bims-tumhet 2022-01-16 papers

bims-tumhet

Biomed News

on Tumor Heterogeneity

Issue of 2022‒01‒16
eight papers selected by
Sergio Marchini
Humanitas Research

Homologous recombination deficiency testing in first-line ovarian cancer.
Preventing and Overcoming Resistance to PARP Inhibitors: A Focus on the Clinical Landscape.
Subclonal landscape of cancer drives resistance to immune therapy.
ChromoMap: an R package for interactive visualization of multi-omics data and annotation of chromosomes.
A Statistical Method for Association Analysis of Cell Type Compositions.
BRCA1 and Metastasis: Outcome of Defective DNA Repair.
Hallmarks of Cancer: New Dimensions.
Cell-free DNA analysis in current cancer clinical trials: a review.

Ann Oncol. 2022 Jan 08. pii: S0923-7534(22)00004-7. [Epub ahead of print]

Homologous recombination deficiency testing in first-line ovarian cancer.

K N Moore, A du Bois.

DOI: https://doi.org/10.1016/j.annonc.2021.12.013
Cancers (Basel). 2021 Dec 23. pii: 44. [Epub ahead of print]14(1):

Preventing and Overcoming Resistance to PARP Inhibitors: A Focus on the Clinical Landscape.

Rosario Prados-Carvajal, Elsa Irving, Natalia Lukashchuk, Josep V Forment.

  Poly(ADP-ribose) polymerase (PARP) inhibitors (PARPi) are now a first-line maintenance treatment in ovarian cancer and have been approved in other cancer types, including breast, pancreatic and prostate. Despite their efficacy, and as is the case for other targeted therapies, resistance to PARPi has been reported clinically and is generating a growing patient population of unmet clinical need. Here, we discuss the mechanisms of resistance that have been described in pre-clinical models and focus on those that have been already identified in the clinic, highlighting the key challenges to fully characterise the clinical landscape of PARPi resistance and proposing ways of preventing and overcoming it.

Keywords:  PARP inhibitor (PARPi); clinical relevance; homologous recombination repair (HRR); molecular mechanisms; resistance

DOI:  https://doi.org/10.3390/cancers14010044
Cancer Treat Res Commun. 2022 Jan 02. pii: S2468-2942(21)00203-3. [Epub ahead of print]30 100507

Subclonal landscape of cancer drives resistance to immune therapy.

Daniel J Craig, Morgan M Bailey, Olivia B Noe, Kada K Williams, Laura Stanbery, Danae M Hamouda, John J Nemunaitis.

  Tumor mutation burden (TMB) is often used as a biomarker for immunogenicity and prerequisite for immune checkpoint inhibitor (ICI) therapy. However, it is becoming increasingly evident that not all tumors with high TMB respond to ICIs as expected. It has been shown that the ability of T-cells to infiltrate the tumor microenvironment and elicit a specific immune response is dependent not only on the TMB, but also on intra-tumor heterogeneity and the fraction of low-frequency subclonal mutations that make up the tumor. High intra-tumor heterogeneity leads to inefficient recognition of tumor neoantigens by T-cells due to their diluted frequency and spatial heterogeneity. Clinical studies have shown that tumors with a high degree of intra-tumor heterogeneity respond poorly to ICI therapy, and previous cytotoxic treatment may increase the intra-tumor heterogeneity and render second-line ICI therapy less effective. This paper reviews the role of ICI therapy when following chemotherapy or radiation to determine if they may be better suited as first-line therapy in patients with high TMB, low intra-tumor heterogeneity, and high PD-1, PD-L1, or CTLA-4 expression.

Keywords:  Immune checkpoint inhibitor; Immunotherapy; Intra-tumor heterogeneity; Tumor mutation burden

DOI:  https://doi.org/10.1016/j.ctarc.2021.100507
BMC Bioinformatics. 2022 Jan 11. 23(1): 33

ChromoMap: an R package for interactive visualization of multi-omics data and annotation of chromosomes.

Lakshay Anand, Carlos M Rodriguez Lopez.

  BACKGROUND: The recent advancements in high-throughput sequencing have resulted in the availability of annotated genomes, as well as of multi-omics data for many living organisms. This has increased the need for graphic tools that allow the concurrent visualization of genomes and feature-associated multi-omics data on single publication-ready plots.RESULTS: We present chromoMap, an R package, developed for the construction of interactive visualizations of chromosomes/chromosomal regions, mapping of any chromosomal feature with known coordinates (i.e., protein coding genes, transposable elements, non-coding RNAs, microsatellites, etc.), and chromosomal regional characteristics (i.e. genomic feature density, gene expression, DNA methylation, chromatin modifications, etc.) of organisms with a genome assembly. ChromoMap can also integrate multi-omics data (genomics, transcriptomics and epigenomics) in relation to their occurrence across chromosomes. ChromoMap takes tab-delimited files (BED like) or alternatively R objects to specify the genomic co-ordinates of the chromosomes and elements to annotate. Rendered chromosomes are composed of continuous windows of a given range, which, on hover, display detailed information about the elements annotated within that range. By adjusting parameters of a single function, users can generate a variety of plots that can either be saved as static image or as HTML documents.
CONCLUSIONS: ChromoMap's flexibility allows for concurrent visualization of genomic data in each strand of a given chromosome, or of more than one homologous chromosome; allowing the comparison of multi-omic data between genotypes (e.g. species, varieties, etc.) or between homologous chromosomes of phased diploid/polyploid genomes. chromoMap is an extensive tool that can be potentially used in various bioinformatics analysis pipelines for genomic visualization of multi-omics data.

Keywords:  Genome visualization; Multi-omics data visualization; R package

DOI:  https://doi.org/10.1186/s12859-021-04556-z
Stat Biosci. 2021 Dec;13(3): 373-385

A Statistical Method for Association Analysis of Cell Type Compositions.

Licai Huang, Paul Little, Jeroen R Huyghe, Qian Shi, Tabitha A Harrison, Greg Yothers, Thomas J George, Ulrike Peters, Andrew T Chan, Polly A Newcomb, Wei Sun.

  Gene expression data are often collected from tissue samples that are composed of multiple cell types. Studies of cell type composition based on gene expression data from tissue samples have recently attracted increasing research interest and led to new method development for cell type composition estimation. This new information on cell type composition can be associated with individual characteristics (e.g., genetic variants) or clinical outcomes (e.g., survival time). Such association analysis can be conducted for each cell type separately followed by multiple testing correction. An alternative approach is to evaluate this association using the composition of all the cell types, thus aggregating association signals across cell types. A key challenge of this approach is to account for the dependence across cell types. We propose a new method to quantify the distances between cell types while accounting for their dependencies, and use this information for association analysis. We demonstrate our method in two applied examples: to assess the association between immune cell type composition in tumor samples of colorectal cancer patients versus survival time and SNP genotypes. We found immune cell composition has prognostic value, and our distance metric leads to more accurate survival time prediction than other distance metrics that ignore cell type dependencies. In addition, survival time-associated SNPs are enriched among the SNPs associated with immune cell composition.

Keywords:  cell type composition; genome-wide associations; survival time

DOI:  https://doi.org/10.1007/s12561-020-09293-0
Cancers (Basel). 2021 Dec 27. pii: 108. [Epub ahead of print]14(1):

BRCA1 and Metastasis: Outcome of Defective DNA Repair.

Rehna Krishnan, Parasvi S Patel, Razqallah Hakem.

  Heritable mutations in BRCA1 and BRCA2 genes are a major risk factor for breast and ovarian cancer. Inherited mutations in BRCA1 increase the risk of developing breast cancers by up to 72% and ovarian cancers by up to 69%, when compared to individuals with wild-type BRCA1. BRCA1 and BRCA2 (BRCA1/2) are both important for homologous recombination-mediated DNA repair. The link between BRCA1/2 mutations and high susceptibility to breast cancer is well established. However, the potential impact of BRCA1 mutation on the individual cell populations within a tumor microenvironment, and its relation to increased aggressiveness of cancer is not well understood. The objective of this review is to provide significant insights into the mechanisms by which BRCA1 mutations contribute to the metastatic and aggressive nature of the tumor cells.

Keywords:  BRCA1; BRCA2; DNA damage; DNA repair; metastasis

DOI:  https://doi.org/10.3390/cancers14010108
Cancer Discov. 2022 Jan;12(1): 31-46

Hallmarks of Cancer: New Dimensions.

Douglas Hanahan.

The hallmarks of cancer conceptualization is a heuristic tool for distilling the vast complexity of cancer phenotypes and genotypes into a provisional set of underlying principles. As knowledge of cancer mechanisms has progressed, other facets of the disease have emerged as potential refinements. Herein, the prospect is raised that phenotypic plasticity and disrupted differentiation is a discrete hallmark capability, and that nonmutational epigenetic reprogramming and polymorphic microbiomes both constitute distinctive enabling characteristics that facilitate the acquisition of hallmark capabilities. Additionally, senescent cells, of varying origins, may be added to the roster of functionally important cell types in the tumor microenvironment. SIGNIFICANCE: Cancer is daunting in the breadth and scope of its diversity, spanning genetics, cell and tissue biology, pathology, and response to therapy. Ever more powerful experimental and computational tools and technologies are providing an avalanche of "big data" about the myriad manifestations of the diseases that cancer encompasses. The integrative concept embodied in the hallmarks of cancer is helping to distill this complexity into an increasingly logical science, and the provisional new dimensions presented in this perspective may add value to that endeavor, to more fully understand mechanisms of cancer development and malignant progression, and apply that knowledge to cancer medicine.

DOI: https://doi.org/10.1158/2159-8290.CD-21-1059
Br J Cancer. 2022 Jan 13.

Cell-free DNA analysis in current cancer clinical trials: a review.

M Cisneros-Villanueva, L Hidalgo-Pérez, M Rios-Romero, A Cedro-Tanda, C A Ruiz-Villavicencio, K Page, R Hastings, D Fernandez-Garcia, R Allsopp, M A Fonseca-Montaño, S Jimenez-Morales, V Padilla-Palma, J A Shaw, A Hidalgo-Miranda.

Cell-free DNA (cfDNA) analysis represents a promising method for the diagnosis, treatment selection and clinical follow-up of cancer patients. Although its general methodological feasibility and usefulness has been demonstrated, several issues related to standardisation and technical validation must be addressed for its routine clinical application in cancer. In this regard, most cfDNA clinical applications are still limited to clinical trials, proving its value in several settings. In this paper, we review the current clinical trials involving cfDNA/ctDNA analysis and highlight those where it has been useful for patient stratification, treatment follow-up or development of novel approaches for early diagnosis. Our query included clinical trials, including the terms 'cfDNA', 'ctDNA', 'liquid biopsy' AND 'cancer OR neoplasm' in the FDA and EMA public databases. We identified 1370 clinical trials (FDA = 1129, EMA = 241) involving liquid-biopsy analysis in cancer. These clinical trials show promising results for the early detection of cancer and confirm cfDNA as a tool for real-time monitoring of acquired therapy resistance, accurate disease-progression surveillance and improvement of treatment, situations that result in a better quality of life and extended overall survival for cancer patients.

DOI: https://doi.org/10.1038/s41416-021-01696-0