bims-tumhet 2023-04-02 papers

Issue of 2023–04–02
nine papers selected by
Sergio Marchini, Humanitas Research

J Genet Genomics. 2023 Mar 27. pii: S1673-8527(23)00075-9. [Epub ahead of print]

Spatially resolved transcriptomics: a comprehensive review of their technological advances, applications, and challenges.

Mengnan Cheng, Yujia Jiang, Jiangshan Xu, Alexios-Fotios A Mentis, Shuai Wang, Huiwen Zheng, Sunil Kumar Sahu, Longqi Liu, Xun Xu.

The ability to explore life kingdoms is largely drive by innovations and breakthroughs in technology, from the invention of the microscope 350 years ago to the recent emergence of single cell sequencing, by which the scientific community has been able to visualize life at an unprecedented resolution. Most recently, the Spatially Resolved Transcriptomics (SRT) technologies have filled the gap in probing the spatial or even three-dimensional (3D) organization of the molecular foundation behind the molecular mysteries of life, including the origin of different cellular populations developed from totipotent cells and human diseases. In this review, we introduce recent progress and challenges on SRT from the perspectives of technologies and bioinformatic tools, as well as the representative SRT applications. With the currently fast-moving progress of the SRT technologies and promising results from early adopted research projects, we can foresee the bright future of such new tools in understanding life at the most profound analytical level.

Keywords: Bioinformatic tools; Cell communications; Spatial single cell; Spatially resolved transcriptomics; Three-dimensional organ; Tissue dissection

DOI: https://doi.org/10.1016/j.jgg.2023.03.011

bioRxiv. 2023 Mar 24. pii: 2023.02.03.527053. [Epub ahead of print]

Gene panel selection for targeted spatial transcriptomics.

Yida Zhang, Viktor Petukhov, Evan Biederstedt, Richard Que, Kun Zhang, Peter V Kharchenko.

Targeted spatial transcriptomics hold particular promise in analysis of complex tissues. Most such methods, however, measure only a limited panel of transcripts, which need to be selected in advance to inform on the cell types or processes being studied. A limitation of existing gene selection methods is that they rely on scRNA-seq data, ignoring platform effects between technologies. Here we describe gpsFISH, a computational method to perform gene selection through optimizing detection of known cell types. By modeling and adjusting for platform effects, gpsFISH outperforms other methods. Furthermore, gpsFISH can incorporate cell type hierarchies and custom gene preferences to accommodate diverse design requirements.

DOI: https://doi.org/10.1101/2023.02.03.527053

bioRxiv. 2023 Mar 14. pii: 2023.03.13.532412. [Epub ahead of print]

Analysis of RNA processing directly from spatial transcriptomics data reveals previously unknown regulation.

Julia Olivieri, Julia Salzman.

Technical advances have led to an explosion in the amount of biological data available in recent years, especially in the field of RNA sequencing. Specifically, spatial transcriptomics (ST) datasets, which allow each RNA molecule to be mapped to the 2D location it originated from within a tissue, have become readily available. Due to computational challenges, ST data has rarely been used to study RNA processing such as splicing or differential UTR usage. We apply the ReadZS and the SpliZ, methods developed to analyze RNA process in scRNA-seq data, to analyze spatial localization of RNA processing directly from ST data for the first time. Using Moranâ€™s I metric for spatial autocorrelation, we identify genes with spatially regulated RNA processing in the mouse brain and kidney, re-discovering known spatial regulation in Myl6 and identifying previously-unknown spatial regulation in genes such as Rps24, Gng13, Slc8a1, Gpm6a, Gpx3, ActB, Rps8 , and S100A9 . The rich set of discoveries made here from commonly used reference datasets provides a small taste of what can be learned by applying this technique more broadly to the large quantity of Visium data currently being created.

DOI: https://doi.org/10.1101/2023.03.13.532412

Medicina (Kaunas). 2023 Mar 10. pii: 544. [Epub ahead of print]59(3):

Ovarian Cancer-Insights into Platinum Resistance and Overcoming It.

Andrei Havasi, Simona Sorana Cainap, Ana Teodora Havasi, Calin Cainap.

Ovarian cancer is the most lethal gynecologic malignancy. Platinum-based chemotherapy is the backbone of treatment for ovarian cancer, and although the majority of patients initially have a platinum-sensitive disease, through multiple recurrences, they will acquire resistance. Platinum-resistant recurrent ovarian cancer has a poor prognosis and few treatment options with limited efficacy. Resistance to platinum compounds is a complex process involving multiple mechanisms pertaining not only to the tumoral cell but also to the tumoral microenvironment. In this review, we discuss the molecular mechanism involved in ovarian cancer cells' resistance to platinum-based chemotherapy, focusing on the alteration of drug influx and efflux pathways, DNA repair, the dysregulation of epigenetic modulation, and the involvement of the tumoral microenvironment in the acquisition of the platinum-resistant phenotype. Furthermore, we review promising alternative treatment approaches that may improve these patients' poor prognosis, discussing current strategies, novel combinations, and therapeutic agents.

Keywords: ovarian cancer; overcoming platinum resistance; platinum resistance; platinum resistance mechanisms

DOI: https://doi.org/10.3390/medicina59030544

J Gene Med. 2023 Mar 30. e3504

Single-Cell RNA-Sequencing Analysis Reveals Divergent Transcriptome Events between Platinum-Sensitive and Platinum-Resistant High-Grade Serous Ovarian Carcinoma.

Zixun Wang, Linlin Yang, Xiaoye Su, Xiaomei Wu, Rongjia Su.

BACKGROUND: Tumor resistance is one of the main reasons leading to the failure of ovarian cancer treatment. Overcoming platinum resistance remains the greatest challenge in the management of High-grade serous ovarian carcinoma (HGSC).
METHODS: ScRNA-seq is a powerful method to explore the complexity of the cellular components and their interactions in the tumor microenvironment. We profiled the transcriptomes of 35042 cells from 2 platinum-sensitive and 3 platinum resistance HGSC clinical cases downloaded from Gene Expression Omnibus (GSE154600) and annotated tumor cells as platinum-resistant or sensitive based on the clinical trait. This study systematically investigated the inter-tumoral (using differential expression analysis, Cellchat, and SCENIC) and intra-tumoral heterogeneity (using enrichment analysis such as GSEA as well as GSVA, WGCNA, and Pseudo-time analysis) of HGSC.
RESULTS: A cellular map of HGSC generated by profiling 30,780 cells was revisualized using UMAP. The inter-tumoral heterogeneity was demonstrated with intercellular ligand-receptor interactions of major cell types and regulons networks. FN1, SPP1, and COLLAGEN play important roles in the crosstalk between tumor cells and the tumor microenvironment. HOXA7, HOXA9_extended, TBL1XR1_extended, KLF5, SOX17 and CTCFL regulons consistent with the distribution of platinum-resistant HGSC cells were the high activity regions. The intra-tumoral heterogeneity of HGSC was presented with corresponding functional pathway characteristics, tumor stemness features, and the cellular lineage transition from platinum-sensitive to resistant condition. EMT played an important role in platinum resistance, while oxidative phosphorylation is the opposite. There was a small subset of cells in platinum-sensitive samples which had transcriptomic characteristics similar to platinum-resistant cells, suggesting that the progression of platinum resistance in ovarian cancer is inevitable.
CONCLUSION: Our study presents a view of HGSC at single-cell resolution that reveals the characteristics of the HGSC heterogeneity and provided a useful framework for future investigation of platinum-resistant.

Keywords: EMT; HGSC; platinum resistance; scRNA-seq; tumor heterogeneity

DOI: https://doi.org/10.1002/jgm.3504

J Clin Invest. 2023 Mar 28. pii: e165934. [Epub ahead of print]

POLQ inhibition elicits an immune response in homologous recombination-deficient pancreatic adenocarcinoma via cGAS/STING signaling.

Grace Oh, Annie Wang, Lidong Wang, Jiufeng Li, Gregor Werba, Daniel Weissinger, Ende Zhao, Surajit Dhara, Rosmel E Hernandez, Amanda Ackermann, Sarina Porcella, Despoina Kalfakakou, Igor Dolgalev, Emily A Kawaler, Talia Golan, Theodore H Welling, Agnel Sfeir, Diane M Simeone.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy that harbors mutations in homologous recombination (HR) repair proteins in 20-25% of cases. Defects in HR impart to tumor cells a specific vulnerability to poly-ADP ribose polymerase inhibitors and platinum-containing chemotherapy. However, not all patients who receive these therapies respond, and many who initially respond ultimately develop resistance. Inactivation of the HR pathway is associated with the overexpression of polymerase theta (Polθ, or POLQ). This key enzyme regulates the microhomology-mediated end-joining (MMEJ) pathway of double-strand break (DSB) repair. Using human and murine HR-deficient PDAC models, we find that POLQ knockdown is synthetically lethal with mutations in HR genes (BRCA1 and BRCA2) and the DNA damage repair gene ATM. Further, POLQ knockdown enhances cytosolic micronuclei formation and activates cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling, leading to enhanced infiltration of activated CD8+ T cells in BRCA2-deficient PDAC tumors in vivo. Overall, POLQ, a key mediator in the MMEJ pathway, is critical for DSB repair in BRCA2-deficient PDAC. Its inhibition represents a synthetic lethal approach to block tumor growth while simultaneously stimulating an immune response.

Keywords: Cancer; Cell Biology; DNA repair; T cells

DOI: https://doi.org/10.1172/JCI165934

Microbiol Spectr. 2023 Mar 28. e0354922

The Interaction between Intratumoral Microbiome and Immunity Is Related to the Prognosis of Ovarian Cancer.

Dashuang Sheng, Kaile Yue, Hongfeng Li, Lanlan Zhao, Guoping Zhao, Chuandi Jin, Lei Zhang.

Microbiota can influence the occurrence, development, and therapeutic response of a wide variety of cancer types by modulating immune responses to tumors. Recent studies have demonstrated the existence of intratumor bacteria inside ovarian cancer (OV). However, whether intratumor microbes are associated with tumor microenvironment (TME) and prognosis of OV still remains unknown. The RNA-sequencing data and clinical and survival data of 373 patients with OV in The Cancer Genome Atlas (TCGA) were collected and downloaded. According to the knowledge-based functional gene expression signatures (Fges), OV was classified into two subtypes, termed immune-enriched and immune-deficient subtypes. The immune-enriched subtype, which had higher immune infiltration enriched with CD8+ T cells and the M1 type of macrophages (M1) and higher tumor mutational burden, exhibited a better prognosis. Based on the Kraken2 pipeline, the microbiome profiles were explored and found to be significantly different between the two subtypes. A prediction model consisting of 32 microbial signatures was constructed using the Cox proportional-hazard model and showed great prognostic value for OV patients. The prognostic microbial signatures were strongly associated with the hosts' immune factors. Especially, M1 was strongly associated with five species (Achromobacter deleyi and Microcella alkaliphila, Devosia sp. strain LEGU1, Ancylobacter pratisalsi, and Acinetobacter seifertii). Cell experiments demonstrated that Acinetobacter seifertii can inhibit macrophage migration. Our study demonstrated that OV could be classified into immune-enriched and immune-deficient subtypes and that the intratumoral microbiota profiles were different between the two subtypes. Furthermore, the intratumoral microbiome was closely associated with the tumor immune microenvironment and OV prognosis. IMPORTANCE Recent studies have demonstrated the existence of intratumoral microorganisms. However, the role of intratumoral microbes in the development of ovarian cancer and their interaction with the tumor microenvironment are largely unknown. Our study demonstrated that OV could be classified into immune-enriched and -deficient subtypes and that the immune enrichment subtype had a better prognosis. Microbiome analysis showed that intratumor microbiota profiles were different between the two subtypes. Furthermore, the intratumor microbiome was an independent predictor of OV prognosis that could interact with immune gene expression. Especially, M1 was closely associated with intratumoral microbes, and Acinetobacter seifertii could inhibit macrophage migration. Together, the findings of our study highlight the important roles of intratumoral microbes in the TME and prognosis of OV, paving the way for further investigation into its underlying mechanisms.

Keywords: gynecological; microbiome; ovarian cancer; prognostic biomarkers; tumor microenvironment

DOI: https://doi.org/10.1128/spectrum.03549-22