bims-tumhet 2021-07-25 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2021–07–25
nine papers selected by
Sergio Marchini, Humanitas Research

Abnormal methylation characteristics predict chemoresistance and poor prognosis in advanced high-grade serous ovarian cancer.
Signed in Blood: Circulating Tumor DNA in Cancer Diagnosis, Treatment and Screening.
Validation of a ctDNA-based next-generation sequencing assay in a cohort of solid tumor patients: a proposed solution for decentralized plasma testing.
Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers.
Modeling High-grade serous ovarian carcinoma using a combination of in vivo fallopian tube electroporation and CRISPR-Cas9-mediated genome editing.
Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer.
Understanding and overcoming resistance to PARP inhibitors in cancer therapy.
Prevalence and Prognostic Implications of PD-L1 Expression in Soft Tissue Sarcomas.
Crosstalk Between DNA Methylation and Gene Mutations in Colorectal Cancer.

Clin Epigenetics. 2021 Jul 21. 13(1): 141

Abnormal methylation characteristics predict chemoresistance and poor prognosis in advanced high-grade serous ovarian cancer.

Li-Yuan Feng, Bing-Bing Yan, Yong-Zhi Huang, Li Li.

   BACKGROUND: Primary or acquired chemoresistance is a key link in the high mortality rate of ovarian cancer. There is no reliable method to predict chemoresistance in ovarian cancer. We hypothesized that specific methylation characteristics could distinguish chemoresistant and chemosensitive ovarian cancer patients.
METHODS: In this study, we used 450 K Infinium Methylation BeadChip to detect the different methylation CpGs between ovarian cancer patients. The differential methylation genes were analyzed by GO and KEGG Pathway bioinformatics analysis. The candidate CpGs were confirmed by pyrosequencing. The expression of abnormal methylation gene was identified by QRT-PCR and IHC. ROC analysis confirmed the ability to predict chemotherapy outcomes. Prognosis was evaluated using Kaplan-Meier.
RESULTS: In advanced high-grade serous ovarian cancer, 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) remained hypermethylated in chemoresistant patients. The sensitivity, specificity and AUC of 8 CpGs (ITGB6:cg21105318, cg07896068, cg18437633; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934, cg13270625) methylation to predict chemotherapy sensitivity were 63.60-97.00%, 46.40-89.30% and 0.774-0.846. PFS of 6 candidate genes (ITGB6:cg21105318, cg07896068; NCALD: cg27637873, cg26782361, cg16265707; LAMA3: cg20937934) hypermethylation patients was significantly shorter. The expression of NCALD and LAMA3 in chemoresistant patients was lower than that of chemosensitive patients. Spearman analysis showed that NCALD and LAMA3 methylations were negatively correlated with their expression.
CONCLUSIONS: As a new biomarker of chemotherapy sensitivity, hypermethylation of NCALD and LAMA3 is associated with poor PFS in advanced high-grade serous ovarian cancer. In the future, further research on NCALD and LAMA3 will be needed to provide guidance for clinical stratification of demethylation therapy.

Keywords:  450 K Infinium Methylation BeadChip; Chemotherapy resistance; DNA methylation; Ovarian cancer; Prognosis

DOI:  https://doi.org/10.1186/s13148-021-01133-2
Cancers (Basel). 2021 Jul 18. pii: 3600. [Epub ahead of print]13(14):

Signed in Blood: Circulating Tumor DNA in Cancer Diagnosis, Treatment and Screening.

Jacob J Adashek, Filip Janku, Razelle Kurzrock.

  With the addition of molecular testing to the oncologist's diagnostic toolbox, patients have benefitted from the successes of gene- and immune-directed therapies. These therapies are often most effective when administered to the subset of malignancies harboring the target identified by molecular testing. An important advance in the application of molecular testing is the liquid biopsy, wherein circulating tumor DNA (ctDNA) is analyzed for point mutations, copy number alterations, and amplifications by polymerase chain reaction (PCR) and/or next-generation sequencing (NGS). The advantages of evaluating ctDNA over tissue DNA include (i) ctDNA requires only a tube of blood, rather than an invasive biopsy, (ii) ctDNA can plausibly reflect DNA shedding from multiple metastatic sites while tissue DNA reflects only the piece of tissue biopsied, and (iii) dynamic changes in ctDNA during therapy can be easily followed with repeat blood draws. Tissue biopsies allow comprehensive assessment of DNA, RNA, and protein expression in the tumor and its microenvironment as well as functional assays; however, tumor tissue acquisition is costly with a risk of complications. Herein, we review the ways in which ctDNA assessment can be leveraged to understand the dynamic changes of molecular landscape in cancers.

Keywords:  biomarkers; ctDNA; next-generation sequencing

DOI:  https://doi.org/10.3390/cancers13143600
Oncologist. 2021 Jul 19.

Validation of a ctDNA-based next-generation sequencing assay in a cohort of solid tumor patients: a proposed solution for decentralized plasma testing.

Wael Al Zoughbi, Jesse Fox, Shaham Beg, Eniko Papp, Erika Hissong, Kentaro Ohara, Laurel Keefer, Michael Sigouros, Troy Kane, Daniel Bockelman, Donna Nichol, Emily Patchell, Rohan Bareja, Aanavi Karandikar, Hussein Alnajar, Gustavo Cerqueira, Violeta Beleva Guthrie, Ellen Verner, Jyothi Manohar, Noah Greco, David Wilkes, Scott Tagawa, Murtaza S Malbari, Kevin Holcomb, Kenneth Wha Eng, Manish Shah, Nasser K Altorki, Andrea Sboner, David Nanus, Bishoy Faltas, Cora N Sternberg, John Simmons, Yariv Houvras, Ana M Molina, Samuel Angiuoli, Olivier Elemento, Juan Miguel Mosquera.

Characterization of circulating tumor DNA (ctDNA) has been integrated into clinical practice. While labs have standardized validation procedures to develop single locus tests, the efficacy of on-site plasma-based next-generation sequencing (NGS) assays still need to be proven. In this retrospective study, we profiled DNA from matched tissue and plasma samples from 75 cancer patients. We applied the NGS test PGDx elio™ plasma resolve-RUO (EPR), which detects clinically relevant alterations in 33 genes and microsatellite instability (MSI), to analyze plasma cell-free DNA (cfDNA). The concordance between alterations detected in both tissue and plasma samples was higher in patients with metastatic disease. EPR detected 77% of sequence alterations, amplifications, and fusions that were found in metastatic samples compared to 45% of those alterations found in the primary tumor samples (P = 0.00005). There was 87% agreement on MSI status between EPR and tumor tissue results. In three patients, MSI-high ctDNA correlated with response to immunotherapy. In addition, EPR revealed an FGFR2 amplification that was not detected in tumor tissue from a patient with metastatic gastric cancer, emphasizing the importance of profiling plasma samples in advanced cancer patients. In conclusion, our validation experience of a plasma-based NGS assay advances current knowledge about translating cfDNA testing into clinical practice, and supports the application of plasma assays in the management of oncology patients with metastatic disease. With an in-house method that minimizes the need for invasive procedures, on-site cfDNA testing supplements tissue biopsy to guide precision therapy and is entitled to become a routine practice. IMPLICATIONS FOR PRACTICE: We propose a solution for decentralized liquid biopsy testing based on our validation of an NGS test detects four classes of genomic alterations in blood: sequence mutations (SNS or INDELs); fusions; amplifications; and microsatellite instability (MSI-H). Although there are reference labs perform single-site comprehensive liquid biopsy testing, the targeted assay we validated can be established locally in any lab with capacity to offer clinical molecular pathology assays. To our knowledge, this is the first report validating evaluating an on-site plasma-based NGS test detects the MSI status along with common sequence alterations encountered in solid tumors.

DOI: https://doi.org/10.1002/onco.13905
Clin Epigenetics. 2021 Jul 22. 13(1): 142

Genome-wide DNA methylome analysis identifies methylation signatures associated with survival and drug resistance of ovarian cancers.

David W Chan, Wai-Yip Lam, Fushun Chen, Mingo M H Yung, Yau-Sang Chan, Wai-Sun Chan, Fangfang He, Stephanie S Liu, Karen K L Chan, Benjamin Li, Hextan Y S Ngan.

   BACKGROUND: In contrast to stable genetic events, epigenetic changes are highly plastic and play crucial roles in tumor evolution and development. Epithelial ovarian cancer (EOC) is a highly heterogeneous disease that is generally associated with poor prognosis and treatment failure. Profiling epigenome-wide DNA methylation status is therefore essential to better characterize the impact of epigenetic alterations on the heterogeneity of EOC.
METHODS: An epigenome-wide association study was conducted to evaluate global DNA methylation in a retrospective cohort of 80 mixed subtypes of primary ovarian cancers and 30 patients with high-grade serous ovarian carcinoma (HGSOC). Three demethylating agents, azacytidine, decitabine, and thioguanine, were tested their anti-cancer and anti-chemoresistant effects on HGSOC cells.
RESULTS: Global DNA hypermethylation was significantly associated with high-grade tumors, platinum resistance, and poor prognosis. We determined that 9313 differentially methylated probes (DMPs) were enriched in their relative gene regions of 4938 genes involved in small GTPases and were significantly correlated with the PI3K-AKT, MAPK, RAS, and WNT oncogenic pathways. On the other hand, global DNA hypermethylation was preferentially associated with recurrent HGSOC. A total of 2969 DMPs corresponding to 1471 genes were involved in olfactory transduction, and calcium and cAMP signaling. Co-treatment with demethylating agents showed significant growth retardation in ovarian cancer cells through differential inductions, such as cell apoptosis by azacytidine or G2/M cell cycle arrest by decitabine and thioguanine. Notably, azacytidine and decitabine, though not thioguanine, synergistically enhanced cisplatin-mediated cytotoxicity in HGSOC cells.
CONCLUSIONS: This study demonstrates the significant association of global hypermethylation with poor prognosis and drug resistance in high-grade EOC and highlights the potential of demethylating agents in cancer treatment.

Keywords:  Demethylating agents; Epigenetic; Methylome profiling; Ovarian cancer; Tumor grading

DOI:  https://doi.org/10.1186/s13148-021-01130-5
Cancer Res. 2021 Jul 23. pii: canres.1518.2020. [Epub ahead of print]

Modeling High-grade serous ovarian carcinoma using a combination of in vivo fallopian tube electroporation and CRISPR-Cas9-mediated genome editing.

Katie Teng, Matthew J Ford, Keerthana Harwalkar, YuQi Li, Alain Sarabia Pacis, David Farnell, Nobuko Yamanaka, Yu-Chang Wang, Dunarel Badescu, Tuyet Nhung Ton Nu, Jiannis Ragoussis, David G Huntsman, Jocelyne Arseneau, Yojiro Yamanaka.

Ovarian cancer is the most lethal gynecological cancer. High-grade serous ovarian carcinoma (HGSOC) accounts for most ovarian cancer cases, and it is most frequently diagnosed at advanced stages. Here we developed a novel strategy to generate somatic ovarian cancer mouse models using a combination of in vivo electroporation and CRISPR-Cas9-mediated genome editing. Mutation of tumour suppressor genes associated with HGSOC in two different combinations (Brca1, Tp53, Pten with and without Lkb1) resulted in successfully generation of HGSOC, albeit with different latencies and pathophysiology. Implementing Cre lineage tracing in this system enabled visualization of peritoneal micrometastases in an immune-competent environment. Additionally, these models displayed copy number alterations and phenotypes similar to human HGSOC. Because this strategy is flexible in selecting mutation combinations and targeting areas, it could prove highly useful for generating mouse models to advance the understanding and treatment of ovarian cancer.

DOI: https://doi.org/10.1158/0008-5472.CAN-20-1518
Gynecol Oncol. 2021 Jul 15. pii: S0090-8258(21)00577-1. [Epub ahead of print]

Integration of histopathological images and multi-dimensional omics analyses predicts molecular features and prognosis in high-grade serous ovarian cancer.

Hao Zeng, Linyan Chen, Mingxuan Zhang, Yuling Luo, Xuelei Ma.

   OBJECTIVE: This study used histopathological image features to predict molecular features, and combined with multi-dimensional omics data to predict overall survival (OS) in high-grade serous ovarian cancer (HGSOC).
METHODS: Patients from The Cancer Genome Atlas (TCGA) were distributed into training set (n = 115) and test set (n = 114). In addition, we collected tissue microarrays of 92 patients as an external validation set. Quantitative features were extracted from histopathological images using CellProfiler, and utilized to establish prediction models by machine learning methods in training set. The prediction performance was assessed in test set and validation set.
RESULTS: The prediction models were able to identify BRCA1 mutation (AUC = 0.952), BRCA2 mutation (AUC = 0.912), microsatellite instability-high (AUC = 0.919), microsatellite stable (AUC = 0.924), and molecular subtypes: proliferative (AUC = 0.961), differentiated (AUC = 0.952), immunoreactive (AUC = 0.941), mesenchymal (AUC = 0.918) in test set. The prognostic model based on histopathological image features could predict OS in test set (5-year AUC = 0.825) and validation set (5-year AUC = 0.703). We next explored the integrative prognostic models of image features, genomics, transcriptomics and proteomics. In test set, the models combining two omics had higher prediction accuracy, such as image features and genomics (5-year AUC = 0.834). The multi-omics model including all features showed the best prediction performance (5-year AUC = 0.911). According to risk score of multi-omics model, the high-risk and low-risk groups had significant survival differences (HR = 18.23, p < 0.001).
CONCLUSIONS: These results indicated the potential ability of histopathological image features to predict above molecular features and survival risk of HGSOC patients. The integration of image features and multi-omics data may improve prognosis prediction in HGSOC patients.

Keywords:  Genomics; Histopathology; Ovarian cancer; Proteomics; Transcriptomics

DOI:  https://doi.org/10.1016/j.ygyno.2021.07.015
Nat Rev Clin Oncol. 2021 Jul 20.

Understanding and overcoming resistance to PARP inhibitors in cancer therapy.

Mariana Paes Dias, Sarah C Moser, Shridar Ganesan, Jos Jonkers.

Developing novel targeted anticancer therapies is a major goal of current research. The use of poly(ADP-ribose) polymerase (PARP) inhibitors in patients with homologous recombination-deficient tumours provides one of the best examples of a targeted therapy that has been successfully translated into the clinic. The success of this approach has so far led to the approval of four different PARP inhibitors for the treatment of several types of cancers and a total of seven different compounds are currently under clinical investigation for various indications. Clinical trials have demonstrated promising response rates among patients receiving PARP inhibitors, although the majority will inevitably develop resistance. Preclinical and clinical data have revealed multiple mechanisms of resistance and current efforts are focused on developing strategies to address this challenge. In this Review, we summarize the diverse processes underlying resistance to PARP inhibitors and discuss the potential strategies that might overcome these mechanisms such as combinations with chemotherapies, targeting the acquired vulnerabilities associated with resistance to PARP inhibitors or suppressing genomic instability.

DOI: https://doi.org/10.1038/s41571-021-00532-x
Pathol Oncol Res. 2021 ;27 1609804

Prevalence and Prognostic Implications of PD-L1 Expression in Soft Tissue Sarcomas.

Mohamed Kelany, Thomas Fe Barth, Dina Salem, Marwa M Shakweer.

  Background: PD-L1 expression differs from 19 to 92% in various cancer subtypes. Its expression carries a worse prognostic value in various malignancies and could also be used as a predictive marker for immune checkpoint inhibitor response. This study aimed to explore the prevalence of PD-L1 expression in soft tissue sarcomas and the correlation of PD-L1 expression with clinicopathological features. Patients and Methods: The tissue samples of 50 patients with STS were tested for PD-L1 expression using immunohistochemistry (IHC). We followed a 6-step proportional scoring system. The patients were treated at Ain Shams University Hospital from 2011 to 2017. We also explored the correlation of PD-L1 expression with different clinical features of the patients. The chi-square test was used to calculate the differences among variables. Results: Twelve cases (24%) showed positive PD-L1 expression with the highest prevalence in rhabdomyosarcoma and desmoid tumors (2/2 and 2/3 cases, respectively), followed by GIST in 2/4 cases and liposarcoma in 3/11 cases. Patients with positive PD-L1 expression showed a trend for worse survival, with a median overall survival of 11 months vs. 19 months for patients with negative PD-L1 expression (p-value = 0.1) and a mean PFS of 6 months vs. 11 months for patients with negative PD-L1 expression (p-value = 0.1). However, these findings did not reach statistical significance. Conclusion: Although the results did not reach statistical significance due to the small number of cases, PD-L1 expression could represent a prognostic factor for poor outcome. Larger clinical trials are recommended for the validation of PD-L1 as a poor prognostic biomarker.

Keywords:  PD-L1 expression; biomarker; prevalence; prognosis; soft tissue sarcomas

DOI:  https://doi.org/10.3389/pore.2021.1609804
Front Oncol. 2021 ;11 697409

Crosstalk Between DNA Methylation and Gene Mutations in Colorectal Cancer.

Maria Dobre, Alessandro Salvi, Iulia Andreea Pelisenco, Florina Vasilescu, Giuseppina De Petro, Vlad Herlea, Elena Milanesi.

  Colorectal cancer (CRC) is often characterized by mutations and aberrant DNA methylation within the promoters of tumor suppressor genes and proto-oncogenes. The most frequent somatic mutations occur within KRAS and BRAF genes. Mutations of the KRAS gene have been detected in approximately 40% of patients, while mutations in BRAF have been detected less frequently at a rate of 10%. In this study, the DNA methylation levels of 22 candidate genes were evaluated in three types of tissue: mucosal tumoral tissue from 18 CRC patients, normal adjacent tissues from 10 CRC patients who underwent surgical resection, and tissue from a control group of six individuals with normal colonoscopies. A differential methylation profile of nine genes (RUNX3, SFRP1, WIF1, PCDH10, DKK2, DKK3, TMEFF2, OPCML, and SFRP2) presenting high methylation levels in tumoral compared to normal tissues was identified. KRAS mutations (codons 12 or 13) were detected in eight CRC cases, and BRAF mutations (codon 600) in four cases. One of the CRC patients presented concomitant mutations in KRAS codon 12 and BRAF, whereas seven patients did not present these mutations (WT). When comparing the methylation profile according to mutation status, we found that six genes (SFRP2, DKK2, PCDH10, TMEFF2, SFRP1, HS3ST2) showed a methylation level higher in BRAF positive cases than BRAF negative cases. The molecular sub-classification of CRC according to mutations and epigenetic modifications may help to identify epigenetic biomarkers useful in designing personalized strategies to improve patient outcomes.

Keywords:  BRAF; DNA methylation; KRAS; colorectal cancer; mutations

DOI:  https://doi.org/10.3389/fonc.2021.697409