New biobank of patient-derived tumour organoid 3D models reveals cancers’ weak spots of five different cancer types

Good news! Cancer is history (soon)! This could be a major advance!

"... The biobank is expected to have wide utility, enabling scientists to identify the genes that specific cancers depend on for growth, revealing potential weak points that could be targeted with future treatments.

The study is published alongside two complementary papers from international collaborators, reflecting a wider multi-year effort to refine organoid models and make them more accessible to the research community.

For decades, cancer researchers have relied on two-dimensional (2D) cell lines to study cancer. These workhorse models, in which cells are grown in a flat layer on laboratory plates, have provided important insights into cancer biology and remain widely used.

However, 2D models have limitations: they do not fully capture the diversity and complexity of tumours seen in patients and they have adapted to laboratory conditions over time. Researchers are therefore increasingly looking to develop next-generation models that better reflect tumours found in patients, such as organoids, to complement 2D cell lines and help address some of these gaps. ...

In a first of its kind study in organoids, the researchers went on to use CRISPR screening, a method they used to systematically switch off genes one by one to see if the cells survived, in order to map the genes that are critical to cancer cell survival across 162 of the organoid models. They identified thousands of genetic dependencies, including both common genes required by many cancers to survive, and more specific vulnerabilities linked to particular tumour types. ..."

From the abstract:

"Cancer cell lines remain foundational for research and drug discovery, yet they incompletely capture tumour diversity, lack linked patient context, and have undergone adaptation to culture.

Tumour organoids are three-dimensional cultures derived from patient tissue that offer a powerful complement to cell lines.

Here we derived and characterized 256 clinically annotated tumour organoids directly from colorectal, oesophageal, ovarian, pancreatic and gastric cancers as renewable, genetically stable models.

Extensive characterization of each model and matched patient tumour samples included whole-genome and transcriptome sequencing, and genome-wide CRISPR–Cas9 screens across 162 organoids mapped gene dependencies. Integrative analyses revealed genomic and clinical markers of dependency across common and rare subtypes, identified organoid-specific essential genes, and revealed targetable vulnerabilities following tumour evolution in paired pre- and post-treatment samples.

In colorectal cancer, functional and pharmacological interrogation of the EGFR–RAS–MAPK axis uncovered differential effects of KRAS variant alleles.

This open, publicly available resource provides a systematic map of gene dependencies in patient-derived organoids, expanding the model diversity and mechanistic insight needed to advance precision oncology."

New biobank of tumour models reveals cancers’ weak spots "The largest characterised collection of patient-derived tumour organoids to date is helping scientists identify the genes cancers need to grow and survive."

A tumour-derived organoid biobank maps cancer gene dependencies (open access)

Fig. 1: Establishment of organoid biobank and patient-linked clinical data.

Fig. 2: Genomic features are conserved between organoid and patient-matched tumour.

Hidden drivers of aggressive childhood cancer revealed

Good news! Cancer is history (soon)!

"New insights into why some children with rhabdomyosarcoma (RMS) develop aggressive disease despite being classified as non-high-risk have been uncovered. ...

RMS is broadly split into two different types, depending on whether the tumour contains a genetic risk marker. This marker is a fusion of two genes that are not normally connected. In patients with this marker, survival is substantially lower than in those who do not carry it, despite intense treatment.2

However, some children whose tumours do not carry the high-risk marker still develop aggressive disease, and it is unclear why this happens.

In a new study, researchers ... sought to understand why this group of non-high-risk patients go on to experience such an aggressive cancer. ...

In particular, they used single-cell RNA sequencing, which is a technique that allowed the team to examine gene activity in individual cancer cells. This revealed the true aggressive face of cancer cells that had ordinarily been classified as non-high-risk.

The team also used a method called spatial transcriptomics, which enabled the scientists to map where the cancer cells were located within the tumour, revealing how aggressive cell populations are organised within the cancer tissue.

The study revealed that aggressive tumours of children who had been classified as non-high-risk have gene expression patterns that closely resemble those of high-risk tumours, despite lacking the genetic risk marker.

They also found that children with non-high-risk tumours which behaved aggressively carry rare genetic changes that affect the same cellular pathway as high-risk tumours. This suggests that there are multiple genetic routes leading to the same aggressive tumours. ..."

From the abstract:

"Somatic mutations often predict survival in childhood cancers, as exemplified in rhabdomyosarcoma (RMS), in which FOXO1 gene fusion status is a key prognostic feature.

In this study, we examined single-cell transcriptomes and discovered that cancer cells of lethal disease converge on a common cell state with a shared transcriptional landscape, irrespective of fusion status.

Nuclear transcriptomics, chromatin accessibility, spatial transcriptomics, perturbation studies, and previously published datasets validated the overarching high-risk cell state.

The convergent cell state only partially overlapped with transcriptional effects of the FOXO1 fusion and unexpectedly exhibited neural features.

Overall, these findings delineate a cell state of high-risk RMS cells that transcends conventional molecular and histologic boundaries, suggesting an overarching disease phenotype that could transform target discovery and inform clinical practice."

Hidden drivers of aggressive childhood cancer revealed "New clues have been uncovered about why the childhood cancer, rhabdomyosarcoma, may behave aggressively. "

High-Risk Rhabdomyosarcomas Feature a Convergent Cell State (open access)

Hidden source of genetic diversity found in human sperm

Amazing stuff!

"... Scientists have identified an unexpected source of genetic variation in human sperm that occurs earlier in sperm development than previously thought. ...

researchers ... found that one type of genetic recombination involving the chromosomes, called non-crossover gene conversion, happens before the cell divisions that produce sperm.

The findings suggest that genetic recombination events in sperm happen in two stages, both before and after cell division. The team found that these DNA recombination patterns can vary between individuals, including between identical twins. This study opens new opportunities to investigate biological mechanisms underlying fertility, genome evolution and inherited disease. ..."

From the abstract:

"Meiotic recombination is a fundamental process that generates genetic diversity by creating new combinations of existing alleles. Whereas crossovers in humans are well characterized, the more frequent non-crossovers that lead to gene conversion remain challenging to study.

Here we show that single high-fidelity long sequencing reads from sperm can capture both crossovers and non-crossovers, which enables effectively arbitrary sample sizes for analysis from a single male.

We analysed 2,382 candidate non-crossovers in 15 sperm samples from 13 donors, and identified a consistent component with properties distinct from PRDM9-induced recombination.

This phenomenon was not associated with meiotic double-strand break sites identified by DMC1 binding, the crossover recombination map or GC-biased gene conversion, but was associated with genomic fragile sites.

This component is also seen in paternal non-crossover gene conversions in pedigree data.

Applying the same analysis to 12 blood samples, we observed non-crossover gene conversions with similar properties, but very few crossover events.

Further, we demonstrate variation between donors for the different types of recombination, even when they share the same PRDM9 genotype.

We suggest that a substantial fraction of the non-crossover gene conversion events seen in sperm arise prior to meiosis."

Hidden source of genetic diversity found in human sperm "New research provides a detailed view of how genetic diversity is generated in sperm and opens new opportunities to investigate the biological mechanisms underlying fertility, genome evolution, and inherited disease."

Long-read sequencing reveals pre-meiotic gene conversion in sperm (open access)

Fig. 1: Detecting recombinant reads in sperm samples.

Fig. 4: Origins of meiotic and pre-meiotic recombination events in the male germline.