The landscape of cancer genes and mutational processes in breast cancer

E239K mutation abolishes the suppressive effects of lysine-specific demethylase 1 on migration and invasion of MCF7 cells

Lysine‐specific demethylase 1 (LSD1) is an important histone demethylase that mediates epithelial to mesenchymal transition (EMT). The E239K mutation of LSD1 was identified in a luminal breast cancer patient from the COSMIC Breast Cancer dataset. To investigate the functional effects of the E239K mutation of LSD1, a stable LSD1 knockdown MCF7 cell line was generated. Rescue with WT LSD1, but not E239K mutated LSD1, suppressed the invasion and migration of the LSD1 knockdown cells, indicating that the E239K mutation abolished the suppressive effects of LSD1 on the invasion and migration of MCF7 cells. Further analysis showed that the E239K mutation abolished LSD1‐mediated invasion and migration of MCF7 cells through downregulation of estrogen receptor α (ERα). Most importantly, the E239K mutation disrupted the interaction between LSD1 and GATA3, which reduced the enrichment of LSD1 at the promoter region of the ERα gene; the reduced enrichment of LSD1 at the promoter region of the ERα gene caused enhanced histone H3K9 methylation, which subsequently suppressed the transcription of the ERα gene. In summary, the E239K mutation abolishes the suppressive function of LSD1 on migration and invasion of breast cancer cells by disrupting the interaction between LSD1 and GATA3.

Dissecting the heterogeneity and tumorigenesis of BRCA1 deficient mammary tumors via single cell RNA sequencing

Background: BRCA1 plays critical roles in mammary gland development and mammary tumorigenesis. And loss of BRCA1 induces mammary tumors in a stochastic manner. These tumors present great heterogeneity at both intertumor and intratumor levels.

Methods: To comprehensively elucidate the heterogeneity of BRCA1 deficient mammary tumors and the underlying mechanisms for tumor initiation and progression, we conducted bulk and single cell RNA sequencing (scRNA-seq) on both mammary gland cells and mammary tumor cells isolated from Brca1 knockout mice.

Results: We found the BRCA1 deficient tumors could be classified into four subtypes with distinct molecular features and different sensitivities to anti-cancer drugs at the intertumor level. Whereas within the tumors, heterogeneous subgroups were classified mainly due to the different activities of cell proliferation, DNA damage response/repair and epithelial-to-mesenchymal transition (EMT). Besides, we reconstructed the BRCA1 related mammary tumorigenesis to uncover the transcriptomes alterations during this process via pseudo-temporal analysis of the scRNA-seq data. Furthermore, from candidate markers for BRCA1 mutant tumors, we discovered and validated one oncogene Mrc2, whose loss could reduce mammary tumor growth in vitro and in vivo.

Conclusion: Our study provides a useful resource for better understanding of mammary tumorigenesis induced by BRCA1 deficiency.

The Single-Cell Sequencing: A Dazzling Light Shining on the Dark Corner of Cancer

Tumorigenesis refers to the process of clonal dysplasia that occurs due to the collapse of normal growth regulation in cells caused by the action of various carcinogenic factors. These “successful” tumor cells pass on the genetic templates to their generations in evolutionary terms, but they also constantly adapt to ever-changing host environments. A unique peculiarity known as intratumor heterogeneity (ITH) is extensively involved in tumor development, metastasis, chemoresistance, and immune escape. An understanding of ITH is urgently required to identify the diversity and complexity of the tumor microenvironment (TME), but achieving this understanding has been a challenge. Single-cell sequencing (SCS) is a powerful tool that can gauge the distribution of genomic sequences in a single cell and the genetic variability among tumor cells, which can improve the understanding of ITH. SCS provides fundamental ideas about existing diversity in specific TMEs, thus improving cancer diagnosis and prognosis prediction, as well as improving the monitoring of therapeutic response. Herein, we will discuss advances in SCS and review SCS application in tumors based on current evidence.

Discovery of a novel potentially transforming somatic mutation in CSF2RB gene in breast cancer

The colony stimulating factor 2 receptor subunit beta (CSF2RB) is the common signaling subunit of the cytokine receptors for IL-3, IL-5, and GM-CSF. Several studies have shown that spontaneous and random mutants of CSF2RB can lead to ligand independence in vitro. To date, no report(s) have been shown for the presence of potentially transforming and oncogenic CSF2RB mutation(s) clinically in cancer patients until the first reported case of a leukemia patient in 2016 harboring a germline-activating mutation (R461C). We combined exome sequencing, pathway analyses, and functional assays to identify novel somatic mutations in KAIMRC1 cells and breast tumor specimen. The patient's peripheral blood mononuclear cell (PBMC) exome served as a germline control in the identification of somatic mutations. Here, we report the discovery of a novel potentially transforming and oncogenic somatic mutation (S230I) in the CSF2RB gene of a breast cancer patient and the cell line, KAIMRC1 established from her breast tumor tissue. KAIMRC1 cells are immortalized and shown to survive and proliferate in ligand starvation condition. Immunoblot analysis showed that mutant CSF2RB signals through JAK2/STAT and PI3K/mTOR pathways in ligand starvation conditions. Screening a small molecule kinase inhibitor library revealed potent JAK2 inhibitors against KAIMRC1 cells. We, for the first time, identified a somatic, potentially transforming, and oncogenic CSF2RB mutation (S230I) in breast cancer patients that seem to be an actionable mutation leading to the development of new therapeutics for breast cancer.

Two oppositely-charged sf3b1 mutations cause defective development, impaired immune response, and aberrant selection of intronic branch sites in Drosophila

SF3B1 mutations occur in many cancers, and the highly conserved His662 residue is one of the hotspot mutation sites. To address effects on splicing and development, we constructed strains carrying point mutations at the corresponding residue His698 in Drosophila using the CRISPR-Cas9 technique. Two mutations, H698D and H698R, were selected due to their frequent presence in patients and notable opposite charges. Both the sf3b1-H698D and–H698R mutant flies exhibit developmental defects, including less egg-laying, decreased hatching rates, delayed morphogenesis and shorter lifespans. Interestingly, the H698D mutant has decreased resistance to fungal infection, while the H698R mutant shows impaired climbing ability. Consistent with these phenotypes, further analysis of RNA-seq data finds altered expression of immune response genes and changed alternative splicing of muscle and neural-related genes in the two mutants, respectively. Expression of Mef2-RB, an isoform of Mef2 gene that was downregulated due to splicing changes caused by H698R, partly rescues the climbing defects of the sf3b1-H698R mutant. Lariat sequencing reveals that the two sf3b1-H698 mutations cause aberrant selection of multiple intronic branch sites, with the H698R mutant using far upstream branch sites in the changed alternative splicing events. This study provides in vivo evidence from Drosophila that elucidates how these SF3B1 hotspot mutations alter splicing and their consequences in development and in the immune system.

In the past decade, one of the important findings in the RNA splicing field has been that somatic SF3B1 mutations widely occur in many cancers. Including R625, H662, K666, K700 and E902, there are five hotspot mutation sites in the highly conserved HEAT repeats of SF3B1. Several kinds of H662 mutations have been found widely in MDS, AML, CLL and breast cancers; however, it remains unclear how these H662 mutations alter splicing and whether they have in vivo effects on development. To address these questions, in this manuscript, we first summarized the H662 mutations in human diseases and constructed two corresponding Drosophila mutant strains, sf3b1-H698D and -H698R using CRISPR-Cas9. Analyses of these two fly strains find that the two oppositely charged Sf3b1-H698 mutants are defective in development. In addition, one mutant has decreased climbing ability, whereas the other mutant has impaired immune response. Further RNA-seq allows us to find responsible genes in each mutant strain, and lariat sequencing reveals that both mutations cause aberrant selection of the intronic branch sites. Our findings provide the first in vivo evidence that Sf3b1 mutations result in defective development, and also reveal a molecular mechanism of these hotspot histidine mutations that enhance the use of cryptic branch sites to alter splicing. Importantly, we demonstrate that the H698R mutant prefers to use far upstream branch sites.

Genomic and Transcriptomic Analyses of Breast Cancer Primaries and Matched Metastases in AURORA, the Breast International Group (BIG) Molecular Screening Initiative

AURORA aims to study the processes of relapse in metastatic breast cancer (MBC) by performing multi-omics profiling on paired primary tumors and early-course metastases. Among 381 patients (primary tumor and metastasis pairs: 252 targeted gene sequencing, 152 RNA sequencing, 67 single nucleotide polymorphism arrays), we found a driver role for GATA1 and MEN1 somatic mutations. Metastases were enriched in ESR1, PTEN, CDH1, PIK3CA, and RB1 mutations; MDM4 and MYC amplifications; and ARID1A deletions. An increase in clonality was observed in driver genes such as ERBB2 and RB1. Intrinsic subtype switching occurred in 36% of cases. Luminal A/B to HER2-enriched switching was associated with TP53 and/or PIK3CA mutations. Metastases had lower immune score and increased immune-permissive cells. High tumor mutational burden correlated to shorter time to relapse in HR+/HER2- cancers. ESCAT tier I/II alterations were detected in 51% of patients and matched therapy was used in 7%. Integration of multi-omics analyses in clinical practice could affect treatment strategies in MBC. SIGNIFICANCE: The AURORA program, through the genomic and transcriptomic analyses of matched primary and metastatic samples from 381 patients with breast cancer, coupled with prospectively collected clinical data, identified genomic alterations enriched in metastases and prognostic biomarkers. ESCAT tier I/II alterations were detected in more than half of the patients.This article is highlighted in the In This Issue feature, p. 2659.

Current and Emerging Molecular Therapies for Head and Neck Squamous Cell Carcinoma

Head and neck cancer affects nearly 750,000 patients, with more than 300,000 deaths annually. Advances in first line surgical treatment have improved survival rates marginally particularly in developed countries, however survival rates for aggressive locally advanced head and neck cancer are still poor. Recurrent and metastatic disease remains a significant problem for patients and the health system. As our knowledge of the genomic landscape of the head and neck cancers continues to expand, there are promising developments occurring in molecular therapies available for advanced or recalcitrant disease. The concept of precision medicine is underpinned by our ability to accurately sequence tumour samples to best understand individual patient genomic variations and to tailor targeted therapy for them based on such molecular profiling. Not only is their purported response to therapy a factor of their genomic variation, but so is their inclusion in biomarker-driven personalised medicine therapeutic trials. With the ever-expanding number of molecular druggable targets explored through advances in next generation sequencing, the number of clinical trials assessing these targets has significantly increased over recent years. Although some trials are focussed on first-line therapeutic approaches, a greater majority are focussed on locally advanced, recurrent or metastatic disease. Similarly, although single agent monotherapy has been found effective in some cases, it is the combination of drugs targeting different signalling pathways that seem to be more beneficial to patients. This paper outlines current and emerging molecular therapies for head and neck cancer, and updates readers on outcomes of the most pertinent clinical trials in this area while also summarising ongoing efforts to bring more molecular therapies into clinical practice.

Comprehensive Analysis of Ferroptosis-Related LncRNAs in Breast Cancer Patients Reveals Prognostic Value and Relationship With Tumor Immune Microenvironment

Background: Breast cancer (BC) is a heterogeneous malignant tumor, leading to the second major cause of female mortality. This study aimed to establish an in-depth relationship between ferroptosis-related LncRNA (FRlncRNA) and the prognosis as well as immune microenvironment of the patients with BC. Methods: We downloaded and integrated the gene expression data and the clinical information of the patients with BC from The Cancer Genome Atlas (TCGA) database. The co-expression network analysis and univariate Cox regression analysis were performed to screen out the FRlncRNAs related to prognosis. A cluster analysis was adopted to explore the difference of immune microenvironment between the clusters. Furthermore, we determined the optimal survival-related FRLncRNAs for final signature by LASSO Cox regression analysis. Afterward, we constructed and validated the prediction models, which were further tested in different subgroups. Results: A total of 31 FRLncRNAs were filtrated as prognostic biomarkers. Two clusters were determined, and C1 showed better prognosis and higher infiltration level of immune cells, such as B cells naive, plasma cells, T cells CD8, and T cells CD4 memory activated. However, there were no significantly different clinical characters between the clusters. Gene Set Enrichment Analysis (GSEA) revealed that some metabolism-related pathways and immune-associated pathways were exposed. In addition, 12 FRLncRNAs were determined by LASSO analysis and used to construct a prognostic signature. In both the training and testing sets, patients in the high-risk group had a worse survival than the low-risk patients. The area under the curves (AUCs) of receiver operator characteristic (ROC) curves were about 0.700, showing positive prognostic capacity. More notably, through the comprehensive analysis of heatmap, we regarded LINC01871, LINC02384, LIPE-AS1, and HSD11B1-AS1 as protective LncRNAs, while LINC00393, AC121247.2, AC010655.2, LINC01419, PTPRD-AS1, AC099329.2, OTUD6B-AS1, and LINC02266 were classified as risk LncRNAs. At the same time, the patients in the low-risk groups were more likely to be assigned to C1 and had a higher immune score, which were consistent with a better prognosis. Conclusion: Our research indicated that the ferroptosis-related prognostic signature could be used as novel biomarkers for predicting the prognosis of BC. The differences in the immune microenvironment exhibited by BC patients with different risks and clusters suggested that there may be a complementary synergistic effect between ferroptosis and immunotherapy.

The Role of Emerin in Cancer Progression and Metastasis

It is commonly recognized in the field that cancer cells exhibit changes in the size and shape of their nuclei. These features often serve as important biomarkers in the diagnosis and prognosis of cancer patients. Nuclear size can significantly impact cell migration due to its incredibly large size. Nuclear structural changes are predicted to regulate cancer cell migration. Nuclear abnormalities are common across a vast spectrum of cancer types, regardless of tissue source, mutational spectrum, and signaling dependencies. The pervasiveness of nuclear alterations suggests that changes in nuclear structure may be crucially linked to the transformation process. The factors driving these nuclear abnormalities, and the functional consequences, are not completely understood. Nuclear envelope proteins play an important role in regulating nuclear size and structure in cancer. Altered expression of nuclear lamina proteins, including emerin, is found in many cancers and this expression is correlated with better clinical outcomes. A model is emerging whereby emerin, as well as other nuclear lamina proteins, binding to the nucleoskeleton regulates the nuclear structure to impact metastasis. In this model, emerin and lamins play a central role in metastatic transformation, since decreased emerin expression during transformation causes the nuclear structural defects required for increased cell migration, intravasation, and extravasation. Herein, we discuss the cellular functions of nuclear lamina proteins, with a particular focus on emerin, and how these functions impact cancer progression and metastasis.

A protein network map of head and neck cancer reveals PIK3CA mutant drug sensitivity

[Figure: see text].

A protein interaction landscape of breast cancer

[Figure: see text].

Mutational signatures: emerging concepts, caveats and clinical applications

Whole-genome sequencing has brought the cancer genomics community into new territory. Thanks to the sheer power provided by the thousands of mutations present in each patient's cancer, we have been able to discern generic patterns of mutations, termed 'mutational signatures', that arise during tumorigenesis. These mutational signatures provide new insights into the causes of individual cancers, revealing both endogenous and exogenous factors that have influenced cancer development. This Review brings readers up to date in a field that is expanding in computational, experimental and clinical directions. We focus on recent conceptual advances, underscoring some of the caveats associated with using the mutational signature frameworks and highlighting the latest experimental insights. We conclude by bringing attention to areas that are likely to see advancements in clinical applications.

Diagnosis, biology and epidemiology of oligometastatic breast cancer

Does oligometastatic breast cancer (OMBC) deserve a dedicated treatment? Although some authors recommend multidisciplinary management of OMBC with a curative intent, there is no evidence proving this strategy beneficial in the absence of a randomized trial. The existing literature sheds little light on OMBC. Incidence is unknown; data available are either obsolete or biased; there is no consensus on the definition of OMBC and metastatic sites, nor on necessary imaging techniques. However, certain proposals merit consideration. Knowledge of eventual specific OMBC biological characteristics is limited to circulating tumor cell (CTC) counts. Given the data available for other cancers, studies on microRNAs (miRNAs), circulating tumor DNA (ctDNA) and genomic alterations should be developed Finally, safe and effective therapies do exist, but results of randomized trials will not be available for many years. Prospective observational cohort studies need to be implemented.

A Four-Gene-Based Risk Score With High Prognostic Value in Gastric Cancer

Background

Gastric adenocarcinoma is an important contributor to cancer mortality and morbidity. This study aimed to explore the prognostic value of mutation patterns in gastric adenocarcinoma.

Materials and Methods

We extracted somatic mutation data for 437 gastric adenocarcinoma samples from The Cancer Genome Atlas (TCGA) Stomach Adenocarcinoma (STAD) cohort. Kaplan-Meier survival in the R package maftools was used to analyze associations between mutations and survival. Multivariate Cox proportional model was used to establish risk formula. A four-gene-based risk score was developed to predict the overall survival of patients with gastric adenocarcinoma. We used the Tianjin cohort dataset with survival information to further evaluate the clinical value of this mutation signature.

Results

Forty-five survival-related mutated genes were identified and verified, most of which were co-occurring in their mutation pattern and co-occurring with MLH3 and polymerase ϵ (POLE) mutations. Gastric adenocarcinoma samples with the 45 mutated genes had a significantly higher mutation count. Four-gene [UTRN, MUC16, coiled-coil domain-containing protein 178 (CCDC178), and HYDIN] mutation status was used to build a prognostic risk score that could be translated into the clinical setting. The association between the four-gene-based signature and overall survival remained statistically significant after controlling for age, sex, TNM stage, and POLE mutation status in the multivariate model [hazard ratio (HR), 1.88; 95% CI, 1.33-2.7; p < 0.001]. The prognostic significance of the four-gene-based risk score identified in TCGA cohort was validated in the Tianjin cohort.

Conclusion

A four-mutated gene risk formula was developed that correlated with the overall survival of patients with gastric adenocarcinoma using a multivariable Cox regression model. In two independent genomic datasets from TCGA and Tianjin cohorts, low risk scores were associated with higher tumor mutation loads and improved outcome in patients with gastric adenocarcinoma. This finding may have implications for prognostic prediction and therapeutic guidance for gastric adenocarcinoma.

RNA-binding proteins of COSMIC importance in cancer

Herculean efforts by the Wellcome Sanger Institute, the National Cancer Institute, and the National Human Genome Research Institute to sequence thousands of tumors representing all major cancer types have yielded more than 700 genes that contribute to neoplastic growth when mutated, amplified, or deleted. While some of these genes (now included in the COSMIC Cancer Gene Census) encode proteins previously identified in hypothesis-driven experiments (oncogenic transcription factors, protein kinases, etc.), additional classes of cancer drivers have emerged, perhaps none more surprisingly than RNA-binding proteins (RBPs). Over 40 RBPs responsible for virtually all aspects of RNA metabolism, from synthesis to degradation, are recurrently mutated in cancer, and just over a dozen are considered major cancer drivers. This Review investigates whether and how their RNA-binding activities pertain to their oncogenic functions. Focusing on several well-characterized steps in RNA metabolism, we demonstrate that for virtually all cancer-driving RBPs, RNA processing activities are either abolished (the loss-of-function phenotype) or carried out with low fidelity (the LoFi phenotype). Conceptually, this suggests that in normal cells, RBPs act as gatekeepers maintaining proper RNA metabolism and the "balanced" proteome. From the practical standpoint, at least some LoFi phenotypes create therapeutic vulnerabilities, which are beginning to be exploited in the clinic.

NCOR1 Sustains Colorectal Cancer Cell Growth and Protects against Cellular Senescence

Simple Summary

NCOR1 is a scaffold protein that interacts with multiple partners to repress gene transcription. NCOR1 controls immunometabolic functions in several tissues and has been recently shown to protect against experimental colitis in mice. Our laboratory has observed a pro-proliferative role of NCOR1 in normal intestinal epithelial cells. However, it is unclear whether NCOR1 is functionally involved in colon cancer. This study demonstrated that NCOR1 is required for colorectal cancer cell growth. Depletion of NCOR1 caused these cells to become senescent. Transcriptomic signatures confirmed these observations but also predicted the potential for these cells to become pro-invasive. Thus, NCOR1 plays a novel role in preventing cancer-associated senescence and could represent a target for controlling colon cancer progression.

Abstract

NCOR1 is a corepressor that mediates transcriptional repression through its association with nuclear receptors and specific transcription factors. Some evidence supports a role for NCOR1 in neonatal intestinal epithelium maturation and the maintenance of epithelial integrity during experimental colitis in mice. We hypothesized that NCOR1 could control colorectal cancer cell proliferation and tumorigenicity. Conditional intestinal epithelial deletion of Ncor1 in Apc^Min/+ mice resulted in a significant reduction in polyposis. RNAi targeting of NCOR1 in Caco-2/15 and HT-29 cell lines led to a reduction in cell growth, characterized by cellular senescence associated with a secretory phenotype. Tumor growth of HT-29 cells was reduced in the absence of NCOR1 in the mouse xenografts. RNA-seq transcriptome profiling of colon cancer cells confirmed the senescence phenotype in the absence of NCOR1 and predicted the occurrence of a pro-migration cellular signature in this context. SOX2, a transcription factor essential for pluripotency of embryonic stem cells, was induced under these conditions. In conclusion, depletion of NCOR1 reduced intestinal polyposis in mice and caused growth arrest, leading to senescence in human colorectal cell lines. The acquisition of a pro-metastasis signature in the absence of NCOR1 could indicate long-term potential adverse consequences of colon-cancer-induced senescence.

Enhancement of E-cadherin expression and processing and driving of cancer cell metastasis by ARID1A deficiency

The ARID1A gene, which encodes a subunit of the SWI/SNF chromatin remodeling complex, has been found to be frequently mutated in many human cancer types. However, the function and mechanism of ARID1A in cancer metastasis are still unclear. Here, we show that knockdown of ARID1A increases the ability of breast cancer cells to proliferate, migrate, invade, and metastasize in vivo. The ARID1A-related SWI/SNF complex binds to the second exon of CDH1 and negatively modulates the expression of E-cadherin/CDH1 by recruiting the transcriptional repressor ZEB2 to the CDH1 promoter and excluding the presence of RNA polymerase II. The silencing of CDH1 attenuated the migration, invasion, and metastasis of breast cancer cells in which ARID1A was silenced. ARID1A depletion increased the intracellular enzymatic processing of E-cadherin and the production of C-terminal fragment 2 (CTF2) of E-cadherin, which stabilized β-catenin by competing for binding to the phosphorylation and degradation complex of β-catenin. The matrix metalloproteinase inhibitor GM6001 inhibited the production of CTF2. In zebrafish and nude mice, ARID1A silencing or CTF2 overexpression activated β-catenin signaling and promoted migration/invasion and metastasis of cancer cells in vivo. The inhibitors GM6001, BB94, and ICG-001 suppressed the migration and invasion of cancer cells with ARID1A-deficiency. Our findings provide novel insights into the mechanism of ARID1A metastasis and offer a scientific basis for targeted therapy of ARID1A-deficient cancer cells.

p27Kip1, an Intrinsically Unstructured Protein with Scaffold Properties

The Cyclin-dependent kinase (CDK) regulator p27^Kip1 is a gatekeeper of G1/S transition. It also regulates G2/M progression and cytokinesis completion, via CDK-dependent or -independent mechanisms. Recently, other important p27^Kip1 functions have been described, including the regulation of cell motility and migration, the control of cell differentiation program and the activation of apoptosis/autophagy. Several factors modulate p27^Kip1 activities, including its level, cellular localization and post-translational modifications. As a matter of fact, the protein is phosphorylated, ubiquitinated, SUMOylated, O-linked N-acetylglicosylated and acetylated on different residues. p27^Kip1 belongs to the family of the intrinsically unstructured proteins and thus it is endowed with a large flexibility and numerous interactors, only partially identified. In this review, we look at p27^Kip1 properties and ascribe part of its heterogeneous functions to the ability to act as an anchor or scaffold capable to participate in the construction of different platforms for modulating cell response to extracellular signals and allowing adaptation to environmental changes.

Cohesin mutations in myeloid malignancies

Cohesin is a multisubunit protein complex that forms a ring-like structure around DNA. It is essential for sister chromatid cohesion, chromatin organization, transcriptional regulation, and DNA damage repair and plays a major role in dynamically shaping the genome architecture and maintaining DNA integrity. The core complex subunits STAG2, RAD21, SMC1, and SMC3, as well as its modulators PDS5A/B, WAPL, and NIPBL, have been found to be recurrently mutated in hematologic and solid malignancies. These mutations are found across the full spectrum of myeloid neoplasia, including pediatric Down syndrome-associated acute megakaryoblastic leukemia, myelodysplastic syndromes, chronic myelomonocytic leukemia, and de novo and secondary acute myeloid leukemias. The mechanisms by which cohesin mutations act as drivers of clonal expansion and disease progression are still poorly understood. Recent studies have described the impact of cohesin alterations on self-renewal and differentiation of hematopoietic stem and progenitor cells, which are associated with changes in chromatin and epigenetic state directing lineage commitment, as well as genomic integrity. Herein, we review the role of the cohesin complex in healthy and malignant hematopoiesis. We discuss clinical implications of cohesin mutations in myeloid malignancies and discuss opportunities for therapeutic targeting.

NCAPG promotes the progression of lung adenocarcinoma via the TGF-β signaling pathway

Background

Lung cancer has the highest case fatality rate among cancers because of uncontrolled proliferation and early metastasis of cancer cells in the lung tissue. This study aimed to clarify the role of the non-SMC condensin I complex, subunit G (NCAPG) in lung adenocarcinoma (LUAD), explore the mechanisms of its progression, and lay the foundation for the search for new biological markers.

Methods

We analyzed overlapping differentially expressed genes (DEGs) from three datasets; a protein–protein interaction (PPI) network was subsequently constructed and analyzed using Cytoscape. We then selected NCAPG for validation because of its poor prognosis and because it has not been sufficiently studied in the context of LUAD. Immunohistochemical analysis was used to detect the expression of NCAPG in LUAD tissues, and the relationships between NCAPG and clinical parameters were analyzed. In vitro and in vivo experiments were conducted to verify the role of NCAPG in LUAD. Finally, we studied the specific mechanism of action of NCAPG in LUAD.

Results

Through comprehensive analysis of the GSE43458, GSE75037, and The Cancer Genome Atlas databases, we identified 517 overlapping DEGs. Among them, NCAPG was identified as a hub gene. Immunohistochemical analysis revealed that NCAPG was strongly associated with the clinical stage, M-classification, and N-classification. Univariate and multivariate Cox regression analyses indicated that NCAPG was a prognostic risk factor for LUAD, while the in vitro experiments showed that NCAPG overexpression promoted proliferation, migration, invasion, and epithelial-mesenchymal transition. Furthermore, knockdown of NCAPG inhibited LUAD progression, both in vitro and in vivo. Mechanistically, NCAPG overexpression increased p-Smad2 and p-Smad3 expressions in the transforming growth factor β (TGF-β) signaling pathway. Additionally, rescue experiments indicated that TGF-β signaling pathway inhibitors could restore the effect of NCAPG overexpression in LUAD cells.

Conclusions

NCAPG may promote proliferation and migration via the TGF-β signaling pathway in LUAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02138-w.

Frame-shifted APOBEC3A encodes two alternative proapoptotic proteins that target the mitochondrial network

The human APOBEC3A (A3A) cytidine deaminase is a powerful DNA mutator enzyme recognized as a major source of somatic mutations in tumor cell genomes. However, there is a discrepancy between APOBEC3A mRNA levels after interferon stimulation in myeloid cells and A3A detection at the protein level. To understand this difference, we investigated the expression of two novel alternative “A3Alt” proteins encoded in the +1-shifted reading frame of the APOBEC3A gene. A3Alt-L and its shorter isoform A3Alt-S appear to be transmembrane proteins targeted to the mitochondrial compartment that induce membrane depolarization and apoptosis. Thus, the APOBEC3A gene represents a new example wherein a single gene encodes two proapoptotic proteins, A3A cytidine deaminases that target the genome and A3Alt proteins that target mitochondria.

Genomic landscape and tumor mutation burden analysis of Chinese patients with sarcomatoid carcinoma of the head and neck

BACKGROUND

Sarcomatoid carcinoma (SC) of the head and neck (HN) is a rare disease that has both sarcomatoid and cancerous components. The genetic background and mechanisms of tumorigenesis remain largely unrevealed, and the progress of precision therapy has been limited.

METHODS

Targeted DNA-based next-generation sequencing (NGS) was performed by a 539 genes panel of pan-cancer in 12 patients with SC of the HN to identify their genetic alterations and investigate clinically actionable mutations for use in precision treatment.

RESULTS

TP53 was identified as the most frequently mutated gene. Genes related to the cell cycling, chromatin remodeling and histone modification were found to be frequently mutated in patients with SC of the HN. Alterations in receptor tyrosine kinases (RTKs) were also found in six patients. In addition, four patients had mutations in members of the downstream RAS and PI3-kinase pathways, PIK3CA was identified as the most frequently mutated gene in this pathway. The tumor mutation burden (TMB) value ranged from 0.71 to 14.71 per megabase, with a median of 4.34. The TMB value of PIK3CA mutation patients was significantly higher than that of PIK3CA wild-type patients.

CONCLUSIONS

This was the first study to investigate genomic alterations specifically in Chinese patients with SC of the HN. Our research results showed that 10 out of 12 patients can match the targeted therapies or immunotherapy currently available in clinical practice or active clinical trials, suggesting precision therapy has the potential utility to improve the long-term prognosis for patients with the rare disease. Due to the small number of patients in this study, the findings need to be validated in a larger cohort.

A systematic view of computational methods for identifying driver genes based on somatic mutation data

Abnormal changes of driver genes are serious for human health and biomedical research. Identifying driver genes, exactly from enormous genes with mutations, promotes accurate diagnosis and treatment of cancer. A lot of works about uncovering driver genes have been developed over the past decades. By analyzing previous works, we find that computational methods are more efficient than traditional biological experiments when distinguishing driver genes from massive data. In this study, we summarize eight common computational algorithms only using somatic mutation data. We first group these methods into three categories according to mutation features they apply. Then, we conclude a general process of nominating candidate cancer driver genes. Finally, we evaluate three representative methods on 10 kinds of cancer derived from The Cancer Genome Atlas Program and five Chinese projects from the International Cancer Genome Consortium. In addition, we compare results of methods with various parameters. Evaluation is performed from four perspectives, including CGC, OG/TSG, Q-value and QQQuantile-Quantileplot. To sum up, we present algorithms using somatic mutation data in order to offer a systematic view of various mutation features and lay the foundation of methods based on integration of mutation information and other types of data.

rs73092672 allele T is significantly associated with the higher risk of breast cancer incidence

Breast cancer is the most common cancer in women worldwide with remarkable proportion of the patients in advanced stage. Recently the importance of genetic mutations in cancers are well established and also the role of tumor suppressor genes such as FHIT gene in both heritable and non-heritable cancer. MicroRNAs are a class of non-coding RNAs which can interfere with cellular regulation. In this study, the association of rs73092672 which is located within the FHIT gene and the 3'UTR of hsa-miR-509-5p with the susceptibility to breast cancer risk has been studied in the Iranian population. By using the PCR_RFLP, the genotype rs73092672 was determined in 90 patients and 100 control subjects. The genotypes of the individuals were analyzed statistically to find the association between rs73092672 and the breast cancer incidence. The results revealed that due to the dominance of the C allele, the frequency of CC + CT genotypes, as compared with TT, had a significant correlation with the incidence of this disease in controls and cases (p = 0.02; OR= 3.6). Moreover, Bioinformatics analysis suggests rs73092672 as a polymorphism in the 3'UTR of hsa-miR-509-5p with higher binding affinity in the presence of T allele than C allele.

Performance Comparisons of AlexNet and GoogLeNet in Cell Growth Inhibition IC50 Prediction

Drug responses in cancer are diverse due to heterogenous genomic profiles. Drug responsiveness prediction is important in clinical response to specific cancer treatments. Recently, multi-class drug responsiveness models based on deep learning (DL) models using molecular fingerprints and mutation statuses have emerged. However, for multi-class models for drug responsiveness prediction, comparisons between convolution neural network (CNN) models (e.g., AlexNet and GoogLeNet) have not been performed. Therefore, in this study, we compared the two CNN models, GoogLeNet and AlexNet, along with the least absolute shrinkage and selection operator (LASSO) model as a baseline model. We constructed the models by taking drug molecular fingerprints of drugs and cell line mutation statuses, as input, to predict high-, intermediate-, and low-class for half-maximal inhibitory concentration (IC50) values of the drugs in the cancer cell lines. Additionally, we compared the models in breast cancer patients as well as in an independent gastric cancer cell line drug responsiveness data. We measured the model performance based on the area under receiver operating characteristic (ROC) curves (AUROC) value. In this study, we compared CNN models for multi-class drug responsiveness prediction. The AlexNet and GoogLeNet showed better performances in comparison to LASSO. Thus, DL models will be useful tools for precision oncology in terms of drug responsiveness prediction.

miRNome and Functional Network Analysis of PGRMC1 Regulated miRNA Target Genes Identify Pathways and Biological Functions Associated With Triple Negative Breast Cancer

Background

Increased expression of the progesterone receptor membrane component 1, a heme and progesterone binding protein, is frequently found in triple negative breast cancer tissue. The basis for the expression of PGRMC1 and its regulation on cellular signaling mechanisms remain largely unknown. Therefore, we aim to study microRNAs that target selective genes and mechanisms that are regulated by PGRMC1 in TNBCs.

Methods

To identify altered miRNAs, whole human miRNome profiling was performed following AG-205 treatment and PGRMC1 silencing. Network analysis identified miRNA target genes while KEGG, REACTOME and Gene ontology were used to explore altered signaling pathways, biological processes, and molecular functions.

Results

KEGG term pathway analysis revealed that upregulated miRNAs target specific genes that are involved in signaling pathways that play a major role in carcinogenesis. While multiple downregulated miRNAs are known oncogenes and have been previously demonstrated to be overexpressed in a variety of cancers. Overlapping miRNA target genes associated with KEGG term pathways were identified and overexpression/amplification of these genes was observed in invasive breast carcinoma tissue from TCGA. Further, the top two genes (CCND1 and YWHAZ) which are highly genetically altered are also associated with poorer overall survival.

Conclusions

Thus, our data demonstrates that therapeutic targeting of PGRMC1 in aggressive breast cancers leads to the activation of miRNAs that target overexpressed genes and deactivation of miRNAs that have oncogenic potential.

Selective therapeutic strategy for p53-deficient cancer by targeting dysregulation in DNA repair

Breast carcinomas commonly carry mutations in the tumor suppressor p53, although therapeutic efforts to target mutant p53 have previously been unfruitful. Here we report a selective combination therapy strategy for treatment of p53 mutant cancers. Genomic data revealed that p53 mutant cancers exhibit high replication activity and express high levels of the Base-Excision Repair (BER) pathway, whereas experimental testing showed substantial dysregulation in BER. This defect rendered accumulation of DNA damage in p53 mutant cells upon treatment with deoxyuridine analogues. Notably, inhibition of poly (ADP-ribose) polymerase (PARP) greatly enhanced this response, whereas normal cells responded with activation of the p53-p21 axis and cell cycle arrest. Inactivation of either p53 or p21/CDKN1A conferred the p53 mutant phenotype. Preclinical animal studies demonstrated a greater anti-neoplastic efficacy of the drug combination (deoxyuridine analogue and PARP inhibitor) than either drug alone. This work illustrates a selective combination therapy strategy for p53 mutant cancers that will improve survival rates and outcomes for thousands of breast cancer patients.

Akt Isoforms: A Family Affair in Breast Cancer

Simple Summary

Breast cancer is the second leading cause of cancer-related death in women in the United States. The Akt signaling pathway is deregulated in approximately 70% of patients with breast cancer. While targeting Akt is an effective therapeutic strategy for the treatment of breast cancer, there are several members in the Akt family that play distinct roles in breast cancer. However, the function of Akt isoforms depends on many factors. This review analyzes current progress on the isoform-specific functions of Akt isoforms in breast cancer.

Abstract

Akt, also known as protein kinase B (PKB), belongs to the AGC family of protein kinases. It acts downstream of the phosphatidylinositol 3-kinase (PI3K) and regulates diverse cellular processes, including cell proliferation, cell survival, metabolism, tumor growth and metastasis. The PI3K/Akt signaling pathway is frequently deregulated in breast cancer and plays an important role in the development and progression of breast cancer. There are three closely related members in the Akt family, namely Akt1(PKBα), Akt2(PKBβ) and Akt3(PKBγ). Although Akt isoforms share similar structures, they exhibit redundant, distinct as well as opposite functions. While the Akt signaling pathway is an important target for cancer therapy, an understanding of the isoform-specific function of Akt is critical to effectively target this pathway. However, our perception regarding how Akt isoforms contribute to the genesis and progression of breast cancer changes as we gain new knowledge. The purpose of this review article is to analyze current literatures on distinct functions of Akt isoforms in breast cancer.

Uncovering the Subtype-Specific Molecular Characteristics of Breast Cancer by Multiomics Analysis of Prognosis-Associated Genes, Driver Genes, Signaling Pathways, and Immune Activity

Breast cancer is a heterogeneous malignant disease with different prognoses and has been divided into four molecular subtypes. It is believed that molecular events occurring in breast stem/progenitor cells contribute to the carcinogenesis and development of different breast cancer subtypes. However, these subtype-specific molecular characteristics are largely unknown. In this study, we employed 1217 breast cancer samples from The Cancer Genome Atlas (TCGA) database for a multiomics analysis of the molecular characteristics of different breast cancer subtypes based on PAM50 algorithms. We detected the expression changes of subtype-specific genes and revealed that the expression of particular subtype-specific genes significantly affected prognosis. We also investigated the mutations and copy number variations (CNVs) of breast cancer driver genes and the representative genes of ten signaling pathways in different subtypes and revealed several subtype-specifically altered genes. Moreover, we detected the infiltration of various immune cells in different subtypes of breast cancer and showed that the infiltration levels of major immune cell types are different among these subtypes. Additionally, we investigated the factors affecting the immune infiltration level and the immune cytolytic activity in different breast cancer subtypes, namely, the mutation burden, genome instability and cancer-associated fibroblast (CAF) infiltration. This study may shed light on the molecular events contributing to carcinogenesis and development and provide potential markers and targets for the clinical diagnosis and treatment of different breast cancer subtypes.

Porcine pancreatic ductal epithelial cells transformed with KRASG12D and SV40T are tumorigenic

We describe our initial studies in the development of an orthotopic, genetically defined, large animal model of pancreatic cancer. Primary pancreatic epithelial cells were isolated from pancreatic duct of domestic pigs. A transformed cell line was generated from these primary cells with oncogenic KRAS and SV40T. The transformed cell lines outperformed the primary and SV40T immortalized cells in terms of proliferation, population doubling time, soft agar growth, transwell migration and invasion. The transformed cell line grew tumors when injected subcutaneously in nude mice, forming glandular structures and staining for epithelial markers. Future work will include implantation studies of these tumorigenic porcine pancreatic cell lines into the pancreas of allogeneic and autologous pigs. The resultant large animal model of pancreatic cancer could be utilized for preclinical research on diagnostic, interventional, and therapeutic technologies.

Transcription Factors: The Fulcrum Between Cell Development and Carcinogenesis

Higher eukaryotic development is a complex and tightly regulated process, whereby transcription factors (TFs) play a key role in controlling the gene regulatory networks. Dysregulation of these regulatory networks has also been associated with carcinogenesis. Transcription factors are key enablers of cancer stemness, which support the maintenance and function of cancer stem cells that are believed to act as seeds for cancer initiation, progression and metastasis, and treatment resistance. One key area of research is to understand how these factors interact and collaborate to define cellular fate during embryogenesis as well as during tumor development. This review focuses on understanding the role of TFs in cell development and cancer. The molecular mechanisms of cell fate decision are of key importance in efforts towards developing better protocols for directed differentiation of cells in research and medicine. We also discuss the dysregulation of TFs and their role in cancer progression and metastasis, exploring TF networks as direct or indirect targets for therapeutic intervention, as well as specific TFs’ potential as biomarkers for predicting and monitoring treatment responses.

Prevalence and Clinicopathological Characteristics of Moderate and High-Penetrance Genes in Non-BRCA1/2 Breast Cancer High-Risk Spanish Families

(1) Background: Over the last decade, genetic counseling clinics have moved from single-gene sequencing to multigene panel sequencing. Multiple genes related to a moderate risk of breast cancer (BC) have emerged, although many questions remain regarding the risks and clinical features associated with these genes. (2) Methods: Ninety-six BC index cases (ICs) with high-risk features for hereditary breast and ovarian cancer (HBOC) and with a previous uninformative result for BRCA1/2 were tested with a panel of 41 genes associated with BC risk. The frequency of pathogenic variants (PVs) was related to the clinical characteristics of BC. (3) Results: We detected a PV rate of 13.5% (excluding two cases each of BRCA1 and MUTYH). Among the 95 assessed cases, 17 PVs were identified in 16 ICs, as follows: BRCA1 (n = 2), CHEK2 (n = 3), ATM (n = 5), MUTYH (n = 2), TP53 (n = 2), BRIP1 (n = 1), CASP8 (n = 1), and MSH2 (n = 1). We also identified a novel loss-of-function variant in CASP8, a candidate gene for increased BC risk. There was no evidence that the clinical characteristics of BC might be related to a higher chance of identifying a PV. (4) Conclusions: In our cohort, which was enriched with families with a high number of BC cases, a high proportion of mutations in ATM and CHEK2 were identified. The clinical characteristics of BC associated with moderate-risk genes were different from those related to BRCA1/2 genes.

DIVIS: Integrated and Customizable Pipeline for Cancer Genome Sequencing Analysis and Interpretation

Next-generation sequencing (NGS) has drastically enhanced human cancer research, but diverse sequencing strategies, complicated open-source software, and the identification of massive numbers of mutations have limited the clinical application of NGS. Here, we first presented GPyFlow, a lightweight tool that flexibly customizes, executes, and shares workflows. We then introduced DIVIS, a customizable pipeline based on GPyFlow that integrates read preprocessing, alignment, variant detection, and annotation of whole-genome sequencing, whole-exome sequencing, and gene-panel sequencing. By default, DIVIS screens variants from multiple callers and generates a standard variant-detection format list containing caller evidence for each sample, which is compatible with advanced analyses. Lastly, DIVIS generates a statistical report, including command lines, parameters, quality-control indicators, and mutation summary. DIVIS substantially facilitates complex cancer genome sequencing analyses by means of a single powerful and easy-to-use command. The DIVIS code is freely available at https://github.com/niu-lab/DIVIS, and the docker image can be downloaded from https://hub.docker.com/repository/docker/sunshinerain/divis.

The temporal mutational and immune tumour microenvironment remodelling of HER2-negative primary breast cancers

The biology of breast cancer response to neoadjuvant therapy is underrepresented in the literature and provides a window-of-opportunity to explore the genomic and microenvironment modulation of tumours exposed to therapy. Here, we characterised the mutational, gene expression, pathway enrichment and tumour-infiltrating lymphocytes (TILs) dynamics across different timepoints of 35 HER2-negative primary breast cancer patients receiving neoadjuvant eribulin therapy (SOLTI-1007 NEOERIBULIN-NCT01669252). Whole-exome data (N = 88 samples) generated mutational profiles and candidate neoantigens and were analysed along with RNA-Nanostring 545-gene expression (N = 96 samples) and stromal TILs (N = 105 samples). Tumour mutation burden varied across patients at baseline but not across the sampling timepoints for each patient. Mutational signatures were not always conserved across tumours. There was a trend towards higher odds of response and less hazard to relapse when the percentage of subclonal mutations was low, suggesting that more homogenous tumours might have better responses to neoadjuvant therapy. Few driver mutations (5.1%) generated putative neoantigens. Mutation and neoantigen load were positively correlated (R2 = 0.94, p = <0.001); neoantigen load was weakly correlated with stromal TILs (R2 = 0.16, p = 0.02). An enrichment in pathways linked to immune infiltration and reduced programmed cell death expression were seen after 12 weeks of eribulin in good responders. VEGF was downregulated over time in the good responder group and FABP5, an inductor of epithelial mesenchymal transition (EMT), was upregulated in cases that recurred (p < 0.05). Mutational heterogeneity, subclonal architecture and the improvement of immune microenvironment along with remodelling of hypoxia and EMT may influence the response to neoadjuvant treatment.

Genomic, Transcriptomic, and Proteomic Profiling of Metastatic Breast Cancer

PURPOSE

Metastatic breast cancer (MBC) is not curable and there is a growing interest in personalized therapy options. Here we report molecular profiling of MBC focusing on molecular evolution in actionable alterations.

EXPERIMENTAL DESIGN

Sixty-two patients with MBC were included. An analysis of DNA, RNA, and functional proteomics was done, and matched primary and metastatic tumors were compared when feasible.

RESULTS

Targeted exome sequencing of 41 tumors identified common alterations in TP53 (21; 51%) and PIK3CA (20; 49%), as well as alterations in several emerging biomarkers such as NF1 mutations/deletions (6; 15%), PTEN mutations (4; 10%), and ARID1A mutations/deletions (6; 15%). Among 27 hormone receptor-positive patients, we identified MDM2 amplifications (3; 11%), FGFR1 amplifications (5; 19%), ATM mutations (2; 7%), and ESR1 mutations (4; 15%). In 10 patients with matched primary and metastatic tumors that underwent targeted exome sequencing, discordances in actionable alterations were common, including NF1 loss in 3 patients, loss of PIK3CA mutation in 1 patient, and acquired ESR1 mutations in 3 patients. RNA sequencing in matched samples confirmed loss of NF1 expression with genomic NF1 loss. Among 33 patients with matched primary and metastatic samples that underwent RNA profiling, 14 actionable genes were differentially expressed, including antibody-drug conjugate targets LIV-1 and B7-H3.

CONCLUSIONS

Molecular profiling in MBC reveals multiple common as well as less frequent but potentially actionable alterations. Genomic and transcriptional profiling demonstrates intertumoral heterogeneity and potential evolution of actionable targets with tumor progression. Further work is needed to optimize testing and integrated analysis for treatment selection.

Mutational profile of ZBTB16-RARA-positive acute myeloid leukemia

Background

The ZBTB16‐RARA fusion gene, resulting from the reciprocal translocation between ZBTB16 on chromosome 11 and RARA genes on chromosome 17 [t(11;17)(q23;q21)], is rarely observed in acute myeloid leukemia (AML), and accounts for about 1% of retinoic acid receptor‐α (RARA) rearrangements. AML with this rare translocation shows unusual bone marrow (BM) morphology, with intermediate aspects between acute promyelocytic leukemia (APL) and AML with maturation. Patients may have a high incidence of disseminated intravascular coagulation at diagnosis, are poorly responsive to all‐trans retinoic acid (ATRA) and arsenic tryoxyde, and are reported to have an overall poor prognosis.

Aims

The mutational profile of ZBTB16‐RARA rearranged AML has not been described so far.

Materials and methods

We performed targeted next‐generation sequencing of 24 myeloid genes in BM diagnostic samples from seven ZBTB16‐RARA+AML, 103 non‐RARA rearranged AML, and 46 APL. The seven ZBTB16‐RARA‐positive patients were then screened for additional mutations using whole exome sequencing (n = 3) or an extended cancer panel including 409 genes (n = 4).

Results

ZBTB16‐RARA+AML showed an intermediate number of mutations per patient and involvement of different genes, as compared to APL and other AMLs. In particular, we found a high incidence of ARID1A mutations in ZBTB16‐RARA+AML (five of seven cases, 71%). Mutations in ARID2 and SMARCA4, other tumor suppressor genes also belonging to SWI/SNF chromatin remodeling complexes, were also identified in one case (14%).

Discussion and conclusion

Our data suggest the association of mutations of the ARID1A gene and of the other members of the SWI/SNF chromatin remodeling complexes with ZBTB16‐RARA+AMLs, where they may support the peculiar disease phenotype.

Deep Large-Scale Multitask Learning Network for Gene Expression Inference

Gene expression profiling makes it possible to conduct many biological studies in a variety of fields due to its thorough characterization of cellular states under various experimental conditions. Despite recent advances in high-throughput technology, profiling an entire set of genomes is still difficult and expensive. Due to the high correlation between expression patterns of different genes, the aforementioned problem can be solved with a cost-effective approach that collects only a small subset of genes, called landmark genes, representing the entire set of genes, and infer the remaining genes, called target genes, using a computational model. There are several shallow and deep regression models in literature to estimate the expressions of target genes from the landmark genes. However, the shallow mostly have limited capacity in learning the nonlinear and complex gene expression data and are prone to underfitting, and the deep models generally do not take advantage of correlation among target genes in the learning process and suffer from overfitting. Considering the gene expression inference as a multitask learning problem, we propose a new deep multitask learning algorithm to tackle these issues. Our learning framework automatically learns the correlation between target genes and uses this knowledge to improve its generalization. Specifically, we utilize a subnetwork with low-dimensional latent variables to discover the relationships between target genes and enforce a seamless and easy to implement regularization to our deep regression model. Unlike the existing multitask learning methods that can only deal with dozens or hundreds of tasks, our algorithm is able to efficiently learn the relationships between ∼10,000 target genes and, thus, is scalable to a large number of tasks. Our proposed method outperforms the shallow and deep regression models for gene expression inference and alternative multitask learning algorithms on two large-scale datasets regardless of the network architecture.

Modeling clonal structure over narrow time frames via circulating tumor DNA in metastatic breast cancer

BACKGROUND

Circulating tumor DNA (ctDNA) offers minimally invasive means to repeatedly interrogate tumor genomes, providing opportunities to monitor clonal dynamics induced by metastasis and therapeutic selective pressures. In metastatic cancers, ctDNA profiling allows for simultaneous analysis of both local and distant sites of recurrence. Despite the promise of ctDNA sampling, its utility in real-time genetic monitoring remains largely unexplored.

METHODS

In this exploratory analysis, we characterize high-frequency ctDNA sample series collected over narrow time frames from seven patients with metastatic triple-negative breast cancer, each undergoing treatment with Cabozantinib, a multi-tyrosine kinase inhibitor (NCT01738438, https://clinicaltrials.gov/ct2/show/NCT01738438 ). Applying orthogonal whole exome sequencing, ultra-low pass whole genome sequencing, and 396-gene targeted panel sequencing, we analyzed 42 plasma-derived ctDNA libraries, representing 4-8 samples per patient with 6-42 days between samples. Integrating tumor fraction, copy number, and somatic variant information, we model tumor clonal dynamics, predict neoantigens, and evaluate consistency of genomic information from orthogonal assays.

RESULTS

We measured considerable variation in ctDNA tumor faction in each patient, often conflicting with RECIST imaging response metrics. In orthogonal sequencing, we found high concordance between targeted panel and whole exome sequencing in both variant detection and variant allele frequency estimation (specificity = 95.5%, VAF correlation, r = 0.949), Copy number remained generally stable, despite resolution limitations posed by low tumor fraction. Through modeling, we inferred and tracked distinct clonal populations specific to each patient and built phylogenetic trees revealing alterations in hallmark breast cancer drivers, including TP53, PIK3CA, CDK4, and PTEN. Our modeling revealed varied responses to therapy, with some individuals displaying stable clonal profiles, while others showed signs of substantial expansion or reduction in prevalence, with characteristic alterations of varied literature annotation in relation to the study drug. Finally, we predicted and tracked neoantigen-producing alterations across time, exposing translationally relevant detection patterns.

CONCLUSIONS

Despite technical challenges arising from low tumor content, metastatic ctDNA monitoring can aid our understanding of response and progression, while minimizing patient risk and discomfort. In this study, we demonstrate the potential for high-frequency monitoring of evolving genomic features, providing an important step toward scalable, translational genomics for clinical decision making.

Signatures of Discriminative Copy Number Aberrations in 31 Cancer Subtypes

Copy number aberrations (CNA) are one of the most important classes of genomic mutations related to oncogenetic effects. In the past three decades, a vast amount of CNA data has been generated by molecular-cytogenetic and genome sequencing based methods. While this data has been instrumental in the identification of cancer-related genes and promoted research into the relation between CNA and histo-pathologically defined cancer types, the heterogeneity of source data and derived CNV profiles pose great challenges for data integration and comparative analysis. Furthermore, a majority of existing studies have been focused on the association of CNA to pre-selected "driver" genes with limited application to rare drivers and other genomic elements. In this study, we developed a bioinformatics pipeline to integrate a collection of 44,988 high-quality CNA profiles of high diversity. Using a hybrid model of neural networks and attention algorithm, we generated the CNA signatures of 31 cancer subtypes, depicting the uniqueness of their respective CNA landscapes. Finally, we constructed a multi-label classifier to identify the cancer type and the organ of origin from copy number profiling data. The investigation of the signatures suggested common patterns, not only of physiologically related cancer types but also of clinico-pathologically distant cancer types such as different cancers originating from the neural crest. Further experiments of classification models confirmed the effectiveness of the signatures in distinguishing different cancer types and demonstrated their potential in tumor classification.

Making Sense of Genetic Information: The Promising Evolution of Clinical Stratification and Precision Oncology Using Machine Learning

Precision medicine is a medical approach to administer patients with a tailored dose of treatment by taking into consideration a person's variability in genes, environment, and lifestyles. The accumulation of omics big sequence data led to the development of various genetic databases on which clinical stratification of high-risk populations may be conducted. In addition, because cancers are generally caused by tumor-specific mutations, large-scale systematic identification of single nucleotide polymorphisms (SNPs) in various tumors has propelled significant progress of tailored treatments of tumors (i.e., precision oncology). Machine learning (ML), a subfield of artificial intelligence in which computers learn through experience, has a great potential to be used in precision oncology chiefly to help physicians make diagnostic decisions based on tumor images. A promising venue of ML in precision oncology is the integration of all available data from images to multi-omics big data for the holistic care of patients and high-risk healthy subjects. In this review, we provide a focused overview of precision oncology and ML with attention to breast cancer and glioma as well as the Bayesian networks that have the flexibility and the ability to work with incomplete information. We also introduce some state-of-the-art attempts to use and incorporate ML and genetic information in precision oncology.

The Context-Dependent Impact of Integrin-Associated CD151 and Other Tetraspanins on Cancer Development and Progression: A Class of Versatile Mediators of Cellular Function and Signaling, Tumorigenesis and Metastasis

Simple Summary

Tetraspanins are a family of molecules abundantly expressed on the surface of normal or tumor cells. They have been implicated in recruiting or sequestering key molecular regulators of malignancy of a variety of human cancers, including breast and lung cancers, glioblastoma and leukemia. Yet, how their actions take place remains mysterious due to a lack of traditional platform for molecular interactions. The current review digs into this mystery by examining findings from recent studies of multiple tetraspanins, particularly CD151. The molecular basis for differential impact of tetraspanins on tumor development, progression, and spreading to secondary sites is highlighted, and the complexity and plasticity of their control over tumor cell activities and interaction with their surroundings is discussed. Finally, an outlook is provided regarding tetraspanins as candidate biomarkers and targets for the diagnosis and treatment of human cancer.

Abstract

As a family of integral membrane proteins, tetraspanins have been functionally linked to a wide spectrum of human cancers, ranging from breast, colon, lung, ovarian, prostate, and skin carcinomas to glioblastoma. CD151 is one such prominent member of the tetraspanin family recently suggested to mediate tumor development, growth, and progression in oncogenic context- and cell lineage-dependent manners. In the current review, we summarize recent advances in mechanistic understanding of the function and signaling of integrin-associated CD151 and other tetraspanins in multiple cancer types. We also highlight emerging genetic and epigenetic evidence on the intrinsic links between tetraspanins, the epithelial-mesenchymal transition (EMT), cancer stem cells (CSCs), and the Wnt/β-catenin pathway, as well as the dynamics of exosome and cellular metabolism. Finally, we discuss the implications of the highly plastic nature and epigenetic susceptibility of CD151 expression, function, and signaling for clinical diagnosis and therapeutic intervention for human cancer.

Prognostic Value of the TP53 Mutation Location in Metastatic Breast Cancer as Detected by Next-Generation Sequencing

Purpose

The status of TP53 mutations was measured in cell-free DNA from patients with metastatic breast cancer (MBC) to investigate disease characteristics and the prognostic role of different locations of the TP53 mutation site.

Patients and Methods

Blood samples were taken from a total of 187 patients diagnosed with MBC who were treated at the Department of Breast Oncology, Peking University Cancer Hospital between January 2013 and March 2020. Next-generation sequencing was used to investigate the TP53 mutation spectra of circulating free DNA in these blood samples.

Results

Among the 187 MBC patients, TP53-mutated patients had a significantly shorter median disease-free survival (DFS) and overall survival (OS) compared with TP53 wild-type patients (P=0.001 and P=0.006, respectively). Additionally, in hormone receptor positive/HER2 negative (HR+/HER2-) and triple negative (TNBC) cohorts, TP53-mutated patients had a significantly shorter median DFS than TP53 wild-type patients (P=0.038 and P=0.023, respectively). The 79 patients with TP53 mutations carried 87 somatic TP53 mutations, of which most (77.0%) mapped to the DNA-binding domain (DBD) of the protein encoded by TP53 exons 5–8. In patients with TP53 mutations, those occurring in the non-DBD had a significantly shorter median DFS and OS than TP53 wild type (P<0.001 and P=0.001, respectively). Additionally, patients with non-missense mutations in the DBD had a significantly shorter median DFS and OS than TP53 wild-type patients (P=0.001 and P<0.001, respectively). TP53-mutated patients had a significantly shorter DFS than TP53 wild-type patients in the adjuvant endocrine therapy sensitive group (P=0.008), but differences in the endocrine therapy resistant group were not significant.

Conclusion

TP53-mutated MBC patients had a significantly worse outcome than TP53 wild-type patients especially those in HR+/HER2– and TNBC cohorts. Of TP53-mutated patients, those with non-missense mutations in the DBD had worse breast cancer-related survival. TP53 mutations were also associated with endocrine resistance.

6-lncRNA Assessment Model for Monitoring and Prognosis of HER2-Positive Breast Cancer: Based on Transcriptome Data

Background: In view of the high malignancy and poor prognosis of human epidermal growth factor receptor 2 (HER2)-positive breast cancer, we analyzed the RNA expression profiles of HER2-positive breast cancer samples to identify the new prognostic biomarkers.

Methods: The linear fitting method was used to identify the differentially expressed RNAs from the HER2-positive breast cancer RNA expression profiles in the Cancer Genome Atlas (TCGA). Then, a series of methods including univariate Cox, Kaplan-Meier, and random forests, were used to identify the core long non-coding RNAs (lncRNAs) with stable prognostic value for HER2-positive breast cancer. A clinical feature analysis was performed, and a competing endogenous RNA network was constructed to explore the role of these core lncRNAs in HER2-positive breast cancer. In addition, a functional analysis of differentially expressed messenger RNAs in HER-2 positive breast cancer also provided us with some enlightening insights.

Results: The high expression of four core lncRNAs (AC010595.1, AC046168.1, AC069277.1, and AP000904.1) was associated with worse overall survival, while the low expression of LINC00528 and MIR762HG was associated with worse overall survival. The 6-lncRNA model has an especially good predictive power for overall survival (p < 0.0001) and 3-year survival (the area under the curve = 0.980) in HER2-positive breast cancer patients.

Conclusion: This study provides a new efficient prognostic model and biomarkers of HER2-positive breast cancer. Meanwhile, it also provides a new perspective for elucidating the molecular mechanisms underlying HER2-positive breast cancer.

Chromatin Regulator SPEN/SHARP in X Inactivation and Disease

Simple Summary

Carcinogenesis is a multistep process involving not only the activation of oncogenes and disabling tumor suppressor genes, but also epigenetic modulation of gene expression. X chromosome inactivation (XCI) is a paradigm to study heterochromatin formation and maintenance. The double dosage of X chromosomal genes in female mammals is incompatible with early development. XCI is an excellent model system for understanding the establishment of facultative heterochromatin initiated by the expression of a 17,000 nt long non-coding RNA, known as Xinactivespecifictranscript (Xist), on the X chromosome. This review focuses on the molecular mechanisms of how epigenetic modulators act in a step-wise manner to establish facultative heterochromatin, and we put these in the context of cancer biology and disease. An in depth understanding of XCI will allow a better characterization of particular types of cancer and hopefully facilitate the development of novel epigenetic therapies.

Abstract

Enzymes, such as histone methyltransferases and demethylases, histone acetyltransferases and deacetylases, and DNA methyltransferases are known as epigenetic modifiers that are often implicated in tumorigenesis and disease. One of the best-studied chromatin-based mechanism is X chromosome inactivation (XCI), a process that establishes facultative heterochromatin on only one X chromosome in females and establishes the right dosage of gene expression. The specificity factor for this process is the long non-coding RNA Xinactivespecifictranscript (Xist), which is upregulated from one X chromosome in female cells. Subsequently, Xist is bound by the corepressor SHARP/SPEN, recruiting and/or activating histone deacetylases (HDACs), leading to the loss of active chromatin marks such as H3K27ac. In addition, polycomb complexes PRC1 and PRC2 establish wide-spread accumulation of H3K27me3 and H2AK119ub1 chromatin marks. The lack of active marks and establishment of repressive marks set the stage for DNA methyltransferases (DNMTs) to stably silence the X chromosome. Here, we will review the recent advances in understanding the molecular mechanisms of how heterochromatin formation is established and put this into the context of carcinogenesis and disease.

GATA3 as an Adjunct Prognostic Factor in Breast Cancer Patients with Less Aggressive Disease: A Study with a Review of the Literature

BACKGROUND

GATA binding protein 3 (GATA3) expression is positively correlated with estrogen receptor (ER) expression, but its prognostic value as an independent factor remains unclear. Thus, we undertook the current study to evaluate the expression of GATA3 and its prognostic value in a large series of breast carcinomas (BCs) with long-term follow-up.

METHODS

A total of 702 consecutive primary invasive BCs resected between 1989 and 1993 in our institution were arranged in tissue microarrays, immunostained for ER, progesterone receptor (PR), ki-67, HER2, p53, and GATA3, and scored. Clinico-pathological data were retrospectively collected.

RESULTS

GATA3 was evaluable in 608 (87%) of the 702 cases; it was positive in 413 (68%) cases and negative in 195 (32%) cases. GATA3 positivity was significantly associated with lower grade (p < 0.0001), size (p = 0.0463), stage (p = 0.0049), ER+ (p < 0.0001), PR+ (p < 0.0001), HER2- (p = 0.0175), and p53 wild-type pattern (p < 0.0001). The median follow-up was 183 months, GATA3 positivity was associated with better overall survival (HR 0.70, p = 0.001), and its prognostic value was retained in a multivariate analysis. The association with better overall survival was stronger in patients with grade 1-2, pT1-2, pN0, stage I-II, ER+, PR+, ki-67 < 20%, HER2-, a wild-type p53 immunohistochemical pattern, and in luminal B BC.

CONCLUSIONS

Our findings indicate that GATA3 is a positive prognostic marker in BC patients, especially in patients with biologically less aggressive BC. Incorporating GATA3 immunohistochemistry into routine practice could help further stratify BC patients for their risk.

Horizons in Veterinary Precision Oncology: Fundamentals of Cancer Genomics and Applications of Liquid Biopsy for the Detection, Characterization, and Management of Cancer in Dogs

Cancer is the leading cause of death in dogs, in part because many cases are identified at an advanced stage when clinical signs have developed, and prognosis is poor. Increased understanding of cancer as a disease of the genome has led to the introduction of liquid biopsy testing, allowing for detection of genomic alterations in cell-free DNA fragments in blood to facilitate earlier detection, characterization, and management of cancer through non-invasive means. Recent discoveries in the areas of genomics and oncology have provided a deeper understanding of the molecular origins and evolution of cancer, and of the "one health" similarities between humans and dogs that underlie the field of comparative oncology. These discoveries, combined with technological advances in DNA profiling, are shifting the paradigm for cancer diagnosis toward earlier detection with the goal of improving outcomes. Liquid biopsy testing has already revolutionized the way cancer is managed in human medicine - and it is poised to make a similar impact in veterinary medicine. Multiple clinical use cases for liquid biopsy are emerging, including screening, aid in diagnosis, targeted treatment selection, treatment response monitoring, minimal residual disease detection, and recurrence monitoring. This review article highlights key scientific advances in genomics and their relevance for veterinary oncology, with the goal of providing a foundational introduction to this important topic for veterinarians. As these technologies migrate from human medicine into veterinary medicine, improved awareness and understanding will facilitate their rapid adoption, for the benefit of veterinary patients.

Computational methods for cancer driver discovery: A survey

Identifying the genes responsible for driving cancer is of critical importance for directing treatment. Accordingly, multiple computational tools have been developed to facilitate this task. Due to the different methods employed by these tools, different data considered by the tools, and the rapidly evolving nature of the field, the selection of an appropriate tool for cancer driver discovery is not straightforward. This survey seeks to provide a comprehensive review of the different computational methods for discovering cancer drivers. We categorise the methods into three groups; methods for single driver identification, methods for driver module identification, and methods for identifying personalised cancer drivers. In addition to providing a “one-stop” reference of these methods, by evaluating and comparing their performance, we also provide readers the information about the different capabilities of the methods in identifying biologically significant cancer drivers. The biologically relevant information identified by these tools can be seen through the enrichment of discovered cancer drivers in GO biological processes and KEGG pathways and through our identification of a small cancer-driver cohort that is capable of stratifying patient survival.

Comparison of tumor microenvironment in primary and paired metastatic ER+/HER2- breast cancers: results of a pilot study

Background

Tumor microenvironment (TME) is a dynamic setting and changes in TILs and their subpopulations are potential candidates to influence the metastatic process. Aim of this pilot study is to describe the changes occurring between primary breast cancers and their paired metastases in terms of TILs composition. To assess if these changes influence the process of metastasis development, we used a control group of patients.

Methods

We retrospectively identified 18 Luminal patients, for whom primary and metastatic tissue were available (cases) and 18 paired-matched patients (controls), not relapsed after at least 9 years of follow-up, and we quantified TILs and their composition (i.e. T CD8+ and CD4+/FOXP3+). The presence of TILs was defined as ≥10%.

Results

Our results showed that the microenvironment composition of relapsed patients was poor of TILs (median = 5%, I-III quartiles = 0.6–5%), CD8+ (2.5%, 0–5%) and CD4+/FOXP3 + (0%, 0–0.6%) in the primary tumor. Comparable results were observed in their related metastases (TILs 3.8%, 0.6–5%; CD8+ 0%, 0–1.3%; CD4+/FOXP3+ 0%,0–1.9%). On the contrary, the microenvironment in the control group was richer of TILs (5%, 5–17.5%) in comparison to cases, both in primary tumor (p = 0.035) and related metastases (p = 0.018). Although CD8+ in controls were similar to cases at primary tumor (p = 0.6498), but not at metastasis (p = 0.0223), they expressed only one part on the TILs subpopulations (p = 0.0060), while TILs in the cases at primary tumor were almost completely CD8+ (p = 0.5034).

Conclusions

These findings suggest that the lack of activation of immune system in the primary tumor might influence the multifactor process of cancer progression.