Biochemical assessment of human uterine cervix by micro-Raman mapping

Cervical Precancerous Lesions and Associated Factors Among Women Screened in Two Hospitals in the City of Douala, Cameroon

INTRODUCTION

Cervical cancer remains the second leading cause of death among women in Cameroon despite the new strategies put in place. This study was conducted in order to determine the prevalence of precancerous cervical lesions and its associated factors in Douala (Cameroon).

METHODS

 A cross-sectional study was conducted over a period of nine months in two hospitals of the city of Douala, Cameroon (Laquintinie Hospital and Gyneco-Ostetric and Pediatric Hospital). Cervico-vaginal and endocervical samples were taken from women attending the above-mentioned hospitals in order to identify and characterize precancerous lesions by cytological examination and to genotype for human papillomavirus (HPV) using the Abbott RealTime High-Risk (HR) HPV kit. Data of sociodemographic characteristics, clinical history, and knowledge about cervical cancer were collected using a questionnaire.

RESULTS

Of the 196 women included in this study, 17% had precancerous lesions, including 1.53% for atypical glandular cells (AGC), 4.53% for atypical squamous cells (ASC), 4.53% for low-grade squamous intraepithelial lesion (LSIL), 5.61% for high-grade squamous intraepithelial lesion (HSIL), 0.51% for atypical squamous cells of undetermined significance (ASC-US), and 0.51% for atypical squamous cells cannot exclude HSIL (ASC-H). In addition, the prevalence of HPV infection was 18%, of which 2% was for HPV 16, 2% for HPV 18, and 14% for undetermined HPV. A positive association was recorded between the occurrence of precancerous lesions and HPV infection (P=0.01), age, and school level. Moreover, the occurrence of precancerous lesions was positively associated with the participants' level of knowledge (P=0.01).

DISCUSSION

Precancerous lesions were predominantly HSIL, and the factor most associated with these lesions was HPV infection.

CONCLUSION

This study demonstrates that diagnosis is made at a relatively late stage due to a low level of knowledge about cervical cancer in the population.

Raman microspectroscopy and machine learning for use in identifying radiation-induced lung toxicity

OBJECTIVE

In this work, we explore and develop a method that uses Raman spectroscopy to measure and differentiate radiation induced toxicity in murine lungs with the goal of setting the foundation for a predictive disease model.

METHODS

Analysis of Raman tissue data is achieved through a combination of techniques. We first distinguish between tissue measurements and air pockets in the lung by using group and basis restricted non-negative matrix factorization. We then analyze the tissue spectra using sparse multinomial logistic regression to discriminate between fibrotic gradings. Model validation is achieved by splitting the data into a training set containing 70% of the data and a test set with the remaining 30%; classification accuracy is used as the performance metric. We also explore several other potential classification tasks wherein the response considered is the grade of pneumonitis and fibrosis sickness.

RESULTS

A classification accuracy of 91.6% is achieved on the test set of fibrotic gradings, illustrating the ability of Raman measurements to detect differing levels of fibrotic disease among the murine lungs. It is also shown via further modeling that coarser consideration of fibrotic grading via binning (ie. 'Low', 'Medium', 'High') does not degrade performance. Finally, we consider preliminary models for pneumonitis discrimination using the same methodologies.

Knockdown of lncRNA PCAT1 Enhances Radiosensitivity of Cervical Cancer by Regulating miR-128/GOLM1 Axis

Purpose

Cervical cancer (CC) is the fourth most common cancer with high death rate in females. The study aims to detect the mechanism of long non-coding RNA (LncRNA) PCAT1 on radiosensitivity of CC.

Methods

The expression of PCAT1, miR-128 and GOLM1 in CC tissues and cells was measured by qRT-PCR. Different doses of X-ray were used for radiation treatment of CC cells and 6 Gy was chosen to perform the following experiments. The proliferation, migration and invasion of CC cells were measured by MTT assay, wound healing assay and transwell assay, respectively. The target relationships among PCAT1, miR-128 and GOLM1 were predicted by StarBase and TargetScan and verified by luciferase reporter assay. The protein level of GOLM1 was determined by Western blot. The xenograft tumor model was constructed in nude mice to verify the effect of PCAT1 on radiosensitivity of CC in vivo.

Results

The PCAT1 expression was upregulated in CC tissues and cells. PCAT1 silencing enhances radiosensitivity of CC cells on proliferation, migration and invasion. MiR-128 was the target of PCAT1 and was negatively regulated by PCAT1. Upregulation of miR-128 enhances radiosensitivity of CC cells on proliferation, migration and invasion. GOLM1 was a target of miR-128 and was negatively regulated by miR-128. Upregulation of GOLM1 and downregulation of miR-128 both reversed the enhanced effect of PCAT1 knockdown on radiosensitivity of CC cells, which partly promoted the proliferation, migration and invasion of CC cells.

Conclusion

Silencing of PCAT1 enhanced radiosensitivity of CC via targeting miR-128/GOLM1, which provided a new idea for treating CC.

HPV Infection Significantly Accelerates Glycogen Metabolism in Cervical Cells with Large Nuclei: Raman Microscopic Study with Subcellular Resolution

Using Raman microscopy, we investigated epithelial cervical cells collected from 96 women with squamous cell carcinoma (SCC) or belonging to groups I, IIa, IIID-1 and IIID-2 according to Munich III classification (IIID-1 and IIID-2 corresponding to Bethesda LSIL and HSIL groups, respectively). All women were tested for human papillomavirus (HPV) infection using PCR. Subcellular resolution of Raman microscopy enabled to understand phenotypic differences in a heterogeneous population of cervical cells in the following groups: I/HPV⁻, IIa/HPV⁻, IIa/HPV⁻, LSIL/HPV⁻, LSIL/HPV⁺, HSIL/HPV⁻, HSIL/HPV⁺ and cancer cells (SCC/HPV⁺). We showed for the first time that the glycogen content in the cytoplasm decreased with the nucleus size of cervical cells in all studied groups apart from the cancer group. For the subpopulation of large-nucleus cells HPV infection resulted in considerable glycogen depletion compared to HPV negative cells in IIa, LSIL (for both statistical significance, ca. 45%) and HSIL (trend, 37%) groups. We hypothesize that accelerated glycogenolysis in large-nucleus cells may be associated with the increased protein metabolism for HPV positive cells. Our work underlines unique capabilities of Raman microscopy in single cell studies and demonstrate potential of Raman-based methods in HPV diagnostics.

Raman spectroscopy and chemometrics: A potential universal method for diagnosing cancer

Cancer is the second-leading cause of death worldwide. It affects an unfathomable number of people, with almost 16 million Americans currently living with it. While many cancers can be detected, current diagnostic efforts exhibit definite room for improvement. It is imperative that a person be diagnosed with cancer as early on in its progression as possible. An earlier diagnosis allows for the best treatment and intervention options available to be presented. Unfortunately, existing methods for diagnosing cancer can be expensive, invasive, inconclusive or inaccurate, and are not always made during initial stages of the disease. As such, there is a crucial unmet need to develop a singular universal method that is reliable, cost-effective, and non-invasive and can diagnose all forms of cancer early-on. Raman spectroscopy in combination with advanced statistical analysis is offered here as a potential solution for this need. This review covers recently published research in which Raman spectroscopy was used for the purpose of diagnosing cancer. The benefits and the risks of the methodology are presented; however, there is overwhelming evidence that suggests Raman spectroscopy is highly suitable for becoming the first universal method to be used for diagnosing cancer.

Assessment of the current state of knowledge and risk factors of cervical cancer among women in the Buea Health District, Cameroon

Introduction

Cervical cancer is a malignant proliferation of the cells of the uterine cervix and can be treated if diagnosed earlier. It is the second most common gynecological malignancy worldwide and the leading cause of cancer associated mortality among women in Africa and Cameroon. This study sort to determine the current state of knowledge of cervical cancer and its risk factors in the Buea Health District of the South West Region of Cameroon.

Methods

This was a cross-sectional community based survey. We recruited 433 eligible women, in four (4) Health Areas (Molyko, Bolifamba, Muea and Buea Town) of the Buea Health District and used validated and pre-tested questionnaires to collect data. Collected data were keyed into Epi info version 7.2 statistical software and exported to SPSS Version 25 for analysis. Level of significance was set at P-value < 0.05.

Results

Fifty eight percent (58%) of the participants had good knowledge of cervical cancer. 58.99% (95%CI = 54.30-63.52) had good knowledge on the risk factors of cervical cancer. 40% knew at least one of the following risk factors; cigarette smoking, many sexual partners, family history of cervical cancer, being HIV/AIDS positive and giving birth 5 or more times. There was a significant association, OR = 7.5; 95%CI = 2.14-26.33; P = 0.001; X² = 11.4 between having heard of cervical cancer and having “good” knowledge of cervical cancer among women in Buea.

Conclusion

Most of the women had heard of cervical cancer but the knowledge of the risk factors of cervical cancer among women aged 18-68 years in the Buea Health District is low. We found no association between awareness and knowledge of risk factors among the women.

Cervical cancer in the Bamenda Regional Hospital, North West Region of Cameroon: a retrospective study

INTRODUCTION

Cervical cancer is ranked the 7th most common cancer in the world. Cancer of the cervix is the second most commonly diagnosed cancer after breast cancer and the third leading cause of cancer deaths among females in less developed countries. Incidence rates are highest in countries with low income. Nearly 90% of cervical cancer deaths occur in developing parts of the world. The study researchers therefore, carried out a retrospective study to determine the proportion of cervical cancer among other types of cancer in the cancer registry of the Bamenda Regional Hospital.

METHODS

The objective of this study was to determine the proportion of cervical cancer among other types of cancers in the cancer registry of the Bamenda Regional Hospital, North West Region of Cameroon from past records. We reviewed all records from the registry of patients who attended the Bamenda Regional Hospital to screen and/or be operated upon for cervical cancer and other types of cancer. Socio-demographic and clinical characteristics of cases were captured using a data collection sheet: age, type of cancer, stage of cancer, type of surgery carried out and date of surgery. Data were entered and analysed in Statistical Package for Social Sciences (SPSS) version 25 software.

RESULTS

59 cancer cases were received in the center between 2012 and 2017. Of these, 31 (52%) had cervical cancer. Most patients who screened positive for cancer of the cervix were of the 50-54 age groups. Most of these patients (47.5%), were received at late stages (stages 3 and 4).

CONCLUSION

Over half (52%) of the patients receiving cancer care in this center have cervical cancer and generally turn up late for management.

Paper-Based Surface-Enhanced Raman Spectroscopy for Diagnosing Prenatal Diseases in Women

We report the development of a surface-enhanced Raman spectroscopy sensor chip by decorating gold nanoparticles (AuNPs) on ZnO nanorod (ZnO NR) arrays vertically grown on cellulose paper (C). We show that these chips can enhance the Raman signal by 1.25 × 10⁷ with an excellent reproducibility of <6%. We show that we can measure trace amounts of human amniotic fluids of patients with subclinical intra-amniotic infection (IAI) and preterm delivery (PTD) using the chip in combination with a multivariate statistics-derived machine-learning-trained bioclassification method. We can detect the presence of prenatal diseases and identify the types of diseases from amniotic fluids with >92% clinical sensitivity and specificity. Our technology has the potential to be used for the early detection of prenatal diseases and can be adapted for point-of-care applications.