bims-tumhet 2024-08-25 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2024‒08‒25
ten papers selected by
Sergio Marchini, Humanitas Research

Ovarian Cancer Risk Prediction - a Clinical Epidemiology Perspective.
Unleashing precision: a review of targeted approaches in pleural mesothelioma.
Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics.
Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in lethal prostate cancer.
Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing.
Latest Research Progress of Liquid Biopsy in Tumor-A Narrative Review.
Genome-scale quantification and prediction of pathogenic stop codon readthrough by small molecules.
Chemotherapy drives tertiary lymphoid structures that correlate with ICI-responsive TCF1+CD8+ T cells in metastatic ovarian cancer.
Applications of single-cell technologies in drug discovery for tumor treatment.
New clinicopathological concept of endometrial carcinoma with integration of histological features and molecular profiles.

Am J Epidemiol. 2024 Aug 21. pii: kwae293. [Epub ahead of print]

Ovarian Cancer Risk Prediction - a Clinical Epidemiology Perspective.

Nicolas Wentzensen, Kari Ring, Britt K Erickson, Brett Reid, Thomas O'Donnell, David Check, Shelley S Tworoger, Parichoy Pal Choudhury.

  Ovarian cancer is a rare and highly heterogeneous disease usually detected at late stages when outcomes are poor. Population-based screening approaches have not been successful at reducing ovarian cancer mortality, but preventive bilateral salpingo-oophorectomy is highly effective at preventing ovarian cancer in high-risk populations. Ovarian cancer risk prediction models may allow identification of populations at increased risk of ovarian cancer for preventive interventions or targeted early detection. We propose a life-course approach to ovarian cancer risk prediction based on the time at which a risk model should be applied and the risk factors that are available. The discriminative ability of ovarian cancer risk prediction models published so far is limited, with areas under the curve ranging from 0.58-0.65 for different combinations of risk factors and genetic susceptibility markers. Currently proposed absolute risk thresholds for preventive surgery are around 4% lifetime risk. The absolute risk predicted by ovarian cancer risk models ranges from 0.6-2.5% lifetime risk in the general population, highlighting the need to improve ovarian cancer risk prediction models and evaluating new preventive approaches that can be offered to individuals at lower risk.

Keywords:  clinical epidemiology; ovarian cancer; prevention; risk prediction

DOI:  https://doi.org/10.1093/aje/kwae293
Crit Rev Oncol Hematol. 2024 Aug 17. pii: S1040-8428(24)00224-5. [Epub ahead of print] 104481

Unleashing precision: a review of targeted approaches in pleural mesothelioma.

Mario Occhipinti, Marta Brambilla, Raimondo Di Liello, Paolo Ambrosini, Lorenzo Lobianco, Rita Leporati, Maria Salvarezza, Fabiana Vitiello, Silvia Marchesi, Sara Manglaviti, Teresa Beninato, Laura Mazzeo, Claudia Proto, Arsela Prelaj, Roberto Ferrara, Carminia Maria Della Corte, Giuseppe Lo Russo, Filippo de Braud, Monica Ganzinelli, Giuseppe Viscardi.

  This review delves into the intricate landscape of pleural mesothelioma (PM), emphasizing the need for nuanced therapeutic strategies. While platinum-based chemotherapy remains a cornerstone, the advent of immune checkpoint inhibitors (ICIs), notably through the Checkmate 743 trial, has reshaped treatment paradigms. Challenges persist due to patient heterogeneity and a lack of specific biomarkers. Targeting genotypic and phenotypic alterations emerges as a promising avenue, demanding precision oncology in this rare disease. CDKN2A loss, prevalent in PM, may respond to CDK4/6 inhibitors. Defects in MMR and HR suggest tailored approaches with ICI or PARP inhibitors, respectively. Ongoing trials explore novel inhibitors and promising targets like MSLN. Implementing these strategies requires overcoming challenges in patient selection, combination therapies, biomarker identification, and cost considerations. Collaboration is crucial for transforming these insights into impactful clinical interventions, heralding the era of personalized and precision medicine for PM.

Keywords:  Pleural mesothelioma; Precision medicine; Targeted treatments

DOI:  https://doi.org/10.1016/j.critrevonc.2024.104481
Nat Rev Mol Cell Biol. 2024 Aug 21.

Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics.

Gunsagar S Gulati, Jeremy Philip D'Silva, Yunhe Liu, Linghua Wang, Aaron M Newman.

Single-cell transcriptomics has broadened our understanding of cellular diversity and gene expression dynamics in healthy and diseased tissues. Recently, spatial transcriptomics has emerged as a tool to contextualize single cells in multicellular neighbourhoods and to identify spatially recurrent phenotypes, or ecotypes. These technologies have generated vast datasets with targeted-transcriptome and whole-transcriptome profiles of hundreds to millions of cells. Such data have provided new insights into developmental hierarchies, cellular plasticity and diverse tissue microenvironments, and spurred a burst of innovation in computational methods for single-cell analysis. In this Review, we discuss recent advancements, ongoing challenges and prospects in identifying and characterizing cell states and multicellular neighbourhoods. We discuss recent progress in sample processing, data integration, identification of subtle cell states, trajectory modelling, deconvolution and spatial analysis. Furthermore, we discuss the increasing application of deep learning, including foundation models, in analysing single-cell and spatial transcriptomics data. Finally, we discuss recent applications of these tools in the fields of stem cell biology, immunology, and tumour biology, and the future of single-cell and spatial transcriptomics in biological research and its translation to the clinic.

DOI: https://doi.org/10.1038/s41580-024-00768-2
Clin Cancer Res. 2024 Aug 23.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in lethal prostate cancer.

Pradeep S Chauhan, Irfan Alahi, Savar Sinha, Elisa M Ledet, Ryan Mueller, Jessica Linford, Alexander L Shiang, Jace Webster, Lilli Greiner, Breanna Yang, Gabris Ni, Ha X Dang, Debanjan Saha, Ramandeep K Babbra, Wenjia Feng, Peter K Harris, Faridi Qaium, Dzifa Y Duose, Alexander Sanchez-Espitia, Alexander D Sherry, Ellen B Jaeger, Patrick J Miller, Sydney A Caputo, Jacob J Orme, Fabrice Lucien, Sean S Park, Chad Tang, Russell K Pachynski, Oliver Sartor, Christopher A Maher, Aadel A Chaudhuri.

PURPOSE: Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor signaling inhibitors (ARSIs) is often lethal. Liquid biopsy biomarkers for this deadly form of disease remain under investigation, and underpinning mechanisms remain ill-understood.EXPERIMENTAL DESIGN: We applied targeted cell-free DNA sequencing to 126 mCRPC patients from three academic cancer centers, and separately performed genome-wide cell-free DNA methylation sequencing on 43 plasma samples collected prior to the initiation of first-line ARSI treatment. To analyze the genome-wide sequencing data, we performed nucleosome-positioning and differential methylated region analysis. We additionally analyzed single-cell and bulk RNA sequencing data from 14 and 80 mCRPC patients, respectively, to develop and validate a stem-like signature, which we inferred from cell-free DNA.
RESULTS: Targeted cell-free DNA sequencing detected AR/enhancer alterations prior to first-line ARSIs which correlated with significantly worse PFS (p = 0.01; HR = 2.12) and OS (p = 0.02; HR = 2.48). Plasma methylome analysis revealed that AR/enhancer lethal mCRPC patients have significantly higher promoter-level hypomethylation than AR/enhancer wild-type mCRPC patients (p < 0.0001). Moreover, gene ontology and CytoTRACE analysis of nucleosomally more accessible transcription factors in cell-free DNA revealed enrichment for stemness-associated transcription factors in lethal mCRPC patients. The resulting stemness signature was then validated in a completely held-out cohort of 80 mCRPC patients profiled by tumor RNA sequencing.
CONCLUSIONS: We analyzed a total of 220 mCRPC patients, validated the importance of cell-free AR/enhancer alterations as a prognostic biomarker in lethal mCRPC and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness.

DOI: https://doi.org/10.1158/1078-0432.CCR-24-1658
Sci Data. 2024 Aug 16. 11(1): 892

Targeted DNA-seq and RNA-seq of Reference Samples with Short-read and Long-read Sequencing.

Binsheng Gong, Dan Li, Paweł P Łabaj, Bohu Pan, Natalia Novoradovskaya, Danielle Thierry-Mieg, Jean Thierry-Mieg, Guangchun Chen, Anne Bergstrom Lucas, Jennifer S LoCoco, Todd A Richmond, Elizabeth Tseng, Rebecca Kusko, Scott Happe, Timothy R Mercer, Carlos Pabón-Peña, Michael Salmans, Hagen U Tilgner, Wenzhong Xiao, Donald J Johann, Wendell Jones, Weida Tong, Christopher E Mason, David P Kreil, Joshua Xu.

Next-generation sequencing (NGS) has revolutionized genomic research by enabling high-throughput, cost-effective genome and transcriptome sequencing accelerating personalized medicine for complex diseases, including cancer. Whole genome/transcriptome sequencing (WGS/WTS) provides comprehensive insights, while targeted sequencing is more cost-effective and sensitive. In comparison to short-read sequencing, which still dominates the field due to high speed and cost-effectiveness, long-read sequencing can overcome alignment limitations and better discriminate similar sequences from alternative transcripts or repetitive regions. Hybrid sequencing combines the best strengths of different technologies for a more comprehensive view of genomic/transcriptomic variations. Understanding each technology's strengths and limitations is critical for translating cutting-edge technologies into clinical applications. In this study, we sequenced DNA and RNA libraries of reference samples using various targeted DNA and RNA panels and the whole transcriptome on both short-read and long-read platforms. This study design enables a comprehensive analysis of sequencing technologies, targeting protocols, and library preparation methods. Our expanded profiling landscape establishes a reference point for assessing current sequencing technologies, facilitating informed decision-making in genomic research and precision medicine.

DOI: https://doi.org/10.1038/s41597-024-03741-y
Cancer Manag Res. 2024 ;16 1031-1042

Latest Research Progress of Liquid Biopsy in Tumor-A Narrative Review.

Hua Jiang.

  Human life expectancy is significantly impacted by cancer, with liquid biopsy emerging as an advantageous method for cancer detection because of its noninvasive nature, high accuracy, ease of sampling, and cost-effectiveness compared with conventional tissue biopsy techniques. Liquid biopsy shows promise in early cancer detection, real-time monitoring, and personalized treatment for various cancers, including lung, cervical, and prostate cancers, and offers innovative approaches for cancer diagnosis and management. By utilizing circulating tumor DNA, circulating tumor cells, and exosomes as biomarkers, liquid biopsy enables the tracking of cancer progression. Various techniques commonly used in life sciences research, such as polymerase chain reaction (PCR), next-generation sequencing (NGS), and droplet digital PCR, are employed to assess cancer progression on the basis of different indicators. This review examines the latest advancements in liquid biopsy markers-circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), and exosomes-for cancer diagnosis over the past three years, with a focus on their detection methodologies and clinical applications. It encapsulates the pivotal aims of liquid biopsy, including early detection, therapy response prediction, treatment monitoring, prognostication, and its relevance in minimal residual disease, while also addressing the challenges facing routine clinical adoption. By combining the latest research advancements and practical clinical experiences, this work focuses on discussing the clinical significance of DNA methylation biomarkers and their applications in tumor screening, auxiliary diagnosis, companion diagnosis, and recurrence monitoring. These discussions may help enhance the application of liquid biopsy throughout the entire process of tumor diagnosis and treatment, thereby providing patients with more precise and effective treatment plans.

Keywords:  DNA methylation; circulating tumor DNA; circulating tumor cells; exosomes; liquid biopsy

DOI:  https://doi.org/10.2147/CMAR.S479338
Nat Genet. 2024 Aug 22.

Genome-scale quantification and prediction of pathogenic stop codon readthrough by small molecules.

Ignasi Toledano, Fran Supek, Ben Lehner.

Premature termination codons (PTCs) cause ~10-20% of inherited diseases and are a major mechanism of tumor suppressor gene inactivation in cancer. A general strategy to alleviate the effects of PTCs would be to promote translational readthrough. Nonsense suppression by small molecules has proven effective in diverse disease models, but translation into the clinic is hampered by ineffective readthrough of many PTCs. Here we directly tackle the challenge of defining drug efficacy by quantifying the readthrough of ~5,800 human pathogenic stop codons by eight drugs. We find that different drugs promote the readthrough of complementary subsets of PTCs defined by local sequence context. This allows us to build interpretable models that accurately predict drug-induced readthrough genome-wide, and we validate these models by quantifying endogenous stop codon readthrough. Accurate readthrough quantification and prediction will empower clinical trial design and the development of personalized nonsense suppression therapies.

DOI: https://doi.org/10.1038/s41588-024-01878-5
Clin Cancer Res. 2024 Aug 20.

Chemotherapy drives tertiary lymphoid structures that correlate with ICI-responsive TCF1+CD8+ T cells in metastatic ovarian cancer.

Tereza Lanickova, Michal Hensler, Lenka Kasikova, Sarka Vosahlikova, Artemis Angelidou, Josef Pasulka, Hannah Griebler, Jana Drozenova, Katerina Mojzisova, Ann Vankerckhoven, Jan Laco, Aleš Ryška, Pavel Dundr, Roman Kocian, David Cibula, Tomas Brtnicky, Petr Skapa, Francis Jacob, Marek Kovar, Ivan Praznovec, Iain A McNeish, Michael J Halaska, Lukas Rob, An Coosemans, Sandra Orsulic, Lorenzo Galluzzi, Radek Spisek, Jitka Fucikova.

PURPOSE: Patients with high-grade serous ovarian carcinoma (HGSOC) are virtually insensitive to immune checkpoint inhibitors (ICIs) employed as standalone therapeutics, at least in part reflecting microenvironmental immunosuppression. Thus, conventional chemotherapeutics and targeted anticancer agents that not only mediate cytotoxic effects but also promote the recruitment of immune effector cells to the HGSOC microenvironment stand out as promising combinatorial partners for ICIs in this oncological indication.EXPERIMENTAL DESIGN: We harnessed a variety of transcriptomic, spatial and functional assays to characterize the differential impact of neo-adjuvant paclitaxel-carboplatin on the immunological configuration of paired primary and metastatic HGSOC biopsies as compared to NACT-naïve HGSOC samples from 5 independent patient cohorts.
RESULTS: We found neo-adjuvant chemotherapy (NACT)-driven endoplasmic reticulum stress and calreticulin exposure in metastatic HGSOC lesions culminates with the establishment of a dense immune infiltrate including follicular T cells (TFH cells), a prerequisite for mature tertiary lymphoid structure (TLS) formation. In this context, TLS maturation was associated with an increased intratumoral density of ICI-sensitive TCF1+PD-1+ CD8+ T cells over their ICI-insensitive TIM-3+PD-1+ counterparts. Consistent with this notion, chemotherapy coupled with a PD-1-targeting ICI provided a significant survival benefit over either therapeutic approach in syngeneic models of HGSOC bearing high (but not low) tumor mutational burden.
CONCLUSION: Altogether, our findings suggest that NACT promotes TLS formation and maturation in HGSOC lesions, de facto preserving an intratumoral ICI-sensitive T-cell phenotype. These observations emphasize the role of rational design, especially relative to the administration schedule, for clinical trials testing chemotherapy plus ICIs in patients with HGSOC.

DOI: https://doi.org/10.1158/1078-0432.CCR-24-1594
iScience. 2024 Aug 16. 27(8): 110486

Applications of single-cell technologies in drug discovery for tumor treatment.

Bingyu Liu, Shunfeng Hu, Xin Wang.

  Single-cell technologies have been known as advanced and powerful tools to study tumor biological systems at the single-cell resolution and are playing increasingly critical roles in multiple stages of drug discovery and development. Specifically, single-cell technologies can promote the discovery of drug targets, help high-throughput screening at single-cell level, and contribute to pharmacokinetic studies of anti-tumor drugs. Emerging single-cell analysis technologies have been developed to further integrating multidimensional single-cell molecular features, expanding the scale of single-cell data, profiling phenotypic impact of genes in single cell, and providing full-length coverage single-cell sequencing. In this review, we systematically summarized the applications of single-cell technologies in various sections of drug discovery for tumor treatment, including target identification, high-throughput drug screening, and pharmacokinetic evaluation and highlighted emerging single-cell technologies in providing in-depth understanding of tumor biology. Single-cell-technology-based drug discovery is expected to further optimize therapeutic strategies and improve clinical outcomes of tumor patients.

Keywords:  Cancer; Cell biology

DOI:  https://doi.org/10.1016/j.isci.2024.110486
Pathol Int. 2024 Aug 22.

New clinicopathological concept of endometrial carcinoma with integration of histological features and molecular profiles.

Masanori Yasuda.

  The dual-stratified pathway of endometrial carcinomas (ECs) has long been dominant. However, in 2013, The Cancer Genome Atlas (TCGA) defined four EC subgroups with distinctive prognoses. Inspired by TCGA, in 2018, the Proactive Molecular Risk Classifier for Endometrial Cancer (ProMisE) provided four pragmatic molecular classifiers to apply surrogate immunohistochemical markers to TCGA subgroup categorization. These trends prompted the revision of 2020 WHO Classification of Female Genital Tumors, 5th edition (2020 WHO classification), in which four molecular subtypes are recognized: POLE-ultramutated; mismatch repair-deficient; p53-mutant; and no specific molecular profile. In the 2020 WHO classification, the diagnostic algorithm is characterized by prioritizing POLEmut over other molecular abnormalities. Following the 2020 WHO classification, Federation of International Gynecology and Obstetrics (FIGO) proposed a new staging system in 2023. The updated system focuses on diagnostic parameters, such as histological type and grade, lymphovascular space invasion, and molecular alterations. These new histomolecular diagnostic concepts of ECs are being accordingly introduced into the routine pathology practice. For the first time, the 2020 WHO classification includes mesonephric-like adenocarcinoma (MLA) as a novel histological entity, mimicking the conventional mesonephric adenocarcinoma, but is considered of Müllerian ductal origin.

Keywords:  POLE mutation; endometrial carcinoma; histomolecular classification; mesonephric‐like adenocarcinoma

DOI:  https://doi.org/10.1111/pin.13471