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Tumor‐agnostic therapies represent a paradigm shift in oncology by altering the traditional means of characterizing tumors based on their origin or location. Instead, they zero in on specific genetic anomalies responsible for fueling malignant growth. The watershed moment for tumor‐agnostic therapies arrived in 2017, with the US Food and Drug Administration's historic approval of pembrolizumab, an immune checkpoint inhibitor. This milestone marked the marriage of genomics and immunology fields, as an immunotherapeutic agent gained approval based on genomic biomarkers, specifically, microsatellite instability‐high or mismatch repair deficiency (dMMR). Subsequently, the approval of NTRK inhibitors, designed to combat NTRK gene fusions prevalent in various tumor types, including pediatric cancers and adult solid tumors, further underscored the potential of tumor‐agnostic therapies. The US Food and Drug Administration approvals of targeted therapies (BRAF V600E, RET fusion), immunotherapies (tumor mutational burden ≥10 mutations per megabase, dMMR) and an antibody‐drug conjugate (Her2‐positive–immunohistochemistry 3+ expression) with pan‐cancer efficacy have continued, offering newfound hope to patients grappling with advanced solid tumors that harbor particular biomarkers. In this comprehensive review, the authors delve into the expansive landscape of tissue‐agnostic targets and drugs, shedding light on the rationale underpinning this approach, the hurdles it faces, presently approved therapies, voices from the patient advocacy perspective, and the tantalizing prospects on the horizon. This is a welcome advance in oncology that transcends the boundaries of histology and location to provide personalized options. [ABSTRACT FROM AUTHOR]

Simple Summary: Individualized medicine means understanding how each tumor is different from normal cells and how each tumor is different from other tumors, including profiling mutations, non-mutational epigenetic changes, and differences in gene expression. This allows the discovery of key processes each tumor absolutely depends on for survival and growth, which are intrinsic weaknesses. This profiling means selecting treatments to specifically target each tumor's survival-dependent pathways, killing them. Tip60 is a master controller of processes that maintain genome stability and signaling regulating gene expression. While disrupted in many cancers, Tip60 is essential for cell survival, and inhibiting Tip60 kills tumors. While we understand some key aspects of the molecular roles Tip60 plays, much more remains to be discovered. A more complete understanding of the diverse roles and functions of Tip60 in cancer, and how targeting Tip60 kills cancer cells, will lead to better treatments for patients and increased survival. Precision (individualized) medicine relies on the molecular profiling of tumors' dysregulated characteristics (genomic, epigenetic, transcriptomic) to identify the reliance on key pathways (including genome stability and epigenetic gene regulation) for viability or growth, and then utilises targeted therapeutics to disrupt these survival-dependent pathways. Non-mutational epigenetic changes alter cells' transcriptional profile and are a key feature found in many tumors. In contrast to genetic mutations, epigenetic changes are reversable, and restoring a normal epigenetic profile can inhibit tumor growth and progression. Lysine acetyltransferases (KATs or HATs) protect genome stability and integrity, and Tip60 is an essential acetyltransferase due to its roles as an epigenetic and transcriptional regulator, and as master regulator of the DNA double-strand break response. Tip60 is commonly downregulated and mislocalized in many cancers, and the roles that mislocalized Tip60 plays in cancer are not well understood. Here we categorize and discuss Tip60-regulated genes, evaluate Tip60-interacting proteins based on cellular localization, and explore the therapeutic potential of Tip60-targeting compounds as epigenetic inhibitors. Understanding the multiple roles Tip60 plays in tumorigenesis will improve our understanding of tumor progression and will inform therapeutic options, including informing potential combinatorial regimes with current chemotherapeutics, leading to improvements in patient outcomes. [ABSTRACT FROM AUTHOR]

The article offers a perspective on variants of unknown significance (VUS) in precision oncology and their impact on treatment choice. It presents clinical cases of patients with pancreatic cancer, a family history of cancer, and germline or somatic VUS, to illustrate the challenges of VUS in clinical practice. It considers pathogenic, germline mutations as loss-of-function mutations in tumor suppressors and presents data regarding pathogenic TET3 mutations and VUS.

Most extrauterine high-grade serous carcinomas (HGSCs) are thought to develop first in the distal fallopian tube. Most models of HGSC assume origin from relatively stable, noninvasive serous tubal intraepithelial carcinomas. However, widespread tumor involvement in the absence of a serous tubal intraepithelial carcinoma could occur after catastrophic genomic events (CGEs; such as chromothripsis or polyploidy). Twenty-six HGSCs assigned to fallopian tube (n = 9, group 1) and/or ovary (n = 9, group 2), and primary peritoneal (n = 8, group 3) were assessed by microarray (Oncoscan). CGEs were identified in 15/26 (57.7%); chromothripsis-like pattern in 13/26 (50.0%) and polyploidy in 6/26 (23.1%). CGE was seen in 4/9 (44.4%), 9/9 (100%), and 2/8 (25%) cases in groups 1. 2, and 3, respectively. Overall, CGEs were seen in 9/9 (100%) cases with grossly evident ovarian parenchymal involvement versus 6/17 (35.3%) without (P = 0.0024). Ovarian size (measured on the long axis) correlated with CGE positivity (P = 0.016). CGEs are significantly more common in HGSCs with ovarian parenchymal involvement compared with those limited to the fallopian tube and/or extraovarian tissues. These associations suggest geographically different tumor growth patterns and support the subdivision of HGSCs according to not only the stage but also tumor distribution. They have implications for clinical and pathologic presentation, trajectory of tumor evolution, and in the case of primary peritoneal HGSCs, potentially unique precursors to tumor transitions that could inform or influence cancer prevention efforts. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer arises through the accumulation of somatic mutations in key biological pathways. This paper aims to develop a probabilistic approach to delineate the temporal order of mutations during cancer development based on mutation profile data from a cohort of patients. A unique feature of our method is that it incorporates intra-tumor heterogeneity (ITH) information, which refers to the heterogeneous cell populations within a tumor and characterizes the evolutionary history of the tumor. We showed that by integrating ITH, pathways, and functional annotation information, our method yielded high accuracy in inferring the temporal order of pathway mutations during carcinogenesis. The development of cancer involves the accumulation of somatic mutations in several essential biological pathways. Delineating the temporal order of pathway mutations during tumorigenesis is crucial for comprehending the biological mechanisms underlying cancer development and identifying potential targets for therapeutic intervention. Several computational and statistical methods have been introduced for estimating the order of somatic mutations based on mutation profile data from a cohort of patients. However, one major issue of current methods is that they do not take into account intra-tumor heterogeneity (ITH), which limits their ability to accurately discern the order of pathway mutations. To address this problem, we propose PATOPAI, a probabilistic approach to estimate the temporal order of mutations at the pathway level by incorporating ITH information as well as pathway and functional annotation information of mutations. PATOPAI uses a maximum likelihood approach to estimate the probability of pathway mutational events occurring in a specific sequence, wherein it focuses on the orders that are consistent with the phylogenetic structure of the tumors. Applications to whole exome sequencing data from The Cancer Genome Atlas (TCGA) illustrate our method's ability to recover the temporal order of pathway mutations in several cancer types. [ABSTRACT FROM AUTHOR]

Simple Summary: This review explores the challenges of drug resistance in cancer treatment and discusses innovative strategies to overcome them. Researchers aim to understand how cancer cells develop resistance to therapies and explore new ways to improve treatment outcomes. They investigate advanced genomic technologies, immunotherapies like CAR-T cells, and targeted therapies that specifically attack cancer cells. By identifying these mechanisms and developing novel approaches, this research aims to enhance the effectiveness of cancer treatments and improve patient survival rates. Insights gained could lead to significant advancements in how we combat drug resistance in cancer, offering hope for better outcomes in the future. The rise of drug resistance in cancer cells presents a formidable challenge in modern oncology, necessitating the exploration of innovative therapeutic strategies. This review investigates the latest advancements in overcoming drug resistance mechanisms employed by cancer cells, focusing on emerging therapeutic modalities. The intricate molecular insights into drug resistance, including genetic mutations, efflux pumps, altered signaling pathways, and microenvironmental influences, are discussed. Furthermore, the promising avenues offered by targeted therapies, combination treatments, immunotherapies, and precision medicine approaches are highlighted. Specifically, the synergistic effects of combining traditional cytotoxic agents with molecularly targeted inhibitors to circumvent resistance pathways are examined. Additionally, the evolving landscape of immunotherapeutic interventions, including immune checkpoint inhibitors and adoptive cell therapies, is explored in terms of bolstering anti-tumor immune responses and overcoming immune evasion mechanisms. Moreover, the significance of biomarker-driven strategies for predicting and monitoring treatment responses is underscored, thereby optimizing therapeutic outcomes. For insights into the future direction of cancer treatment paradigms, the current review focused on prevailing drug resistance challenges and improving patient outcomes, through an integrative analysis of these emerging therapeutic strategies. [ABSTRACT FROM AUTHOR]

Simple Summary: The purpose of this study is to emphasize the importance of genetic testing for healthy individuals with a strong family history of hereditary malignancies. A total of 103 healthy subjects with at least two relatives with cancer were enrolled. By NGS analysis of 27 genes, 5% were found to carry a pathogenic variant in a hereditary cancer susceptibility gene. In the era of personalized medicine, genetic testing of healthy subjects in the absence of a living affected collateral is crucially important for early diagnosis, clinical surveillance and surgical choice. Hereditary cancer syndromes caused by germline mutations account for 5–10% of all cancers. The finding of a genetic mutation could have far-reaching consequences for pharmaceutical therapy, personalized prevention strategies, and cascade testing. According to the National Comprehensive Cancer Network's (NCCN) and the Italian Association of Medical Oncology (AIOM) guidelines, unaffected family members should be tested only if the affected one is unavailable. This article explores whether germline genetic testing may be offered to high-risk families for hereditary cancer even if a living affected relative is missing. A retrospective study was carried out on 103 healthy subjects tested from 2017 to 2023. We enrolled all subjects with at least two first- or second-degree relatives affected by breast, ovarian, pancreatic, gastric, prostate, or colorectal cancer. All subjects were tested by Next Generation Sequencing (NGS) multi-gene panel of 27 cancer-associated genes. In the study population, 5 (about 5%) pathogenic/likely pathogenic variants (PVs/LPVs) were found, while 40 (42%) had a Variant of Uncertain Significance (VUS). This study highlights the importance of genetic testing for individuals with a strong family history of hereditary malignancies. This approach would allow women who tested positive to receive tailored treatment and prevention strategies based on their personal mutation status. [ABSTRACT FROM AUTHOR]

In Brief: While approximately 15% of patients with advanced cancer have an inherited predisposition to malignancy, many patients who carry a pathogenic germline variant do not qualify for genetic testing based on current clinical guidelines. Offering genetic testing to those patients with the highest likelihood of carrying a germline mutation is preferable to unselected screening. In this study, investigators used a tiered gene list to help identify patients whose somatic mutations were more likely to be found in the germline. Genes were classified into 3 tiers based on the likelihood of germline pathogenicity. Patients whose routine somatic sequencing tests revealed a mutation that was classified as high-risk (tier 1) were offered participation in this study. Enrolled patients received standard genetic counseling and were offered germline genetic testing via a commercial laboratory next-generation sequencing panel. In all, 9.2% of somatic sequencing tests harbored a high-risk (tier 1) gene mutation; an inherited predisposition to cancer was confirmed in almost 50% of patients enrolled in the study. Patients with gastrointestinal or brain cancers that displayed a high-risk variant were more likely to be confirmed as having a germline mutation than were those with other cancer types. These findings support expanding clinical criteria and lowering barriers for germline genetic testing in patients with advanced cancer. [ABSTRACT FROM AUTHOR]

The last decade has seen rapid progress in the use of genomic tests, including gene panels, whole‐exome sequencing, and whole‐genome sequencing, in research and clinical cancer care. These advances have created expansive opportunities to characterize the molecular attributes of cancer, revealing a subset of cancer‐associated aberrations called driver mutations. The identification of these driver mutations can unearth vulnerabilities of cancer cells to targeted therapeutics, which has led to the development and approval of novel diagnostics and personalized interventions in various malignancies. The applications of this modern approach, often referred to as precision oncology or precision cancer medicine, are already becoming a staple in cancer care and will expand exponentially over the coming years. Although genomic tests can lead to better outcomes by informing cancer risk, prognosis, and therapeutic selection, they remain underutilized in routine cancer care. A contributing factor is a lack of understanding of their clinical utility and the difficulty of results interpretation by the broad oncology community. Practical guidelines on how to interpret and integrate genomic information in the clinical setting, addressed to clinicians without expertise in cancer genomics, are currently limited. Building upon the genomic foundations of cancer and the concept of precision oncology, the authors have developed practical guidance to aid the interpretation of genomic test results that help inform clinical decision making for patients with cancer. They also discuss the challenges that prevent the wider implementation of precision oncology. [ABSTRACT FROM AUTHOR]

Simple Summary: BRAF mutations are classified into four categories based on molecular characteristics, but only Class 1 BRAF V600 have effective targeted treatment strategies. With increasing access to next-generation sequencing, oncologists are more frequently uncovering non-V600 BRAF mutations, where there remains a scarcity of effective therapies. Responsiveness to MAPK pathway inhibitors differs according to the BRAF mutation class and primary tumor type. For this reason, we sought to determine whether key demographic, genomic, and transcriptomic differences existed between classes. This cross-sectional study analyzes the largest dataset of BRAF-mutated cancers to date. Our findings propose insights to optimize clinical trial design and patient selection in the pursuit of developing effective treatment strategies for patients whose tumors harbor non-V600 BRAF mutations. This study also offers insights into the potential of targeting alternative pathways in addition to the MAPK pathway as part of combinatorial treatment strategies. Background: BRAF mutations are classified into four molecularly distinct groups, and Class 1 (V600) mutant tumors are treated with targeted therapies. Effective treatment has not been established for Class 2/3 or BRAF Fusions. We investigated whether BRAF mutation class differed according to clinical, genomic, and transcriptomic variables in cancer patients. Methods: Using the AACR GENIE (v.12) cancer database, the distribution of BRAF mutation class in adult cancer patients was analyzed according to sex, age, primary race, and tumor type. Genomic alteration data and transcriptomic analysis was performed using The Cancer Genome Atlas. Results: BRAF mutations were identified in 9515 (6.2%) samples among 153,834, with melanoma (31%), CRC (20.7%), and NSCLC (13.9%) being the most frequent cancer types. Class 1 harbored co-mutations outside of the MAPK pathway (TERT, RFN43) vs. Class 2/3 mutations (RAS, NF1). Across all tumor types, Class 2/3 were enriched for alterations in genes involved in UV response and WNT/β-catenin. Pathway analysis revealed enrichment of WNT/β-catenin and Hedgehog signaling in non-V600 mutated CRC. Males had a higher proportion of Class 3 mutations vs. females (17.4% vs. 12.3% q = 0.003). Non-V600 mutations were generally more common in older patients (aged 60+) vs. younger (38% vs. 15% p < 0.0001), except in CRC (15% vs. 30% q = 0.0001). Black race was associated with non-V600 BRAF alterations (OR: 1.58; p < 0.0001). Conclusions: Class 2/3 BRAFs are more present in Black male patients with co-mutations outside of the MAPK pathway, likely requiring additional oncogenic input for tumorigenesis. Improving access to NGS and trial enrollment will help the development of targeted therapies for non-V600 BRAF mutations. [ABSTRACT FROM AUTHOR]

Simple Summary: This study addresses the global healthcare challenge of cancer by investigating hereditary cancer syndromes (HCS) and their genetic underpinnings. Using a multigene hereditary cancer panel, we examined Russian patients with suspected HCS, revealing that 21.6% had pathogenic or likely pathogenic genetic variants. Predominant mutations were found in BRCA1/BRCA2, CHEK2, and ATM genes, and we identified 16 previously undescribed variants in MUTYH, GALNT12, MSH2, MLH1, MLH3, EPCAM, and POLE genes. Our findings underscore the importance of comprehensive genetic testing for personalized cancer prevention and treatment. This research contributes essential genetic insights, particularly in regions like Russia where epidemiological data are limited, establishing the way for improved understanding and management of hereditary cancer syndromes. Cancer is a major global public health challenge, affecting both quality of life and mortality. Recent advances in genetic research have uncovered hereditary cancer syndromes (HCS) that predispose individuals to malignant neoplasms. While traditional single-gene testing has focused on high-penetrance genes, the past decade has seen a shift toward multigene panels, which facilitate the analysis of multiple genes associated with specific HCS. This approach reveals variants in less-studied gene regions and improves our understanding of cancer predisposition. In a study composed of Russian patients with clinical signs of HCS, we used a multigene hereditary cancer panel and revealed 21.6% individuals with pathogenic or likely pathogenic genetic variants. BRCA1/BRCA2 mutations predominated, followed by the CHEK2 and ATM variants. Of note, 16 previously undescribed variants were identified in the MUTYH, GALNT12, MSH2, MLH1, MLH3, EPCAM, and POLE genes. The implications of the study extend to personalized cancer prevention and treatment strategies, especially in populations lacking extensive epidemiological data, such as Russia. Overall, our research provides valuable genetic insights that give the way for further investigation and advances in the understanding and management of hereditary cancer syndromes. [ABSTRACT FROM AUTHOR]

Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools. [ABSTRACT FROM AUTHOR]

Simple Summary: During the last few decades, the basis for a genetic predisposition for several cancer syndromes has been clarified, and the highly penetrant/high-risk genes mutated in familial cases are currently subjected to genetic diagnostic screening programs. Mutation testing in these genes has a major impact on genetic counseling, defines the prognosis of carriers, identifies the most appropriate and personalized prophylactic measures, and increases the chance of survival. We aim to underline the effectiveness of the multigene panel in increasing the detection rate of germline mutations in cancer patients and consequently improve the healthy carriers' identification. Background: Several hereditary–familial syndromes associated with various types of tumors have been identified to date, evidencing that hereditary cancers caused by germline mutations account for 5–10% of all tumors. Advances in genetic technology and the implementation of Next-Generation Sequencing (NGS) have accelerated the discovery of several susceptibility cancer genes, allowing for the detection of cancer-predisposing mutations in a larger number of cases. The aim of this study is to highlight how the application of an NGS-multigene panel to a group of oncological patients subsequently leads to improvement in the identification of carriers of healthy pathogenic variants/likely pathogenic variants (PVs/LPVs) and prevention of the disease in these cases. Methods: Starting from a total of 110 cancer patients carrying PVs/LPVs in genes involved in cancer susceptibility detected via a customized NGS panel of 27 cancer-associated genes, we enrolled 250 healthy collateral family members from January 2020 to July 2022. The specific PVs/LPVs identified in each proband were tested in healthy collateral family members via Sanger sequencing. Results: A total of 131 out of the 250 cases (52%) were not carriers of the mutation detected in the affected relative, while 119 were carriers. Of these, 81/250 patients carried PVs/LPVs on BRCA1/2 (33%), 35/250 harbored PVs/LPVs on other genes beyond BRCA1 and BRCA2 (14%), and 3/250 (1%) were PVs/LPVs carriers both on BRCA1/2 and on another susceptibility gene. Conclusion: Our results show that the analysis of BRCA1/2 genes would have only resulted in a missed diagnosis in a number of cases and in the lack of prevention of the disease in a considerable percentage of healthy carriers with a genetic mutation (14%). [ABSTRACT FROM AUTHOR]

It has been 70 years since Barbara McClintock discovered transposable elements (TE), and the mechanistic studies and functional applications of transposable elements have been at the forefront of life science research. As an essential part of the genome, TEs have been discovered in most species of prokaryotes and eukaryotes, and the relative proportion of the total genetic sequence they comprise gradually increases with the expansion of the genome. In humans, TEs account for about 40% of the genome and are deeply involved in gene regulation, chromosome structure maintenance, inflammatory response, and the etiology of genetic and non-genetic diseases. In-depth functional studies of TEs in mammalian cells and the human body have led to a greater understanding of these fundamental biological processes. At the same time, as a potent mutagen and efficient genome editing tool, TEs have been transformed into biological tools critical for developing new techniques. By controlling the random insertion of TEs into the genome to change the phenotype in cells and model organisms, critical proteins of many diseases have been systematically identified. Exploiting the TE's highly efficient in vitro insertion activity has driven the development of cuttingedge sequencing technologies. Recently, a new technology combining CRISPR with TEs was reported, which provides a novel targeted insertion system to both academia and industry. We suggest that interrogating biological processes that generally depend on the actions of TEs with TEs-derived genetic tools is a very efficient strategy. For example, excessive activation of TEs is an essential factor in the occurrence of cancer in humans. As potent mutagens, TEs have also been used to unravel the key regulatory elements and mechanisms of carcinogenesis. Through this review, we aim to effectively combine the traditional views of TEs with recent research progress, systematically link the mechanistic discoveries of TEs with the technological developments of TE-based tools, and provide a comprehensive approach and understanding for researchers in different fields. [ABSTRACT FROM AUTHOR]

Background: Recent advances in molecular biology and genomics have revolutionized the understanding of the intricate molecular underpinnings of cancer. Next-generation sequencing analysis now allows identification of specific actionable genetic alterations. This breakthrough has paved the way for precision medicine in oncology, redefining the conventional clinical trial landscape and enabling personalized approaches to cancer treatment. Current Concepts: The shift toward precision medicine involves a fundamental departure from the traditional Phases 1-4 clinical trial protocols. Instead of using uniform treatment pathways, personalized therapies are designed based on the genetic profiles of individual patients. Tumor-agnostic clinical trials are becoming as a prominent concept, encompassing innovative adaptive designs that adapt treatments to specific genetic variations. Master protocols such as umbrella studies, basket trials, platform studies, and master observational trials exemplify this transformation. Discussion and Conclusion: International precision medicine research is characterized by exemplar studies such as the NCI-MATCH study in the United States, the Drug Rediscovery Protocol study in the Netherlands, and the Targeted Agent and Profiling Utilization Registry study in the United States. Korean oncology research also contributed to the international effort in precision medicine through initiatives like K-MASTER and the Korean Precision Medicine Networking Group, which is making commendable contributions to the global precision medicine movements. [ABSTRACT FROM AUTHOR]

Melanoma antigen (MAGE) genes encode for a family of proteins that share a common MAGE homology domain. These genes are conserved in eukaryotes and have been linked to a variety of cellular and developmental processes including ubiquitination and oncogenesis in cancer. Current knowledge on the MAGE family of proteins mainly comes from the analysis of yeast and human cell lines, and their functions have not been reported at an organismal level in animals. Caenorhabditis elegans only encodes 1 known MAGE gene member, mage-1 (NSE3 in yeast), forming part of the SMC-5/6 complex. Here, we characterize the role of mage-1/nse-3 in mitosis and meiosis in C. elegans. mage-1/nse-3 has a role in inter-sister recombination repair during meiotic recombination and for preserving chromosomal integrity upon treatment with a variety of DNA-damaging agents. MAGE-1 directly interacts with NSE-1 and NSE-4. In contrast to smc-5, smc-6, and nse-4 mutants which cause the loss of NSE-1 nuclear localization and strong cytoplasmic accumulation, mage-1/nse-3 mutants have a reduced level of NSE-1::GFP, remnant NSE-1::GFP being partially nuclear but largely cytoplasmic. Our data suggest that MAGE-1 is essential for NSE-1 stability and the proper functioning of the SMC-5/6 complex. [ABSTRACT FROM AUTHOR]

Introduction: Sarcomas are classified into two types, bone sarcoma and soft tissue sarcoma (STS), which account for approximately 1% of adult solid malignancies and 20% of pediatric solid malignancies. There exist more than 50 subtypes within the two types of sarcoma. Each subtype is highly diverse and characterized by significant variations in morphology and phenotypes. Understanding tumor molecular genetics is helpful in improving the diagnostic accuracy of tumors that have been difficult to classify based on morphology alone or that have overlapping morphological features. The different molecular characteristics of bone sarcoma and STS in China remain poorly understood. Therefore, this study aimed to analyze genomic landscapes and actionable genomic alterations (GAs) as well as tumor mutational burden (TMB), microsatellite instability (MSI), and programmed death ligand-1 (PD-L1) expression among Chinese individuals diagnosed with primary bone sarcomas and STS. Methods: This retrospective study included 145 patients with primary bone sarcomas (n = 75) and STS (n = 70), who were categorized based on the 2020 World Health Organization classification system. Results: Patients diagnosed with bone sarcomas were significantly younger than those diagnosed with STS (p < 0.01). The top 10 frequently altered genes in bone sarcoma and STS were TP53, CDKN2A, CDKN2B, MAP3K1, LRP1B, MDM2, RB1, PTEN, MYC, and CDK4. The EWSR1 fusions exhibited statistically significant differences (p < 0.01) between primary bone sarcoma and STS in terms of their altered genes. Based on the actionable genes defined by OncoKB, actionable GAs was found in 30.7% (23/75) of the patients with bone sarcomas and 35.7% (25/70) of those with STS. There were 4.0% (3/75) patients with bone sarcoma and 4.3% (3/70) patients with STS exhibited high tumor mutational burden (TMBH) (TMB = 10). There was only one patient with STS exhibited MSI-L, while the remaining cases were microsatellite stable. The positive rate of PD-L1 expression was slightly higher in STS (35.2%) than in bone sarcoma (33.3%), however, this difference did not reach statistical significance. The expression of PD-L1 in STS patients was associated with a poorer prognosis (p = 0.007). Patients with STS had a better prognosis than those with bone sarcoma, but the observed difference did not attain statistical significance (p = 0.21). Amplification of MET and MYC genes were negatively correlated with clinical prognosis in bone tumors (p<0.01). Discussion: In conclusion, bone sarcoma and STS have significantly different clinical and molecular characteristics, suggesting that it is vital to diagnose accurately for clinical treatment. Additionally, comprehensive genetic landscape can provide novel treatment perspectives for primary bone sarcoma and STS. Taking TMB, MSI, PD-L1 expression, and OncoKB definition together into consideration, there are still many patients who have the potential to respond to targeted therapy or immunotherapy. [ABSTRACT FROM AUTHOR]

Simple Summary: This review describes how the two processes of angiogenesis (the generation of new blood vessels) and neurogenesis (the generation of new nerve fibers) act together to drive cancer progression. It also describes how they are both associated with a lower rate of patient survival. These two processes share signaling pathways and, in many cases, the initiation of one leads to the initiation of the other. Both processes require tissue alterations and are reliant on cell migration. They favor cancer progression by supplying the tumor with nutrients and facilitating communication/movements within the tumor. Thus, these two processes contribute to the spread of cancers, as tumors can use nerve fibers and blood vessels as a routes to migrate from the initial point of cancer development to the surrounding area or to the distal sites of the body. Angiogenesis, the generation of new blood vessels, is one of the hallmarks of cancer. The growing tumor requires nutrients and oxygen. Recent evidence has shown that tumors release signals to attract new nerve fibers and stimulate the growth of new nerve fibers. Neurogenesis, neural extension, and axonogenesis assist in the migration of cancer cells. Cancer cells can use both blood vessels and nerve fibers as routes for cells to move along. In this way, neurogenesis and angiogenesis both contribute to cancer metastasis. As a result, tumor-induced neurogenesis joins angiogenesis and immunosuppression as aberrant processes that are exacerbated within the tumor microenvironment. The relationship between these processes contributes to cancer development and progression. The interplay between these systems is brought about by cytokines, neurotransmitters, and neuromodulators, which activate signaling pathways that are common to angiogenesis and the nervous tissue. These include the AKT signaling pathways, the MAPK pathway, and the Ras signaling pathway. These processes also both require the remodeling of tissues. The interplay of these processes in cancer provides the opportunity to develop novel therapies that can be used to target these processes. [ABSTRACT FROM AUTHOR]

Simple Summary: Uterine serous carcinomas (USC) represent a rare and aggressive subtype of uterine cancer. Patients often receive adjuvant therapy including chemotherapy and/or radiation after surgery, which has limited efficacy in preventing high rates of recurrence. Understanding the tumor microenvironment in USC is paramount to developing new targeted therapies at the time of progression. This study evaluated the genomic instability score (GIS), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs) in 53 patients with USC. In this cohort, the median TMB was 1.35 mutations/megabase (mt/Mb); patients with TMB greater than the median had improved survival outcomes. The median GIS was 31, and a higher GIS was not associated with improved survival. We characterized immune cell populations and found that increased immune populations were not associated with a better prognosis. Background: Uterine serous carcinomas represent 10% of uterine carcinomas but account for nearly 40% of deaths from the disease. Improved molecular characterization of these tumors is instrumental in guiding targeted treatment and improving outcomes. This study assessed the genomic instability score (GIS), tumor mutational burden (TMB), and tumor-infiltrating lymphocytes (TILs) in patients with USC. Methods: A retrospective cohort study evaluated patients with USC following staging surgery. The GIS and TMB were determined from archived specimens. We evaluated the tumoral expression of CD3, CD4, CD8, FOXP3, and CD68 using immunohistochemistry. T-tests were used to assess associations of TILs with the GIS. Results: We evaluated 53 patients with USC. The median GIS was 31 (range: 0–52) and a higher GIS was not associated with progression-free (PFS) or overall survival (OS). The median TMB was 1.35 mt/Mb; patients with TMB > 1.35 mt/Mb had improved PFS and OS (p = 0.005; p = 0.002, respectively). Tumors with increased CD3+ and CD4+ immune cells had a higher mean GIS (p = 0.013, p = 0.002). Conclusions: TMB > 1.35 mt/Mb was associated with improved survival in USC patients, whereas the GIS was not. Lower TMB thresholds may provide prognostic value for less immunogenic tumors such as USC. In this limited cohort, we observed that increased TIL populations were correlated with a higher GIS. [ABSTRACT FROM AUTHOR]

We convened an international working group to examine the issues that challenge equity and inclusion in genetic medicine. Specifically, 72 internationally known experts in oncology and cancer genetics from 34 countries (the Global Oncology Medical Diplomacy Working Group), gathered virtually on January 4–5, 2022, for the "Humanity Cancer Germline Convergence and Divergence Cancer Predispositions" conference hosted by Memorial Sloan Kettering Cancer Center, in collaboration with the United Arab Emirates Ministry of Health and the Al Jalila Foundation. The goal of the conference was to broaden transnational understanding of the current state of genetics in preventive and therapeutic cancer medicine, and to define barriers to increased uptake of germline genomics to decrease the international burden of cancer. Here, we highlight the overarching barriers that were defined through this effort. These global barriers to incorporating germline genomics into optimal cancer care can inform ongoing research, collaboration, and advocacy for equitable, cost-effective genomic medicine for populations worldwide. [ABSTRACT FROM AUTHOR]

Simple Summary: Cells infected with high-risk human papillomaviruses (HPV) can accumulate DNA damage and eventually transform into HPV-driven cancers. Genome instability, or the progressive accumulation of DNA alterations (e.g., mutations), in HPV-infected cells is directly induced by the HPV genes and indirectly promoted by HPV infection through the consequences of chronic infection maintenance, increased cell growth, and accumulation of damaging mutations in genes that themselves affect genome instability. While the HPV genome typically exists as a separate entity within cells, genome instability increases the chances of HPV integrating within the host (human) genome, which is common in HPV-induced cancers. The DNA regions surrounding HPV integrations are unstable and can undergo complex alterations that affect both human and HPV genes. This review discusses HPV-dependent and -independent drivers and mechanisms of genome instability in HPV-driven cancers, both globally and around sites of HPV integration, and describes the changes induced in the tumour genome. Human papillomavirus (HPV) is the causative driver of cervical cancer and a contributing risk factor of head and neck cancer and several anogenital cancers. HPV's ability to induce genome instability contributes to its oncogenicity. HPV genes can induce genome instability in several ways, including modulating the cell cycle to favour proliferation, interacting with DNA damage repair pathways to bring high-fidelity repair pathways to viral episomes and away from the host genome, inducing DNA-damaging oxidative stress, and altering the length of telomeres. In addition, the presence of a chronic viral infection can lead to immune responses that also cause genome instability of the infected tissue. The HPV genome can become integrated into the host genome during HPV-induced tumorigenesis. Viral integration requires double-stranded breaks on the DNA; therefore, regions around the integration event are prone to structural alterations and themselves are targets of genome instability. In this review, we present the mechanisms by which HPV-dependent and -independent genome instability is initiated and maintained in HPV-driven cancers, both across the genome and at regions of HPV integration. [ABSTRACT FROM AUTHOR]

Simple Summary: Recently, radiogenomics has played a significant role and offered a new understanding of cancer's biology and behavior in response to standard therapy. It also provides a more precise prognosis, investigation, and analysis of the patient's cancer. Over the years, Artificial Intelligence (AI) has provided a significant strength in radiogenomics. In this paper, we offer computational and oncological prospects of the role of AI in radiogenomics, as well as its offers, achievements, opportunities, and limitations in the current clinical practices. Radiogenomics, a combination of "Radiomics" and "Genomics," using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computational as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles. [ABSTRACT FROM AUTHOR]

Simple Summary: The metabolic alterations characteristic of cancer cells play a significant role in tumors' natural history and response to therapy. Recent technological advances have allowed the production of unprecedented amounts of data on many types of cancers. We exploited the most comprehensive collection of such data, The Cancer Genome Atlas (TCGA), to systematically investigate the associations between metabolic alterations and other tumor features. We used sets of genes known to be associated with specific metabolic pathways to classify patients into "metabolic subtypes". Then, we systematically looked for associations between the metabolic subtypes and other tumor features, including histological classification, patient survival, and genome alterations. Our results, while correlative in nature, can provide a guide to the formulation of specific mechanistic hypotheses to be tested experimentally so as to improve our understanding of the biology of cancer and our ability to tailor therapeutic interventions to the specific features of each patient. The alterations of metabolic pathways in cancer have been investigated for many years, beginning long before the discovery of the role of oncogenes and tumor suppressors, and the last few years have witnessed renewed interest in this topic. Large-scale molecular and clinical data on tens of thousands of samples allow us to tackle the problem from a general point of view. Here, we show that transcriptomic profiles of tumors can be exploited to define metabolic cancer subtypes, which can be systematically investigated for associations with other molecular and clinical data. We find thousands of significant associations between metabolic subtypes and molecular features such as somatic mutations, structural variants, epigenetic modifications, protein abundance and activation, and with clinical/phenotypic data, including survival probability, tumor grade, and histological types, which we make available to the community in a dedicated web resource. Our work provides a methodological framework and a rich database of statistical associations, which will contribute to the understanding of the role of metabolic alterations in cancer and to the development of precision therapeutic strategies. [ABSTRACT FROM AUTHOR]

The incidence of cancer globally is increasing, partly due to lifestyle factors. Despite a better understanding of cancer biology and advancement in cancer management and therapies, current strategies in cancer treatment remain costly and cause socioeconomic burden especially in Asian countries. Hence, instead of putting more efforts in searches for new cancer cures, attention has now shifted to understanding how to mitigate cancer risk by modulating lifestyle factors. It has been established that carcinogenesis is multifactorial, and the important detrimental role of oxidative stress, chronic inflammation, and genomic instability is evident. To date, there is no study linking dietary pattern and genomic stability in cancer risk in the Asian food landscape. Thus, this present review article discusses recent literature on dietary pattern and genomic stability and its relationship with cancer risk in Asia. [ABSTRACT FROM AUTHOR]

The difficulty in interpreting somatic alterations is correlated with the increase in sequencing panel size. To correctly guide the clinical management of patients with cancer, there needs to be accurate classification of pathogenicity followed by actionability assessment. Here, we describe a specific detailed workflow for the classification of the pathogenicity of somatic variants in cancer into five categories: benign, likely benign, unknown significance, likely pathogenic and pathogenic. Classification is obtained by combining a set of eight relevant criteria in favour of either a pathogenic or a benign effect (pathogenic stand-alone, pathogenic very strong, pathogenic strong, pathogenic moderate, pathogenic supporting, benign supporting, benign strong and benign stand-alone). Our guide is concordant with the ACMG/AMP 2015 guidelines for germline variants. Interpretation of somatic variants requires considering specific criteria, such as the disease and therapeutic context, co-occurring genomic events in the tumour when available and the use of cancer-specific variant databases. In addition, the gene role in tumorigenesis (oncogene or tumour suppressor gene) also needs to be taken into consideration. Our classification could contribute to homogenize best practices on somatic variant pathogenicity interpretation and improve interpretation consistency both within and between laboratories. • Assessing pathogenicity of tumour variants with a systematic approach. • Connecting with the ACMG/AMP guidelines for germline variants. • Encompassing somatic specific criteria. [ABSTRACT FROM AUTHOR]

With the significant advances in cancer genomics using next-generation sequencing technologies, genomic and molecular profiling-based precision medicine is used as a part of routine clinical test for guiding and selecting the most appropriate treatments for individual cancer patients. Although many molecular-targeted therapies for a number of actionable genomic alterations have been developed, the clinical application of such information is still limited to a small proportion of cancer patients. In this review, we summarize the current status of personalized drug selection based on genomic and molecular profiling and highlight the challenges how we can further utilize the individual genomic information. Cancer immunotherapies, including immune checkpoint inhibitors, would be one of the potential approaches to apply the results of genomic sequencing most effectively. Highly cancer-specific antigens derived from somatic mutations, the so-called neoantigens, occurring in individual cancers have been in focus recently. Cancer immunotherapies, which target neoantigens, could lead to a precise treatment for cancer patients, despite the challenge in accurately predicting neoantigens that can induce cytotoxic T cells in individual patients. Precise prediction of neoantigens should accelerate the development of personalized immunotherapy including cancer vaccines and T-cell receptor-engineered T-cell therapy for a broader range of cancer patients. [ABSTRACT FROM AUTHOR]

The article discusses about cancer genomic sequencing and precision medicine. Topics of discussion includes Genome sequencing technology is used to benefit patients through precision medicine. The PM is the medical treatments personalized according to individual's germline or tumor characteristics using genomic sequencing to optimize health outcomes. But it lacks clinical implementation, access and benefit among poor and minority patients.

The article discusses "genetic science has significantly changed the way approach testing for and treating hereditary cancer syndromes." Topics include "identifying a family at high risk for cancer lead to genetic testing for cancer susceptibility," and a systematic process begins with identifying a condition or a pathogenic variant associated with the condition in an individual patient.

BACKGROUND AND PURPOSE: Glioblastomas (GBMs) that involve the subventricular zone (SVZ) have a poor prognosis, possibly due to recruitment of neural stem cells. The purpose of this study was to evaluate whether SVZ involvement by lower grade gliomas (LGG), WHO grade II and III, similarly predicts poorer outcomes. We further assessed whether tumor genetics and cellularity are associated with SVZ involvement and outcomes. METHODS: Forty‐five consecutive LGG patients with preoperative imaging and next generation sequencing were included in this study. Regional SVZ involvement and whole tumor apparent diffusion coefficient (ADC) values, as a measure of cellularity, were assessed on magnetic resonance imaging. Progression was determined by RANO criteria. Kaplan‐Meier curves and Cox regression analyses were used to determine the hazard ratios (HR) for progression and survival. RESULTS: Frontal, parietal, temporal, and overall SVZ involvement and ADC values were not associated with progression or survival (P ≥.05). However, occipital SVZ involvement, seen in two patients, was associated with a higher risk of tumor progression (HR = 6.6, P =.016) and death (HR = 31.5, P =.015), CDKN2A/B mutations (P =.03), and lower ADC histogram values at the 5th (P =.026) and 10th percentiles (P =.046). Isocitrate dehydrogenase, phosphatase and tensin homolog, epidermal growth factor receptor, and cyclin‐dependent kinase 4 mutations were also prognostic (P ≤.05). CONCLUSIONS: Unlike in GBM, overall SVZ involvement was not found to strongly predict poor prognosis in LGGs. However, occipital SVZ involvement, though uncommon, was prognostic and found to be associated with CDKN2A/B mutations and tumor hypercellularity. Further investigation into these molecular mechanisms underlying occipital SVZ involvement in larger cohorts is warranted. [ABSTRACT FROM AUTHOR]

Background: Androgen deprivation therapy (ADT) is extensively employed in treatment of prostate cancer. Some studies have found increased risk of Alzheimer's disease and cognitive impairment in patients treated with ADT. Aim: Since the uncertainty about ADT and dementia might relate to the genetics of prostate cancer and Alzheimer's disease, we used the Cancer Genome Atlas (TCGA) to examine the relationship between genes implicated in Alzheimer's disease and genes implicated in prostate cancer in men with prostate cancer. Materials and Methods: The genomics of 492 prostate cancer cases in the Genomic Data Commons TCGA Prostate Cancer data set were examined. Results: Alterations (mutation, amplification or deletion) in prostate cancer gene speckletype POZ protein (SPOP) significantly co-occurred with alterations in Alzheimer's disease gene bridging integrator-1 (BIN1). Alterations in prostate cancer gene spectrin alpha 1 (SPTA1) significantly co-occurred with alterations in Alzheimer's disease gene CD2-associated protein (CD2AP) (p<0.001). The presence of somatic mutations (deleterious and missense/in frame) in SPOP disturbs BIN1 gene expression. SPOP and BIN1 RNA expression in 492 prostate cancer specimens was significantly positively correlated (p<0.001). Increased expression of SPOP in 492 cases of prostate cancer was associated with reduced survival (p=0.00275). BIN1 forms part of a network that interacts with the MYC oncogene, which is activated at the earliest phases of prostate cancer and is linked to disease aggressiveness. Men receiving ADT had tumor with a significantly higher Gleason score (p=0.023). Gleason score and BIN1 RNA expression in 499 prostate cancer specimens were significantly correlated (p<0.001). Conclusion: The severity of prostate cancer is determined by the genetics of the tumor itself, possibly at least in part by the interactions of SPOP/BIN1, MYC/BIN1 and SPTA1/CD2AP. Oncologists treats higher grade prostate cancer with more ADT, which serves as a surrogate marker for disease severity. A weakness of our study is that we did not examine Alzheimer's disease or dementia at all in patients with cancer, only co-occurrence of genetic alterations. Nevertheless, our analysis of TCGA data does not support the idea that ADT causes Alzheimer's disease or dementia. [ABSTRACT FROM AUTHOR]

The article presents the text of the lecture by clinical genetics professor John Burn. Among the issues he discussed include the emergence of genetic medicine and the role that clinical geneticists play in these development, the history of genomics, and the reliance of the diagnosis of metabolic disorders on technological advances in chromosome analysis.

There have been rapid advances in precision medicine since the Human Genome Project was completed in 2003, including several noteworthy advances in Women's Health. This includes significant advances in predicting individualized cancer risk based on hereditary cancer genetic testing, with the number of known cancer-predisposition genes extending well beyond BRCA1 and BRCA2. This has been coupled with gene-specific management guidelines for several gynecologic cancers. In addition, genetic testing can also inform therapy selection for women with gynecologic cancers. Here we address hereditary cancer and practical cancer genetics as it relates to the practicing Obstetrician/Gynecologist. [ABSTRACT FROM AUTHOR]

Background: Incorporation of next‐generation sequencing (NGS) technology into clinical utility in targeted and immunotherapies requires stringent validation, including the assessment of tumor mutational burden (TMB) and microsatellite instability (MSI) status by NGS as important biomarkers for response to immune checkpoint inhibitors. Materials and Methods: We designed an NGS assay, Cancer Sequencing YS panel (CSYS), and applied algorithms to detect five classes of genomic alterations and two genomic features of TMB and MSI. Results: By stringent validation, CSYS exhibited high sensitivity and predictive positive value of 99.7% and 99.9%, respectively, for single nucleotide variation; 100% and 99.9%, respectively, for short insertion and deletion (indel); and 95.5% and 100%, respectively, for copy number alteration (CNA). Moreover, CSYS achieved 100% specificity for both long indel (50–3,000 bp insertion and deletion) and gene rearrangement. Overall, we used 33 cell lines and 208 clinical samples to validate CSYS's NGS performance, and genomic alterations in clinical samples were also confirmed by fluorescence in situ hybridization, immunohistochemistry, and polymerase chain reaction (PCR). Importantly, the landscape of TMB across different cancers of Chinese patients (n = 3,309) was studied. TMB by CSYS exhibited a high correlation (Pearson correlation coefficient r = 0.98) with TMB by whole exome sequencing (WES). MSI measurement showed 98% accuracy and was confirmed by PCR. Application of CSYS in a clinical setting showed an unexpectedly high occurrence of long indel (6.3%) in a cohort of tumors from Chinese patients with cancer (n = 3,309), including TP53, RB1, FLT3, BRCA2, and other cancer driver genes with clinical impact. Conclusion: CSYS proves to be clinically applicable and useful in disclosing genomic alterations relevant to cancer target therapies and revealing biomarkers for immune checkpoint inhibitors. Implications for Practice: The study describes a specially designed sequencing panel assay to detect genomic alterations and features of 450 cancer genes, including its overall workflow and rigorous clinical and analytical validations. The distribution of pan‐cancer tumor mutational burden, microsatellite instability, gene rearrangement, and long insertion and deletion mutations was assessed for the first time by this assay in a broad array of Chinese patients with cancer. The Cancer Sequencing YS panel and its validation study could serve as a blueprint for developing next‐generation sequencing‐based assays, particularly for the purpose of clinical application. Incorporating next‐generation sequencing technology for use in targeted therapies and immunotherapies requires precise validation. This article describes a reliable next‐generation sequencing‐based panel assay, Cancer Sequencing YS panel (CSYS), for detecting genomic alterations. [ABSTRACT FROM AUTHOR]

Background: CDK12 loss‐of‐function (LOF) genomic alterations are associated with focal tandem duplications (FTDs) in ovarian and prostate cancers. Because these FTDs may produce fusion‐induced neoantigens (FINAs), CDK12 alteration is a candidate biomarker for immune checkpoint inhibitor sensitivity. Here we determine the prevalence of CDK12‐LOF alterations and their association with FTDs across diverse tumor types. Materials and Methods: A total of 142,133 tumor samples comprising 379 cancer types were sequenced (August 2014 to April 2018) by hybrid capture‐based comprehensive genomic profiling (Foundation Medicine, Cambridge, MA) as part of routine clinical care. Results were analyzed for base substitutions, short insertions/deletions, rearrangements, and copy number alterations. CDK12‐LOF genomic alterations were assessed for zygosity status and association with FTDs/focal copy number gain. Results: CDK12 genomic alterations were detected in 1.1% of all cases, most frequently in prostate cancer (5.6%), but were also observed at >1% frequency in 11 cancer types. Across multiple cancer types, including prostate, gastric/esophageal, ovarian, breast, and endometrial cancer, the number of FTDs was significantly increased in CDK12‐LOF versus CDK12 wild‐type cases. Notably, CDK12‐LOF was not consistently associated with a homologous recombination deficiency genomic signature. Quantitative assessment of CDK12‐associated FTDs by measurement of single copy number gains identified novel likely deleterious CDK12 kinase‐domain mutations in prostate and ovarian cancers. Conclusion: Detection of CDK12‐LOF genomic alterations and their association with FTDs in a diverse spectrum of malignancies suggests that immunotherapy approaches targeting FINAs derived from CDK12‐associated FTDs may be a broadly applicable strategy that could be explored across cancer types in a tumor‐agnostic manner. Implications for Practice: CDK12 inactivation in ovarian and prostate cancer results in the generation of focal tandem duplications, which can cause fusion‐induced neoantigens. In prostate cancer, CDK12 alterations have demonstrated promise as a potential predictive biomarker for response to immune checkpoint blockade. This study evaluated genomic profiling data from >142,000 tumors to determine the prevalence of CDK12 loss‐of‐function genomic alterations across tumor types and demonstrated that CDK12 alterations are associated with the tandem‐duplicator phenotype in cancer types other than ovarian and prostate cancer. The association of CDK12 alterations with focal tandem duplications across broad cancer types suggests that CDK12 inactivation warrants further investigation as a pan‐cancer biomarker for immunotherapy benefit. This article reports results of a comprehensive genomic profiling to determine the prevalence of CDK12 loss‐of‐function genomic alterations in multiple tumor types and associations with focal tandem duplications, potentially leading to a genomic biomarker of immunotherapy benefit. [ABSTRACT FROM AUTHOR]

In recent years, with both the development of next‐generation sequencing approaches and the Supreme Court decision invalidating gene patents, declining costs have contributed to the emergence of a new model of hereditary cancer genetic testing. Multigene panel testing (or multiplex testing) involves using next‐generation sequencing technology to determine the sequence of multiple cancer‐susceptibility genes. In addition to high‐penetrance cancer‐susceptibility genes, multigene panels frequently include genes that are less robustly associated with cancer predisposition. Scientific understanding about associations between many specific moderate‐penetrance gene variants and cancer risks is incomplete. The emergence of multigene panel tests has created unique challenges that may have meaningful psychosocial implications. Contrasted with the serial testing process, wherein patients consider the personal and clinical implications of each evaluated gene, with multigene panel testing, patients provide broad consent to whichever genes are included in a particular panel and then, after the test, receive in‐depth genetic counseling to clarify the distinct implications of their specific results. Consequently, patients undergoing multigene panel testing may have a less nuanced understanding of the test and its implications, and they may have fewer opportunities to self‐select against the receipt of particular types of genetic‐risk information. Evidence is conflicting regarding the emotional effects of this testing. [ABSTRACT FROM AUTHOR]

At the root of the so-called precision medicine or precision oncology, which is our focus here, is the hypothesis that cancer treatment would be considerably better if therapies were guided by a tumor’s genomic alterations. This hypothesis has sparked major initiatives focusing on whole-genome and/or exome sequencing, creation of large databases, and developing tools for their statistical analyses—all aspiring to identify actionable alterations, and thus molecular targets, in a patient. At the center of the massive amount of collected sequence data is their interpretations that largely rest on statistical analysis and phenotypic observations. Statistics is vital, because it guides identification of cancer-driving alterations. However, statistics of mutations do not identify a change in protein conformation; therefore, it may not define sufficiently accurate actionable mutations, neglecting those that are rare. Among the many thematic overviews of precision oncology, this review innovates by further comprehensively including precision pharmacology, and within this framework, articulating its protein structural landscape and consequences to cellular signaling pathways. It provides the underlying physicochemical basis, thereby also opening the door to a broader community. [ABSTRACT FROM AUTHOR]

Abstract Identifying people with an increased risk of developing cancer allows prophylactic surgery or screening to be offered, to try to reduce the chance of cancer developing or to detect it earlier. Family history information may indicate who should be assessed for cancer predisposition syndromes, but individual clinical and tumour characteristics are equally important to consider. Technological advances have expanded the availability of genetic analysis, which is now becoming mainstreamed into cancer diagnostic pathways. Identifying inherited mutations in cancer predisposition genes or somatic genetic variants within cancers has important implications for treatment decisions. Genomic analysis of tumours will increasingly be exploited to enable more accurate diagnosis, prognosis and targeted therapies with improved patient outcomes. [ABSTRACT FROM AUTHOR]

Purpose The implementation, benefits, and challenges of clinical pharmacist services within a Precision Medicine Program for cancer patients are described. By relating the practice model that was developed, this report may further encourage pharmacists at cancer centers nationally to be involved and lead precision-based care in the oncology setting. Summary A clinical pharmacist was integrated into a Precision Medicine Program for oncology patients using somatic testing to identify actionable mutations and apply targeted therapy to malignancies. This pharmacist served as a drug resource for the program's molecular tumor board and oncologists seeking precision-based oncologic strategies. The pharmacist was a facilitator of drug assistance and dispensing in collaboration with the specialty pharmacy and provided care to 14 oncology patients receiving precision-based therapies. The clinical pharmacist was readily accepted as an addition to the team by both oncologists and patients and the experience served as an important learning opportunity. Conclusion The success of integrating this precision medicine pharmacist into a newly formed Precision Medicine Program and the model it can serve as may be considered for other cancer centers that may or may not have easily accessible pharmacogenomic experts and resources. This service highlights the importance of pharmacist care in such a program and the various opportunities for integration. Oncology clinical pharmacists should seek to integrate into Precision Medicine Programs and systems directing this care and develop their knowledge and understanding of genomics to continue providing the highest level of cancer care as a pivotal member of the cancer care team. [ABSTRACT FROM AUTHOR]

Previous studies have identified multiple loci for inherited susceptibility to glioma development, including the regulator of telomere elongation helicase 1 (RTEL1). However, the association between RTEL1 variants and risk of glioma has not been well understood. Therefore, we sought to comprehensively examine the genetic interaction between RTEL1 variants and risk of glioma with respect to defined histological and molecular subtypes. We employed a case-control study involving 250 adult glioma patients with previous molecular alterations and 375 population–based controls within Korean populations. Statistical analyses on the association between RTEL1 single nucleotide polymorphisms (SNPs) and glioma risk were conducted using unconditional logistic regression. Additional conditional and stepwise analyses were performed on significant RTEL1 SNPs. We detected significant associations (Bonferroni P < .05) between six SNPs (rs6089953, rs3848669, rs6010620, rs3787089, rs6062302, and rs115303435) and risk of glioma in the Korean subjects. The two coding variants, rs6062302 (D664D) and rs115303435 (A1059T), were plausibly causal variants and were independent among the significantly associated RTEL1 variants. The glioma subgroup analyses showed that the causal variants (rs6062302 and rs115303435) may be associated with increased risk of glioma regardless of histological grades and molecular alterations. This study provides a deeper understanding of relationships between RTEL1 variants and risk of glioma. Further studies are required to ascertain the impact of those variants on glioma susceptibility. [ABSTRACT FROM AUTHOR]

The paper presents the application of Grade Correspondence Analysis (GCA) and Grade Correspondence Cluster Analysis (GCCA) for ordering and grouping -omics datasets, using transcriptomic data as an example. Based on gene expression data describing 256 patients with Multiple Myeloma it was shown that the GCA method could be used to find regularities in the analyzed collections and to create characteristic gene expression profiles for individual groups of patients. GCA iteratively permutes rows and columns to maximize the tau-Kendall or rho-Spearman coefficients, which makes it possible to arrange rows and columns in such a way that the most similar ones remain in each other’s neighbourhood. In this way, the GCA algorithm highlights regularities in the data matrix. The ranked data can then be grouped using the GCCA method, and after that aggregated in clusters, providing a representation that is easier to analyze–especially in the case of large sets of gene expression profiles. Regularization of transcriptomic data, which is presented in this manuscript, has enabled division of the data set into column clusters (representing genes) and row clusters (representing patients). Subsequently, rows were aggregated (based on medians) to visualise the gene expression profiles for patients with Multiple Myeloma in each collection. The presented analysis became the starting point for characterisation of differentiated genes and biochemical processes in which they are involved. GCA analysis may provide an alternative analytical method to support differentiation and analysis of gene expression profiles characterising individual groups of patients. [ABSTRACT FROM AUTHOR]

Context: One of the most important achievements in cancer research is the development of cancer immunotherapy. However, only a subset of patients respond to immunotherapy modalities, and few patients respond for a durable time. Here, we review the possible genomic mechanisms of response and resistance to these therapies, which can lead to the selection of responders, who may benefit most from immunotherapy. Evidence Acquisition: We searched PubMed, Scopus, and Web of Science Core Collection with the following keywords: "Immunotherapy, Resistance, Response, Programmed cell death 1 receptor, CTLA-4, Cancer immunity, Tumor Genomics, and Somatic Mutations". Results: T cells that specifically recognize cancer-associated antigens, are responsible for the immune system response against cancer. Nonsynonymous mutations, which are transcribed and translated into polypeptides,maygeneratenewepitopes (neoepitopes), which can lead to their presentation on major histocompatibility (MHC) class I molecules and subsequently recognized by the adaptive immune system. Despite the unprecedented durable responses, the majority of patients treated with cancer immunotherapies do not respond to the therapy (primary resistance), and some patients relapse after an initial response (acquired resistance). Resistance to immunotherapy can be a result of tumor cell intrinsic or extrinsic factors. There is correlation between tumor mutation burden (TMB) and response to immunotherapy. In addition, mismatch repair deficient tumors harbor considerably more somatic mutations compared to mismatch repair proficient tumors and respond better to anti-programmed cell death protein 1 (anti-PD1) therapy. Mutations in other DNA repair genes may also affect immunotherapy response. Conclusions: Neoantigen specific T cells constitute a major "active component" for the success of cancer immunotherapies. The genetic damage that confers tumorigenic growth, can also be targeted by the immune machinery to inhibit cancer development and progression. With further validation of experiments, genomics-based approaches can allow to select patients most likely to achieve durable responses to immunotherapy modalities. [ABSTRACT FROM AUTHOR]

The hallmarks of cancer were proposed as a logical framework to guide research efforts that aim to understand the molecular mechanisms and derive treatments for this highly complex disease. Recent technological advances, including comprehensive sequencing of different cancer subtypes, have illuminated how genetic and epigenetic alterations are associated with specific hallmarks of cancer. However, as these associations are purely descriptive, one particularly exciting development is the emergence of genome editing technologies, which enable rapid generation of precise genetic and epigenetic modifications to assess the consequences of these perturbations on the cancer phenotype. The most recently developed of these tools, the system of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), consists of an RNA-guided endonuclease that can be repurposed to edit both genome and epigenome with high specificity, and facilitates the functional interrogation of multiple loci in parallel. This system has the potential to dramatically accelerate progress in cancer research, whether by modelling the genesis and progression of cancer in vitro and in vivo , screening for novel therapeutic targets, conducting functional genomics/epigenomics, or generating targeted cancer therapies. Here, we discuss CRISPR research on each of the ten hallmarks of cancer, outline potential barriers for its clinical implementation and speculate on the advances it may allow in cancer research in the near future. [ABSTRACT FROM AUTHOR]

Radiomics is a rapidly growing field in which sophisticated imaging features are extracted from radiology images to predict clinical outcomes/responses, genetic alterations, and other outcomes relevant to a patient's prognosis or response to therapy. This approach can effectively capture intratumor phenotypic heterogeneity by interrogating the "larger" image field, which is not possible with traditional biopsy procedures that interrogate specific subregions alone. Most models in radiomics derive numerous imaging features (eg, texture, shape, size) from a radiology data set and then learn complex nonlinear hypotheses to solve a given prediction task. This presents the challenge of visual interpretability of radiomic features necessary for effective adoption of radiomic models into the clinical decision-making process. To this end, we employed a dictionary learning approach to derive visually interpretable imaging features relevant to genetic alterations in low-grade gliomas. This model can identify regions of a medical image that potentially influence the prediction process. Using a publicly available data set of magnetic resonance imaging images from patients diagnosed with low-grade gliomas, we demonstrated that the dictionary-based model performs well in predicting 2 biomarkers of interest (1p/19q codeletion and IDH1 mutation). Furthermore, the visual regions (atoms) associated with these dictionaries show association with key molecular pathways implicated in gliomagenesis. Our results show that dictionary learning is a promising approach to obtain insights into the diagnostic process and to potentially aid radiologists in selecting physiologically relevant biopsy locations. [ABSTRACT FROM AUTHOR]

Tumor mutation load (TML) has been proposed as a biomarker of patient response to immunotherapy in several studies. TML is usually determined by tumor biopsy DNA (tDNA) whole exome sequencing (WES), therefore TML evaluation is limited by informative biopsy availability. Circulating cell free DNA (cfDNA) provided by liquid biopsy is a surrogate specimen to biopsy for molecular profiling. Nevertheless performing WES on DNA from plasma is technically challenging and the ability to determine tumor mutation load from liquid biopsies remains to be demonstrated. In the current study, WES was performed on cfDNA from 32 metastatic patients of various cancer types included into MOSCATO 01 (NCT01566019) and/or MATCHR (NCT02517892) molecular triage trials. Results from targeted gene sequencing (TGS) and WES performed on cfDNA were compared to results from tumor tissue biopsy. In cfDNA samples, WES mutation detection sensitivity was 92% compared to targeted sequencing (TGS). When comparing cfDNA-WES to tDNA-WES, mutation detection sensitivity was 53%, consistent with previously published prospective study comparing cfDNA-TGS to tDNA-TGS. For samples in which presence of tumor DNA was confirmed in cfDNA, tumor mutation load from liquid biopsy was correlated with tumor biopsy. Taken together, this study demonstrated that liquid biopsy may be applied to determine tumor mutation load. Qualification of liquid biopsy for interpretation is a crucial point to use cfDNA for mutational load estimation. [ABSTRACT FROM AUTHOR]