Proteogenomic characterization of small cell lung cancer identifies biological insights and subtype-specific therapeutic strategies.

We performed comprehensive proteogenomic characterization of small cell lung cancer (SCLC) using paired tumors and adjacent lung tissues from 112 treatment-naive patients who underwent surgical resection. Integrated multi-omics analysis illustrated cancer biology downstream of genetic aberrations and highlighted oncogenic roles of FAT1 mutation, RB1 deletion, and chromosome 5q loss. Two prognostic biomarkers, HMGB3 and CASP10, were identified. Overexpression of HMGB3 promoted SCLC cell migration via transcriptional regulation of cell junction-related genes. Immune landscape characterization revealed an association between ZFHX3 mutation and high immune infiltration and underscored a potential immunosuppressive role of elevated DNA damage response activity via inhibition of the cGAS-STING pathway. Multi-omics clustering identified four subtypes with subtype-specific therapeutic vulnerabilities. Cell line and patient-derived xenograft-based drug tests validated the specific therapeutic responses predicted by multi-omics subtyping. This study provides a valuable resource as well as insights to better understand SCLC biology and improve clinical practice.

Rapid diagnosis and precision treatment of Helicobacter pylori infection in clinical settings.

Helicobacter pylori is a gram-negative bacterium that colonizes the stomach of approximately half of the worldwide population, with higher prevalence in densely populated areas like Asia, the Caribbean, Latin America, and Africa. H. pylori infections range from asymptomatic cases to potentially fatal diseases, including peptic ulcers, chronic gastritis, and stomach adenocarcinoma. The management of these conditions has become more difficult due to the rising prevalence of drug-resistant H. pylori infections, which ultimately lead to gastric cancer and mucosa-associated lymphoid tissue (MALT) lymphoma. In 1994, the International Agency for Research on Cancer (IARC) categorized H. pylori as a Group I carcinogen, contributing to approximately 780,000 cancer cases annually. Antibiotic resistance against drugs used to treat H. pylori infections ranges between 15% and 50% worldwide, with Asian countries having exceptionally high rates. This review systematically examines the impacts of H. pylori infection, the increasing prevalence of antibiotic resistance, and the urgent need for accurate diagnosis and precision treatment. The present status of precision treatment strategies and prospective approaches for eradicating infections caused by antibiotic-resistant H. pylori will also be evaluated.

Deep learning in computed tomography to predict endotype in chronic rhinosinusitis with nasal polyps.

BACKGROUND: As treatment strategies differ according to endotype, rhinologists must accurately determine the endotype in patients affected by chronic rhinosinusitis with nasal polyps (CRSwNP) for the appropriate management. In this study, we aim to construct a novel deep learning model using paranasal sinus computed tomography (CT) to predict the endotype in patients with CRSwNP. METHODS: We included patients diagnosed with CRSwNP between January 1, 2020, and April 31, 2023. The endotype of patients with CRSwNP in this study was classified as eosinophilic or non-eosinophilic. Sinus CT images (29,993 images) were retrospectively collected, including the axial, coronal, and sagittal planes, and randomly divided into training, validation, and testing sets. A residual network-18 was used to construct the deep learning model based on these images. Loss functions, accuracy functions, confusion matrices, and receiver operating characteristic curves were used to assess the predictive performance of the model. Gradient-weighted class activation mapping was performed to visualize and interpret the operating principles of the model. RESULTS: Among 251 included patients, 86 and 165 had eosinophilic or non-eosinophilic CRSwNP, respectively. The median (interquartile range) patient age was 49 years (37-58 years), and 153 (61.0%) were male. The deep learning model showed good discriminative performance in the training and validation sets, with areas under the curves of 0.993 and 0.966, respectively. To confirm the model generalizability, the receiver operating characteristic curve in the testing set showed good discriminative performance, with an area under the curve of 0.963. The Kappa scores of the confusion matrices in the training, validation, and testing sets were 0.985, 0.928, and 0.922, respectively. Finally, the constructed deep learning model was used to predict the endotype of all patients, resulting in an area under the curve of 0.962. CONCLUSIONS: The deep learning model developed in this study may provide a novel noninvasive method for rhinologists to evaluate endotypes in patients with CRSwNP and help develop precise treatment strategies.

A glimpse of research cores and frontiers on the relationship between long noncoding RNAs (lncRNAs) and colorectal cancer (CRC) using the VOSviewer tool.

As lncRNAs are essential participants in colorectal carcinogenesis. This study aimed to use the VOSviewer tool to access the research cores and frontiers on the relationship between lncRNAs and CRC. Our findings showed that the mechanism of lncRNA in the occurrence and development of CRC was the core theme of the field. (1) Immunotherapy and immune microenvironment of CRC and lncRNAs, (2) CRC and lncRNAs in exosomes and (3) CRC and lncRNA-targeted therapy might represent three research frontiers. A comprehensive understanding of their existing mechanisms and the search for new regulatory paradigms are the core topics of future research. This knowledge will also help us select appropriate targeting methods and select appropriate preclinical models to promote clinical translation and ultimately achieve precise treatment of CRC.

ROS1 genomic rearrangements are rare actionable drivers in microsatellite stable colorectal cancer.

c-Ros oncogene 1, receptor tyrosine kinase (ROS1) genomic rearrangements have been reported previously in rare cases of colorectal cancer (CRC), yet little is known about the frequency, molecular characteristics, and therapeutic vulnerabilities of ROS1-driven CRC. We analyzed a clinical dataset of 40 589 patients with CRC for ROS1 genomic rearrangements and their associated genomic characteristics (Foundation Medicine, Inc [FMI]). We moreover report the disease course and treatment response of an index patient with ROS1-rearranged metastatic CRC. ROS1 genomic rearrangements were identified in 34 (0.08%) CRC samples. GOPC-ROS1 was the most common ROS1 fusion identified (11 samples), followed by TTC28-ROS1 (3 samples). Four novel 5' gene partners of ROS1 were identified (MCM9, SRPK1, EPHA6, P4HA1). Contrary to previous reports on fusion-positive CRC, ROS1-rearrangements were found exclusively in microsatellite stable (MSS) CRCs. KRAS mutations were significantly less abundant in ROS1-rearranged vs ROS1 wild type cases. The index patient presented with chemotherapy-refractory metastatic right-sided colon cancer harboring GOPC-ROS1. Molecularly targeted treatment with crizotinib induced a rapid and sustained partial response. After 15 months on crizotinib disseminated tumor progression occurred and KRAS Q61H emerged in tissue and liquid biopsies. ROS1 rearrangements define a small, yet therapeutically actionable molecular subgroup of MSS CRC. In summary, the high prevalence of GOPC-ROS1 and noncanonical ROS1 fusions pose diagnostic challenges. We advocate NGS-based comprehensive molecular profiling of MSS CRCs that are wild type for RAS and BRAF and patient enrollment in precision trials.

Outcomes of postoperative adjuvant transarterial chemoembolization for hepatocellular carcinoma according to the Ki67 index.

Aim: To assess whether Ki67 is related to the efficacy of postoperative adjuvant transarterial chemoembolization (PA-TACE) in hepatocellular carcinoma patients at high risk of postsurgical recurrence. Methods: A total of 716 patients undergoing surgical resection with or without PA-TACE were retrospectively enrolled. Immunohistochemistry was used to analyze Ki67 expression. Results: There was no significant difference in tumor-free survival between patients who underwent resection with or without chemoembolization. However, chemoembolization was associated with significantly higher tumor-free survival rates among patients with 'low' (<30%) or 'moderate' (30-59%) levels of Ki67. Patients highly expressing Ki67 displayed higher rates of overall recurrence, earlier recurrence, multiple intrahepatic recurrence and extrahepatic metastasis. Conclusion: In patients with relatively high Ki67 levels, PA-TACE does not appear to improve outcomes.

Postoperative adjuvant transarterial chemoembolization (PA-TACE), as an adjuvant treatment to surgery, is widely recommended in patients with high-risk factors for recurrence. Nevertheless, some studies challenge whether it actually improves prognosis, thus the influence of PA-TACE on prognosis remains controversial. The present research indicated that the ability of PA-TACE to help inhibit hepatocellular carcinoma recurrence is conditionally restrictive, and it appears to be beneficial only in those patients with a low or moderate Ki67 index (<60%). For patients with high Ki67 expression, compared with PA-TACE, 'adjuvant immunotherapy' may be a potential alternative option. This finding suggests a valuable reference to identify the best beneficiaries of PA-TACE for individualized treatment.

Nanotechnology for research and treatment of the intestine.

The establishment of intestinal in vitro models is crucial for elucidating intestinal cell-microbe intrinsic connections and interaction mechanisms to advance normalized intestinal diagnosis and precision therapy. This review discusses the application of nanomaterials in mucosal therapy and mechanism research in combination with the study of nanoscaffold in vitro models of the gut. By reviewing the original properties of nanomaterials synthesized by different physicochemical principles and modifying the original properties, the contribution of nanomaterials to solving the problems of short survival period, low cell differentiation rate, and poor reduction ability in traditional intestinal models is explored. According to nanomaterials' different diagnostic mediators and therapeutic targets, the current diagnostic principles in inflammatory bowel disease, intestinal cancer, and other diseases are summarized inductively. In addition, the mechanism of action of nanomedicines in repairing mucosa, inhibiting inflammation, and alleviating the disease process is also discussed. Through such systematic elaboration, it offers a basis for nanomaterials to help advance in vitro research on the intestine and provide precision treatments in the clinic.

Identification of key non-coding RNAs and transcription factors regulators and their potential drugs for steroid-induced femoral head necrosis.

Steroid-induced necrosis of femoral head (SINFH) is a femoral head necrotic disease caused by prolonged use of hormones. The detailed pathogenesis has not been fully demonstrated. In this study, we employed the bioinformatics approach to probe the roles of SINFH inhibitors. Core dysfunction modules related to SINFH was obtained. Meanwhile, GO and KEGG analysis of genes in dysfunction modules are carried out. Furthermore, the pivot prediction analysis of dysfunction modules related to ncRNA and transcription factor (TF) has been performed. The functions of the enriched modules were focused on multiple perspectives, including circulation, gland development, bone development and reconstruction, calcium production, and fatty acid metabolism regulation. The ncRNAs and TFs analysis showed that miR-322-5p, miR-124-3p, miR-125a-3p, and Ctnnb1 were important members of SINFH dysfunction. Drug targets suggested that Zinc and adenosine monophosphate may have an impact on SINFH dysfunction. SINFH was closely related to bone development and reconstruction.

[Roles of long non-coding RNAs in prostate cancer and their action mechanisms].

Prostate cancer (PCa) is one of the most common male malignancies as well as one of the frequent causes of tumor-induced death. Long non-coding RNAs (lncRNAs) are RNA transcripts that are more than 200 nucleotides in length, lack an open reading frame, and do not encode proteins. LncRNAs are abnormally expressed in most tumors including PCa and closely related to the recurrence, metastasis and prognosis of PCa. LncRNAs regulate gene expressions at multiple levels such as epigenetics, transcription and post-transcription, change metabolic pathways, and play a carcinogenic or anti-tumor role in the development and progression of PCa. Continuous androgen receptor (AR) signal transduction is one of the key features of castration-resistant PCa. This review briefly introduces the role of lncRNAs as oncogenes or tumor suppressor genes in the development and progression of PCa, and expounds the possible molecular mechanisms of lncRNAs mediating PCa through the AR signaling pathway, post-transcriptional regulation represented by ceRNA, and tumor metabolism, aiming to provide potential biomarkers and therapeutic targets for the clinical diagnosis and treatment of PCa.

Multiomics data reveals the influences of myasthenia gravis on thymoma and its precision treatment.

Thymoma is a rare characterized by a unique association with autoimmune diseases, especially myasthenia gravis (MG). However, little is known about the molecular characteristics of MG-associated thymoma individuals. We aim to examine the influences of MG on thymoma by analyzing multiomics data. A total of 105 samples with thymoma was analyzed from TCGA and these samples were divided into subgroups with MG (MGT) or without MG (MGF) according to clinical information. We then characterized the differential gene expression, pathway activity, somatic mutation frequency, and likelihood of responding to chemotherapies and immunotherapies of the two identified subgroups. MGT subgroup was characterized by elevated inflammatory responses and metabolically related pathways, whereas the MGF subgroup was predicted to be more sensitive to chemotherapy and presented with mesenchymal characteristics. More copy number amplifications and deletions were observed in MGT, whereas GTF2I mutations occur at significantly higher frequencies in MGF. Two molecular subtypes were further identified within MGF samples by unsupervised clustering where one subtype was enriched in TGF-ß and WNT pathways with higher sensitivity to relevant targeted drugs but hardly respond to immunotherapy. For another subtype, a higher recurrence rate of thymoma and more likelihood of responding to immunotherapy were observed. Our findings presented a comprehensive molecular characterization of thymoma patients given the status of MG, and provided potential strategies to help individualized management and treatment.

The establishment of a prognostic scoring model based on the new tumor immune microenvironment classification in acute myeloid leukemia.

BACKGROUND: The high degree of heterogeneity brought great challenges to the diagnosis and treatment of acute myeloid leukemia (AML). Although several different AML prognostic scoring models have been proposed to assess the prognosis of patients, the accuracy still needs to be improved. As important components of the tumor microenvironment, immune cells played important roles in the physiological functions of tumors and had certain research value. Therefore, whether the tumor immune microenvironment (TIME) can be used to assess the prognosis of AML aroused our great interest. METHODS: The patients' gene expression profile from 7 GEO databases was normalized after removing the batch effect. TIME cell components were explored through Xcell tools and then hierarchically clustered to establish TIME classification. Subsequently, a prognostic model was established by Lasso-Cox. Multiple GEO databases and the Cancer Genome Atlas dataset were employed to validate the prognostic performance of the model. Receiver operating characteristic (ROC) and the concordance index (C-index) were utilized to assess the prognostic efficacy. RESULTS: After analyzing the composition of TIME cells in AML, we found infiltration of ten types of cells with prognostic significance. Then using hierarchical clustering methods, we established a TIME classification system, which clustered all patients into three groups with distinct prognostic characteristics. Using the differential genes between the first and third groups in the TIME classification, we constructed a 121-gene prognostic model. The model successfully divided 1229 patients into the low and high groups which had obvious differences in prognosis. The high group with shorter overall survival had more patients older than 60 years and more poor-risk patients (both P< 0.001). Besides, the model can perform well in multiple datasets and could further stratify the cytogenetically normal AML patients and intermediate-risk AML population. Compared with the European Leukemia Net Risk Stratification System and other AML prognostic models, our model had the highest C-index and the largest AUC of the ROC curve, which demonstrated that our model had the best prognostic efficacy. CONCLUSION: A prognostic model for AML based on the TIME classification was constructed in our study, which may provide a new strategy for precision treatment in AML.

Technological readiness and implementation of genomic-driven precision medicine for complex diseases.

The fields of human genetics and genomics have generated considerable knowledge about the mechanistic basis of many diseases. Genomic approaches to diagnosis, prognostication, prevention and treatment - genomic-driven precision medicine (GDPM) - may help optimize medical practice. Here, we provide a comprehensive review of GDPM of complex diseases across major medical specialties. We focus on technological readiness: how rapidly a test can be implemented into health care. Although these areas of medicine are diverse, key similarities exist across almost all areas. Many medical areas have, within their standards of care, at least one GDPM test for a genetic variant of strong effect that aids the identification/diagnosis of a more homogeneous subset within a larger disease group or identifies a subset with different therapeutic requirements. However, for almost all complex diseases, the majority of patients do not carry established single-gene mutations with large effects. Thus, research is underway that seeks to determine the polygenic basis of many complex diseases. Nevertheless, most complex diseases are caused by the interplay of genetic, behavioural and environmental risk factors, which will likely necessitate models for prediction and diagnosis that incorporate genetic and non-genetic data.

An individualized treatment rule to optimize probability of remission by continuation, switching, or combining antidepressant medications after failing a first-line antidepressant in a two-stage randomized trial.

BACKGROUND: There is growing interest in using composite individualized treatment rules (ITRs) to guide depression treatment selection, but best approaches for doing this are not widely known. We develop an ITR for depression remission based on secondary analysis of a recently published trial for second-line antidepression medication selection using a cutting-edge ensemble machine learning method. METHODS: Data come from the SUN(^_^)D trial, an open-label, assessor blinded pragmatic trial of previously-untreated patients with major depressive disorder from 48 clinics in Japan. Initial clinic-level randomization assigned patients to 50 or 100 mg/day sertraline. We focus on the 1549 patients who failed to remit within 3 weeks and were then rerandomized at the individual-level to continuation with sertraline, switching to mirtazapine, or combining mirtazapine with sertraline. The outcome was remission 9 weeks post-baseline. Predictors included socio-demographics, clinical characteristics, baseline symptoms, changes in symptoms between baseline and week 3, and week 3 side effects. RESULTS: Optimized treatment was associated with significantly increased cross-validated week 9 remission rates in both samples [5.3% (2.4%), p = 0.016 50 mg/day sample; 5.1% (2.7%), p = 0.031 100 mg/day sample] compared to randomization (30.1-30.8%). Optimization was also associated with significantly increased remission in both samples compared to continuation [24.7% in both: 11.2% (3.8%), p = 0.002 50 mg/day sample; 11.7% (3.9%), p = 0.001 100 mg/day sample]. Non-significant gains were found for optimization compared to switching or combining. CONCLUSIONS: An ITR can be developed to improve second-line antidepressant selection, but replication in a larger study with more comprehensive baseline predictors might produce stronger and more stable results.

Multi-Omics Reveal the Immunological Role and the Theragnostic Value of miR-216a/GDF15 Axis in Human Colon Adenocarcinoma.

Colon adenocarcinoma (COAD) is the most common type of gastrointestinal cancer and is still the third leading cause of cancer-related mortality worldwide. Accurate screening tools for early diagnosis and prediction of prognosis and precision treatment strategies are urgently required to accommodate the unmet medical needs of COAD management. We herein aimed to explore the significance of the microRNA (miR)-216a/growth differentiation factor 15 (GDF15) axis in terms of clinical value, tumor immunity, and potential mechanisms in COAD by using multi-omic analysis. The gene expression levels of miR-216a and GDF15 showed an increase in the COAD group compared to those of the normal group. The expression of miR-216a presented a negative correlation with GDF15 in COAD tumor tissue. The use of an in vitro luciferase reporter assay and bioinformatic prediction revealed that miR-216a-3p acted toward translational inhibition on GDF15 by targeting its 3'untranslated region (UTR) site. High miR-216a expression was associated with decreased overall survival (OS), while the high expression of GDF15 was associated with increased OS. Enriched type 1 T-helper (Th1), enriched regulatory T (Treg), enriched eosinophils, and decreased nature killer T-cells (NKTs) in COAD tumor tissue may play counteracting factors on the tumor-regulatory effects of miR-216a and GDF15. In addition, high GDF15 expression had associations with suppressed immunoinhibitory genes and negative correlations with the infiltration of macrophages and endothelial cells. The enrichment analysis revealed that GDF15 and its co-expression network may be implicated in mitochondrial organization, apoptosis signaling, and endoplasmic reticulum (ER) stress response. The Genomics of Drug Sensitivity in Cancer (GDSC) and Cancer Therapeutics Response Portal (CTRP) analysis identified that Gemcitabine acted as a precision treatment for COAD when GDF15 expression was low. This study supports the miR-216a/GDF15 axis as a diagnostic/prognostic panel for COAD, identifies Th1, Treg, eosinophils, and NKTs as counteracting factors, indicates potential relationships underlying immunomodulation, mitochondrial organization, apoptotic signaling, and ER stress and unveil Gemcitabine as a potential drug for the development of treatment strategy when combined with targeting GDF15.

Precision medicine in diabetes: a Consensus Report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD).

The convergence of advances in medical science, human biology, data science and technology has enabled the generation of new insights into the phenotype known as 'diabetes'. Increased knowledge of this condition has emerged from populations around the world, illuminating the differences in how diabetes presents, its variable prevalence and how best practice in treatment varies between populations. In parallel, focus has been placed on the development of tools for the application of precision medicine to numerous conditions. This Consensus Report presents the American Diabetes Association (ADA) Precision Medicine in Diabetes Initiative in partnership with the European Association for the Study of Diabetes (EASD), including its mission, the current state of the field and prospects for the future. Expert opinions are presented on areas of precision diagnostics and precision therapeutics (including prevention and treatment) and key barriers to and opportunities for implementation of precision diabetes medicine, with better care and outcomes around the globe, are highlighted. Cases where precision diagnosis is already feasible and effective (i.e. monogenic forms of diabetes) are presented, while the major hurdles to the global implementation of precision diagnosis of complex forms of diabetes are discussed. The situation is similar for precision therapeutics, in which the appropriate therapy will often change over time owing to the manner in which diabetes evolves within individual patients. This Consensus Report describes a foundation for precision diabetes medicine, while highlighting what remains to be done to realise its potential. This, combined with a subsequent, detailed evidence-based review (due 2022), will provide a roadmap for precision medicine in diabetes that helps improve the quality of life for all those with diabetes.

Natural killer cells in cancer biology and therapy.

The tumor microenvironment is highly complex, and immune escape is currently considered an important hallmark of cancer, largely contributing to tumor progression and metastasis. Named for their capability of killing target cells autonomously, natural killer (NK) cells serve as the main effector cells toward cancer in innate immunity and are highly heterogeneous in the microenvironment. Most current treatment options harnessing the tumor microenvironment focus on T cell-immunity, either by promoting activating signals or suppressing inhibitory ones. The limited success achieved by T cell immunotherapy highlights the importance of developing new-generation immunotherapeutics, for example utilizing previously ignored NK cells. Although tumors also evolve to resist NK cell-induced cytotoxicity, cytokine supplement, blockade of suppressive molecules and genetic engineering of NK cells may overcome such resistance with great promise in both solid and hematological malignancies. In this review, we summarized the fundamental characteristics and recent advances of NK cells within tumor immunometabolic microenvironment, and discussed potential application and limitations of emerging NK cell-based therapeutic strategies in the era of presicion medicine.

Precision treatment of post pneumonectomy unilateral laryngeal paralysis due to cancer.

Aim: The aim of this study is to assess the efficacy of external laryngeal medialization acquired through a Gore-Tex implant in a 45 patients affected by unilateral vocal fold paralysis in abduction after pneumonectomy. Method: The cohort of patients was made up of 30 male (73.1%) and 11 female patients (26.9%) with an average age of 66.7 years in a range between 46 and 78 years. Results: The results were analyzed with the objective and subjective analysis of voicing and swallowing. In 95.2% of cases, voice and swallow improvement with statistically significant evidences. Conclusion: We can conclude that Gore-Tex implantation is a simple, reproducible and minimally invasive procedure for management of selected cases of vocal fold unilateral paralysis in the abductory position.

A Microthermal Sensor for Cryoablation Balloons.

Treatment of atrial fibrillation by cryoablation of the pulmonary vein (PV) suffers from an inability to assess probe contact, tissue thickness, and freeze completion through the wall. Unfortunately, clinical imaging cannot be used for this purpose as these techniques have resolutions similar in scale (∼1 to 2 mm) to PV thickness and therefore are unable to resolve changes within the PV during treatment. Here, a microthermal sensor based on the "3ω" technique which has been used for thin biological systems is proposed as a potential solution and tested for a cryoablation scenario. First, the sensor was modified from a linear format to a serpentine format for integration onto a flexible balloon. Next, using numerical analyses, the ability of the modified sensor on a flat substrate was studied to differentiate measurements in limiting cases of ice, water, and fat. These numerical results were then complemented by experimentation by micropatterning the serpentine sensor onto a flat substrate and onto a flexible balloon. In both formats (flat and balloon), the serpentine sensor was experimentally shown to: (1) identify tissue contact versus fluid, (2) distinguish tissue thickness in the 0.5 to 2 mm range, and (3) measure the initiation and completion of freezing as previously reported for a linear sensor. This study demonstrates proof of principle that a serpentine 3ω sensor on a balloon can monitor tissue contact, thickness, and phase change which is relevant to cryo and other focal thermal treatments of PV to treat atrial fibrillation.

Genetic Landscape of Common Epilepsies: Advancing towards Precision in Treatment.

Epilepsy, a neurological disease characterized by recurrent seizures, is highly heterogeneous in nature. Based on the prevalence, epilepsy is classified into two types: common and rare epilepsies. Common epilepsies affecting nearly 95% people with epilepsy, comprise generalized epilepsy which encompass idiopathic generalized epilepsy like childhood absence epilepsy, juvenile myoclonic epilepsy, juvenile absence epilepsy and epilepsy with generalized tonic-clonic seizure on awakening and focal epilepsy like temporal lobe epilepsy and cryptogenic focal epilepsy. In 70% of the epilepsy cases, genetic factors are responsible either as single genetic variant in rare epilepsies or multiple genetic variants acting along with different environmental factors as in common epilepsies. Genetic testing and precision treatment have been developed for a few rare epilepsies and is lacking for common epilepsies due to their complex nature of inheritance. Precision medicine for common epilepsies require a panoramic approach that incorporates polygenic background and other non-genetic factors like microbiome, diet, age at disease onset, optimal time for treatment and other lifestyle factors which influence seizure threshold. This review aims to comprehensively present a state-of-art review of all the genes and their genetic variants that are associated with all common epilepsy subtypes. It also encompasses the basis of these genes in the epileptogenesis. Here, we discussed the current status of the common epilepsy genetics and address the clinical application so far on evidence-based markers in prognosis, diagnosis, and treatment management. In addition, we assessed the diagnostic predictability of a few genetic markers used for disease risk prediction in individuals. A combination of deeper endo-phenotyping including pharmaco-response data, electro-clinical imaging, and other clinical measurements along with genetics may be used to diagnose common epilepsies and this marks a step ahead in precision medicine in common epilepsies management.

Oral Cancer: Integration of Studies for Diagnostic and Therapeutic Precision.

Head and neck cancers are among the 10 most common cancers in the world and include cancers of the oral cavity, hypopharynx, larynx, nasopharynx, and oropharynx. At least 90% of head and neck cancers are squamous cell carcinomas (SCCs). This summary discusses the integration of clinical and mechanistic studies in achieving diagnostic and therapeutic precision in the context of oral cancer. Specifically, based on recent mechanistic studies, a subsequent study reevaluated current diagnostic criteria of perineural invasion in patients with oral cavity SCC showing that overall survival could be associated with nerve-tumor distance; validation of the findings of this study from a small group of patients could lead to a personalized approach to treatment selection in patients with oral cavity SCC. Moreover, delineation of key pathways in SCC revealed novel treatment targets that can be exploited to develop personalized treatment strategies to achieve long-term remission.