96). These samples were analyzed using synchronous fluorescence spectroscopy to measure the total fluorescent metabolome profile, and specific fluorescence ratios were created to differentiate between control, benign, and malignant samples. These spectral markers demonstrated potential clinical applicability with AUC as high as 80%. Partial Least Squares Discriminant Analysis (PLS-DA) was employed to reduce data dimensionality and enhance class separation. Additionally, machine learning models, including Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD), were utilized to distinguish between controls and endometrial cancer patients. PLS-DA achieved an overall accuracy of 79% and an AUC of 90%. These promising results indicate that urinary fluorescence spectroscopy, combined with advanced machine learning models, has the potential to revolutionize endometrial cancer diagnostics, offering a rapid, accurate, and non-invasive alternative to current methods.

Spatial profiling of non-small cell lung cancer provides insights into tumorigenesis and immunotherapy response

Lung cancer is the second most common cancer worldwide and a leading cause of cancer-related deaths. Despite advances in targeted therapy and immunotherapy, the prognosis remains unfavorable, especially in metastatic cases. This study aims to identify molecular changes in non-small cell lung cancer (NSCLC) patients based on their response to treatment. Using tumor and matched immune cell rich peritumoral tissues, we perform a retrospective, comprehensive spatial transcriptomic analysis of a proven malignant NSCLC sample treated with immune checkpoint inhibitor (ICI). In addition to T cells, other immune cell types, such as B cells and macrophages, were also activated in responders to ICI treatment. In particular, B cells and B cell-mediated immunity pathways are consistently found to be activated. Analysis of the histologic subgroup (lung squamous cell carcinoma, LUSC; lung adenocarcinoma, LUAD) of NSCLC also confirms activation of B cell mediated immunity. Analysis of B cell subtypes shows that B cell subtypes were more activated in immune cell-rich tissues near tumor tissue. Furthermore, increased expression of B cell immunity-related genes is associated with better prognosis. These findings provide insight into predicting ICI treatment responses and identifying appropriate candidates for immunotherapy in NSCLC patients.

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk of false-negative results. Surface-enhanced Raman spectroscopy (SERS) combined with machine learning algorithms holds promise for cancer diagnosis. In this study, we develop a label-free SERS liquid biopsy method with machine learning for the rapid and accurate diagnosis of thyroid cancer by using thyroid FNA washout fluids. These liquid supernatants are mixed with silver nanoparticle colloids, and dispersed in quartz capillary for SERS measurements to discriminate between healthy and malignant samples. We collect Raman spectra of 36 thyroid FNA samples (18 malignant and 18 benign) and compare four classification models: Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA), Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN). The results show that the CNN algorithm is the most precise, with a high accuracy of 88.1%, sensitivity of 87.8%, and the area under the receiver operating characteristic curve of 0.953. Our approach is simple, convenient, and cost-effective. This study indicates that label-free SERS liquid biopsy assisted by deep learning models holds great promise for the early detection and screening of thyroid cancer.

Investigation of SPOCD1 as A Suitable Diagnostic and Prognostic Biomarker in Various Common Cancer Types: Bioinformatics and Practical Analysis.

The objective of this study was to assess whether Spen paralogue and orthologue C-terminal domain containing 1 (SPOCD1) gene expression could serve as a valuable prognostic and diagnostic biomarker in common cancers, drawing from insights in recent literature. We sought to verify this concept by utilizing data sourced from The Cancer Genome Atlas (TCGA) alongside clinical samples. In this bioinformatics and experimental study, SPOCD1 RNA-seq data from 12 common cancers were collected from TCGA Pan-Cancer Atlas using the R package "TCGA BIOLINKS" and normalized for analysis. Various analytical tools, including receiver operating characteristic (ROC) curves, Kaplan-Meier and Coxregression analyses, and pathway enrichment analysis via the molecular signatures database (MSigDB), were applied. Drug resistance/sensitivity correlations with SPOCD1 expression were explored using the Gene Expression Omnibus (GEO) database. Clinical colorectal cancer (CRC) samples, including both colon and rectal malignant samples, were also evaluated. The results showed elevated SPOCD1 expression in most cancers (9/12), with notable prognostic value in COAD, HNSC, KICH, and LIHC, and a correlation with poor prognosis in COAD for disease-free survival. ROC curve analysis suggested SPOCD1 as a diagnostic biomarker in the majority of cases (7/12), although this pattern was inconsistent in clinical CRC samples. Pathway enrichment analysis revealed a strong correlation between SPOCD1 expression and critical molecular pathways. Unlike former results, we found that SPOCD1 upregulated when interacting with PD-0325901. However, treating with Panobinostat led to downregulation. Both are as anticancer reagents. This study confirms the potential of SPOCD1 as a diagnostic and prognostic biomarker in prevalent cancers. However, extensive clinical data, particularly for CRC, are required to validate its reliability. Different COAD subtypes may exhibit varying correlations with SPOCD1 expression levels, underscoring the need for further investigation to fully understand its diagnostic and prognostic value.

Zeolite Functionalized with Magnesium/Aluminum/Lanthanum Ternary Hydroxide for the Phosphometabolite Profiling of Malignant Neoplastic Serum Samples.

ATP upregulation is a significant driver of aggressive cancer cell phenotypes. Phosphometabolites participate in metabolic pathways and are overexpressed in cancer cell activity. Therefore, developing novel and accurate methods for detecting phosphometabolites in biological fluids is essential. In this research, a novel zeolite composite comprising magnesium, aluminum, and lanthanum hydroxides (MALZ) is developed and used for the first time to enrich phosphorylated metabolites via its inherent interaction with phosphate groups. SEM micrographs show a crystalline cubic structure with a small diameter of 36.62 nm. FTIR analysis confirms the phosphate adsorption and desorption using AMP and ATP as the standards. XRD analysis of MALZ provides structural information about the synthesized composite. Adsorption-desorption parameters, such as pH, shaking time, and MALZ concentration, are optimized to analyze the binding capacity of the fabricated material for phosphorylated metabolites. A kinetic study reveals the rapid and effective AMP and ATP adsorptions on MALZ. The multiple hydroxyl groups of ternary hydroxides and high affinity of lanthanum toward the phosphate group enrich 26 phosphometabolites from serum samples of malignant neoplastic patients. The LC-MS profile shows characteristic phosphometabolites that may act as signatures of cancer-related abnormal metabolic pathways. This study may provide an experimental pathway for detecting metabolites in human body fluids.

Conundrum in primary care: should all cervical polyps be removed?

The management of asymptomatic cervical polyps has long been debated due to the scarcity of literature and guidelines regarding the need for polypectomy. While the majority of cervical polyps are diagnosed incidentally by GPs during routine cervical smears, there are no clear recommendations on referral pathways for further histological investigations. To investigate the need for polypectomy in women presenting with asymptomatic polyps. In addition, the study explores potential suggestions and guidelines for the referral of asymptomatic cervical polyps in general practice. A retrospective study on the histological findings of extracted cervical polyps examined by the pathology department at the Countess of Chester Hospital (COCH) over 9 years (2010- 2019). Of the 514 patients presented with cervical polyps (74% were asymptomatic), approximately 97% of the referrals made were by GPs. Additionally, we identified 74 inappropriate referrals through the 2-week wait cancer pathway. Overall, there were no malignant samples and five (0.97%) premalignant lesions were presented. This study supported the evidence that most cervical polyps are benign. However, inappropriate referrals prompt more education on cervical pathologies. Furthermore, there is a need for robust guidelines on the management of asymptomatic cervical polyps in general practice. To lessen the financial burden of managing cervical polyps in a secondary care setting, workshops on polyp removal can be developed for GPs.

Automated Whole Slide Imaging for Label-Free Histology Using Photon Absorption Remote Sensing Microscopy.

Pathologists rely on histochemical stains to impart contrast in thin translucent tissue samples, revealing tissue features necessary for identifying pathological conditions. However, the chemical labeling process is destructive and often irreversible or challenging to undo, imposing practical limits on the number of stains that can be applied to the same tissue section. Here we present an automated label-free whole slide scanner using a PARS microscope designed for imaging thin, transmissible samples. Peak SNR and in-focus acquisitions are achieved across entire tissue sections using the scattering signal from the PARS detection beam to measure the optimal focal plane. Whole slide images (WSI) are seamlessly stitched together using a custom contrast leveling algorithm. Identical tissue sections are subsequently H&E stained and brightfield imaged. The one-to-one WSIs from both modalities are visually and quantitatively compared. PARS WSIs are presented at standard 40x magnification in malignant human breast and skin samples. We show correspondence of subcellular diagnostic details in both PARS and H&E WSIs and demonstrate virtual H&E staining of an entire PARS WSI. The one-to-one WSI from both modalities show quantitative similarity in nuclear features and structural information. PARS WSIs are compatible with existing digital pathology tools, and samples remain suitable for histochemical, immunohistochemical, and other staining techniques. This work is a critical advance for integrating label-free optical methods into standard histopathology workflows.

CD20-bispecific antibodies improve response to CD19-CAR T cells in lymphoma in vitro and CLL in vivo models

AbstractRelapse after anti-CD19 chimeric antigen receptor (CD19-CAR) occurs in a substantial proportion of patients with lymphoid malignancies. We assessed the potential benefits of co-administering CD20-targeting bispecific antibodies (CD20-BsAbs) with CD19-CAR T cells with the aim of enhancing immunotherapeutic efficacy. Addition of CD20-BsAbs to cocultures of CD19-CARs and primary samples of B-cell malignancies, comprising malignant B cells and endogenous T cells, significantly improved killing of malignant cells and enhanced the expansion of both endogenous T cells and CD19-CAR T cells. In an immunocompetent mouse model of chronic lymphocytic leukemia, relapse after initial treatment response frequently occurred after CD19-CAR T-cell monotherapy. Additional treatment with CD20-BsAbs significantly enhanced the treatment response and led to improved eradication of malignant cells. Higher efficacy was accompanied by improved T-cell expansion with CD20-BsAb administration and led to longer survival with 80% of the mice being cured with no detectable malignant cell population within 8 weeks of therapy initiation. Collectively, our in vitro and in vivo data demonstrate enhanced therapeutic efficacy of CD19-CAR T cells when combined with CD20-BsAbs in B-cell malignancies. Activation and proliferation of both infused CAR T cells and endogenous T cells may contribute to improved disease control.

Molecular Identification of the Gag and Tax Gene of Bovine Leukemia Virus (BLV) in Women with Breast Cancer

Background: Breast cancer is one of the most common cancers in the world particularly among Iranian women. Although the mortality rate decreased in developed countries, there were increased changes in breast cancer incidences. The study aimed at evaluating the correlation between BLV infection and breast cancer in Iran. Methods: In the cross-sectional study, a total of 85 breast cancer tissue samples and adjacent tumor samples (normal tissue) were collected during the year 2022 from women referred to general hospitals in Qom Province, Iran. The nested PCR technique was performed to determine the presence of tax and gag genes of BLV in the collected samples. To confirm the presence of the tax gene of BLV, PCR products of some BLV-positive samples were subjected to direct sequencing. Results: Based on nested PCR technique, tax and gag genes of BLV were detected in 12.9% (11.85) and 3.4% (3.85) of breast cancer tissue samples, respectively. Also, the tax gene was present in 4.7% of the control samples, but the presence of the gag gene was not observed. Most malignant samples of BLV were III grade. The constructed phylogenetic trees for the tax gene of BLV showed most BLV isolates had similar sequences to Iranian isolates. Conclusion: The results of the study by using nested PCR technique, demonstrate a possible relationship between human breast cancer and bovine leukemia virus infection in women of Iran. BLV is one of the main risk factors for breast cancer.

Classification of Benign-Malignant Thyroid Nodules Based on Hyperspectral Technology.

In recent years, the incidence of thyroid cancer has rapidly increased. To address the issue of the inefficient diagnosis of thyroid cancer during surgery, we propose a rapid method for the diagnosis of benign and malignant thyroid nodules based on hyperspectral technology. Firstly, using our self-developed thyroid nodule hyperspectral acquisition system, data for a large number of diverse thyroid nodule samples were obtained, providing a foundation for subsequent diagnosis. Secondly, to better meet clinical practical needs, we address the current situation of medical hyperspectral image classification research being mainly focused on pixel-based region segmentation, by proposing a method for nodule classification as benign or malignant based on thyroid nodule hyperspectral data blocks. Using 3D CNN and VGG16 networks as a basis, we designed a neural network algorithm (V3Dnet) for classification based on three-dimensional hyperspectral data blocks. In the case of a dataset with a block size of 50 × 50 × 196, the classification accuracy for benign and malignant samples reaches 84.63%. We also investigated the impact of data block size on the classification performance and constructed a classification model that includes thyroid nodule sample acquisition, hyperspectral data preprocessing, and an algorithm for thyroid nodule classification as benign and malignant based on hyperspectral data blocks. The proposed model for thyroid nodule classification is expected to be applied in thyroid surgery, thereby improving surgical accuracy and providing strong support for scientific research in related fields.

HPV Detection on Lung Interstitium Through Bronchoalveolar Lavage (BAL) in Patients from City Recife, Pernambuco-Brazil

Bronchoalveolar lavage (BAL) is a non-invasive tool that allows direct sampling of the lung interstitium, facilitating cytological, microbiological, and molecular analyses. The Human Papillomavirus (HPV), known for its oncogenic role mainly in the genital regions, also can be found in the lungs, but its pathological implications remain poorly elucidated. This study aims to identify the presence of HPV-DNA in patients with suspected lung diseases through BAL. A cross-sectional and analytical study was carried out involving 146 patients admitted to hospitals in the Metropolitan Region of Recife. To detect HPV DNA, 46 samples were processed using PCR technique with MY09/11 consensus primers, followed by Nested-PCR with GP5/6 primers. The presence of HPV-DNA was confirmed in 4 (8.69%) samples, all benign and suspected of interstitial diseases. These findings indicate the feasibility of detecting HPV in the lung interstitium by BAL using Nested-PCR and suggest a new perspective in understanding the presence of HPV in lung tissue. In addition, to corroborating the statement that HPV is not limited to tissue and malignant samples, offering a new methodological dimension to the HPV investigation on lung.

MAPP unravels frequent co-regulation of splicing and polyadenylation by RNA-binding proteins and their dysregulation in cancer

Maturation of eukaryotic pre-mRNAs via splicing and polyadenylation is modulated across cell types and conditions by a variety of RNA-binding proteins (RBPs). Although there exist over 1,500 RBPs in human cells, their binding motifs and functions still remain to be elucidated, especially in the complex environment of tissues and in the context of diseases. To overcome the lack of methods for the systematic and automated detection of sequence motif-guided pre-mRNA processing regulation from RNA sequencing (RNA-Seq) data we have developed MAPP (Motif Activity on Pre-mRNA Processing). Applying MAPP to RBP knock-down experiments reveals that many RBPs regulate both splicing and polyadenylation of nascent transcripts by acting on similar sequence motifs. MAPP not only infers these sequence motifs, but also unravels the position-dependent impact of the RBPs on pre-mRNA processing. Interestingly, all investigated RBPs that act on both splicing and 3’ end processing exhibit a consistently repressive or activating effect on both processes, providing a first glimpse on the underlying mechanism. Applying MAPP to normal and malignant brain tissue samples unveils that the motifs bound by the PTBP1 and RBFOX RBPs coordinately drive the oncogenic splicing program active in glioblastomas demonstrating that MAPP paves the way for characterizing pre-mRNA processing regulators under physiological and pathological conditions.

A clinical-information-free method for early diagnosis of lung cancer from the patients with pulmonary nodules based on backpropagation neural network model

Lung cancer is the main cause of cancer-related deaths worldwide. Due to lack of obvious clinical symptoms in the early stage of the lung cancer, it is hard to distinguish between malignancy and pulmonary nodules. Understanding the immune responses in the early stage of malignant lung cancer patients may provide new insights for diagnosis. Here, using high-through-put sequencing, we obtained the TCRβ repertoires in the peripheral blood of 100 patients with Stage I lung cancer and 99 patients with benign pulmonary nodules. Our analysis revealed that the usage frequencies of TRBV, TRBJ genes, and V-J pairs and TCR diversities indicated by D50s, Shannon indexes, Simpson indexes, and the frequencies of the largest TCR clone in the malignant samples were significantly different from those in the benign samples. Furthermore, reduced TCR diversities were correlated with the size of pulmonary nodules. Moreover, we built a backpropagation neural network model with no clinical information to identify lung cancer cases from patients with pulmonary nodules using 15 characteristic TCR clones. Based on the model, we have created a web server named “Lung Cancer Prediction” (LCP), which can be accessed at http://i.uestc.edu.cn/LCP/index.html.