bims-tumhet 2022-10-30 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2022‒10‒30
eleven papers selected by
Sergio Marchini
Humanitas Research

Clinical and molecular characteristics of ARIEL3 patients who derived exceptional benefit from rucaparib maintenance treatment for high-grade ovarian carcinoma.
The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer.
Single-cell genomic variation induced by mutational processes in cancer.
Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.
Focus on PD-1/PD-L1 as a Therapeutic Target in Ovarian Cancer.
GOF Mutant p53 in Cancers: A Therapeutic Challenge.
Spatially resolved epigenomic profiling of single cells in complex tissues.
Annotation of spatially resolved single-cell data with STELLAR.
Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma.
Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity.
Spatial transcriptomic analysis of a diverse patient cohort reveals a conserved architecture in triple-negative breast cancer.

Gynecol Oncol. 2022 Oct 20. pii: S0090-8258(22)00575-3. [Epub ahead of print]

Clinical and molecular characteristics of ARIEL3 patients who derived exceptional benefit from rucaparib maintenance treatment for high-grade ovarian carcinoma.

David M O'Malley, Amit M Oza, Domenica Lorusso, Carol Aghajanian, Ana Oaknin, Andrew Dean, Nicoletta Colombo, Johanne I Weberpals, Andrew R Clamp, Giovanni Scambia, Alexandra Leary, Robert W Holloway, Margarita Amenedo Gancedo, Peter C Fong, Jeffrey C Goh, Elizabeth M Swisher, Lara Maloney, Sandra Goble, Kevin K Lin, Tanya Kwan, Jonathan A Ledermann, Robert L Coleman.

  OBJECTIVE: ARIEL3 (NCT01968213) is a placebo-controlled randomized trial of the poly(ADP-ribose) polymerase inhibitor rucaparib as maintenance treatment in patients with recurrent high-grade ovarian carcinoma who responded to their latest line of platinum therapy. Rucaparib improved progression-free survival across all predefined subgroups. Here, we present an exploratory analysis of clinical and molecular characteristics associated with exceptional benefit from rucaparib.METHODS: Patients were randomized 2:1 to receive rucaparib 600 mg twice daily or placebo. Molecular features (genomic alterations, BRCA1 promoter methylation) and baseline clinical characteristics were evaluated for association with exceptional benefit (progression-free survival ≥2 years) versus progression on first scan (short-term subgroup) and other efficacy outcomes.
RESULTS: Rucaparib treatment was significantly associated with exceptional benefit compared with placebo: 79/375 (21.1%) vs 4/189 (2.1%), respectively (p < 0.0001). Exceptional benefit was more frequent among patients with favorable baseline clinical characteristics and with carcinomas harboring molecular evidence of homologous recombination deficiency (HRD). A comparison between patients who derived exceptional benefit from rucaparib and those in the short-term subgroup revealed both clinical markers (no measurable disease at baseline, complete response to latest platinum, longer penultimate platinum-free interval) and molecular markers (BRCA1, BRCA2, RAD51C, and RAD51D alterations and genome-wide loss of heterozygosity) significantly associated with exceptional benefit.
CONCLUSIONS: Exceptional benefit in ARIEL3 was more common in, but not exclusive to, patients with favorable clinical characteristics or molecular features associated with HRD. Our results suggest that rucaparib can deliver exceptional benefit to a diverse set of patients with recurrent high-grade ovarian carcinoma.

Keywords:  Genomics; Ovarian carcinoma; Rucaparib; Safety

DOI:  https://doi.org/10.1016/j.ygyno.2022.08.021
Mol Cell Probes. 2022 Oct 22. pii: S0890-8508(22)00082-2. [Epub ahead of print] 101871

The application of circulating tumor cell and cell-free DNA liquid biopsies in ovarian cancer.

Abigél Balla, Jong Bhak, Orsolya Biró.

  Ovarian cancer is the deadliest gynecological cancer. 70% of the cases are diagnosed at late stages with already developed metastases due to the absence of easily noticeable symptoms. Early-stage ovarian cancer has a good prognosis with a 5-year survival rate reaching 95%, hence the identification of effective biomarkers for early diagnosis is important. Advances in liquid biopsy-based methods can have a significant impact not just on the development of an efficient screening strategy, but also in clinical decision-making with additional molecular profiling and genetic alterations linked to therapy resistance. Despite the well-known advantages of liquid biopsy, there are still challenges that need to be addressed before its routine use in clinical practice. Various liquid biopsy-based biomarkers have been investigated in ovarian cancer; however, in this review, we are concentrating on the current use of cell-free DNA (cfDNA) and circulating tumor cells (CTCs) in disease management, focusing on their emerging importance in clinical practice. We also discuss the technical aspects of these workflows. The analysis of cfDNA is often chosen for the detection of mutations, copy number aberrations, and DNA methylation changes, whereas CTC analysis provides a unique opportunity to study whole cells, thus allowing DNA, RNA, and protein-based molecular profiling as well as in vivo studies. Combined solutions which merge the strengths of cfDNA and CTC approaches should be developed to maximize the potential of liquid biopsy technology.

Keywords:  Circulating cell-free DNA (cfDNA); Circulating tumor cell (CTC); Liquid biopsy; Ovarian cancer

DOI:  https://doi.org/10.1016/j.mcp.2022.101871
Nature. 2022 Oct 26.

Single-cell genomic variation induced by mutational processes in cancer.

IMAXT Consortium

How cell-to-cell copy number alterations that underpin genomic instability1 in human cancers drive genomic and phenotypic variation, and consequently the evolution of cancer2, remains understudied. Here, by applying scaled single-cell whole-genome sequencing3 to wild-type, TP53-deficient and TP53-deficient;BRCA1-deficient or TP53-deficient;BRCA2-deficient mammary epithelial cells (13,818 genomes), and to primary triple-negative breast cancer (TNBC) and high-grade serous ovarian cancer (HGSC) cells (22,057 genomes), we identify three distinct 'foreground' mutational patterns that are defined by cell-to-cell structural variation. Cell- and clone-specific high-level amplifications, parallel haplotype-specific copy number alterations and copy number segment length variation (serrate structural variations) had measurable phenotypic and evolutionary consequences. In TNBC and HGSC, clone-specific high-level amplifications in known oncogenes were highly prevalent in tumours bearing fold-back inversions, relative to tumours with homologous recombination deficiency, and were associated with increased clone-to-clone phenotypic variation. Parallel haplotype-specific alterations were also commonly observed, leading to phylogenetic evolutionary diversity and clone-specific mono-allelic expression. Serrate variants were increased in tumours with fold-back inversions and were highly correlated with increased genomic diversity of cellular populations. Together, our findings show that cell-to-cell structural variation contributes to the origins of phenotypic and evolutionary diversity in TNBC and HGSC, and provide insight into the genomic and mutational states of individual cancer cells.

DOI: https://doi.org/10.1038/s41586-022-05249-0
Nat Commun. 2022 Oct 26. 13(1): 6360

Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer.

Filipe Correia Martins, Dominique-Laurent Couturier, Ines de Santiago, Carolin Margarethe Sauer, Maria Vias, Mihaela Angelova, Deborah Sanders, Anna Piskorz, James Hall, Karen Hosking, Anumithra Amirthanayagam, Sabina Cosulich, Larissa Carnevalli, Barry Davies, Thomas B K Watkins, Ionut G Funingana, Helen Bolton, Krishnayan Haldar, John Latimer, Peter Baldwin, Robin Crawford, Matthew Eldridge, Bristi Basu, Mercedes Jimenez-Linan, Andrew W Mcpherson, Nicholas McGranahan, Kevin Litchfield, Sohrab P Shah, Iain McNeish, Carlos Caldas, Gerard Evan, Charles Swanton, James D Brenton.

Chromosomal instability is a major challenge to patient stratification and targeted drug development for high-grade serous ovarian carcinoma (HGSOC). Here we show that somatic copy number alterations (SCNAs) in frequently amplified HGSOC cancer genes significantly correlate with gene expression and methylation status. We identify five prevalent clonal driver SCNAs (chromosomal amplifications encompassing MYC, PIK3CA, CCNE1, KRAS and TERT) from multi-regional HGSOC data and reason that their strong selection should prioritise them as key biomarkers for targeted therapies. We use primary HGSOC spheroid models to test interactions between in vitro targeted therapy and SCNAs. MYC chromosomal copy number is associated with in-vitro and clinical response to paclitaxel and in-vitro response to mTORC1/2 inhibition. Activation of the mTOR survival pathway in the context of MYC-amplified HGSOC is statistically associated with increased prevalence of SCNAs in genes from the PI3K pathway. Co-occurrence of amplifications in MYC and genes from the PI3K pathway is independently observed in squamous lung cancer and triple negative breast cancer. In this work, we show that identifying co-occurrence of clonal driver SCNA genes could be used to tailor therapeutics for precision medicine.

DOI: https://doi.org/10.1038/s41467-022-33870-0
Int J Mol Sci. 2022 Oct 11. pii: 12067. [Epub ahead of print]23(20):

Focus on PD-1/PD-L1 as a Therapeutic Target in Ovarian Cancer.

Adrian Dumitru, Elena-Codruta Dobrica, Adina Croitoru, Sanda Maria Cretoiu, Bogdan Severus Gaspar.

  Ovarian cancer is considered one of the most aggressive and deadliest gynecological malignancies worldwide. Unfortunately, the therapeutic methods that are considered the gold standard at this moment are associated with frequent recurrences. Survival in ovarian cancer is associated with the presence of a high number of intra tumor infiltrating lymphocytes (TILs). Therefore, immunomodulation is considered to have an important role in cancer treatment, and immune checkpoint inhibitors may be useful for restoring T cell-mediated antitumor immunity. However, the data presented in the literature until now are not sufficient to allow for the identification and selection of patients who really respond to immunotherapy among those with ovarian cancer. Although there are some studies with favorable results, more prospective trials are needed in this sense. This review focuses on the current and future perspectives of PD-1/L1 blockade in ovarian cancer and analyzes the most important immune checkpoint inhibitors used, with the aim of achieving optimal clinical outcomes. Future studies and trials are needed to maximize the efficacy of immune checkpoint blockade therapy in ovarian cancer, as well as in all cancers, in general.

Keywords:  PD-1/PD-L1; gynecological malignancy; lncRNAs; miRNAs; ovarian cancer

DOI:  https://doi.org/10.3390/ijms232012067
Cancers (Basel). 2022 Oct 18. pii: 5091. [Epub ahead of print]14(20):

GOF Mutant p53 in Cancers: A Therapeutic Challenge.

Lobsang Dolma, Patricia A J Muller.

  TP53 is mutated in the majority of human cancers. Mutations can lead to loss of p53 expression or expression of mutant versions of the p53 protein. These mutant p53 proteins have oncogenic potential. They can inhibit any remaining WTp53 in a dominant negative manner, or they can acquire new functions that promote tumour growth, invasion, metastasis and chemoresistance. In this review we explore some of the mechanisms that make mutant p53 cells resistant to chemotherapy. As mutant p53 tumours are resistant to many traditional chemotherapies, many have sought to explore new ways of targeting mutant p53 tumours and reinstate chemosensitivity. These approaches include targeting of mutant p53 stability, mutant p53 binding partners and downstream pathways, p53 vaccines, restoration of WTp53 function, and WTp53 gene delivery. The current advances and challenges of these strategies are discussed.

Keywords:  GOF; gain-of-function; mutant p53 chemoresistance; targeted therapy

DOI:  https://doi.org/10.3390/cancers14205091
Cell. 2022 Oct 14. pii: S0092-8674(22)01254-5. [Epub ahead of print]

Spatially resolved epigenomic profiling of single cells in complex tissues.

Tian Lu, Cheen Euong Ang, Xiaowei Zhuang.

  The recent development of spatial omics methods has enabled single-cell profiling of the transcriptome and 3D genome organization with high spatial resolution. Expanding the repertoire of spatial omics tools, a spatially resolved single-cell epigenomics method will accelerate understanding of the spatial regulation of cell and tissue functions. Here, we report a method for spatially resolved epigenomic profiling of single cells using in situ tagmentation and transcription followed by multiplexed imaging. We demonstrated the ability to profile histone modifications marking active promoters, putative enhancers, and silent promoters in individual cells, and generated high-resolution spatial atlas of hundreds of active promoters and putative enhancers in embryonic and adult mouse brains. Our results suggested putative promoter-enhancer pairs and enhancer hubs regulating developmentally important genes. We envision this approach will be generally applicable to spatial profiling of epigenetic modifications and DNA-binding proteins, advancing our understanding of how gene expression is spatiotemporally regulated by the epigenome.

Keywords:  MERFISH; brain; development; enhancer; enhancer hub; enhancer-promoter interaction; epigenomic MERFISH; promoter; single-cell epigenomics; spatial epigenomic

DOI:  https://doi.org/10.1016/j.cell.2022.09.035
Nat Methods. 2022 Oct 24.

Annotation of spatially resolved single-cell data with STELLAR.

Maria Brbić, Kaidi Cao, John W Hickey, Yuqi Tan, Michael P Snyder, Garry P Nolan, Jure Leskovec.

Accurate cell-type annotation from spatially resolved single cells is crucial to understand functional spatial biology that is the basis of tissue organization. However, current computational methods for annotating spatially resolved single-cell data are typically based on techniques established for dissociated single-cell technologies and thus do not take spatial organization into account. Here we present STELLAR, a geometric deep learning method for cell-type discovery and identification in spatially resolved single-cell datasets. STELLAR automatically assigns cells to cell types present in the annotated reference dataset and discovers novel cell types and cell states. STELLAR transfers annotations across different dissection regions, different tissues and different donors, and learns cell representations that capture higher-order tissue structures. We successfully applied STELLAR to CODEX multiplexed fluorescent microscopy data and multiplexed RNA imaging datasets. Within the Human BioMolecular Atlas Program, STELLAR has annotated 2.6 million spatially resolved single cells with dramatic time savings.

DOI: https://doi.org/10.1038/s41592-022-01651-8
Front Genet. 2022 ;13 1022078

Identification and analysis of DNA methylation-driven signatures for prognostic and immune microenvironments evaluation in hepatocellular carcinoma.

Bingbing Shen, Zhen Wen, Gang Lv, Jianguo Wang, Ruijie Han, Jianxin Jiang.

  Liver cancer is the main reason of cancer deaths globally, with an unfavorable prognosis. DNA methylation is one of the epigenetic modifications and maintains the right adjustment of gene expression and steady gene silencing. We aim to explore the novel signatures for prognosis by using DNA methylation-driven genes. To acquire the DNA methylation-driven genes, we perform the difference analysis from the gene expression data and DNA methylation data in TCGA or GEO databases. And we obtain the 31 DNA methylation-driven genes. Subsequently, consensus clustering analysis was utilized to identify the molecular subtypes based on the 31 DNA methylation-driven genes. So, two molecular subtypes were identified to perform those analyses: Survival, immune cell infiltration, and tumor mutation. Results showed that two subtypes were clustered with distinct prognoses, tumor-infiltrating immune cell and tumor mutation burden. Furthermore, the 31 DNA methylation-driven genes were applied to perform the survival analysis to select the 14 survival-related genes. Immediately, a five methylation-driven genes risk model was built, and the patients were divided into high and low-risk groups. The model was established with TCGA as the training cohort and GSE14520 as the validation cohort. According to the risk model, we perform the systematical analysis, including survival, clinical feature, immune cell infiltration, somatic mutation status, underlying mechanisms, and drug sensitivity. Results showed that the high and low groups possessed statistical significance. In addition, the ROC curve was utilized to measure the accuracy of the risk model. AUCs at 1-year, 3-years, and 5-years were respectively 0.770, 0.698, 0.676 in training cohort and 0.717, 0.649, 0.621 in validation cohort. Nomogram was used to provide a better prediction for patients' survival. Risk score increase the accuracy of survival prediction in HCC patients. In conclusion, this study developed a novel risk model of five methylation-driven genes based on the comprehensive bioinformatics analysis, which accurately predicts the survival of HCC patients and reflects the immune and mutation features of HCC. This study provides novel insights for immunotherapy of HCC patients and promotes medical progress.

Keywords:  DNA methylation; bioinformatics; clinical; hepatocellular carcinoma; immune; immunotherapy; mutation; prognostic model

DOI:  https://doi.org/10.3389/fgene.2022.1022078
Cancers (Basel). 2022 Oct 12. pii: 4986. [Epub ahead of print]14(20):

Chromosomal Instability, Selection and Competition: Factors That Shape the Level of Karyotype Intra-Tumor Heterogeneity.

Tom van den Bosch, Sarah Derks, Daniël M Miedema.

  Intra-tumor heterogeneity (ITH) is a pan-cancer predictor of survival, with high ITH being correlated to a dismal prognosis. The level of ITH is, hence, a clinically relevant characteristic of a malignancy. ITH of karyotypes is driven by chromosomal instability (CIN). However, not all new karyotypes generated by CIN are viable or competitive, which limits the amount of ITH. Here, we review the cellular processes and ecological properties that determine karyotype ITH. We propose a framework to understand karyotype ITH, in which cells with new karyotypes emerge through CIN, are selected by cell intrinsic and cell extrinsic selective pressures, and propagate through a cancer in competition with other malignant cells. We further discuss how CIN modulates the cell phenotype and immune microenvironment, and the implications this has for the subsequent selection of karyotypes. Together, we aim to provide a comprehensive overview of the biological processes that shape the level of karyotype heterogeneity.

Keywords:  aneuploidy; chromosomal instability; immunological pressure; intra-tumor heterogeneity

DOI:  https://doi.org/10.3390/cancers14204986
Cancer Res. 2022 Oct 25. pii: CAN-22-2682. [Epub ahead of print]

Spatial transcriptomic analysis of a diverse patient cohort reveals a conserved architecture in triple-negative breast cancer.

Rania Bassiouni, Michael O Idowu, Lee D Gibbs, Valentina Robila, Pamela J Grizzard, Michelle G Webb, Jiarong Song, Ashley Noriega, David W Craig, John D Carpten.

Triple-negative breast cancer (TNBC) is an aggressive disease that disproportionately affects African American (AA) women. Limited targeted therapeutic options exist for TNBC patients. Here, we employ spatial transcriptomics to interrogate tissue from a racially diverse TNBC cohort to comprehensively annotate the transcriptional states of spatially resolved cellular populations. A total of 38,706 spatial features from a cohort of 28 sections from 14 patients were analyzed. Intratumoral analysis of spatial features from individual sections revealed heterogeneous transcriptional substructures. However, integrated analysis of all samples resulted in nine transcriptionally distinct clusters that mapped across all individual sections. Furthermore, novel use of join count analysis demonstrated non-random directional spatial dependencies of the transcriptionally defined shared clusters, supporting a conserved spatio-transcriptional architecture in TNBC. These findings were substantiated in an independent validation cohort comprising 17,861 spatial features representing 15 samples from 8 patients. Stratification of samples by race revealed race-associated differences in hypoxic tumor content and regions of immune-rich infiltrate. Overall, this study combined spatial and functional molecular analyses to define the tumor architecture of TNBC, with potential implications in understanding TNBC disparities.

DOI: https://doi.org/10.1158/0008-5472.CAN-22-2682