Synaptonemal complex proteins modulate the level of genome integrity in cancers

Identification of potential prognostic biomarkers in vulval squamous cell carcinoma based on human papillomavirus infection Status-Analysis of GSE183454

This study aimed to elucidate the differences in vulval squamous cell carcinomas (VSCC) based on the HPV infection status. The sequencing data GSE183454 which contains 23 VSCC samples based on its HPV infection status was obtained from the Gene Expression Omnibus (GEO) database. We comprehensively dissected the differences of genomic and tumour microenvironment (TME) immune cell infiltration landscapes between HPV + and HPV- VSCC. The potential molecular mechanisms of prognostic genes were explored by functional enrichment analysis. Five novel key molecules (SYCP2, SMC1B, RNF212, MAJIN and C14orf39) with significantly up-regulated expression in HPV + VSCC were identified while protein-protein interaction (PPI) networks were created upon Cytoscape software. Additionally, VSCC with up-regulated expression of these key molecules exhibited a significantly decreased TME immune cell infiltration. SYCP2 is overexpressed in HPV + VSCC and could be a candidate therapy target for further research.IMPACT STATEMENTWhat is already known on this subject? VSCC are characterised by two aetiological pathways. The former occurs in the background of lichen sclerosus, while the latter is related to HPV infection. VSCC most commonly arises from the non-HPV related pathway portends worse prognosis than VSCC derived from HPV infection.What do the results of this study add? Five key molecules are identified and significantly up-regulated in HPV + VSCC. In which, SYCP2 is overexpressed in HPV + VSCC and exhibited a significantly decreased TME immune cell infiltration. SYCP2 constant expression could be a potential biomarker of neoplasms associated with HPV and could be a candidate therapy target in VSCC especially HPV + VSCC for further research.What are the implications of these findings for clinical practice and/or further research? SYCP2 could be a candidate therapy target in VSCC especially with HPV + for further research.

Tensor Decomposition-based Feature Extraction and Classification to Detect Natural Selection from Genomic Data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under nonconvex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data although preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx, which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

Immunological modifications following chemotherapy are associated with delayed recurrence of ovarian cancer

Introduction

Ovarian cancer recurs in most High Grade Serous Ovarian Cancer (HGSOC) patients, including initial responders, after standard of care. To improve patient survival, we need to identify and understand the factors contributing to early or late recurrence and therapeutically target these mechanisms. We hypothesized that in HGSOC, the response to chemotherapy is associated with a specific gene expression signature determined by the tumor microenvironment. In this study, we sought to determine the differences in gene expression and the tumor immune microenvironment between patients who show early recurrence (within 6 months) compared to those who show late recurrence following chemotherapy.

Methods

Paired tumor samples were obtained before and after Carboplatin and Taxol chemotherapy from 24 patients with HGSOC. Bioinformatic transcriptomic analysis was performed on the tumor samples to determine the gene expression signature associated with differences in recurrence pattern. Gene Ontology and Pathway analysis was performed using AdvaitaBio's iPathwayGuide software. Tumor immune cell fractions were imputed using CIBERSORTx. Results were compared between late recurrence and early recurrence patients, and between paired pre-chemotherapy and post-chemotherapy samples.

Results

There was no statistically significant difference between early recurrence or late recurrence ovarian tumors pre-chemotherapy. However, chemotherapy induced significant immunological changes in tumors from late recurrence patients but had no impact on tumors from early recurrence patients. The key immunological change induced by chemotherapy in late recurrence patients was the reversal of pro-tumor immune signature.

Discussion

We report for the first time, the association between immunological modifications in response to chemotherapy and the time of recurrence. Our findings provide novel opportunities to ultimately improve ovarian cancer patient survival.

Synaptonemal Complex in Human Biology and Disease

The synaptonemal complex (SC) is a meiosis-specific multiprotein complex that forms between homologous chromosomes during prophase of meiosis I. Upon assembly, the SC mediates the synapses of the homologous chromosomes, leading to the formation of bivalents, and physically supports the formation of programmed double-strand breaks (DSBs) and their subsequent repair and maturation into crossovers (COs), which are essential for genome haploidization. Defects in the assembly of the SC or in the function of the associated meiotic recombination machinery can lead to meiotic arrest and human infertility. The majority of proteins and complexes involved in these processes are exclusively expressed during meiosis or harbor meiosis-specific subunits, although some have dual functions in somatic DNA repair and meiosis. Consistent with their functions, aberrant expression and malfunctioning of these genes have been associated with cancer development. In this review, we focus on the significance of the SC and their meiotic-associated proteins in human fertility, as well as how human genetic variants encoding for these proteins affect the meiotic process and contribute to infertility and cancer development.

Tensor decomposition based feature extraction and classification to detect natural selection from genomic data

Inferences of adaptive events are important for learning about traits, such as human digestion of lactose after infancy and the rapid spread of viral variants. Early efforts toward identifying footprints of natural selection from genomic data involved development of summary statistic and likelihood methods. However, such techniques are grounded in simple patterns or theoretical models that limit the complexity of settings they can explore. Due to the renaissance in artificial intelligence, machine learning methods have taken center stage in recent efforts to detect natural selection, with strategies such as convolutional neural networks applied to images of haplotypes. Yet, limitations of such techniques include estimation of large numbers of model parameters under non-convex settings and feature identification without regard to location within an image. An alternative approach is to use tensor decomposition to extract features from multidimensional data while preserving the latent structure of the data, and to feed these features to machine learning models. Here, we adopt this framework and present a novel approach termed T-REx , which extracts features from images of haplotypes across sampled individuals using tensor decomposition, and then makes predictions from these features using classical machine learning methods. As a proof of concept, we explore the performance of T-REx on simulated neutral and selective sweep scenarios and find that it has high power and accuracy to discriminate sweeps from neutrality, robustness to common technical hurdles, and easy visualization of feature importance. Therefore, T-REx is a powerful addition to the toolkit for detecting adaptive processes from genomic data.

The pan-cancer landscape of abnormal DNA methylation and intratumor microorganisms

Microorganisms play very important roles in carcinogenesis, tumor progression, and resistance upon treatment. Due to the challenge of accurately acquiring samples and quantifying low-biomass tissue microorganisms, most studies have focused on the effect of gut microorganisms on cancer treatments, especially the efficacy of immunotherapy. Although recent publications reveal the potential interactions between intratumor microorganisms and the immune microenvironment, whether and to what extent the intratumor microorganism could affect progression and treatment outcome remain controversial. This study is aiming to evaluate the associations among intratumor microorganisms, DNA methylation cancer driver genes, immune response, and clinical outcomes from a pan-cancer perspective, using 6,876 TCGA samples across 21 cancer types. We revealed that tumor microorganism dysbiosis is closely associated with the abnormal tumor methylome and/or tumor microenvironment, which might serve to enhance the proliferation ability and fitness for the therapy of tumors. These findings shed the light on a better understanding of the interactions between tumor cells and carcinogens during and after tumor formation, as well as microorganism-associated methylation alterations that could further serve as biomarkers for clinical outcome assessment.

Coiled-coil structure of meiosis protein TEX12 and conformational regulation by its C-terminal tip

Meiosis protein TEX12 is an essential component of the synaptonemal complex (SC), which mediates homologous chromosome synapsis. It is also recruited to centrosomes in meiosis, and aberrantly in certain cancers, leading to centrosome dysfunction. Within the SC, TEX12 forms an intertwined complex with SYCE2 that undergoes fibrous assembly, driven by TEX12’s C-terminal tip. However, we hitherto lack structural information regarding SYCE2-independent functions of TEX12. Here, we report X-ray crystal structures of TEX12 mutants in three distinct conformations, and utilise solution light and X-ray scattering to determine its wild-type dimeric four-helical coiled-coil structure. TEX12 undergoes conformational change upon C-terminal tip mutations, indicating that the sequence responsible for driving SYCE2-TEX12 assembly within the SC also controls the oligomeric state and conformation of isolated TEX12. Our findings provide the structural basis for SYCE2-independent roles of TEX12, including the possible regulation of SC assembly, and its known functions in meiotic centrosomes and cancer.

The X-ray crystal structures of C-terminal mutants of the coiled-coil protein cancer testis antigen TEX12 in combination with modeling of the TEX12 wild-type dimer reveal the protein’s control of its oligomeric state, which resembles assembly of its complex with synaptonemal complex central element protein SYCE2.

Cancer and meiotic gene expression: Two sides of the same coin?

Meiosis increases genetic diversity in offspring by generating genetically unique haploid gametes with reshuffled chromosomes. This process requires a specialized set of meiotic proteins, which facilitate chromosome recombination and segregation. However, re-expression of meiotic proteins in mitosis can have catastrophic oncogenic consequences and aberrant expression of meiotic proteins is a common occurrence in human tumors. Mechanistically, re-activation of meiotic genes in cancer promotes oncogenesis likely because cancers-conversely to healthy mitosis-are fueled by genetic instability which promotes tumor evolution, and evasion of immune response and treatment pressure. In this review, we explore similarities between meiotic and cancer cells with a particular focus on the oncogenic activation of meiotic genes in cancer. We emphasize the role of histones and their modifications, DNA methylation, genome organization, R-loops and the availability of distal enhancers.

Checkpoint control in meiotic prophase: Idiosyncratic demands require unique characteristics

Chromosomal transactions such as replication, recombination and segregation are monitored by cell cycle checkpoint cascades. These checkpoints ensure the proper execution of processes that are needed for faithful genome inheritance from one cell to the next, and across generations. In meiotic prophase, a specialized checkpoint monitors defining events of meiosis: programmed DNA break formation, followed by dedicated repair through recombination based on interhomolog (IH) crossovers. This checkpoint shares molecular characteristics with canonical DNA damage checkpoints active during somatic cell cycles. However, idiosyncratic requirements of meiotic prophase have introduced unique features in this signaling cascade. In this review, we discuss the unique features of the meiotic prophase checkpoint. While being related to canonical DNA damage checkpoint cascades, the meiotic prophase checkpoint also shows similarities with the spindle assembly checkpoint (SAC) that guards chromosome segregation. We highlight these emerging similarities in the signaling logic of the checkpoints that govern meiotic prophase and chromosome segregation, and how thinking of these similarities can help us better understand meiotic prophase control. We also discuss work showing that, when aberrantly expressed, components of the meiotic prophase checkpoint might alter DNA repair fidelity and chromosome segregation in cancer cells. Considering checkpoint function in light of demands imposed by the special characteristics of meiotic prophase helps us understand checkpoint integration into the meiotic cell cycle machinery.

Meiotic chromosome organization and its role in recombination and cancer

Chromosomes adopt specific conformations to regulate various cellular processes. A well-documented chromosome configuration is the highly compacted chromosome structure during metaphase. More regional chromatin conformations have also been reported, including topologically associated domains encompassing mega-bases of DNA and local chromatin loops formed by kilo-bases of DNA. In this review, we discuss the changes in chromatin conformation taking place between somatic and meiotic cells, with a special focus on the establishment of a proteinaceous structure, called the chromosome axis, at the beginning of meiosis. The chromosome axis is essential to support key meiotic processes such as chromosome pairing, homologous recombination, and balanced chromosome segregation to transition from a diploid to a haploid stage. We review the role of the chromosome axis in meiotic chromatin organization and provide a detailed description of its protein composition. We also review the conserved and distinct roles between species of axis proteins in meiotic recombination, which is a major factor contributing to the creation of genetic diversity and genome evolution. Finally, we discuss situations where the chromosome axis is deregulated and evaluate the effects on genome integrity and the consequences from protein deregulation in meiocytes exposed to heat stress, and aberrant expression of genes encoding axis proteins in mammalian somatic cells associated with certain types of cancers.

Meiotic Genes and DNA Double Strand Break Repair in Cancer

Tumor cells show widespread genetic alterations that change the expression of genes driving tumor progression, including genes that maintain genomic integrity. In recent years, it has become clear that tumors frequently reactivate genes whose expression is typically restricted to germ cells. As germ cells have specialized pathways to facilitate the exchange of genetic information between homologous chromosomes, their aberrant regulation influences how cancer cells repair DNA double strand breaks (DSB). This drives genomic instability and affects the response of tumor cells to anticancer therapies. Since meiotic genes are usually transcriptionally repressed in somatic cells of healthy tissues, targeting aberrantly expressed meiotic genes may provide a unique opportunity to specifically kill cancer cells whilst sparing the non-transformed somatic cells. In this review, we highlight meiotic genes that have been reported to affect DSB repair in cancers derived from somatic cells. A better understanding of their mechanistic role in the context of homology-directed DNA repair in somatic cancers may provide useful insights to find novel vulnerabilities that can be targeted.

Role and Clinical Utility of Cancer/Testis Antigens in Head and Neck Squamous Cell Carcinoma

Cancer/testis (CT) antigens exhibit selective expression predominantly in immunoprivileged tissues in non-pathological contexts but are aberrantly expressed in diverse cancers. Due to their expression pattern, they have historically been attractive targets for immunotherapies. A growing number of studies implicate CT antigens in almost all hallmarks of cancer, suggesting that they may act as cancer drivers. CT antigens are expressed in head and neck squamous cell carcinomas. However, their role in the pathogenesis of these cancers remains poorly studied. Given that CT antigens hold intriguing potential as therapeutic targets and as biomarkers for prognosis and that they can provide novel insights into oncogenic mechanisms, their further study in the context of head and squamous cell carcinoma is warranted.

Prevalence of HPV in Mexican Patients with Head and Neck Squamous Carcinoma and Identification of Potential Prognostic Biomarkers

Simple Summary

Head and neck squamous cell carcinomas (HNSCC) are a heterogeneous group of neoplasms that show diverse clinical and biological characteristics associated with human papillomavirus (HPV). Biological and clinical characterization is essential to stratify patients based on prognostic and predictive factors. The biological features of HNSCC may change according to geography and population characteristics. Studies on the molecular biology of HNSCC in Mexico are scarce. In the present study, we analyzed 414 Mexican patients with HNSCC and determined the presence and genotype of HPV, p16 expression, and global gene expression profiles. Twenty-two percent of total cases were HPV+, and 32% were p16+. We identified genes associated with survival, such as SLIRP, KLF10, AREG, ACT1, and LIMA. In addition, CSF1R, MYC, and SRC genes were identified as potential therapeutic targets. This study offers information that may be relevant for our understanding of the biology of HNSCC and the development of therapeutic strategies.

Abstract

Head and neck squamous cell carcinomas (HNSCC) show a variety of biological and clinical characteristics that could depend on the association with the human papillomavirus (HPV). Biological and clinical characterization is essential to stratify patients based on prognostic and predictive factors. Reports on HNSCC are scarce in Mexico. Herein, we analyzed 414 Mexican patients with HNSCC, including oropharynx (OPSCC), larynx (LASCC), and oral cavity (OCSCC), and identified HPV DNA and p16 expression. Global gene expression profiles were analyzed in 25 HPV+/p16+ vs. HPV−/p16− cases. We found 32.3% p16+ and 22.3% HPV+ samples, HPV 16, 18, 39, 52, and 31 being the most frequent genotypes. For OPSCC, LASCC and OCSCC, 39.2, 14.7, and 9.6% were HPV+/p16+, respectively. High expression of SLIRP, KLF10, AREG, and LIMA was associated with poor survival; in contrast, high expression of MYB and SYCP2 correlated with better survival. In HPV+ cases, high expression of SLC25A39 and GJB2 was associated with poor survival. Likewise, EGFR, IL-1, IL-6, JAK-STAT, WNT, NOTCH, and ESR1 signaling pathways were downregulated in HPV+ cases. CSF1R, MYC, and SRC genes were identified as key hubs and therapeutic targets. Our study offers information regarding the molecular and clinical characteristics of HNSCC in Mexican patients.

Guardians of the Genome: BRCA2 and Its Partners

The tumor suppressor BRCA2 functions as a central caretaker of genome stability, and individuals who carry BRCA2 mutations are predisposed to breast, ovarian, and other cancers. Recent research advanced our mechanistic understanding of BRCA2 and its various interaction partners in DNA repair, DNA replication support, and DNA double-strand break repair pathway choice. In this review, we discuss the biochemical and structural properties of BRCA2 and examine how these fundamental properties contribute to DNA repair and replication fork stabilization in living cells. We highlight selected BRCA2 binding partners and discuss their role in BRCA2-mediated homologous recombination and fork protection. Improved mechanistic understanding of how BRCA2 functions in genome stability maintenance can enable experimental evidence-based evaluation of pathogenic BRCA2 mutations and BRCA2 pseudo-revertants to support targeted therapy.

Synaptonemal complex proteins modulate the level of genome integrity in cancers

The synaptonemal complex (SC) is a proteinaceous structure that is transiently formed during meiosis to promote homologous recombination between maternal and paternal chromosomes. As this structure is required only for meiotic recombination, the proteins constituting the complex are almost undetectable in normal somatic cells, but they can be expressed under the conditions in which the transcriptional machinery is deregulated. Accumulating evidence indicates that they are epigenetically expressed in cancers of various origin. Not surprisingly, in contrast to their meiotic roles, the somatic roles of the SC proteins remain to be investigated. However, it has recently been reported that SYCP3 and SYCE2 control DNA double‐strand break repair negatively and positively, respectively, suggesting that the ectopic expression of the SC proteins in somatic cells could be associated with the maintenance of genomic instability. Thus, it is highly likely that the investigation of the somatic roles of the SC proteins would improve our understanding of the mechanisms underlying tumor development.