TROPION-Breast02: Datopotamab deruxtecan for locally recurrent inoperable or metastatic triple-negative breast cancer

Despite recent treatment advances, the prognosis for patients with locally recurrent inoperable or metastatic triple-negative breast cancer (TNBC) remains poor. The antibody-drug conjugate datopotamab deruxtecan (Dato-DXd) is composed of a humanized anti-TROP2 IgG1 monoclonal antibody linked to a topoisomerase I inhibitor payload via a stable, cleavable linker. The phase III TROPION-Breast02 trial in patients previously untreated for locally recurrent inoperable or metastatic TNBC, who are not candidates for PD-1/PD-L1 inhibitors is evaluating efficacy and safety of Dato-DXd versus investigator's choice of chemotherapy (ICC). Approximately 600 patients will be randomized 1:1 to Dato-DXd 6 mg/kg iv. every 3 weeks or ICC (paclitaxel, nab-paclitaxel, carboplatin, capecitabine or eribulin mesylate). Dual primary end points are progression-free survival by blinded independent central review and overall survival.

A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application

BACKGROUND

Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various malignancies. Initially, a series of preprocessing steps and image segmentation steps are performed to extract region of interest features from noisy features. Then, the extracted features are applied to several machine learning and deep learning methods for the detection of cancer.

METHODS

In this work, a review of all the methods that have been applied to develop machine learning algorithms that detect cancer is provided. With more than 100 types of cancer, this study only examines research on the four most common and prevalent cancers worldwide: lung, breast, prostate, and colorectal cancer. Next, by using state-of-the-art sentence transformers namely: SBERT (2019) and the unsupervised SimCSE (2021), this study proposes a new methodology for detecting cancer. This method requires raw DNA sequences of matched tumor/normal pair as the only input. The learnt DNA representations retrieved from SBERT and SimCSE will then be sent to machine learning algorithms (XGBoost, Random Forest, LightGBM, and CNNs) for classification. As far as we are aware, SBERT and SimCSE transformers have not been applied to represent DNA sequences in cancer detection settings.

RESULTS

The XGBoost model, which had the highest overall accuracy of 73 ± 0.13 % using SBERT embeddings and 75 ± 0.12 % using SimCSE embeddings, was the best performing classifier. In light of these findings, it can be concluded that incorporating sentence representations from SimCSE's sentence transformer only marginally improved the performance of machine learning models.

Discriminatory Gleason grade group signatures of prostate cancer: An application of machine learning methods

One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological pattern. However, this is not only laborious, but also relies on the experience of the pathologist and tends to suffer from the lack of reproducibility of biopsy outcomes across pathologists. As a result, computational approaches are being sought and machine learning has been gaining momentum in the prediction of the Gleason grade group. To date, machine learning literature has addressed this problem by using features from magnetic resonance imaging images, whole slide images, tissue microarrays, gene expression data, and clinical features. However, there is a gap with regards to predicting the Gleason grade group using DNA sequences as the only input source to the machine learning models. In this work, using whole genome sequence data from South African prostate cancer patients, an application of machine learning and biological experiments were combined to understand the challenges that are associated with the prediction of the Gleason grade group. A series of machine learning binary classifiers (XGBoost, LSTM, GRU, LR, RF) were created only relying on DNA sequences input features. All the models were not able to adequately discriminate between the DNA sequences of the studied Gleason grade groups (Gleason grade group 1 and 5). However, the models were further evaluated in the prediction of tumor DNA sequences from matched-normal DNA sequences, given DNA sequences as the only input source. In this new problem, the models performed acceptably better than before with the XGBoost model achieving the highest accuracy of 74 ± 01, F1 score of 79 ± 01, recall of 99 ± 0.0, and precision of 66 ± 0.1.

A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without

BACKGROUND

Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus have been extensively investigated using a variety of -omics approaches, including genome-wide association studies, candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to controls.

METHODS

This study analyses a combination of existing microarray data sets to identify differentially regulated genetic pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression microarray datasets and perform a meta-analysis of differentially expressed genes.

RESULTS

Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis, in agreement with the findings of the individual studies that generated the datasets used. In contrast to the individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls.

CONCLUSION

Our analysis demonstrates that it is possible to derive additional information from publicly available expression data using meta-analysis techniques, which is particularly relevant to research into rare diseases where sample numbers can be limiting.

Identification and characterization of microRNAs expressed in the African malaria vector Anopheles funestus life stages using high throughput sequencing

BACKGROUND

Over the past several years, thousands of microRNAs (miRNAs) have been identified in the genomes of various insects through cloning and sequencing or even by computational prediction. However, the number of miRNAs identified in anopheline species is low and little is known about their role. The mosquito Anopheles funestus is one of the dominant malaria vectors in Africa, which infects and kills millions of people every year. Therefore, small RNA molecules isolated from the four life stages (eggs, larvae, pupae and unfed adult females) of An. funestus were sequenced using next generation sequencing technology.

RESULTS

High throughput sequencing of four replicates in combination with computational analysis identified 107 mature miRNA sequences expressed in the An. funestus mosquito. These include 20 novel miRNAs without sequence identity in any organism and eight miRNAs not previously reported in the Anopheles genus but are known in non-anopheles mosquitoes. Finally, the changes in the expression of miRNAs during the mosquito development were determined and the analysis showed that many miRNAs have stage-specific expression, and are co-transcribed and co-regulated during development.

CONCLUSIONS

This study presents the first direct experimental evidence of miRNAs in An. funestus and the first profiling study of miRNA associated with the maturation in this mosquito. Overall, the results indicate that miRNAs play important roles during the growth and development. Silencing such molecules in a specific life stage could decrease the vector population and therefore interrupt malaria transmission.

Baseline Predictors of Mortality among Predominantly Rural-Dwelling End-Stage Renal Disease Patients on Chronic Dialysis Therapies in Limpopo, South Africa

BACKGROUND

Dialysis therapy for end-stage renal disease (ESRD) continues to be the readily available renal replacement option in developing countries. While the impact of rural/remote dwelling on mortality among dialysis patients in developed countries is known, it remains to be defined in sub-Saharan Africa.

METHODS

A single-center database of end-stage renal disease patients on chronic dialysis therapies treated between 2007 and 2014 at the Polokwane Kidney and Dialysis Centre (PKDC) of the Pietersburg Provincial Hospital, Limpopo South Africa, was retrospectively reviewed. All-cause, cardiovascular, and infection-related mortalities were assessed and associated baseline predictors determined.

RESULTS

Of the 340 patients reviewed, 52.1% were male, 92.9% were black Africans, 1.8% were positive for the human immunodeficiency virus (HIV), and 87.5% were rural dwellers. The average distance travelled to the dialysis centre was 112.3 ± 73.4 Km while 67.6% of patients lived in formal housing. Estimated glomerular filtration rate (eGFR) at dialysis initiation was 7.1 ± 3.7 mls/min while hemodialysis (HD) was the predominant modality offered (57.1%). Ninety-two (92) deaths were recorded over the duration of follow-up with the majority (34.8%) of deaths arising from infection-related causes. Continuous ambulatory peritoneal dialysis (CAPD) was a significant predictor of all-cause mortality (HR: 1.62, CI: 1.07-2.46) and infection-related mortality (HR: 2.27, CI: 1.13-4.60). On multivariable cox regression, CAPD remained a significant predictor of all-cause mortality (HR: 2.00, CI: 1.29-3.10) while the risk of death among CAPD patients was also significantly modified by diabetes mellitus (DM) status (HR: 4.99, CI: 2.13-11.71).

CONCLUSION

CAPD among predominantly rural dwelling patients in the Limpopo province of South Africa is associated with an increased risk of death from all-causes and infection-related causes.

Lupus nephritis is associated with poor pregnancy outcomes in pregnant SLE patients in Cape Town: a retrospective analysis

Introduction

Systemic lupus erythematosus (SLE) is a multi-system auto-immune disease common in females of child-bearing age. The effect of pregnancy on SLE and vice versa have not been well characterised in Africans. The aim of this study is to describe the pregnancy outcomes of patients with SLE presenting to the maternity department of Groote Schuur Hospital, Cape Town.

Methods

This study was designed as a retrospective review of records of pregnant women known with SLE and followed-up at the maternity section of Groote Schuur Hospital. The duration of survey was from the 1^st January 2003 to 31^st December 2013.

Results

There were 61 pregnancies reviewed in 49 patients; 80.3% of the pregnancies were in patients of mixed ancestry and the rest (19.7%) in black African patients. The mean age at presentation of the current pregnancy was 27.2±5.0 years. Mean gestational age at presentation and delivery was 13.0 ± 6.0 weeks and 28.9 ± 9.8 weeks respectively and 47.5% of the pregnancies were in patients with lupus nephritis (LN). Thirty nine (63.9%) pregnancies reached the third trimester and 11.5% of all pregnancies ended in the first trimester. There was a lower number of live births to mothers of African ancestry than to those of mixed ancestry (p=0.001). In 55.7% of the pregnancies, no flare was reported while a renal flare was reported in 23%. Pregnancies in patients with LN had higher frequencies of flares (58.6% vs 31.3%; p=0.032), pre-eclampsia (34.5% vs 12.5%; p=0.041), longer stay in hospital (12.0 ± 9.1 days vs 6.1 ± 5.1 days; p=0.004) and low birth weight babies (1.94 ± 1.02 kg vs 2.55±0.95 kg; p=0.046) than in patients without LN. Only 36 (59%) of the neonates were discharged home alive and of these 2 (5.6%) were to mothers of black African ancestry (p=0.001).

Conclusion

Increased lupus activity in pregnant SLE patients may account for the increased deaths of neonates born to SLE mothers. Patients of black African descent and those with LN tend to have a poorer outcome. A multi-disciplinary approach to the management of SLE patients (of child-bearing age or pregnant) needs to be further assessed for better outcomes.

The African Lupus Genetics Network (ALUGEN) registry: standardized, prospective follow-up studies in African patients with systemic lupus erythematosus

Background

The prevalence and severity of systemic lupus erythematosus (SLE) differs between ethnic groups and geographical regions. Although initially reported as rare, there is growing evidence that SLE is prevalent and runs a severe course in Africa. There is a paucity of prospective studies on African SLE patients.

Objective

The African Lupus Genetics Network (ALUGEN) is a multicentred framework seeking to prospectively assess outcomes in SLE patients in Africa. Outcomes measured will be death, hospital admission, disease activity flares, and SLE-related damage. We will explore predictors for these outcomes including clinical, serological, socio-demographic, therapeutic and genetic factors. Further, we will investigate comorbidities and health-related quality of life amongst these patients.

Methods

Data of patients recently (≤5 yrs) diagnosed with SLE will be collected at baseline and annual follow-up visits, and captured electronically. The ALUGEN project will facilitate standardized data capture for SLE cases in Africa, allowing participating centres to develop their own SLE registries, and enabling collaboration to enrich our understanding of inter-ethnic and regional variations in disease expression.

Conclusion

Comprehensive, high-quality multi-ethnic data on African SLE patients will expand knowledge of the disease and inform clinical practice, in addition to augmenting research capacity and networking links and providing a platform for future biomarker and interventional studies.

Continuous ambulatory peritoneal dialysis in Limpopo province, South Africa: predictors of patient and technique survival

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INTRODUCTION AND AIM

Continuous ambulatory peritoneal dialysis (CAPD) is not a frequently used modality of dialysis in many parts of Africa due to several socio-economic factors. Available studies from Africa have shown a strong association between outcome and socio-demographic variables. We sought to assess the outcome of patients treated with CAPD in Limpopo, South Africa. ♦

METHODS

This was a retrospective study of 152 patients treated with CAPD at the Polokwane Kidney and Dialysis Centre (PKDC) from 2007 to 2012. We collected relevant demographic and biochemical data for all patients included in the study. A composite outcome of death while still on peritoneal dialysis (PD) or CAPD technique failure from any cause requiring a change of modality to hemodialysis (HD) was selected. The peritonitis rate and causes of peritonitis were assessed from 2008 when all related data could be obtained. ♦

RESULTS

There were 52% males in the study and the average age of the patients was 36.8 ± 11.4 years. Unemployment rate was high (71.1%), 41.1% had tap water at home, the average distance travelled to the dialysis center was 122.9 ± 78.2 kilometres and half the patients had a total income less than USD ($)180 per month. Level of education, having electricity at home, having tap water at home, body mass index (BMI), serum albumin and hemoglobin were significantly different between those reaching the composite outcome and those not reaching it (p < 0.05). The overall peritonitis rate was 0.82/year with 1-year, 2-year and 5-year survival found to be 86.7%, 78.7% and 65.3% (patient survival) and 83.3%, 71.7% and 62.1% (technique survival). Predictors of the composite outcome were BMI (p = 0.011), serum albumin (p = 0.030), hemoglobin (p = 0.002) and more than 1 episode of peritonitis (p = 0.038). ♦

CONCLUSION

Treatment of anemia and malnutrition as well as training and re-training of CAPD patients and staff to prevent recurrence of peritonitis can have positive impacts on CAPD outcomes in this population.