Addressing Ancestral Underrepresentation in Oncobiology: The Need for Sub-Saharan African-Specific In Vitro Models

Cancer is an increasing public health burden, including in Sub-Saharan African (SSA) populations, where cancer incidence is predicted to increase by around 140% between 2022 and 2050. These rates require a better understanding of the epidemiological, clinical, and genetic/molecular characteristics of cancer in SSA populations. There is an urgent need to improve the genomic characterization of SSA tumour samples and also to establish suitable in vitro models for hypothesis testing. In fact, even though thousands of cancer cell lines (CCLs) have been established employing different methods of cell immortalization and have been included in deep molecular characterization panels, SSA ancestry is limited to only ~6% (mostly African Americans, who represent limited diversity in the context of the African continent) of publicly available CCLs. This disparity needs to be addressed by using next-generation immortalization methods such as conditional reprogramming to establish CCLs derived from SSA cancer patients that also represent the diversity within the African continent. Research in SSA oncobiology has the potential to add essential information to better understand the diverse molecular pathways leading to cancer and to find promising therapeutic avenues. We also discuss the challenges to conducting oncobiology studies with cell modelling derived from SSA patients in low-to-middle-income African countries, such as Portuguese-speaking African countries.

Authors

Institutions

Publication Details

Journal
Genes
Published
2025-11-24
DOI
https://doi.org/10.3390/genes16121403
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Addressing Ancestral Underrepresentation in Oncobiology: The Need for Sub-Saharan African-Specific In Vitro Models

Lúcio Lara Santos, Pamela Borges, Fernando Miguel, Luı́sa Pereira et al.
Genes
Cancer Genomics and Diagnostics
article

Addressing Ancestral Underrepresentation in Oncobiology: The Need for Sub-Saharan African-Specific In Vitro Models

Lúcio Lara Santos, Pamela Borges, Fernando Miguel, Luı́sa Pereira, Ricardo Pinto, Ana C. Magalhães, Carla Carrilho, Carla S. dos Santos, Cláudia Pereira
article en

Abstract

Cancer is an increasing public health burden, including in Sub-Saharan African (SSA) populations, where cancer incidence is predicted to increase by around 140% between 2022 and 2050. These rates require a better understanding of the epidemiological, clinical, and genetic/molecular characteristics of cancer in SSA populations. There is an urgent need to improve the genomic characterization of SSA tumour samples and also to establish suitable in vitro models for hypothesis testing. In fact, even though thousands of cancer cell lines (CCLs) have been established employing different methods of cell immortalization and have been included in deep molecular characterization panels, SSA ancestry is limited to only ~6% (mostly African Americans, who represent limited diversity in the context of the African continent) of publicly available CCLs. This disparity needs to be addressed by using next-generation immortalization methods such as conditional reprogramming to establish CCLs derived from SSA cancer patients that also represent the diversity within the African continent. Research in SSA oncobiology has the potential to add essential information to better understand the diverse molecular pathways leading to cancer and to find promising therapeutic avenues. We also discuss the challenges to conducting oncobiology studies with cell modelling derived from SSA patients in low-to-middle-income African countries, such as Portuguese-speaking African countries.

GenesVol. 16(12)
University of Lisbon (PT), Eduardo Mondlane University (MZ), Universidade do Porto (PT), Agostinho Neto University (AO), IPO Porto (PT), Maputo Central Hospital (MZ), Câmara Municipal de Almada (PT), Clínica Sagrada Esperança (AO), i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto (PT), Universidade Lusíada de Angola (AO)
Openalex Percentile: Top 55%
Cancer Genomics and Diagnostics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.