Despite significant advances in the treatment of major depression, there is a high degree of variability in how patients respond to treatment. Approximately 70% of patients show some improvement following standard antidepressant treatment and are classified as having non-refractory depressive disorder (NDD), while the remaining 30% of patients do not respond to treatment and are classified as having refractory depressive disorder (RDD). At present, there are no objective, neurological markers which can be used to identify individuals with depression and predict clinical outcome. We therefore examined the diagnostic and prognostic potential of pre-treatment structural neuroanatomy using support vector machine (SVM). Sixty-one drug-naïve adults suffering from depression and 42 healthy volunteers were scanned using structural magnetic resonance imaging (sMRI). Patients then received standard antidepressant medication (either tricyclic, typical serotonin-norepinephrine reuptake inhibitor or typical selective serotonin reuptake inhibitor). Based on clinical outcome, we selected two groups of RDD (n=23) and NDD (n=23) patients matched for age, sex and pre-treatment severity of depression. Diagnostic accuracy of gray matter was 67.39% for RDD (p=0.01) and 76.09% for NDD (p<0.001), while diagnostic accuracy of white matter was 58.70% for RDD (p=0.13) and 84.65% for NDD (p<0.001). SVM applied to gray matter correctly distinguished between RDD and NDD patients with an accuracy of 69.57% (p=0.006); in contrast, SVM applied to white matter predicted clinical outcome with an accuracy of 65.22% (p=0.02). These results indicate that both gray and white matter have diagnostic and prognostic potential in major depression and may provide an initial step towards the use of biological markers to inform clinical treatment. Future studies will benefit from the integration of structural neuroimaging with other imaging modalities as well as genetic, clinical and cognitive information.

The genetic basis of autosomal dominant nonsyndromic hearing loss is complex. Genetic factors are responsible for approximately 50% of cases with congenital hearing loss. However, no previous studies have documented the clinical phenotype and genetic basis of autosomal dominant nonsyndromic hearing loss in Mongolians.

Most migraineurs develop cutaneous allodynia (CA) during migraine, and the underlying mechanism of CA in migraine is thought to be sensitization of the third-order trigeminovascular neurons in the posterior thalamic nuclei. This study aimed to investigate whether the ascending/descending pathway associated with the thalamus is disturbed in migraineurs with CA (MWCA) using effective connectivity analysis of resting-state functional magnetic resonance imaging.

Regulatory T (Treg) cells are important in maintaining self-tolerance and immune homeostasis. The Treg cell transcription factor Foxp3 works in concert with other co-regulatory molecules, including Eos, to determine the transcriptional signature and characteristic suppressive phenotype of Treg cells. Here, we report that the inflammatory cytokine interleukin-6 (IL-6) actively repressed Eos expression through microRNA-17 (miR-17). miR-17 expression increased in Treg cells in the presence of IL-6, and its expression negatively correlated with that of Eos. Treg cell suppressive activity was diminished upon overexpression of miR-17 in vitro and in vivo, which was mitigated upon co-expression of an Eos mutant lacking miR-17 target sites. Also, RNAi of miR-17 resulted in enhanced suppressive activity. Ectopic expression of miR-17 imparted effector-T-cell-like characteristics to Treg cells via the de-repression of genes encoding effector cytokines. Thus, miR-17 provides a potent layer of Treg cell control through targeting Eos and additional Foxp3 co-regulators.

Loss of 53BP1 rescues BRCA1 deficiency and is associated with BRCA1-deficient and triple-negative breast cancers (TNBC) and with resistance to genotoxic drugs. The mechanisms responsible for decreased 53BP1 transcript and protein levels in tumors remain unknown. Here, we demonstrate that BRCA1 loss activates cathepsin L (CTSL)-mediated degradation of 53BP1. Activation of this pathway rescued homologous recombination repair and allowed BRCA1-deficient cells to bypass growth arrest. Importantly, depletion or inhibition of CTSL with vitamin D or specific inhibitors stabilized 53BP1 and increased genomic instability in response to radiation and poly(adenosine diphosphate-ribose) polymerase inhibitors, compromising proliferation. Analysis of human breast tumors identified nuclear CTSL as a positive biomarker for TNBC, which correlated inversely with 53BP1. Importantly, nuclear levels of CTSL, vitamin D receptor, and 53BP1 emerged as a novel triple biomarker signature for stratification of patients with BRCA1-mutated tumors and TNBC, with potential predictive value for drug response. We identify here a novel pathway with prospective relevance for diagnosis and customization of breast cancer therapy.

Homologous recombination (HR) is a major mechanism utilized to repair blockage of DNA replication forks. Here, we report that a sister chromatid exchange (SCE) generated by crossover-associated HR efficiently occurs in response to replication fork stalling before any measurable DNA double-strand breaks (DSBs). Interestingly, SCE produced by replication fork collapse following DNA DSBs creation is specifically suppressed by ATR, a central regulator of the replication checkpoint. BRCA1 depletion leads to decreased RPA2 phosphorylation (RPA2-P) following replication fork stalling but has no obvious effect on RPA2-P following replication fork collapse. Importantly, we found that BRCA1 promotes RAD51 recruitment and SCE induced by replication fork stalling independent of ATR. In contrast, BRCA1 depletion leads to a more profound defect in RAD51 recruitment and SCE induced by replication fork collapse when ATR is depleted. We concluded that BRCA1 plays a dual role in two distinct HR-mediated repair upon replication fork stalling and collapse. Our data established a molecular basis for the observation that defective BRCA1 leads to a high sensitivity to agents that cause replication blocks without being associated with DSBs, and also implicate a novel mechanism by which loss of cell cycle checkpoints promotes BRCA1-associated tumorigenesis via enhancing HR defect resulting from BRCA1 deficiency.

The aim of this study is to examine whether advanced magnetic resonance imaging (MRI) techniques can detect early brain injury caused by intrauterine inflammation and inappropriate initial respiratory support in preterm lambs.

DNA lesion bypass facilitates DNA synthesis across bulky DNA lesions, playing a critical role in DNA damage tolerance and cell survival after DNA damage. Assessing lesion bypass efficiency in the cell is important to better understanding of the mechanism of carcinogenesis and chemoresistance. Here we developed a chromatin immunoprecipitation (ChIP)-based method to measure lesion bypass activity across cisplatin-induced intrastrand crosslinks in cancer cells. DNA lesion bypass enables the replication to continue in the presence of replication blocks. Thus, the successful lesion bypass should result in the coexistence of DNA lesions and the newly synthesized DNA fragment opposite to this lesion. Using ChIP, we precipitated the cisplatin-induced intrastrand crosslinks, and quantitated the precipitated newly synthesized DNA that was labeled with BrdU. We validated this method on ovarian cancer cells with inhibited TLS activity. We then applied this method to show that ovarian cancer stem cells exhibit high lesion bypass activity relative to bulk cancer cells from the same cell line. In conclusion, this novel ChIP-based lesion bypass assay can detect the extent to which cisplatin-induced DNA lesions are bypassed in live cells. Our study may be applied more broadly to the study of other DNA lesions, as specific antibodies to these specific lesions are available.

High-grade serous carcinoma (HGSC) is the most common and lethal ovarian cancer subtype. PARP inhibitors (PARPi) have become the mainstay of HGSC-targeted therapy, given that these tumors are driven by a high degree of genomic instability (GI) and homologous recombination (HR) defects. Nonetheless, approximately 30% of patients initially respond to treatment, ultimately relapsing with resistant disease. Thus, despite recent advances in drug development and an increased understanding of genetic alterations driving HGSC progression, mortality has not declined, highlighting the need for novel therapies. Using a small-molecule activator of protein phosphatase 2A (PP2A; SMAP-061), we investigated the mechanism by which PP2A stabilization induces apoptosis in patient-derived HGSC cells and xenograft (PDX) models alone or in combination with PARPi. We uncovered that PP2A genes essential for cellular transformation (B56α, B56γ, and PR72) and basal phosphatase activity (PP2A-A and -C) are heterozygously lost in the majority of HGSC. Moreover, loss of these PP2A genes correlates with worse overall patient survival. We show that SMAP-061-induced stabilization of PP2A inhibits the HR output by targeting RAD51, leading to chronic accumulation of DNA damage and ultimately apoptosis. Furthermore, combination of SMAP-061 and PARPi leads to enhanced apoptosis in both HR-proficient and HR-deficient HGSC cells and PDX models. Our studies identify PP2A as a novel regulator of HR and indicate PP2A modulators as a therapeutic therapy for HGSC. In summary, our findings further emphasize the potential of PP2A modulators to overcome PARPi insensitivity, given that targeting RAD51 presents benefits in overcoming PARPi resistance driven by BRCA1/2 mutation reversions.

Poly (ADP-ribose) Polymerase (PARP) inhibitors (PARPi) have been approved for both frontline and recurrent setting in ovarian cancer with homologous recombination (HR) repair deficiency. However, more than 40% of BRCA1/2-mutated ovarian cancer lack the initial response to PARPi treatment, and the majority of those that initially respond eventually develop resistance. Our previous study has demonstrated that increased expression of aldehyde dehydrogenase 1A1 (ALDH1A1) contributes to PARPi resistance in BRCA2-mutated ovarian cancer cells by enhancing microhomology-mediated end joining (MMEJ) but the mechanism remains unknown. Here, we find that ALDH1A1 enhances the expression of DNA polymerase θ (Polθ, encoded by the POLQ gene) in ovarian cancer cells. Furthermore, we demonstrate that the retinoic acid (RA) pathway is involved in the transcription activation of the POLQ gene. The RA receptor (RAR) can bind to the retinoic acid response element (RARE) located in the promoter of the POLQ gene, promoting transcription activation-related histone modification in the presence of RA. Given that ALDH1A1 catalyzes the biosynthesis of RA, we conclude that ALDH1A1 promotes POLQ expression via the activation of the RA signaling pathway. Finally, using a clinically-relevant patient-derived organoid (PDO) model, we find that ALDH1A1 inhibition by the pharmacological inhibitor NCT-505 in combination with the PARP inhibitor olaparib synergistically reduce the cell viability of PDOs carrying BRCA1/2 mutation and positive ALDH1A1 expression. In summary, our study elucidates a new mechanism contributing to PARPi resistance in HR-deficient ovarian cancer and shows the therapeutic potential of combining PARPi and ALDH1A1 inhibition in treating these patients.

Recently, deep learning technologies have rapidly expanded into medical image analysis, including both disease detection and classification. As far as we know, migraine is a disabling and common neurological disorder, typically characterized by unilateral, throbbing and pulsating headaches. Unfortunately, a large number of migraineurs do not receive the accurate diagnosis when using traditional diagnostic criteria based on the guidelines of the International Headache Society. As such, there is substantial interest in developing automated methods to assist in the diagnosis of migraine.

This paper proposed a prewhitening invariance of noise space (PW-INN) as a new magnetoencephalography (MEG) source analysis method, which is particularly suitable for localizing closely spaced and highly correlated cortical sources under real MEG noise. Conventional source localization methods, such as sLORETA and beamformer, cannot distinguish closely spaced cortical sources, especially under strong intersource correlation. Our previous work proposed an invariance of noise space (INN) method to resolve closely spaced sources, but its performance is seriously degraded under correlated noise between MEG sensors. The proposed PW-INN method largely mitigates the adverse influence of correlated MEG noise by projecting MEG data to a new space defined by the orthogonal complement of dominant eigenvectors of correlated MEG noise. Simulation results showed that PW-INN is superior to INN, sLORETA, and beamformer in terms of localization accuracy for closely spaced and highly correlated sources. Lastly, source connectivity between closely spaced sources can be satisfactorily constructed from source time courses estimated by PW-INN but not from results of other conventional methods. Therefore, the proposed PW-INN method is a promising MEG source analysis to provide a high spatial-temporal characterization of cortical activity and connectivity, which is crucial for basic and clinical research of neural plasticity.

Mongolians have played a significant role in modern human evolution, especially after the rise of Genghis Khan (1162[?]-1227). Although the social cultural impacts of Genghis Khan and the Mongolian population have been well documented, explorations of their genome structure and genetic imprints on other human populations have been lacking. We here present the genome of a Mongolian male individual. The genome was de novo assembled using a total of 130.8-fold genomic data produced from massively parallel whole-genome sequencing. We identified high-confidence variation sets, including 3.7 million single nucleotide polymorphisms (SNPs) and 756,234 short insertions and deletions. Functional SNP analysis predicted that the individual has a pathogenic risk for carnitine deficiency. We located the patrilineal inheritance of the Mongolian genome to the lineage D3a through Y haplogroup analysis and inferred that the individual has a common patrilineal ancestor with Tibeto-Burman populations and is likely to be the progeny of the earliest settlers in East Asia. We finally investigated the genetic imprints of Mongolians on other human populations using different approaches. We found varying degrees of gene flows between Mongolians and populations living in Europe, South/Central Asia, and the Indian subcontinent. The analyses demonstrate that the genetic impacts of Mongolians likely resulted from the expansion of the Mongolian Empire in the 13th century. The genome will be of great help in further explorations of modern human evolution and genetic causes of diseases/traits specific to Mongolians.

The aims are to investigate and compare the activated cerebral regions of Uygur-speaking and Chinese-speaking participants during verb generation task.A total of 31 cases of Uygur and 28 cases of Han healthy volunteers were enrolled. They were requested to take verb generation tasks. Blood oxygenation level-dependent functional magnetic resonance imaging (BOLD-fMRI) was performed. The fMRI images were collected and activated brain regions were analyzed.In Chinese-speaking participants, the main activated cerebral regions were as follows: the left caudate nucleus, the left occipital gyrus, the left fusiform gyrus, bilateral supplementary motor area (BA8/ 6), the left BA32, left precuneus, the left superior parietal lobule, the left inferior parietal lobule (BA7), the left angular gyrus, the right side of the central gyrus (BA9), the left inferior frontal gyrus triangular section, the right pars opercularis gyri frontalis inferiorista, and bilateral cerebellum. In Uygur-speaking subjects, the main activated cerebral regions included left precentral gyrus (BA9 region), inferior frontal gyrus of left opercular part, inferior frontal gyrus of left triangle part, and left cerebellum. Left caudate nucleus, left orbital frontal gyrus, right caudate nucleus, and bilateral anterior cingulate gyrus (BA32 region) of Chinese group were significantly activated compared with Uygur group. By contrast, Uygur group showed no region that was more activated than Chinese group.The present study demonstrates that activated brain regions in verb generation tasks are different between Uygur and Chinese languages. Processing of Uygur characters is mainly in the left hemisphere of the brain, while the processing of Chinese characters needs more participation by the right hemisphere of the brain.

We showed in this study that cells deficient of the BRCA1-associated BACH1 helicase, also known as BRIP1, failed to elicit homologous recombination (HR) after DNA double-stranded breaks (DSBs). BACH1-deficient cells were also sensitive to mitomycin C (MMC) and underwent MMC-induced chromosome instability. Moreover, we identified a homozygous nonsense mutation in BACH1 in a FA-J patient-derived cell line and could not detect BACH1 protein in this cell line. Expression of wild-type BACH1 in this cell line reduced the accumulation of cells at G2/M phases following exposure to DNA crosslinkers, a characteristic of Fanconi anemia (FA) cells. These results support the conclusion that BACH1 is FANCJ.

Rationale: The mitogen-activated protein kinase pathway (MAPK) is one of the major cancer-driving pathways found in non-small cell lung cancer (NSCLC) patients. ERK inhibitors (ERKi) have been shown to be effective in NSCLC patients with MAPK pathway mutations. However, like other MAPK inhibitors, ERKi rarely confers complete and durable responses. The mechanism of tumor relapse after ERKi treatment is yet defined. Methods: To best study the mechanism of tumor relapse after ERK inhibitor treatment in NSCLC patients, we treated various NSCLC cell lines and patient-derived xenograft (PDX) with ERK inhibitors and evaluated the enrichment of cancer stem cell (CSC) population. We then performed a Next-generation sequencing (NGS) to identify potential pathways that are responsible for the CSC enrichment. Further, the involvement of specific pathways was examined using molecular and cellular methods. Finally, we investigated the therapeutic benefits of ERKi treatment combined with JAK/STAT pathway inhibitor using cellular and xenograft NSCLC models. Results: We found that ERKi treatment expands the CSC population in NSCLC cells through enhanced epithelial-to-mesenchymal transition (EMT)-mediated cancer cell dedifferentiation. Mechanistically, ERK inactivation induces EMT via pSTAT3-mediated upregulation of Slug, in which, upregulation of miR-204 and downregulation of SPDEF, a transcription repressor of Slug, are involved. Finally, the JAK/STAT pathway inhibitor Ruxolitinib blocks the ERK inactivation-induced EMT and CSC expansion, as well as the tumor progression in xenograft models after ERKi treatment. Conclusions: This study revealed a potential tumor relapse mechanism of NSCLC after ERK inhibition through the unintended activation of the EMT program, ascertained the pSTAT-miR-204-SPDEF-Slug axis, and provided a promising combination inhibitor approach to prevent tumor relapse in patients.

Checkpoint kinase 1 (CHK1) is critical for cell survival under replication stress (RS). CHK1 inhibitors (CHK1i's) in combination with chemotherapy have shown promising results in preclinical studies but minimal efficacy with substantial toxicity in clinical trials. To explore novel combinational strategies that can overcome these limitations, we performed an unbiased high-throughput screen in a non-small cell lung cancer (NSCLC) cell line and identified thioredoxin1 (Trx1), a major component of the mammalian antioxidant-system, as a novel determinant of CHK1i sensitivity. We established a role for redox recycling of RRM1, the larger subunit of ribonucleotide reductase (RNR), and a depletion of the deoxynucleotide pool in this Trx1-mediated CHK1i sensitivity. Further, the TrxR1 inhibitor auronafin, an anti-rheumatoid arthritis drug, shows a synergistic interaction with CHK1i via interruption of the deoxynucleotide pool. Together, these findings identify a new pharmacological combination to treat NSCLC that relies on a redox regulatory link between the Trx system and mammalian RNR activity.

Alternative non-homologous end joining (alt-NHEJ) was originally identified as a backup repair mechanism in the absence of classical NHEJ (c-NHEJ) factors but recent studies have demonstrated that alt-NHEJ is active even when c-NHEJ as well as homologous recombination is available. The functions of 53BP1 in NHEJ processes are not well understood. Here, we report that 53BP1 promotes DNA double-strand break (DSB) repair and genomic stability not only in c-NHEJ-proficient but also -deficient human G1-phase cells. Using an array of repair substrates we show that these effects of 53BP1 are correlated with a promotion of microhomology-mediated end-joining (MMEJ), a subtype of alt-NHEJ, in G1-phase. Consistent with a specific role in MMEJ we confirm that 53BP1 status does not affect c-NHEJ. 53BP1 supports sequence deletion during MMEJ consistent with a putative role in facilitating end-resection. Interestingly, promotion of MMEJ by 53BP1 in G1-phase cells is only observed in the presence of functional BRCA1. Depletion of both 53BP1 and BRCA1 increases repair needing microhomology usage and augments loss of DNA sequence, suggesting that MMEJ is a highly regulated DSB repair process. Together, these findings significantly expand our understanding of the cell-cycle-dependent roles of 53BP1 in DSB repair.

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid.

Magnetic resonance imaging (MRI) is by nature a multi-modality technique that provides complementary information about different aspects of diseases. So far no attempts have been reported to assess the potential of multi-modal MRI in discriminating individuals with and without migraine, so in this study, we proposed a classification approach to examine whether or not the integration of multiple MRI features could improve the classification performance between migraine patients without aura (MWoA) and healthy controls. Twenty-one MWoA patients and 28 healthy controls participated in this study. Resting-state functional MRI data was acquired to derive three functional measures: the amplitude of low-frequency fluctuations, regional homogeneity and regional functional correlation strength; and structural MRI data was obtained to measure the regional gray matter volume. For each measure, the values of 116 pre-defined regions of interest were extracted as classification features. Features were first selected and combined by a multi-kernel strategy; then a support vector machine classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using a leave-one-out cross-validation method, and the final classification accuracy obtained was 83.67% (with a sensitivity of 92.86% and a specificity of 71.43%). The anterior cingulate cortex, prefrontal cortex, orbitofrontal cortex and the insula contributed the most discriminative features. In general, our proposed framework shows a promising classification capability for MWoA by integrating information from multiple MRI features.