Comprehensive and Accurate Molecular Profiling of Breast Cancer through mRNA Expression of ESR1, PGR, ERBB2, MKI67, and a Novel Proliferation Signature.

BACKGROUND: An accurate status determination of breast cancer biomarkers (ER, PR, HER2, Ki67) is crucial for guiding patient management. The "gold standard" for assessing these biomarkers in FFPE tissue is IHC, which faces challenges in standardization and exhibits substantial variability. In this study, we compare the concordance of a new commercial RT-qPCR kit with IHC in determining BC biomarker status. METHODS: The performance was evaluated using 634 FFPE specimens, which underwent histological analysis in accordance with standard of care methods. HER2 2+ tumors were referred to ISH testing. An immunoreactive score of ≥2/12 was considered positive for ER/PR and 20% staining was used as a cut-off for Ki67 high/low score. RT-qPCR and results calling were performed according to the manufacturer's instructions. RESULTS: High concordance with IHC was seen for all markers (93.2% for ER, 87.1% for PR, 93.9% for HER2, 77.9% for Ki67 and 80.1% for proliferative signature (assessed against Ki67 IHC)). CONCLUSIONS: By assessing the concordance with the results obtained through IHC, we sought to demonstrate the reliability and utility of the kit for precise BC subtyping. Our findings suggest that the kit provides a highly precise and accurate quantitative assessment of BC biomarkers.

CD301 and LSECtin glycan-binding receptors of innate immune cells serve as prognostic markers and potential predictors of immune response in breast cancer subtypes.

Glycosylation is a prominent posttranslational modification, and alterations in glycosylation are a hallmark of cancer. Glycan-binding receptors, primarily expressed on immune cells, play a central role in glycan recognition and immune response. Here, we used the recombinant C-type glycan-binding receptors CD301, Langerin, SRCL, LSECtin, and DC-SIGNR to recognize their ligands on tissue microarrays (TMA) of a large cohort (n = 1859) of invasive breast cancer of different histopathological types to systematically determine the relevance of altered glycosylation in breast cancer. Staining frequencies of cancer cells were quantified in an unbiased manner by a computer-based algorithm. CD301 showed the highest overall staining frequency (40%), followed by LSECtin (16%), Langerin (4%) and DC-SIGNR (0.5%). By Kaplan-Meier analyses, we identified LSECtin and CD301 as prognostic markers in different breast cancer subtypes. Positivity for LSECtin was associated with inferior disease-free survival in all cases, particularly in estrogen receptor positive (ER+) breast cancer of higher histological grade. In triple negative breast cancer, positivity for CD301 correlated with a worse prognosis. Based on public RNA single-cell sequencing data of human breast cancer infiltrating immune cells, we found CLEC10A (CD301) and CLEC4G (LSECtin) exclusively expressed in distinct subpopulations, particularly in dendritic cells and macrophages, indicating that specific changes in glycosylation may play a significant role in breast cancer immune response and progression.

Re-evaluation of publicly available gene-expression databases using machine-learning yields a maximum prognostic power in breast cancer.

Gene expression signatures refer to patterns of gene activities and are used to classify different types of cancer, determine prognosis, and guide treatment decisions. Advancements in high-throughput technology and machine learning have led to improvements to predict a patient's prognosis for different cancer phenotypes. However, computational methods for analyzing signatures have not been used to evaluate their prognostic power. Contention remains on the utility of gene expression signatures for prognosis. The prevalent approaches include random signatures, expert knowledge, and machine learning to construct an improved signature. We unify these approaches to evaluate their prognostic power. Re-evaluation of publicly available gene-expression data from 8 databases with 9 machine-learning models revealed previously unreported results. Gene-expression signatures are confirmed to be useful in predicting a patient's prognosis. Convergent evidence from [Formula: see text] 10,000 signatures implicates a maximum prognostic power. By calculating the concordance index, which measures how well patients with different prognoses can be discriminated, we show that a signature can correctly discriminate patients' prognoses no more than 80% of the time. Additionally, we show that more than 50% of the potentially available information is still missing at this value. We surmise that an accurate prognosis must incorporate molecular, clinical, histological, and other complementary factors.

Synchronous High-Grade Squamous Intraepithelial Lesion of the Fimbria of the Fallopian Tube in a 51-Year-Old Woman with Invasive Squamous Cell Carcinoma of the Uterine Cervix.

Primary squamous cell carcinoma or squamous intraepithelial lesion of the fallopian tube is a very rare finding with only a small number of cases worldwide. We describe the case of a 51-year-old woman, undergoing an abdominal hysterectomy after the diagnosis of an HPV-associated invasive squamous cell carcinoma of the uterine cervix with the unexpected detection of an HPV16-positive high-grade squamous intraepithelial lesion of the fimbria of the right fallopian tube in the resection specimen. The finding of an isolated, HPV-associated squamous intraepithelial lesion in the fallopian tube raises the question of a de novo development in this body compartment (after exclusion of a continuous metastatic spread from the uterine cervix) by taking a virus-associated field effect into account and should encourage the inclusion of this possibility when examining the fallopian tube in a routine setting.

Altona Prognostic Index: A New Prognostic Index for ER-Positive and Her2-Negative Breast Cancer of No Special Type.

Breast cancer is a heterogeneous disease representing a number of different histopathologic and molecular types which should be taken into consideration if prognostic or predictive models are to be developed. The aim of the present study was to demonstrate the validity of the long-known Nottingham prognostic index (NPI) in a large retrospective study (n = 6654 women with a first primary unilateral and unifocal invasive breast cancer diagnosed and treated between April 1996 and October 2018; median follow-up time of breast cancer cases was 15.5 years [14.9-16.8]) from a single pathological institution. Furthermore, it was intended to develop an even superior risk stratification model considering an additional variable, namely the patient's age at the time of diagnosis. Heterogeneity of these cases was addressed by focusing on estrogen receptor-positive as well as Her2-negative cases and taking the WHO-defined different tumor types into account. Calculating progression free survival Cox-regression and CART-analysis revealed significantly superior iAUC as well as concordance values in comparison to the NPI based stratification, leading to an alternative, namely the Altona prognostic index (API). The importance of the histopathological tumor type was corroborated by the fact that when calculated separately and in contrast to the most frequent so-called "No Special Type" (NST) carcinomas, neither NPI nor API could show valid prognostic stratification.

Sensitivity of tumor surface brushings to detect human papilloma virus DNA in head and neck cancer.

OBJECTIVE: Human papilloma virus (HPV) induced head and neck squamous cell carcinoma (HNSCC) represents a distinct tumor subset. We questioned how accurately a brushing from the tumor surface detects HPV in patients with HNSCC. MATERIALS AND METHODS: Brushings from the tumor surface were compared with HPV DNA isolation from formalin-fixed and paraffin-embedded (FFPE) tumor biopsies, which served as the reference standard. In both matrices, HPV DNA was detected using a commercially available test kit. In addition, p16 was assessed in tumor biopsies by immunohistochemistry (IHC). The tumors were considered p16 positive if 70% or more of cancer cells expressed p16. RESULTS: 93 patients with HNSCC were included. Sensitivity and specificity of the brush test were 83% (95%CI: 67-92%) and 85% (95%CI: 72-93%). Results of p16 IHC were concordant with FFPE samples DNA determinations in 73/93 patients. In 53 patients (57%) the tumor was located in the oropharynx and in 40 patients (43%) the tumor was located in the non-oropharynx region. Sensitivity and specificity of the brush test in patients with oropharyngeal cancer was higher with 86% (95%CI: 70-95%) and 89% (95%CI: 65-99%). CONCLUSION: Superficial brushes from the tumor surface may be used to identify HPV positive HNSCC.