bims-tumhet 2022-11-27 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2022‒11‒27
eleven papers selected by
Sergio Marchini
Humanitas Research

Benchmarking cell-type clustering methods for spatially resolved transcriptomics data.
Aetiology, Epidemiology, Histopathology, Classification, Detailed Evaluation, and Treatment of Ovarian Cancer.
Role of PARP Inhibitors in Cancer Immunotherapy: Potential Friends to Immune Activating Molecules and Foes to Immune Checkpoints.
Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives.
Spatially aware dimension reduction for spatial transcriptomics.
Regulatory T Cells in Ovarian Carcinogenesis and Future Therapeutic Opportunities.
The Emerging Role of Chromatin Remodeling Complexes in Ovarian Cancer.
Recent advances in the activation and regulation of the cGAS-STING pathway.
Up-front mutation detection in circulating tumor DNA by droplet digital PCR has added diagnostic value in lung cancer.
Trabectedin and lurbinectedin: Mechanisms of action, clinical impact, and future perspectives in uterine and soft tissue sarcoma, ovarian carcinoma, and endometrial carcinoma.
Establishment of an ovarian cancer omentum metastasis-related prognostic model by integrated analysis of scRNA-seq and bulk RNA-seq.

Brief Bioinform. 2022 Nov 21. pii: bbac475. [Epub ahead of print]

Benchmarking cell-type clustering methods for spatially resolved transcriptomics data.

Andrew Cheng, Guanyu Hu, Wei Vivian Li.

  Spatially resolved transcriptomics technologies enable the measurement of transcriptome information while retaining the spatial context at the regional, cellular or sub-cellular level. While previous computational methods have relied on gene expression information alone for clustering single-cell populations, more recent methods have begun to leverage spatial location and histology information to improve cell clustering and cell-type identification. In this study, using seven semi-synthetic datasets with real spatial locations, simulated gene expression and histology images as well as ground truth cell-type labels, we evaluate 15 clustering methods based on clustering accuracy, robustness to data variation and input parameters, computational efficiency, and software usability. Our analysis demonstrates that even though incorporating the additional spatial and histology information leads to increased accuracy in some datasets, it does not consistently improve clustering compared with using only gene expression data. Our results indicate that for the clustering of spatial transcriptomics data, there are still opportunities to enhance the overall accuracy and robustness by improving information extraction and feature selection from spatial and histology data.

Keywords:  Clustering; Single-cell genomics; Spatial trasncriptomics

DOI:  https://doi.org/10.1093/bib/bbac475
Cureus. 2022 Oct;14(10): e30561

Aetiology, Epidemiology, Histopathology, Classification, Detailed Evaluation, and Treatment of Ovarian Cancer.

Udit M Zamwar, Ashish P Anjankar.

  There are a minimum of five distinct sub-types of ovarian cancer based on histology, each of which has distinct factors of risk, types of cells, molecular makeups, clinical characteristics, and therapeutic approaches. Ovarian cancer is detected usually at later stages, and there is no reliable screening method. Cytoreductive surgery and chemotherapy which use platinum-containing drugs are the standard treatments used for freshly detected cancer. Chemotherapy, drugs that are anti-angiogenic, poly ADP-ribose polymerase inhibitors, and immunological treatments are all used to treat recurrent cancer. The most frequent type of ovarian cancer to be diagnosed is high-grade serous carcinoma (HGSC), which often responds well to platinum-based chemotherapy when discovered. However, HGSCs commonly relapse and develop increased treatment resistance in addition to the other histologies. As a result, ovarian cancer research is actively focused on understanding the processes causing platinum resistance and developing strategies to combat it. Serous tubal intraepithelial carcinoma is an HGSC precursor lesion. It is one of the early complications seen in ovarian carcinoma. It has been very useful in identifying the people who have a greater chance of developing ovarian cancer and development of strategies to prevent it. This has led to a significant progress for identification of the genes which are found in people with greater chances of development of ovarian carcinoma (for example, the BRCA1 and BRCA2).

Keywords:  aetiology; differential diagnosis; epidemiology; histopathology; ovarian cancer; risk factors

DOI:  https://doi.org/10.7759/cureus.30561
Cancers (Basel). 2022 Nov 16. pii: 5633. [Epub ahead of print]14(22):

Role of PARP Inhibitors in Cancer Immunotherapy: Potential Friends to Immune Activating Molecules and Foes to Immune Checkpoints.

Ornella Franzese, Grazia Graziani.

  Poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi) induce cytotoxic effects as single agents in tumors characterized by defective repair of DNA double-strand breaks deriving from BRCA1/2 mutations or other abnormalities in genes associated with homologous recombination. Preclinical studies have shown that PARPi-induced DNA damage may affect the tumor immune microenvironment and immune-mediated anti-tumor response through several mechanisms. In particular, increased DNA damage has been shown to induce the activation of type I interferon pathway and up-regulation of PD-L1 expression in cancer cells, which can both enhance sensitivity to Immune Checkpoint Inhibitors (ICIs). Despite the recent approval of ICIs for a number of advanced cancer types based on their ability to reinvigorate T-cell-mediated antitumor immune responses, a consistent percentage of treated patients fail to respond, strongly encouraging the identification of combination therapies to overcome resistance. In the present review, we analyzed both established and unexplored mechanisms that may be elicited by PARPi, supporting immune reactivation and their potential synergism with currently used ICIs. This analysis may indicate novel and possibly patient-specific immune features that might represent new pharmacological targets of PARPi, potentially leading to the identification of predictive biomarkers of response to their combination with ICIs.

Keywords:  BRCA; CTLA-4; DNA damage response; PARP inhibitor; PD-1; PD-L1; cancer; combination therapy; immune checkpoint inhibitor; immunotherapy

DOI:  https://doi.org/10.3390/cancers14225633
Eur J Cancer. 2022 Oct 27. pii: S0959-8049(22)01308-9. [Epub ahead of print]178 91-113

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives.

Joe Ibrahim, Marc Peeters, Guy Van Camp, Ken Op de Beeck.

  The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Keywords:  Biomarkers; Cancer; Diagnosis; Early detection; Methylation

DOI:  https://doi.org/10.1016/j.ejca.2022.10.015
Nat Commun. 2022 Nov 23. 13(1): 7203

Spatially aware dimension reduction for spatial transcriptomics.

Lulu Shang, Xiang Zhou.

Spatial transcriptomics are a collection of genomic technologies that have enabled transcriptomic profiling on tissues with spatial localization information. Analyzing spatial transcriptomic data is computationally challenging, as the data collected from various spatial transcriptomic technologies are often noisy and display substantial spatial correlation across tissue locations. Here, we develop a spatially-aware dimension reduction method, SpatialPCA, that can extract a low dimensional representation of the spatial transcriptomics data with biological signal and preserved spatial correlation structure, thus unlocking many existing computational tools previously developed in single-cell RNAseq studies for tailored analysis of spatial transcriptomics. We illustrate the benefits of SpatialPCA for spatial domain detection and explores its utility for trajectory inference on the tissue and for high-resolution spatial map construction. In the real data applications, SpatialPCA identifies key molecular and immunological signatures in a detected tumor surrounding microenvironment, including a tertiary lymphoid structure that shapes the gradual transcriptomic transition during tumorigenesis and metastasis. In addition, SpatialPCA detects the past neuronal developmental history that underlies the current transcriptomic landscape across tissue locations in the cortex.

DOI: https://doi.org/10.1038/s41467-022-34879-1
Cancers (Basel). 2022 Nov 08. pii: 5488. [Epub ahead of print]14(22):

Regulatory T Cells in Ovarian Carcinogenesis and Future Therapeutic Opportunities.

Emily Cassar, Apriliana E R Kartikasari, Magdalena Plebanski.

  Regulatory T cells (Tregs) have been shown to play a role in the development of solid tumors. A better understanding of the biology of Tregs, immune suppression by Tregs, and how cancer developed with the activity of Tregs has facilitated the development of strategies used to improve immune-based therapy. In ovarian cancer, Tregs have been shown to promote cancer development and resistance at different cancer stages. Understanding the various Treg-mediated immune escape mechanisms provides opportunities to establish specific, efficient, long-lasting anti-tumor immunity. Here, we review the evidence of Treg involvement in various stages of ovarian cancer. We further provide an overview of the current and prospective therapeutic approaches that arise from the modulation of Treg-related tumor immunity at those specific stages. Finally, we propose combination strategies of Treg-related therapies with other anti-tumor therapies to improve clinical efficacy and overcome tumor resistance in ovarian cancer.

Keywords:  cancer; chemotherapy; combination therapy; epigenetics; immunotherapy; ovarian cancer; regulatory T cells

DOI:  https://doi.org/10.3390/cancers14225488
Int J Mol Sci. 2022 Nov 08. pii: 13670. [Epub ahead of print]23(22):

The Emerging Role of Chromatin Remodeling Complexes in Ovarian Cancer.

Ieva Vaicekauskaitė, Rasa Sabaliauskaitė, Juozas Rimantas Lazutka, Sonata Jarmalaitė.

  Ovarian cancer (OC) is the fifth leading cause of women's death from cancers. The high mortality rate is attributed to the late presence of the disease and the lack of modern diagnostic tools, including molecular biomarkers. Moreover, OC is a highly heterogeneous disease, which contributes to early treatment failure. Thus, exploring OC molecular mechanisms could significantly enhance our understanding of the disease and provide new treatment options. Chromatin remodeling complexes (CRCs) are ATP-dependent molecular machines responsible for chromatin reorganization and involved in many DNA-related processes, including transcriptional regulation, replication, and reparation. Dysregulation of chromatin remodeling machinery may be related to cancer development and chemoresistance in OC. Some forms of OC and other gynecologic diseases have been associated with mutations in specific CRC genes. Most notably, ARID1A in endometriosis-related OC, SMARCA4, and SMARCB1 in hypercalcemic type small cell ovarian carcinoma (SCCOHT), ACTL6A, CHRAC1, RSF1 amplification in high-grade serous OC. Here we review the available literature on CRCs' involvement in OC to improve our understanding of its development and investigate CRCs as possible biomarkers and treatment targets for OC.

Keywords:  ARID1A; CHD; INO80; ISWI; SWI/SNF; chromatin remodeling complexes; ovarian cancer

DOI:  https://doi.org/10.3390/ijms232213670
Adv Immunol. 2022 ;pii: S0065-2776(22)00029-3. [Epub ahead of print]156 55-102

Recent advances in the activation and regulation of the cGAS-STING pathway.

Run Fang, Qifei Jiang, Xiaoyu Yu, Zhen Zhao, Zhengfan Jiang.

  The cGAS-STING pathway is responsible for cytoplasmic double-stranded DNA (dsDNA) -triggered innate immunity and involved in the pathology of various diseases including infection, autoimmune diseases, neurodegeneration and cancer. Understanding the activation and regulatory mechanisms of this pathway is critical to develop therapeutic strategies toward these diseases. Here, we review the signal transduction, cellular functions and regulations of cGAS and STING, particularly highlighting the latest understandings on the activation of cGAS by dsDNA and/or Manganese (Mn2+), STING trafficking, sulfated glycosaminoglycans (sGAGs)-induced STING polymerization and activation, and also regulation of the cGAS-STING pathway by different biocondensates formed via phase separation of proteins from host cells and viruses.

Keywords:  Apoptosis; Biomolecular condensate; Cancer immunotherapy; Caspase; Cyclic-dinucleotides (CDNs); DAMPs; Double-stranded DNA (dsDNA); Infection; Inflammasome; Innate immunity; Manganese (Mn(2+)); PAMPs; Phase separation; STING; STING phase-separator; STING trafficking; Sulfated glycosaminoglycans (sGAGs); TBK1; Type I-IFNs; cGAMP; cGAS

DOI:  https://doi.org/10.1016/bs.ai.2022.09.003
Transl Oncol. 2022 Nov 19. pii: S1936-5233(22)00248-0. [Epub ahead of print]27 101589

Up-front mutation detection in circulating tumor DNA by droplet digital PCR has added diagnostic value in lung cancer.

Esther Visser, Remco de Kock, Sylvia Genet, Ben van den Borne, Maggy Youssef-El Soud, Huub Belderbos, Gerben Stege, Marleen de Saegher, Susan van 't Westeinde, Maarten Broeren, Federica Eduati, Birgit Deiman, Volkher Scharnhorst.

  Identification of actionable mutations in advanced stage non-squamous non-small-cell lung cancer (NSCLC) patients is recommended by guidelines as it enables treatment with targeted therapies. In current practice, mutations are identified by next-generation sequencing of tumor DNA (tDNA-NGS), which requires tissue biopsies of sufficient quality. Alternatively, circulating tumor DNA (ctDNA) could be used for mutation analysis. This prospective, multicenter study establishes the diagnostic value of ctDNA analysis by droplet digital PCR (ctDNA-ddPCR) in patients with primary lung cancer. CtDNA from 458 primary lung cancer patients was analyzed using a panel of multiplex ddPCRs for EGFR (Ex19Del, G719S, L858R, L861Q and S768I), KRAS G12/G13 and BRAF V600 mutations. For 142 of 175 advanced stage non-squamous NSCLC patients tDNA-NGS results were available to compare to ctDNA-ddPCR. tDNA-NGS identified 98 mutations, of which ctDNA-ddPCR found 53 mutations (54%), including 32 of 45 (71%) targetable driver mutations. In 2 of these 142 patients, a mutation was found by ctDNA-ddPCR only. In 33 advanced stage patients lacking tDNA-NGS results, ctDNA-ddPCR detected 15 additional mutations, of which 7 targetable. Overall, ctDNA-ddPCR detected 70 mutations and tDNA-NGS 98 mutations in 175 advanced NSCLC patients. Using an up-front ctDNA-ddPCR strategy, followed by tDNA-NGS only if ctDNA-ddPCR analysis is negative, increases the number of mutations found from 98 to 115 (17%). At the same time, up-front ctDNA-ddPCR reduces tDNA-NGS analyses by 40%, decreasing the need to perform (additional) biopsies.

Keywords:  Circulating tumor DNA; Droplet-digital PCR; Liquid biopsy; Mutation analysis; NSCLC

DOI:  https://doi.org/10.1016/j.tranon.2022.101589
Front Oncol. 2022 ;12 914342

Trabectedin and lurbinectedin: Mechanisms of action, clinical impact, and future perspectives in uterine and soft tissue sarcoma, ovarian carcinoma, and endometrial carcinoma.

Angiolo Gadducci, Stefania Cosio.

  The ecteinascidins trabectedin and lurbinectedin are very interesting antineoplastic agents, with a favorable toxicity profile and peculiar mechanisms of action. These drugs form adducts in the minor groove of DNA, which produce single-strand breaks (SSBs) and double-strand breaks (DSBs) and trigger a series of events resulting in cell cycle arrest and apoptosis. Moreover, the ecteinascidins interact with the tumor microenvironment, reduce the number of tumor-associated macrophages, and inhibit the secretion of cytokines and chemokines. Trabectedin has been approved by the Federal Drug Administration (FDA) for patients with unresectable or metastatic liposarcoma or leiomyosarcoma who received a prior anthracycline-based regimen. Moreover, trabectedin in combination with pegylated liposomal doxorubicin (PLD) has been approved in the European Union for the treatment of platinum-sensitive recurrent ovarian cancer. Lurbinectedin has been approved by the FDA for patients with metastatic small cell lung cancer with disease progression on or after platinum-based chemotherapy. The review assesses in vitro and in vivo experimental studies on the antineoplastic effects of both ecteinascidins as well as the clinical trials on the activity of trabectedin in uterine sarcoma and ovarian carcinoma and of lurbinectedin in ovarian carcinoma and endometrial carcinoma.

Keywords:  endometrial cancer; lurbinectedin; ovarian cancer; trabectedin; tumor microenvironment; uterine sarcoma

DOI:  https://doi.org/10.3389/fonc.2022.914342
J Ovarian Res. 2022 Nov 23. 15(1): 123

Establishment of an ovarian cancer omentum metastasis-related prognostic model by integrated analysis of scRNA-seq and bulk RNA-seq.

Dongni Zhang, Wenping Lu, Shasha Cui, Heting Mei, Xiaoqing Wu, Zhili Zhuo.

  OBJECTIVE: Ovarian cancer has the highest mortality rate among gynecological malignant tumors, and it preferentially metastasizes to omental tissue, leading to intestinal obstruction and death. scRNA-seq is a powerful technique to reveal tumor heterogeneity. Analyzing omentum metastasis of ovarian cancer at the single-cell level may be more conducive to exploring and understanding omentum metastasis and prognosis of ovarian cancer at the cellular function and genetic levels.METHODS: The omentum metastasis site scRNA-seq data of GSE147082 were acquired from the GEO (Gene Expression Omnibus) database, and single cells were clustered by the Seruat package and annotated by the SingleR package. Cell differentiation trajectories were reconstructed through the monocle package. The ovarian cancer microarray data of GSE132342 were downloaded from GEO and were clustered by using the ConsensusClusterPlus package into omentum metastasis-associated clusters according to the marker genes gained from single-cell differentiation trajectory analysis. The tumor microenvironment (TME) and immune infiltration differences between clusters were analyzed by the estimate and CIBERSORT packages. The expression matrix of genes used to cluster GSE132342 patients was extracted from bulk RNA-seq data of TCGA-OV (The Cancer Genome Atlas ovarian cancer), and least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression were performed to establish an omentum metastasis-associated gene (OMAG) signature. The signature was then tested by GSE132342 data. Finally, the clinicopathological characteristics of TCGA-OV were screened by univariate and multivariate Cox regression analysis to draw the nomogram.
RESULTS: A total of 9885 cells from 6 patients were clustered into 18 cell clusters and annotated into 14 cell types. Reconstruction of differentiation trajectories divided the cells into 5 branches, and a total of 781 cell trajectory-related characteristic genes were obtained. A total of 3769 patients in GSE132342 were subtyped into 3 clusters by 74 cell trajectory-related characteristic genes. Kaplan-Meier (K-M) survival analysis showed that the prognosis of cluster 2 was the worst, P < 0.001. The TME analysis showed that the ESTIMATE score and stromal score in cluster 2 were significantly higher than those in the other two clusters, P < 0.001. The immune infiltration analysis showed differences in the fraction of 8 immune cells among the 3 clusters, P < 0.05. The expression data of 74 genes used for GEO clustering were extracted from 379 patients in TCGA-OV, and combined with survival information, 10 candidates for OMAGs were filtered by LASSO. By using multivariate Cox regression, the 6-OMAGs signature was established as RiskScore = 0.307*TIMP3 + 3.516*FBN1-0.109*IGKC + 0.209*RPL21 + 0.870*UCHL1 + 0.365*RARRES1. Taking TCGA-OV as the training set and GSE132342 as the test set, receiver operating characteristic (ROC) curves were drawn to verify the prognostic value of 6-OMAGs. Screened by univariate and multivariate Cox regression analysis, 3 (age, cancer status, primary therapy outcome) of 5 clinicopathological characteristics were used to construct the nomogram combined with risk score.
CONCLUSION: We constructed an ovarian cancer prognostic model related to omentum metastasis composed of 6-OMAGs and 3 clinicopathological features and analyzed the potential mechanism of these 6-OMAGs in ovarian cancer omental metastasis.

Keywords:  6-OMAGs; Omentum metastasis; Ovarian cancer; Prognosis; Tumor microenvironment; scRNA-seq

DOI:  https://doi.org/10.1186/s13048-022-01059-0