The Predictive Impact of HPV Genotypes, Tumor Suppressors and Local Immune Response in the Regression of Cervical Intraepithelial Neoplasia 2-3: A Prospective Population-Based Cohort Study.

Cervical intraepithelial neoplasia (CIN) is caused by human papillomavirus (HPV); however, factors such as HPV genotype and individual immune response may also contribute to its development. The loop electrosurgical excision procedure (LEEP) is a treatment for high-grade cervical intraepithelial neoplasia (CIN), as approximately 30% of these cases may progress to cancer. However, 20-40% of cases will regress spontaneously.

Biobanking after Radical Prostatectomy: Comparison of Slice and Punch Protocols.

Biobanking of prostate cancer tissue is crucial for advancing biomarker-guided precision medicine. However, there is no standardized optimal protocol for biobanking prostatectomy specimens. This study aims to compare the representativeness and sustainability of two biobanking protocols-"Punch" and "Slice"-currently used in Norway.

Dual Functions of Androgen Receptor Overexpression in Triple-Negative Breast Cancer: A Complex Prognostic Marker.

A subset of triple-negative breast cancer (TNBC) expresses the androgen receptor (AR), but thresholds for AR positivity and its clinical significance vary. We hypothesize that objective assessment outperforms subjective methods, and that high AR negatively impacts prognosis. In a population-based TNBC cohort ( = 198) with long follow-up (4-383 months), AR expression was evaluated via subjective scoring (AR-Manual) and automated digital image analysis (AR-DIA).

Integrating Genetic Alterations and Histopathological Features for Enhanced Risk Stratification in Non-Muscle-Invasive Bladder Cancer.

Background: Urothelial carcinoma presents as non-muscle-invasive bladder cancer (NMIBC) in ~75% of primary cases. Addressing the limitations of the TNM and WHO04/16 classification systems, this study investigates genetic alterations, the mitotic activity index (MAI), and immunohistochemistry (IHC) markers CK20, p53, and CD25 as better prognostic biomarkers in NMIBC.

Methods: Using the Oncomine™ Focus Assay for targeted next-generation sequencing (NGS), 409 single-nucleotide variations (SNVs) and 193 copy number variations (CNVs) were identified across 287 patients with TaT1 tumors.

Equipping computational pathology systems with artifact processing pipelines: a showcase for computation and performance trade-offs.

Background: Histopathology is a gold standard for cancer diagnosis. It involves extracting tissue specimens from suspicious areas to prepare a glass slide for a microscopic examination. However, histological tissue processing procedures result in the introduction of artifacts, which are ultimately transferred to the digitized version of glass slides, known as whole slide images (WSIs).

NMGrad: Advancing Histopathological Bladder Cancer Grading with Weakly Supervised Deep Learning.

The most prevalent form of bladder cancer is urothelial carcinoma, characterized by a high recurrence rate and substantial lifetime treatment costs for patients. Grading is a prime factor for patient risk stratification, although it suffers from inconsistencies and variations among pathologists. Moreover, absence of annotations in medical imaging renders it difficult to train deep learning models.

No signs of mast cell involvement in long-COVID: A case-control study.

Long-COVID caused by SARS-CoV-2 infection has significant and increasing effects on human health worldwide. Although a unifying molecular or biological explanation is lacking, several pathophysiological mechanisms have been proposed. Involvement of mast cells-evolutionary old "multipurpose" innate immune cells-was reported recently in studies of acute infection and post-acute-COVID-19 syndrome.

Globalization of a telepathology network with artificial intelligence applications in Colombia: The GLORIA program study protocol.

In Colombia, cancer is recognized as a high-cost pathology by the national government and the Colombian High-Cost Disease Fund. As of 2020, the situation is most critical for adult cancer patients, particularly those under public healthcare and residing in remote regions of the country. The highest lag time for a diagnosis was observed for cervical cancer (79.

Quantitative proteomics reveals serum proteome alterations during metastatic disease progression in breast cancer patients.

Background: Tumor recurrence and metastatic progression remains the leading cause for breast cancer related mortalities. However, the proteomes of patient- matched primary breast cancer (BC) and metastatic lesions have not yet been identified, due to the lack of clinically annotated longitudinal samples. In this study, we evaluated the global-proteomic landscape of BC patients with and without distant metastasis as well as compared the proteome of distant metastatic disease with its corresponding primary BC, within the same patient.

Nottingham prognostic x (NPx): a risk stratification tool in ER-positive HER2-negative breast cancer: a validation study.

Aims: In this study, we validate the use of Nottingham Prognostic x (NPx), consisting of tumour size, tumour grade, progesterone receptor (PR) and Ki67 in luminal BC.

Materials And Methods: Two large cohorts of luminal early-stage BC (n = 2864) were included. PR and Ki67 expression were assessed using full-face resection samples using immunohistochemistry.

The Ki67 dilemma: investigating prognostic cut-offs and reproducibility for automated Ki67 scoring in breast cancer.

Purpose: Quantification of Ki67 in breast cancer is a well-established prognostic and predictive marker, but inter-laboratory variability has hampered its clinical usefulness. This study compares the prognostic value and reproducibility of Ki67 scoring using four automated, digital image analysis (DIA) methods and two manual methods.

Methods: The study cohort consisted of 367 patients diagnosed between 1990 and 2004, with hormone receptor positive, HER2 negative, lymph node negative breast cancer.

Proliferation and immunohistochemistry for p53, CD25 and CK20 in predicting prognosis of non-muscle invasive papillary urothelial carcinomas.

Non-muscle invasive papillary urothelial carcinoma is a prevalent disease with a high recurrence tendency. Good prognostic and reproducible biomarkers for tumor recurrence and disease progression are lacking. Currently, WHO grade and tumor stage are essential in risk stratification and treatment decision-making.

Uninformed Teacher-Student for hard-samples distillation in weakly supervised mitosis localization.

Background And Objective: Mitotic activity is a crucial biomarker for diagnosing and predicting outcomes for different types of cancers, particularly breast cancer. However, manual mitosis counting is challenging and time-consuming for pathologists, with moderate reproducibility due to biopsy slide size, low mitotic cell density, and pattern heterogeneity. In recent years, deep learning methods based on convolutional neural networks (CNNs) have been proposed to address these limitations.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.

Background: Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment in NAC response in patients with TNBC remains unclear.

Predicting Neoadjuvant Treatment Response in Triple-Negative Breast Cancer Using Machine Learning.

Background: Neoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30-40% of TNBC patients.

Prenatal BRCA1 epimutations contribute significantly to triple-negative breast cancer development.

Background: Normal cell BRCA1 epimutations have been associated with increased risk of triple-negative breast cancer (TNBC). However, the fraction of TNBCs that may have BRCA1 epimutations as their underlying cause is unknown. Neither are the time of occurrence and the potential inheritance patterns of BRCA1 epimutations established.

Homologous Recombination Deficiency Across Subtypes of Primary Breast Cancer.

Purpose: Homologous recombination deficiency (HRD) is highly prevalent in triple-negative breast cancer (TNBC) and associated with response to PARP inhibition (PARPi). Here, we studied the prevalence of HRD in non-TNBC to assess the potential for PARPi in a wider group of patients with breast cancer.

Methods: HRD status was established using targeted gene panel sequencing (360 genes) and methylation analysis of pretreatment biopsies from 201 patients with primary breast cancer in the phase II PETREMAC trial (ClinicalTrials.

Digital image analysis and machine learning-assisted prediction of neoadjuvant chemotherapy response in triple-negative breast cancer.

Background: Pathological complete response (pCR) is associated with favorable prognosis in patients with triple-negative breast cancer (TNBC). However, only 30-40% of TNBC patients treated with neoadjuvant chemotherapy (NAC) show pCR, while the remaining 60-70% show residual disease (RD). The role of the tumor microenvironment (TME) in NAC response in patients with TNBC remains unclear.

Importance of endocrine treatment adherence and persistence in breast cancer survivorship: a systematic review.

Purpose: Adjuvant endocrine treatment is essential for treating luminal subtypes of breast cancer, which constitute 75% of all breast malignancies. However, the detrimental side effects of treatment make it difficult for many patients to complete the guideline-required treatment. Such non-adherence may jeopardize the lifesaving ability of anti-estrogen therapy.

Non-muscle-invasive bladder cancer molecular subtypes predict differential response to intravesical Bacillus Calmette-Guérin.

The recommended treatment for patients with high-risk non-muscle-invasive bladder cancer (HR-NMIBC) is tumor resection followed by adjuvant Bacillus Calmette-Guérin (BCG) bladder instillations. However, only 50% of patients benefit from this therapy. If progression to advanced disease occurs, then patients must undergo a radical cystectomy with risks of substantial morbidity and poor clinical outcome.

Predicting neoadjuvant treatment response in triple-negative breast cancer using machine learning.

Background: Neoadjuvant chemotherapy (NAC) is the standard treatment for early-stage triple negative breast cancer (TNBC). The primary endpoint of NAC is a pathological complete response (pCR). NAC results in pCR in only 30%â€"40% of TNBC patients.

Impact of KRAS and BRAF mutations on treatment efficacy and survival in high-grade gastroenteropancreatic neuroendocrine neoplasms.

High-grade gastroenteropancreatic neuroendocrine neoplasms (HG GEP-NEN) typically disseminate early. Treatment of metastatic disease has limited benefit and prognosis is generally discouraging. Data on the clinical impact of mutations in HG GEP-NEN are scarce.

Automated Prognostic Assessment of Endometrial Hyperplasia for Progression Risk Evaluation Using Artificial Intelligence.

Endometrial hyperplasia is a precursor to endometrial cancer, characterized by excessive proliferation of glands that is distinguishable from normal endometrium. Current classifications define 2 types of EH, each with a different risk of progression to endometrial cancer. However, these schemes are based on visual assessments and, therefore, subjective, possibly leading to overtreatment or undertreatment.

Estimating diagnostic uncertainty in artificial intelligence assisted pathology using conformal prediction.

Unreliable predictions can occur when an artificial intelligence (AI) system is presented with data it has not been exposed to during training. We demonstrate the use of conformal prediction to detect unreliable predictions, using histopathological diagnosis and grading of prostate biopsies as example. We digitized 7788 prostate biopsies from 1192 men in the STHLM3 diagnostic study, used for training, and 3059 biopsies from 676 men used for testing.

A Case Series Exploration of Multi-Regional Expression Heterogeneity in Triple-Negative Breast Cancer Patients.

Extensive intratumoral heterogeneity (ITH) is believed to contribute to therapeutic failure and tumor recurrence, as treatment-resistant cell clones can survive and expand. However, little is known about ITH in triple-negative breast cancer (TNBC) because of the limited number of single-cell sequencing studies on TNBC. In this study, we explored ITH in TNBC by evaluating gene expression-derived and imaging-derived multi-region differences within the same tumor.