bims-tumhet Biomed News
on Tumor Heterogeneity
Issue of 2023‒02‒26
fourteen papers selected by
Sergio Marchini
Humanitas Research
  1. Functional homologous recombination assay on FFPE specimens of advanced high-grade serous ovarian cancer predicts clinical outcomes.
  2. RAD51/geminin/γH2AX immunohistochemical expression predicts platinum-based chemotherapy response in ovarian high-grade serous carcinoma.
  3. Unraveling Spatial Gene Associations with SEAGAL: a Python Package for Spatial Transcriptomics Data Analysis and Visualization.
  4. Spatial profiling technologies illuminate the tumor microenvironment.
  5. Assessing the clinical utility of multi-omics data for predicting serous ovarian cancer prognosis.
  6. Clinical Utility of Genomic Tests Evaluating Homologous Recombination Repair Deficiency (HRD) for Treatment Decisions in Early and Metastatic Breast Cancer.
  7. SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains.
  8. Update on Prognostic and Predictive Markers in Mucinous Ovarian Cancer.
  9. Function and regulation of cGAS-STING signaling in infectious diseases.
  10. The Search for Genomic Biomarkers of Response to Immunotherapy in Ovarian Cancer.
  11. The repertoire of copy number alteration signatures in human cancer.
  12. PTEN Deficiency in Tubo-Ovarian High-Grade Serous Carcinoma is Associated with Poor Progression-Free Survival and is Mutually Exclusive with CCNE1 Amplification.
  13. Liquid biopsy accelerates precision medicine.
  14. Immunological Role of TP53 Somatic Mutation Classification in Human Cancers.
  1. Clin Cancer Res. 2023 Feb 20. pii: CCR-22-3156. [Epub ahead of print]
    Functional homologous recombination assay on FFPE specimens of advanced high-grade serous ovarian cancer predicts clinical outcomes.
    Sanna Pikkusaari, Manuela Tumiati, Anni Virtanen, Jaana Oikkonen, Yilin Li, Fernando Perez-Villatoro, Taru Muranen, Matilda Salko, Kaisa Huhtinen, Anna Kanerva, Heidi Koskela, Johanna Tapper, Riitta Koivisto-Korander, Titta Joutsiniemi, Ulla-Maija Haltia, Heini Lassus, Sampsa Hautaniemi, Anniina Farkkila, Johanna Hynninen, Sakari Hietanen, Olli Carpén, Liisa Kauppi.
      PURPOSE: Deficiency in homologous recombination (HR) repair of DNA damage is characteristic of many high-grade serous ovarian cancers (HGSC). It is imperative to identify patients with homologous recombination deficient (HRD) tumors as they are most likely to benefit from platinum-based chemotherapy and PARP inhibitors (PARPi). Existing methods measure historical, not necessarily current HRD, and/or require high tumor cell content which is not achievable for many patients. We set out to develop a clinically feasible assay for identifying functionally HRD tumors that can predict clinical outcomes.EXPERIMENTAL DESIGN: We quantified RAD51, a key HR protein, in immunostained FFPE tumor samples obtained from both chemotherapy-naïve and neoadjuvant chemotherapy (NACT) treated HGSC patients. We defined cut-offs for functional HRD separately for these sample types, classified the patients accordingly as HR-deficient or HR-proficient, and analyzed correlations with clinical outcomes. From the same specimens, genomics-based HRD estimates (HR gene mutations, genomic signatures and genomic scars) were also determined, and compared with functional HR status.
    RESULTS: Functional HR status significantly predicted several clinical outcomes, including progression-free survival (PFS) and overall survival (OS), when determined from chemo-naïve (PFS p<0.0001; OS p<0.0001) as well as NACT-treated (PFS p<0.0001; OS p=0.0033) tumor specimens. The functional HR test also identified as HRD those PARPi-at-recurrence -treated patients with longer OS (p=0.0188).
    CONCLUSIONS: We developed a functional HR assay performed on routine FFPE specimens, obtained from either chemo-naïve or NACT-treated HGSC patients, that can significantly predict real-world platinum-based chemotherapy and PARPi response.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-22-3156
  2. J Gynecol Oncol. 2023 Feb 03.
    RAD51/geminin/γH2AX immunohistochemical expression predicts platinum-based chemotherapy response in ovarian high-grade serous carcinoma.
    Kyeongmin Kim, Se Hoon Kim, Jung-Yun Lee, Yoo-Na Kim, Seung-Tae Lee, Eunhyang Park.
      OBJECTIVE: The RAD51 assay is a recently developed functional assay for homologous recombination deficiency (HRD) that reflects real-time HRD status. We aimed to identify the applicability and predictive value of RAD51 immunohistochemical expression in pre- and post-neoadjuvant chemotherapy (NAC) samples of ovarian high-grade serous carcinoma (HGSC).METHODS: We evaluated the immunohistochemical expression of RAD51/geminin/γH2AX in ovarian HGSC before and after NAC.
    RESULTS: In pre-NAC tumors (n=51), 74.5% (39/51) showed at least 25% of γH2AX-positive tumor cells, suggesting endogenous DNA damage. The RAD51-high group (41.0%, 16/39) showed significantly worse progression-free survival (PFS) compared to the RAD51-low group (51.3%, 20/39) (p=0.032). In post-NAC tumors (n=50), the RAD51-high group (36.0%, 18/50) showed worse PFS (p=0.013) and tended to present worse overall survival (p=0.067) compared to the RAD51-low group (64.0%, 32/50). RAD51-high cases were more likely to progress than RAD51-low cases at both 6 months and 12 months (p=0.046 and p=0.019, respectively). Of 34 patients with matched pre- and post-NAC RAD51 results, 44% (15/34) of pre-NAC RAD51 results were changed in the post-NAC tissue, and the RAD51 high-to-high group showed the worst PFS, while the low-to-low group showed the best PFS (p=0.031).
    CONCLUSION: High RAD51 expression was significantly associated with worse PFS in HGSC, and post-NAC RAD51 status showed higher association than pre-NAC RAD51 status. Moreover, RAD51 status can be evaluated in a significant proportion of treatment-naïve HGSC samples. As RAD51 status dynamically changes, sequential follow-up of RAD51 status might reflect the biological behavior of HGSCs.
    Keywords:  Homologous Recombination; Immunohistochemistry; Neoadjuvant Chemotherapy; Ovarian Cancer; RAD51 recombinase
    DOI:  https://doi.org/10.3802/jgo.2023.34.e45
  3. bioRxiv. 2023 Feb 13. pii: 2023.02.13.528331. [Epub ahead of print]
    Unraveling Spatial Gene Associations with SEAGAL: a Python Package for Spatial Transcriptomics Data Analysis and Visualization.
    Linhua Wang, Chaozhong Liu, Zhandong Liu.
      Summary: In the era where transcriptome profiling moves towards single-cell and spatial resolutions, the traditional co-expression analysis lacks the power to fully utilize such rich information to unravel spatial gene associations. Here we present a Python package called Spatial Enrichment Analysis of Gene Associations using L-index (SEAGAL) to detect and visualize spatial gene correlations at both single-gene and gene-set levels. Our package takes spatial transcriptomics data sets with gene expression and the aligned spatial coordinates as input. It allows for analyzing and visualizing spatial correlations at both single-gene and gene-set levels. The output could be visualized as volcano plots and heatmaps with a few lines of code, thus providing an easy-yet-comprehensive tool for mining spatial gene associations.Availability and Implementation: The Python package SEAGAL can be installed using pip: https://pypi.org/project/seagal/ . The source code and step-by-step tutorials are available at: https://github.com/linhuawang/SEAGAL .
    Contact: linhuaw@bcm.edu.
    DOI:  https://doi.org/10.1101/2023.02.13.528331
  4. Cancer Cell. 2023 Feb 13. pii: S1535-6108(23)00010-7. [Epub ahead of print]
    Spatial profiling technologies illuminate the tumor microenvironment.
    Ofer Elhanani, Raz Ben-Uri, Leeat Keren.
      The tumor microenvironment (TME) is composed of many different cellular and acellular components that together drive tumor growth, invasion, metastasis, and response to therapies. Increasing realization of the significance of the TME in cancer biology has shifted cancer research from a cancer-centric model to one that considers the TME as a whole. Recent technological advancements in spatial profiling methodologies provide a systematic view and illuminate the physical localization of the components of the TME. In this review, we provide an overview of major spatial profiling technologies. We present the types of information that can be extracted from these data and describe their applications, findings and challenges in cancer research. Finally, we provide a future perspective of how spatial profiling could be integrated into cancer research to improve patient diagnosis, prognosis, stratification to treatment and development of novel therapeutics.
    Keywords:  multiplexed imaging; spatial profiling; spatial transcriptomics; tumor microenvironment
    DOI:  https://doi.org/10.1016/j.ccell.2023.01.010
  5. J Obstet Gynaecol. 2023 Dec;43(1): 2171778
    Assessing the clinical utility of multi-omics data for predicting serous ovarian cancer prognosis.
    Zhe Zhang, Zhiyao Wei, Luyang Zhao, Chenglei Gu, Yuanguang Meng.
      Ovarian cancer (OC) is characterised by heterogeneity that complicates the prediction of patient survival and treatment outcomes. Here, we conducted analyses to predict the prognosis of patients from the Genomic Data Commons database and validated the predictions by fivefold cross-validation and by using an independent dataset in the International Cancer Genome Consortium database. We analysed the somatic DNA mutation, mRNA expression, DNA methylation, and microRNA expression data of 1203 samples from 599 serous ovarian cancer (SOC) patients. We found that principal component transformation (PCT) improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than the decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes. Our study provides perspective on building reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC.Impact statementWhat is already known on this subject? Recent studies have focussed on predicting cancer outcomes based on omics data. But the limitation is the performance of single-platform genomic analyses or the small numbers of genomic analyses.What do the results of this study add? We analysed multi-omics data, found that principal component transformation (PCT) significantly improved the predictive performance of the survival and therapeutic models. Deep learning algorithms also showed better predictive power than did decision tree (DT) and random forest (RF). Furthermore, we identified a series of molecular features and pathways that are associated with patient survival and treatment outcomes.What are the implications of these findings for clinical practice and/or further research? Our study provides perspective on how to build reliable prognostic and therapeutic strategies and further illuminates the molecular mechanisms of SOC for future studies.
    Keywords:  Ovarian cancer; biomarker; multi-omics data and prediction model; prognosis; treatment
    DOI:  https://doi.org/10.1080/01443615.2023.2171778
  6. Cancers (Basel). 2023 Feb 18. pii: 1299. [Epub ahead of print]15(4):
    Clinical Utility of Genomic Tests Evaluating Homologous Recombination Repair Deficiency (HRD) for Treatment Decisions in Early and Metastatic Breast Cancer.
    Loïck Galland, Nicolas Roussot, Isabelle Desmoulins, Didier Mayeur, Courèche Kaderbhai, Silvia Ilie, Audrey Hennequin, Manon Reda, Juliette Albuisson, Laurent Arnould, Romain Boidot, Caroline Truntzer, François Ghiringhelli, Sylvain Ladoire.
      Breast cancer is the most frequently occurring cancer worldwide. With its increasing incidence, it is a major public health problem, with many therapeutic challenges such as precision medicine for personalized treatment. Thanks to next-generation sequencing (NGS), progress in biomedical technologies, and the use of bioinformatics, it is now possible to identify specific molecular alterations in tumor cells-such as homologous recombination deficiencies (HRD)-enabling us to consider using DNA-damaging agents such as platinum salts or PARP inhibitors. Different approaches currently exist to analyze impairment of the homologous recombination pathway, e.g., the search for specific mutations in homologous recombination repair (HRR) genes, such as BRCA1/2; the use of genomic scars or mutational signatures; or the development of functional tests. Nevertheless, the role and value of these different tests in breast cancer treatment decisions remains to be clarified. In this review, we summarize current knowledge on the clinical utility of genomic tests, evaluating HRR deficiency for treatment decisions in early and metastatic breast cancer.
    Keywords:  BRCA; HRD score; NGS; PARPi; breast cancer; early breast cancer; homologous recombination deficiency; metastatic breast cancer; mutational signature; platinum salts
    DOI:  https://doi.org/10.3390/cancers15041299
  7. Cells. 2023 Feb 13. pii: 604. [Epub ahead of print]12(4):
    SINFONIA: Scalable Identification of Spatially Variable Genes for Deciphering Spatial Domains.
    Rui Jiang, Zhen Li, Yuhang Jia, Siyu Li, Shengquan Chen.
      Recent advances in spatial transcriptomics have revolutionized the understanding of tissue organization. The identification of spatially variable genes (SVGs) is an essential step for downstream spatial domain characterization. Although several methods have been proposed for identifying SVGs, inadequate ability to decipher spatial domains, poor efficiency, and insufficient interoperability with existing standard analysis workflows still impede the applications of these methods. Here we propose SINFONIA, a scalable method for identifying spatially variable genes via ensemble strategies. Implemented in Python, SINFONIA can be seamlessly integrated into existing analysis workflows. Using 15 spatial transcriptomic datasets generated with different protocols and with different sizes, dimensions and qualities, we show the advantage of SINFONIA over three baseline methods and two variants via systematic evaluation of spatial clustering, domain resolution, latent representation, spatial visualization, and computational efficiency with 21 quantitative metrics. Additionally, SINFONIA is robust relative to the choice of the number of SVGs. We anticipate SINFONIA will facilitate the analysis of spatial transcriptomics.
    Keywords:  spatial autocorrelation; spatial domains; spatial transcriptomics; spatially variable genes
    DOI:  https://doi.org/10.3390/cells12040604
  8. Cancers (Basel). 2023 Feb 12. pii: 1172. [Epub ahead of print]15(4):
    Update on Prognostic and Predictive Markers in Mucinous Ovarian Cancer.
    Fulvio Borella, Marco Mitidieri, Stefano Cosma, Chiara Benedetto, Luca Bertero, Stefano Fucina, Isabelle Ray-Coquard, Annalisa Carapezzi, Domenico Ferraioli.
      This review includes state-of-the-art prognostic and predictive factors of mucinous ovarian cancer (MOC), a rare tumor. Clinical, pathological, and molecular features and treatment options according to prognosis are comprehensively discussed. Different clinical implications of MOC are described according to the The International Federation of Gynecology and Obstetrics (FIGO) stage: early MOC (stage I-II) and advanced MOC (stage III-IV). Early MOC is characterized by a good prognosis. Surgery is the mainstay of treatment. Fertility-sparing surgery could be performed in patients who wish to become pregnant and that present low recurrence risk of disease. Adjuvant chemotherapy is not recommended, except in patients with high-risk clinical and pathological features. Regarding the histological features, an infiltrative growth pattern is the major prognostic factor of MOC. Furthermore, novel molecular biomarkers are emerging for tailored management of early-stage MOC. In contrast, advanced MOC is characterized by poor survival. Radical surgery is the cornerstone of treatment and adjuvant chemotherapy is recommended, although the efficacy is limited by the intrinsic chemoresistance of these tumors. Several molecular hallmarks of advanced MOC have been described in recent years (e.g., HER2 amplification, distinct methylation profiles, peculiar immunological microenvironment), but target therapy for these rare tumors is not available yet.
    Keywords:  molecular features; mucinous ovarian cancer; ovarian cancer; pathology; predictive factors; prognosis; prognostic factors; surgery; survival; target therapy
    DOI:  https://doi.org/10.3390/cancers15041172
  9. Front Immunol. 2023 ;14 1130423
    Function and regulation of cGAS-STING signaling in infectious diseases.
    Yang Du, Zhiqiang Hu, Yien Luo, Helen Y Wang, Xiao Yu, Rong-Fu Wang.
      The efficacious detection of pathogens and prompt induction of innate immune signaling serve as a crucial component of immune defense against infectious pathogens. Over the past decade, DNA-sensing receptor cyclic GMP-AMP synthase (cGAS) and its downstream signaling adaptor stimulator of interferon genes (STING) have emerged as key mediators of type I interferon (IFN) and nuclear factor-κB (NF-κB) responses in health and infection diseases. Moreover, both cGAS-STING pathway and pathogens have developed delicate strategies to resist each other for their survival. The mechanistic and functional comprehension of the interplay between cGAS-STING pathway and pathogens is opening the way for the development and application of pharmacological agonists and antagonists in the treatment of infectious diseases. Here, we briefly review the current knowledge of DNA sensing through the cGAS-STING pathway, and emphatically highlight the potent undertaking of cGAS-STING signaling pathway in the host against infectious pathogenic organisms.
    Keywords:  STING; cGAS; immune regulation; infectious diseases; innate immunity
    DOI:  https://doi.org/10.3389/fimmu.2023.1130423
  10. Clin Cancer Res. 2023 Feb 24. pii: CCR-23-0048. [Epub ahead of print]
    The Search for Genomic Biomarkers of Response to Immunotherapy in Ovarian Cancer.
    Duaa H Al-Rawi, Nicole Rusk, Claire F Friedman.
      Immune checkpoint blockade has been ineffective in ovarian cancer and there is an ongoing effort to identify biomarkers of therapeutic benefit. Despite promising preclinical data, a substudy of the IMagyn050 trial found that patients with homologous recombination deficient tumors did not have improved progression-free survival with the addition of atezolizumab.
    DOI:  https://doi.org/10.1158/1078-0432.CCR-23-0048
  11. Brief Bioinform. 2023 Feb 20. pii: bbad053. [Epub ahead of print]
    The repertoire of copy number alteration signatures in human cancer.
    Ziyu Tao, Shixiang Wang, Chenxu Wu, Tao Wu, Xiangyu Zhao, Wei Ning, Guangshuai Wang, Jinyu Wang, Jing Chen, Kaixuan Diao, Fuxiang Chen, Xue-Song Liu.
      Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.
    Keywords:  cancer genome; cancer prognosis; copy number alteration; copy number signature; mutational signature
    DOI:  https://doi.org/10.1093/bib/bbad053
  12. Mod Pathol. 2023 Feb 01. pii: S0893-3952(23)00011-X. [Epub ahead of print]36(5): 100106
    PTEN Deficiency in Tubo-Ovarian High-Grade Serous Carcinoma is Associated with Poor Progression-Free Survival and is Mutually Exclusive with CCNE1 Amplification.
    Xiaoming Zhang, Aihui Wang, Lucy Han, Brooke Liang, Grace Allard, Elisabeth Diver, Brooke E Howitt.
      As a critical tumor suppressor, PTEN has gained much attention in cancer research. Emerging evidence suggests an association between PTEN status and clinical outcome in certain tumors, and may be predictive of response to several therapies. However, the significance of PTEN deficiency in tubo-ovarian high-grade serous carcinomas (HGSCs) is still poorly understood. We evaluated PTEN expression in HGSCs and determined its clinical relevance. A cohort of 76 HGSC specimens was profiled using tissue microarray. Immunohistochemistry (IHC) of PTEN, ER, PR, AR, CD8, FOXP3, and PD-L1 was performed. Targeted gene panel testing by massively parallel sequencing was performed in 51 cases. PTEN deficiency (complete or subclonal loss) detected by IHC was identified in 13 of the 62 HGSCs (21%) and was significantly correlated with reduced expression of ER and worse first progression-free survival (P < .05) but not with PD-L1 expression, the density of intratumoral T lymphocytes, or overall survival. In our cohort, tumor progression within 1 year of PARP inhibitor therapy was found more frequently in PTEN-deficient cases than in PTEN-intact cases (100% vs 52%). Molecular profiling showed that intragenic mutation or deletion was not the predominant mechanism for PTEN inactivation in HGSCs. In addition, CCNE1 amplification was found to be mutually exclusive with PTEN deficiency at both protein and DNA levels. An analysis of the genomic data from 1702 HGSC samples deposited with The Cancer Genome Atlas database obtained from cBioPortal confirmed the low rate of detection of PTEN gene alterations and the mutually exclusive nature of PTEN loss and CCNE1 amplification in HGSCs. These findings indicate that PTEN deficiency defines a distinct clinically significant subgroup of HGSCs with a tendency for ER negativity, wild-type CCNE1 status, inferior clinical outcomes, and potential drug resistance. These tumors may benefit from PI3K pathway inhibitors in combination with other ovarian cancer regimens, which deserves further investigation.
    Keywords:  CCNE1 amplification; PARP inhibitor; PTEN deficiency; high-grade serous carcinoma; immunotherapy
    DOI:  https://doi.org/10.1016/j.modpat.2023.100106
  13. Ann Oncol. 2023 Feb 15. pii: S0923-7534(23)00074-1. [Epub ahead of print]
    Liquid biopsy accelerates precision medicine.
    O Amato, P Aftimos, M Ignatiadis.
      The concept of liquid biopsies based on circulating tumoral DNA (ctDNA) has gained space in precision oncology in the last few years. Indeed, molecular alterations can be detected in ctDNA fragments released by cancer cells in the bloodstream. This technique can then be used for tumor genotyping, to study tumor evolution as genomic alterations are acquired under therapy pressure, for the evaluation of anti-tumor response during follow-up, and for the detection of minimal residual disease1. In this Issue of Annals of Oncology, Bayle et al. present results from the STING study2 in the context of the PRISM French initiative, involving the comprehensive molecular profiling of ctDNA in 1,772 patients with advanced solid tumors to guide matched targeted therapy, representing the largest exclusively ctDNA-based molecular profiling program across multiple advanced cancers reporting results to date.
    DOI:  https://doi.org/10.1016/j.annonc.2023.02.004
  14. J Oncol. 2023 ;2023 1904309
    Immunological Role of TP53 Somatic Mutation Classification in Human Cancers.
    Jianfei Fang, Ying Yang, Lina Xie, Wenjuan Yin.
      Background: TP53 is a very common tumor suppressor gene and has implicated in various cancers. A systematic immunological analysis of TP53 somatic mutation classification in multiple cancers is still lacking.Methods: To assess the immunological value of TP53 somatic mutation classification in various cancers, we integrated a series of bioinformatics methods to analyze the role of TP53 gene across the public databases, such as UCSC Xena, Cancer Cell Line Encyclopedia (CCLE), Ensembl, and Genotype-Tissue Expression (GTEx).
    Results: The results revealed that the TP53 expression level had significant difference in tumor tissues and normal tissues, and it had a high expression level in most malignant tumors. Moreover, the missense mutation is the most common type of TP53 mutation in most cancers. In addition, the Cox proportional hazards model analysis and Kaplan-Meier (KM) survival analysis demonstrated that the TP53 expression is a high-risk factor in brain lower-grade glioma (LGG), prostate adenocarcinoma (PRAD), and uterine carcinosarcoma (UCS), which is opposite in uterine corpus endometrial carcinoma (UCEC). Besides, compared to the TP53 nontruncating mutation classification samples, we found that TP53 truncating mutation samples had lower TP53 expression levels in certain types of cancer. Notably, TP53 was associated with the mismatch repair (MMR) gene in some cancers which contained truncating or nontruncating mutation. Based on the classification of truncating or nontruncating mutation, we also discovered that TP53 expression was positively or negatively correlated with the immune score, stromal score, and the levels of immune cell infiltration in different cancers.
    Conclusions: Our research reveals an overarching landscape of immunological value on TP53 status in various malignant tumors. According to our results, we demonstrate that TP53 also plays an immunological role in various cancers.
    DOI:  https://doi.org/10.1155/2023/1904309
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