bims-tumhet 2024-06-16 papers

Issue of 2024–06–16
seven papers selected by
Sergio Marchini, Humanitas Research

J Cancer Res Clin Oncol. 2024 Jun 08. 150(6): 296

Spatial transcriptomics in cancer research and potential clinical impact: a narrative review.

Michael A Cilento, Christopher J Sweeney, Lisa M Butler.

Spatial transcriptomics (ST) provides novel insights into the tumor microenvironment (TME). ST allows the quantification and illustration of gene expression profiles in the spatial context of tissues, including both the cancer cells and the microenvironment in which they are found. In cancer research, ST has already provided novel insights into cancer metastasis, prognosis, and immunotherapy responsiveness. The clinical precision oncology application of next-generation sequencing (NGS) and RNA profiling of tumors relies on bulk methods that lack spatial context. The ability to preserve spatial information is now possible, as it allows us to capture tumor heterogeneity and multifocality. In this narrative review, we summarize precision oncology, discuss tumor sequencing in the clinic, and review the available ST research methods, including seqFISH, MERFISH (Vizgen), CosMx SMI (NanoString), Xenium (10x), Visium (10x), Stereo-seq (STOmics), and GeoMx DSP (NanoString). We then review the current ST literature with a focus on solid tumors organized by tumor type. Finally, we conclude by addressing an important question: how will spatial transcriptomics ultimately help patients with cancer?

Keywords: Genetics; Precision oncology; Solid tumors; Spatial transcriptomics; Tumor microenvironment

DOI: https://doi.org/10.1007/s00432-024-05816-0

Nat Commun. 2024 Jun 11. 15(1): 4987

Optimizing the design of spatial genomic studies.

Andrew Jones, Diana Cai, Didong Li, Barbara E Engelhardt.

Spatial genomic technologies characterize the relationship between the structural organization of cells and their cellular state. Despite the availability of various spatial transcriptomic and proteomic profiling platforms, these experiments remain costly and labor-intensive. Traditionally, tissue slicing for spatial sequencing involves parallel axis-aligned sections, often yielding redundant or correlated information. We propose structured batch experimental design, a method that improves the cost efficiency of spatial genomics experiments by profiling tissue slices that are maximally informative, while recognizing the destructive nature of the process. Applied to two spatial genomics studies-one to construct a spatially-resolved genomic atlas of a tissue and another to localize a region of interest in a tissue, such as a tumor-our approach collects more informative samples using fewer slices compared to traditional slicing strategies. This methodology offers a foundation for developing robust and cost-efficient design strategies, allowing spatial genomics studies to be deployed by smaller, resource-constrained labs.

DOI: https://doi.org/10.1038/s41467-024-49174-4

Front Oncol. 2024 ;14 1388663

Unlocking ovarian cancer heterogeneity: advancing immunotherapy through single-cell transcriptomics.

Dharvind Balan, Nirmala Chandralega Kampan, Magdalena Plebanski, Nor Haslinda Abd Aziz.

Ovarian cancer, a highly fatal gynecological cancer, warrants the need for understanding its heterogeneity. The disease's prevalence and impact are underscored with statistics on mortality rates. Ovarian cancer is categorized into distinct morphological groups, each with its characteristics and prognosis. Despite standard treatments, survival rates remain low due to relapses and chemoresistance. Immune system involvement is evident in ovarian cancer's progression, although the tumor employs immune evasion mechanisms. Immunotherapy, particularly immune checkpoint blockade therapy, is promising, but ovarian cancer's heterogeneity limits its efficacy. Single-cell sequencing technology could be explored as a solution to dissect the heterogeneity within tumor-associated immune cell populations and tumor microenvironments. This cutting-edge technology has the potential to enhance diagnosis, prognosis, and personalized immunotherapy in ovarian cancer, reflecting its broader application in cancer research. The present review focuses on recent advancements and the challenges in applying single-cell transcriptomics to ovarian cancer.

Keywords: heterogeneity; ovarian cancer; precision medicine; single-cell sequencing; tumor-microenvironment

DOI: https://doi.org/10.3389/fonc.2024.1388663

bioRxiv. 2024 May 28. pii: 2024.05.23.595550. [Epub ahead of print]

Stromal mediated DNA damage promotes high grade serous ovarian cancer initiation.

Geyon L Garcia, Taylor Orellana, Grace Gorecki, Leonard G Frisbie, Roja Baruwal, Ester Goldfield, Ian Beddows, Ian P MacFawn, Ananya K Britt, Macy M Hale, Hui Shen, Ronald Buckanovich, Toren Finkel, Ronny Drapkin, T Rinda Soong, Tullia C Bruno, Huda I Atiya, Lan Coffman.

The fundamental steps in high-grade serous ovarian cancer (HGSOC) initiation are unclear, thus providing critical barriers to the development of prevention or early detection strategies for this deadly disease. Increasing evidence demonstrates most HGSOC starts in the fallopian tube epithelium (FTE). Current models propose HGSOC initiates when FTE cells acquire increasing numbers of mutations allowing cells to evolve into serous tubal intraepithelial carcinoma (STIC) precursors and then to full blown cancer. Here we report that epigenetically altered mesenchymal stem cells (termed high risk MSC-hrMSCs) can be detected prior to the formation of ovarian cancer precursor lesions. These hrMSCs drive DNA damage in the form of DNA double strand breaks in FTE cells while also promoting the survival of FTE cells in the face of DNA damage. Indicating the hrMSC may actually drive cancer initiation, we find hrMSCs induce full malignant transformation of otherwise healthy, primary FTE resulting in metastatic cancer in vivo . Further supporting a role for hrMSCs in cancer initiation in humans, we demonstrate that hrMSCs are highly enriched in BRCA1/2 mutation carriers and increase with age. Combined these findings indicate that hrMSCs may incite ovarian cancer initiation. These findings have important implications for ovarian cancer detection and prevention.

DOI: https://doi.org/10.1101/2024.05.23.595550

Nat Med. 2024 Jun 14.

Ultrasensitive plasma-based monitoring of tumor burden using machine-learning-guided signal enrichment.

Adam J Widman, Minita Shah, Amanda Frydendahl, Daniel Halmos, Cole C Khamnei, Nadia Øgaard, Srinivas Rajagopalan, Anushri Arora, Aditya Deshpande, William F Hooper, Jean Quentin, Jake Bass, Mingxuan Zhang, Theophile Langanay, Laura Andersen, Zoe Steinsnyder, Will Liao, Mads Heilskov Rasmussen, Tenna Vesterman Henriksen, Sarah Østrup Jensen, Jesper Nors, Christina Therkildsen, Jesus Sotelo, Ryan Brand, Joshua S Schiffman, Ronak H Shah, Alexandre Pellan Cheng, Colleen Maher, Lavinia Spain, Kate Krause, Dennie T Frederick, Wendie den Brok, Caroline Lohrisch, Tamara Shenkier, Christine Simmons, Diego Villa, Andrew J Mungall, Richard Moore, Elena Zaikova, Viviana Cerda, Esther Kong, Daniel Lai, Murtaza S Malbari, Melissa Marton, Dina Manaa, Lara Winterkorn, Karen Gelmon, Margaret K Callahan, Genevieve Boland, Catherine Potenski, Jedd D Wolchok, Ashish Saxena, Samra Turajlic, Marcin Imielinski, Michael F Berger, Sam Aparicio, Nasser K Altorki, Michael A Postow, Nicolas Robine, Claus Lindbjerg Andersen, Dan A Landau.

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole-genome sequencing (WGS). Here we now introduce MRD-EDGE, a machine-learning-guided WGS ctDNA single-nucleotide variant (SNV) and copy-number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by ~300× compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, vastly expanding its applicability within solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in TF in response to neoadjuvant immunotherapy in lung cancer and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables plasma-only (non-tumor-informed) disease monitoring in advanced melanoma and lung cancer, yielding clinically informative TF monitoring for patients on immune-checkpoint inhibition.

DOI: https://doi.org/10.1038/s41591-024-03040-4

Cancer Discov. 2024 Jun 12. OF1-OF7

Tumor Promoters and Opportunities for Molecular Cancer Prevention.

William Hill, Clare E Weeden, Charles Swanton.

Environmental carcinogens increase cancer incidence via both mutagenic and non-mutagenic mechanisms. There are over 500 known or suspected carcinogens classified by the International Agency for Research on Cancer. Sequencing of both cancerous and histologically non-cancerous tissue has been instrumental in improving our understanding of how environmental carcinogens cause cancer. Understanding how and defining which environmental or lifestyle exposures drive cancer will support cancer prevention. Recent research is revisiting the mechanisms of early tumorigenesis, paving the way for an era of molecular cancer prevention. Significance: Recent data have improved our understanding of how carcinogens cause cancer, which may reveal novel opportunities for molecular cancer prevention.

DOI: https://doi.org/10.1158/2159-8290.CD-24-0128

J Transl Med. 2024 Jun 10. 22(1): 556

Genome-wide DNA methylation in relation to ARID1A deficiency in ovarian clear cell carcinoma.

Shang Li, Gert Jan Meersma, Jolanta Kupryjanczyk, Steven de Jong, G Bea A Wisman.

BACKGROUND: The poor chemo-response and high DNA methylation of ovarian clear cell carcinoma (OCCC) have attracted extensive attentions. Recently, we revealed the mutational landscape of the human kinome and additional cancer-related genes and found deleterious mutations in ARID1A, a component of the SWI/SNF chromatin-remodeling complex, in 46% of OCCC patients. The present study aims to comprehensively investigate whether ARID1A loss and genome-wide DNA methylation are co-regulated in OCCC and identify putative therapeutic targets epigenetically regulated by ARID1A.
METHODS: DNA methylation of ARID1Amt/ko and ARID1Awt OCCC tumors and cell lines were analyzed by Infinium MethylationEPIC BeadChip. The clustering of OCCC tumors in relation to clinical and mutational status of tumors were analyzed by hierarchical clustering analysis of genome-wide methylation. GEO expression profiles were used to identify differentially methylated (DM) genes and their expression level in ARID1Amt/ko vs ARID1Awt OCCCs. Combining three pre-ranked GSEAs, pathways and leading-edge genes epigenetically regulated by ARID1A were revealed. The leading-edge genes that passed the in-silico validation and showed consistent ARID1A-related methylation change in tumors and cell lines were regarded as candidate genes and finally verified by bisulfite sequencing and RT-qPCR.
RESULTS: Hierarchical clustering analysis of genome-wide methylation showed two clusters of OCCC tumors. Tumor stage, ARID1A/PIK3CA mutations and TP53 mutations were significantly different between the two clusters. ARID1A mutations in OCCC did not cause global DNA methylation changes but were related to DM promoter or gene-body CpG islands of 2004 genes. Three pre-ranked GSEAs collectively revealed the significant enrichment of EZH2- and H3K27me3-related gene-sets by the ARID1A-related DM genes. 13 Leading-edge DM genes extracted from the enriched gene-sets passed the expression-based in-silico validation and showed consistent ARID1A-related methylation change in tumors and cell lines. Bisulfite sequencing and RT-qPCR analysis showed promoter hypermethylation and lower expression of IRX1, TMEM101 and TRIP6 in ARID1Amt compared to ARID1Awt OCCC cells, which was reversed by 5-aza-2'-deoxycytidine treatment.
CONCLUSIONS: Our study shows that ARID1A loss is related to the differential methylation of a number of genes in OCCC. ARID1A-dependent DM genes have been identified as key genes of many cancer-related pathways that may provide new candidates for OCCC targeted treatment.

Keywords: ARID1A; DNA methylation; EZH2; Ovarian clear cell carcinoma

DOI: https://doi.org/10.1186/s12967-024-05311-7