Overexpression of centromeric proteins has been identified in a number of human malignancies, but the functional and mechanistic contributions of these proteins to disease progression have not been characterized. The centromeric histone H3 variant centromere protein A (CENPA) is an epigenetic mark that determines centromere identity. Here, using an array of approaches, including RNA-sequencing and ChIP-sequencing analyses, immunohistochemistry-based tissue microarrays, and various cell biology assays, we demonstrate that CENPA is highly overexpressed in prostate cancer in both tissue and cell lines and that the level of CENPA expression correlates with the disease stage in a large cohort of patients. Gain-of-function and loss-of-function experiments confirmed that CENPA promotes prostate cancer cell line growth. The results from the integrated sequencing experiments suggested a previously unidentified function of CENPA as a transcriptional regulator that modulates expression of critical proliferation, cell-cycle, and centromere/kinetochore genes. Taken together, our findings show that CENPA overexpression is crucial to prostate cancer growth.

Centromere defects in Systemic Sclerosis (SSc) have remained unexplored despite the fact that many centromere proteins were discovered in patients with SSc. Here we report that lesion skin fibroblasts from SSc patients show marked alterations in centromeric DNA. SSc fibroblasts also show DNA damage, abnormal chromosome segregation, aneuploidy (only in diffuse cutaneous (dcSSc)) and micronuclei (in all types of SSc), some of which lose centromere identity while retaining centromere DNA sequences. Strikingly, we find cytoplasmic “leaking” of centromere proteins in limited cutaneous SSc (lcSSc) fibroblasts. Cytoplasmic centromere proteins co-localize with antigen presenting MHC Class II molecules, which correlate precisely with the presence of anti-centromere antibodies. CENPA expression and micronuclei formation correlate highly with activation of the cGAS-STING/IFN-β pathway as well as markers of reactive oxygen species (ROS) and fibrosis, ultimately suggesting a link between centromere alterations, chromosome instability, SSc autoimmunity, and fibrosis.

Centromere genomics remain poorly characterized in cancer, due to technologic limitations in sequencing and bioinformatics methodologies that make high-resolution delineation of centromeric loci difficult to achieve. We here leverage a highly specific and targeted rapid PCR methodology to quantitatively assess the genomic landscape of centromeres in cancer cell lines and primary tissue. PCR-based profiling of centromeres revealed widespread heterogeneity of centromeric and pericentromeric sequences in cancer cells and tissues as compared to healthy counterparts. Quantitative reductions in centromeric core and pericentromeric markers (α-satellite units and HERV-K copies) were observed in neoplastic samples as compared to healthy counterparts. Subsequent phylogenetic analysis of a pericentromeric endogenous retrovirus amplified by PCR revealed possible gene conversion events occurring at numerous pericentromeric loci in the setting of malignancy. Our findings collectively represent a more comprehensive evaluation of centromere genetics in the setting of malignancy, providing valuable insight into the evolution and reshuffling of centromeric sequences in cancer development and progression.

Background: Approximately 8% of the human genome consists of sequences of retroviral origin, a result of ancestral infections of the germ line over millions of years of evolution. The most recent of these infections is attributed to members of the human endogenous retrovirus type-K (HERV-K) (HML-2) family. We recently reported that a previously undetected, large group of HERV-K (HML-2) proviruses, which are descendants of the ancestral K111 infection, are spread throughout human centromeres. Results: Studying the genomes of certain cell lines and the DNA of healthy individuals that seemingly lack K111, we discover new HERV-K (HML-2) members hidden in pericentromeres of several human chromosomes. All are related through a common ancestor, termed K222, which is a virus that infected the germ line approximately 25 million years ago. K222 exists as a single copy in the genomes of baboons and high order primates, but not New World monkeys, suggesting that progenitor K222 infected the primate germ line after the split between New and Old World monkeys. K222 exists in modern humans at multiple loci spread across the pericentromeres of nine chromosomes, indicating it was amplified during the evolution of modern humans. Conclusions: Copying of K222 may have occurred through recombination of the pericentromeres of different chromosomes during human evolution. Evidence of recombination between K111 and K222 suggests that these retroviral sequences have been templates for frequent cross-over events during the process of centromere recombination in humans.

Background: During the initial months of the COVID-19 pandemic, rapidly rising disease prevalence in the United States created a demand for patient-facing information exchanges that addressed questions and concerns about the disease. One approach to managing increased patient volumes during a pandemic involves the implementation of telephone-based triage systems. During a pandemic, telephone triage hotlines can be employed in innovative ways to conserve medical resources and offer useful population-level data about disease symptomatology and risk factor profiles. Objective: The aim of this study is to describe and evaluate the COVID-19 telephone triage hotline used by a large academic medical center in the midwestern United States. Methods: Michigan Medicine established a telephone hotline to triage inbound patient calls related to COVID-19. For calls received between March 24, 2020, and May 5, 2020, we described total call volume, data reported by callers including COVID-19 risk factors and symptomatology, and distribution of callers to triage algorithm endpoints. We also described symptomatology reported by callers who were directed to the institutional patient portal (online medical visit questionnaire). Results: A total of 3929 calls (average 91 calls per day) were received by the call center during the study period. The maximum total number of daily calls peaked at 211 on March 24, 2020. Call volumes were the highest from 6 AM to 11 AM and during evening hours. Callers were most often directed to the online patient portal (1654/3929, 42%), nursing hotlines (1338/3929, 34%), or employee health services (709/3929, 18%). Cough (126/370 of callers, 34%), shortness of breath (101/370, 27%), upper respiratory infection (28/111, 25%), and fever (89/370, 24%) were the most commonly reported symptoms. Immunocompromised state (23/370, 6%) and age >65 years (18/370, 5%) were the most commonly reported risk factors. Conclusions: The triage algorithm successfully diverted low-risk patients to suitable algorithm endpoints, while directing high-risk patients onward for immediate assessment. Data collected from hotline calls also enhanced knowledge of symptoms and risk factors that typified community members, demonstrating that pandemic hotlines can aid in the clinical characterization of novel diseases.

Sri Lanka is experiencing a rapid increase in the number of people with diabetes mellitus (DM) due to population growth and aging. Physician shortages, outdated technology, and insufficient health education have contributed to the difficulties associated with managing the burden of disease. New models of chronic disease management are needed to address the increasing prevalence of DM. Medical students, business students, and faculty members from the University of Michigan partnered with the Grace Girls’ Home, Trincomalee General Hospital, and Selvanayakapuram Central Hospital to identify and train diabetes-focused medical assistants (MAs) to collect and enter patient data and educate patients about their disease. Return visits to these MAs were encouraged so that patient progress and disease progression could be tracked longitudinally. Data entry was conducted through a cloud-based mechanism, facilitating patient management and descriptive characterization of the population. We implemented this pilot program in June 2016 in coordination with Trincomalee General Hospital and Selvanayakapuram Central Hospital. Over a 12-month period, 93 patients were systematically assessed by the medical assistants. All patients received education and were provided materials after the visit to better inform them about the importance of controlling their disease. Fifteen percent (14/93) of patients returned for follow-up consultation. Trained MAs have the potential to provide support to physicians working in congested health systems in low-resource settings. Public investment in training programs for MAs and greater acceptance by physicians and patients will be essential for handling the growing burden associated with chronic illnesses like DM. Trained MAs may also play a role in improved patient education and awareness regarding diabetes self-management.