bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2024‒02‒11
nine papers selected by
Sergio Marchini, Humanitas Research
  1. Improving liquid biopsy for cancer detection.
  2. The interaction between DNA methylation and tumor immune microenvironment: from the laboratory to clinical applications.
  3. Identification of colon cancer subtypes based on multi-omics data-construction of methylation markers for immunotherapy.
  4. The web-based portal SpatialTME integrates histological images with single-cell and spatial transcriptomics to explore the tumor microenvironment.
  5. Intraperitoneal Therapy for Ovarian Cancer - Some Answers, More Questions, and Missed Opportunities.
  6. Cell-free DNA methylation analysis as a marker of malignancy in pleural fluid.
  7. Clinical and molecular biomarkers predicting response to PARP inhibitors in ovarian cancer.
  8. Intraperitoneal Carboplatin for Ovarian Cancer - A Phase 2/3 Trial.
  9. Cervical cancer could be eliminated: here's how.
  1. Nat Rev Drug Discov. 2024 Feb 07.
    Improving liquid biopsy for cancer detection.
    Sarah Crunkhorn.
      
    DOI:  https://doi.org/10.1038/d41573-024-00025-3
  2. Clin Epigenetics. 2024 Feb 08. 16(1): 24
    The interaction between DNA methylation and tumor immune microenvironment: from the laboratory to clinical applications.
    Daoqi Zhu, Siying Zeng, Chao Su, Jingjun Li, Yiwen Xuan, Yongkai Lin, Enwu Xu, Qin Fan.
      DNA methylation is a pivotal epigenetic modification that affects gene expression. Tumor immune microenvironment (TIME) comprises diverse immune cells and stromal components, creating a complex landscape that can either promote or inhibit tumor progression. In the TIME, DNA methylation has been shown to play a critical role in influencing immune cell function and tumor immune evasion. DNA methylation regulates immune cell differentiation, immune responses, and TIME composition Targeting DNA methylation in TIME offers various potential avenues for enhancing immune cytotoxicity and reducing immunosuppression. Recent studies have demonstrated that modification of DNA methylation patterns can promote immune cell infiltration and function. However, challenges persist in understanding the precise mechanisms underlying DNA methylation in the TIME, developing selective epigenetic therapies, and effectively integrating these therapies with other antitumor strategies. In conclusion, DNA methylation of both tumor cells and immune cells interacts with the TIME, and thus affects clinical efficacy. The regulation of DNA methylation within the TIME holds significant promise for the advancement of tumor immunotherapy. Addressing these challenges is crucial for harnessing the full potential of epigenetic interventions to enhance antitumor immune responses and improve patient outcomes.
    Keywords:  DNA methylation; Epigenetic regulation; Immune cell function; Immunotherapy challenges; Tumor immune microenvironment
    DOI:  https://doi.org/10.1186/s13148-024-01633-x
  3. Front Oncol. 2024 ;14 1335670
    Identification of colon cancer subtypes based on multi-omics data-construction of methylation markers for immunotherapy.
    Benjie Xu, Jie Lian, Xiangyi Pang, Yue Gu, Jiahao Zhu, Yan Zhang, Haibo Lu.
      Background: Being the most widely used biomarker for immunotherapy, the microsatellite status has limitations in identifying all patients who benefit in clinical practice. It is essential to identify additional biomarkers to guide immunotherapy. Aberrant DNA methylation is consistently associated with changes in the anti-tumor immune response, which can promote tumor progression. This study aims to explore immunotherapy biomarkers for colon cancers from the perspective of DNA methylation.Methods: The related data (RNA sequencing data and DNA methylation data) were obtained from The Cancer Genome Atlas (TCGA) and UCSC XENA database. Methylation-driven genes (MDGs) were identified through the Pearson correlation analysis. Unsupervised consensus clustering was conducted using these MDGs to identify distinct clusters of colon cancers. Subsequently, we evaluated the immune status and predicted the efficacy of immunotherapy by tumor immune dysfunction and exclusion (Tide) score. Finally, The Quantitative Differentially Methylated Regions (QDMR) software was used to identify the specific DNA methylation markers within particular clusters.
    Results: A total of 282 MDGs were identified by integrating the DNA methylation and RNA-seq data. Consensus clustering using the K-means algorithm revealed that the optimal number of clusters was 4. It was revealed that the composition of the tumor immune microenvironment (TIME) in Cluster 1 was significantly different from others, and it exhibited a higher level of tumor mutation burdens (TMB) and stronger anti-tumor immune activity. Furthermore, we identified three specific hypermethylation genes that defined Cluster 1 (PCDH20, APCDD1, COCH). Receiver operating characteristic (ROC) curves demonstrated that these specific markers could effectively distinguish Cluster 1 from other clusters, with an AUC of 0.947 (95% CI 0.903-0.990). Finally, we selected clinical samples for immunohistochemical validation.
    Conclusion: In conclusion, through the analysis of DNA methylation, consensus clustering of colon cancer could effectively identify the cluster that benefit from immunotherapy along with specific methylation biomarkers.
    Keywords:  DNA methylation; colon cancer; immunotherapy; microsatellite status; specific DNA methylation markers
    DOI:  https://doi.org/10.3389/fonc.2024.1335670
  4. Cancer Res. 2024 Feb 05.
    The web-based portal SpatialTME integrates histological images with single-cell and spatial transcriptomics to explore the tumor microenvironment.
    Jintong Shi, Xia Wei, Zhenzhen Xun, Xinyu Ding, Yao Liu, Lianxin Liu, Youqiong Ye.
      The tumor microenvironment (TME) represents a complex network in which tumor cells communicate not only with each other but also with stromal and immune cells. The intercellular interactions in the TME contribute to tumor initiation, progression, metastasis, and treatment outcome. Recent advances in spatial transcriptomics (ST) have revolutionized the molecular understanding of the TME at the spatial level. A comprehensive interactive analysis resource specifically designed for characterizing the spatial tumor microenvironment could facilitate further advances using ST. In this study, we collected 296 ST slides covering 19 cancer types and developed a computational pipeline to delineate the spatial structure along the malignant-boundary-nonmalignant axis. The pipeline identified differentially expressed genes and their functional enrichment, deconvoluted the cellular composition of the TME, reconstructed cell type-specific gene expression profiles at the sub-spot level, and performed cell-cell interaction analysis. Finally, the user-friendly database SpatialTME (http://www.spatialtme.yelab.site/) was constructed to provide search, visualization, and downloadable results. These detailed analyses are able to reveal the heterogeneous regulatory network of the spatial microenvironment and elucidate associations between spatial features and tumor development or response to therapy, offering a valuable resource to study the complex TME.
    DOI:  https://doi.org/10.1158/0008-5472.CAN-23-2650
  5. NEJM Evid. 2023 May;2(5): EVIDe2300048
    Intraperitoneal Therapy for Ovarian Cancer - Some Answers, More Questions, and Missed Opportunities.
    Oladapo O Yeku.
      Intraperitoneal (i.p.) therapy set a new treatment standard for patients with advanced-stage ovarian cancer in 2006 based on data showing improved overall survival in the trial by Armstrong et al.1 This trial showed a statistically significant and clinically meaningful improvement in median overall survival of almost 16 months in favor of patients treated with i.p. chemotherapy compared with an intravenous approach. Since then, several clinical trials have aimed to better understand what population of patients are most likely to benefit from this therapy. Will patients with earlier-stage disease or suboptimal cytoreduction after surgery benefit? Does tumor histology matter?
    DOI:  https://doi.org/10.1056/EVIDe2300048
  6. Sci Rep. 2024 02 05. 14(1): 2939
    Cell-free DNA methylation analysis as a marker of malignancy in pleural fluid.
    Billie Bixby, Lukas Vrba, Jyoti Lenka, Marc M Oshiro, George S Watts, Trina Hughes, Heidi Erickson, Madhav Chopra, James L Knepler, Kenneth S Knox, Lisa Jarnagin, Raed Alalawi, Mrinalini Kala, Richard Bernert, Joshua Routh, Denise J Roe, Linda L Garland, Bernard W Futscher, Mark A Nelson.
      Diagnosis of malignant pleural effusion (MPE) is made by cytological examination of pleural fluid or histological examination of pleural tissue from biopsy. Unfortunately, detection of malignancy using cytology has an overall sensitivity of 50%, and is dependent upon tumor load, volume of fluid assessed, and cytopathologist experience. The diagnostic yield of pleural fluid cytology is also compromised by low abundance of tumor cells or when morphology is obscured by inflammation or reactive mesothelial cells. A reliable molecular marker that may complement fluid cytology for the diagnosis of malignant pleural effusion is needed. The purpose of this study was to establish a molecular diagnostic approach based on pleural effusion cell-free DNA methylation analysis for the differential diagnosis of malignant pleural effusion and benign pleural effusion. This was a blind, prospective case-control biomarker study. We recruited 104 patients with pleural effusion for the study. We collected pleural fluid from patients with: MPE (n = 48), indeterminate pleural effusion in subjects with known malignancy or IPE (n = 28), and benign PE (n = 28), and performed the Sentinel-MPE liquid biopsy assay. The methylation level of Sentinel-MPE was markedly higher in the MPE samples compared to BPE control samples (p < 0.0001) and the same tendency was observed relative to IPE (p = 0.004). We also noted that the methylation signal was significantly higher in IPE relative to BPE (p < 0.001). We also assessed the diagnostic efficiency of the Sentinel-MPE test by performing receiver operating characteristic analysis (ROC). For the ROC analysis we combined the malignant and indeterminate pleural effusion groups (n = 76) and compared against the benign group (n = 28). The detection sensitivity and specificity of the Sentinel-MPE test was high (AUC = 0.912). The Sentinel-MPE appears to have better performance characteristics than cytology analysis. However, combining Sentinel-MPE with cytology analysis could be an even more effective approach for the diagnosis of MPE. The Sentinel-MPE test can discriminate between BPE and MPE. The Sentinel-MPE liquid biopsy test can detect aberrant DNA in several different tumor types. The Sentinel-MPE test can be a complementary tool to cytology in the diagnosis of MPE.
    DOI:  https://doi.org/10.1038/s41598-024-53132-x
  7. J Gynecol Oncol. 2024 Jan 24.
    Clinical and molecular biomarkers predicting response to PARP inhibitors in ovarian cancer.
    Takahiro Nozaki, Ikuko Sakamoto, Keiko Kagami, Kenji Amemiya, Yosuke Hirotsu, Hitoshi Mochizuki, Masao Omata.
      OBJECTIVE: To determine the useful biomarker for predicting the effects of poly-(ADP ribose)-polymerase (PARP) inhibitors in Japanese patients with ovarian cancer.METHODS: We collected clinical information and performed molecular biological analysis on 42 patients with ovarian, fallopian tube, and primary peritoneal carcinomas who received PARP inhibitors.
    RESULTS: Among the analyzed patients with ovarian cancer, 23.8% had germline BRCA mutation (gBRCAm), 42.9% had homologous recombination repair-related gene mutation (HRRm), and 61.1% had a genomic instability score (GIS) of ≥42. Patients with HRRm had a significantly longer progression-free survival (PFS) than those without HRRm (median PFS 35.6 vs. 7.9 months; p=0.009), with a particularly marked increase in PFS in patients with gBRCAm (median PFS 42.3 months). Similarly, among patients with recurrent ovarian cancer, those with HRRm had a longer PFS than those without HRRm (median PFS 42.3 vs. 7.7 months; p=0.040). Multivariate Cox proportional hazards regression analysis found that performance status and gBRCAm status were independent factors associated with prolonged PFS with PARP inhibitors. In recurrent ovarian cancer, multivariate regression analysis identified platinum-free interval (PFI) in addition to performance status as a significant predictor of PFS. On the contrary, no significant association was observed between PFS and a GIS of ≥42 used in clinical practice.
    CONCLUSION: We found that HRRm can be a useful biomarker for predicting the effects of PARP inhibitors in treating ovarian cancer and that the PFI can also be useful in recurrent ovarian cancer.
    Keywords:  Genomics; Homologous Recombination; Mutation; Ovarian Cancer
    DOI:  https://doi.org/10.3802/jgo.2024.35.e55
  8. NEJM Evid. 2023 May;2(5): EVIDoa2200225
    Intraperitoneal Carboplatin for Ovarian Cancer - A Phase 2/3 Trial.
    Shoji Nagao, Keiichi Fujiwara, Kouji Yamamoto, Hiroshi Tanabe, Aikou Okamoto, Kazuhiro Takehara, Motoaki Saito, Hiroyuki Fujiwara, David S P Tan, Satoshi Yamaguchi, Sosuke Adachi, Akira Kikuchi, Takeshi Hirasawa, Takeshi Yokoi, Tomonori Nagai, Toyomi Sato, Shoji Kamiura, Akira Fujishita, Wong Wai Loong, Karen Chan, Peter Syks, Alexsander Olawaye, Sang-Young Ryu, Hiroyuki Shigeta, Eiji Kondo, Yoshihito Yokoyama, Takashi Matsumoto, Kosei Hasegawa, Takayuki Enomoto.
      Intraperitoneal Carboplatin for Ovarian CancerThis trial compared intravenous weekly paclitaxel administered with intraperitoneal or intravenous carboplatin. There was a statistically significant increase in progression-free survival in patients with ovarian cancer treated with intraperitoneal versus intravenous carboplatin and paclitaxel, with no difference in overall survival between groups.
    DOI:  https://doi.org/10.1056/EVIDoa2200225
  9. Nature. 2024 Feb 04.
    Cervical cancer could be eliminated: here's how.
    Nick Petrić Howe, Jennifer Gardiner.
      
    Keywords:  Cancer; Public health; Vaccines
    DOI:  https://doi.org/10.1038/d41586-024-00302-6
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