F-Box Protein-Mediated Resistance to PARP Inhibitor Therapy.

PARP inhibitor (PARPi) therapy targets BRCA1/2 mutant tumor cells, but acquired resistance limits its effectiveness. In this issue of Molecular Cell, Marzio et al. (2019) identify a novel mechanism of resistance to PARPi through regulation of RAD51 protein stability via an SCF ubiquitin ligase dependent on EMI1.

Pharmacogenomics: Driving Personalized Medicine.

Personalized medicine tailors therapies, disease prevention, and health maintenance to the individual, with pharmacogenomics serving as a key tool to improve outcomes and prevent adverse effects. Advances in genomics have transformed pharmacogenetics, traditionally focused on single gene-drug pairs, into pharmacogenomics, encompassing all "-omics" fields (e.g., proteomics, transcriptomics, metabolomics, and metagenomics). This review summarizes basic genomics principles relevant to translation into therapies, assessing pharmacogenomics' central role in converging diverse elements of personalized medicine. We discuss genetic variations in pharmacogenes (drug-metabolizing enzymes, drug transporters, and receptors), their clinical relevance as biomarkers, and the legacy of decades of research in pharmacogenetics. All types of therapies, including proteins, nucleic acids, viruses, cells, genes, and irradiation, can benefit from genomics, expanding the role of pharmacogenomics across medicine. Food and Drug Administration approvals of personalized therapeutics involving biomarkers increase rapidly, demonstrating the growing impact of pharmacogenomics. A beacon for all therapeutic approaches, molecularly targeted cancer therapies highlight trends in drug discovery and clinical applications. To account for human complexity, multicomponent biomarker panels encompassing genetic, personal, and environmental factors can guide diagnosis and therapies, increasingly involving artificial intelligence to cope with extreme data complexities. However, clinical application encounters substantial hurdles, such as unknown validity across ethnic groups, underlying bias in health care, and real-world validation. This review address the underlying science and technologies germane to pharmacogenomics and personalized medicine, integrated with economic, ethical, and regulatory issues, providing insights into the current status and future direction of health care. SIGNIFICANCE STATEMENT: Personalized medicine aims to optimize health care for the individual patients with use of predictive biomarkers to improve outcomes and prevent adverse effects. Pharmacogenomics drives biomarker discovery and guides the development of targeted therapeutics. This review addresses basic principles and current trends in pharmacogenomics, with large-scale data repositories accelerating medical advances. The impact of pharmacogenomics is discussed, along with hurdles impeding broad clinical implementation, in the context of clinical care, ethics, economics, and regulatory affairs.

Germline Variants Impact Somatic Events during Tumorigenesis.

Cancer is characterized by diverse genetic alterations in both germline and somatic genomes that disrupt normal biology and provide a selective advantage to cells during tumorigenesis. Germline and somatic genomes have been extensively studied independently, leading to numerous biological insights. Analyses integrating data from both genomes have identified genetic variants impacting somatic events in tumors, including hotspot driver mutations. Interactions among specific germline variants and somatic events influence cancer subtypes, treatment response, and clinical outcomes. Investigation of these complex interactions is increasing our understanding of aberrant pathways in tumors that may uncover novel therapeutic targets. Here, we review the literature describing the role of germline genetic variants in promoting the selection and generation of specific mutations during tumorigenesis.

Differences in somatic TP53 mutation type in breast tumors by race and receptor status.

PURPOSE: Somatic driver mutations in TP53 are associated with triple-negative breast cancer (TNBC) and poorer outcomes. Breast cancers in women of African ancestry (AA) are more likely to be TNBC and have somatic TP53 mutations than cancers in non-Hispanic White (NHW) women. Missense driver mutations in TP53 have varied functional impact including loss-of-function (LOF) or gain-of-function (GOF) activity, and dominant negative (DNE) effects. We aimed to determine if there were differences in somatic TP53 mutation types by patient ancestry or TNBC status. METHODS: We identified breast cancer datasets with somatic TP53 mutation data, ancestry, age, and hormone receptor status. Mutations were classified for functional impact using published data and type of mutation. We assessed differences using Fisher's exact test. RESULTS: From 96 breast cancer studies, we identified 2964 women with somatic TP53 mutations: 715 (24.1%) Asian, 258 (8.7%) AA, 1931 (65.2%) NHW, and 60 (2%) Latina. The distribution of TP53 mutation type was similar by ancestry. However, 35.8% of tumors from NHW individuals had GOF mutations compared to 29% from AA individuals (p = 0.04). Mutations with DNE activity were positively associated with TNBC (OR 1.37, p = 0.03) and estrogen receptor (ER) negative status (OR 1.38; p = 0.005). CONCLUSIONS: Somatic TP53 mutation types did not differ by ancestry overall, but GOF mutations were more common in NHW women than AA women. ER-negative and TNBC tumors are less likely to have DNE+ TP53 mutations which could reflect biological processes. Larger cohorts and functional studies are needed to further elucidate these findings.

Genetic analysis of a malignant meningioma and associated metastases.

To identify genes altered in a highly aggressive metastatic meningioma primary as well as its metastases. Exome sequencing of a primary anaplastic meningioma and metastatic lesions in which DNA could be extracted and compared to germline DNA. Genetic analysis of the metastatic sites found 31 common mutations among the primary tumor and two metastatic sites. Additionally, genetic mutations were identified which were either infrequently (MUC3A, ALDH1A3, HOXA1) or not at all previously described in meningiomas (CASS4, CMKLR1). Exome sequencing of a metastatic meningioma and its distant metastases outside the CNS identified mutations that were not previously well described.

Machine learning approaches reveal subtle differences in breathing and sleep fragmentation in Phox2b-derived astrocytes ablated mice.

Modern neurophysiology research requires the interrogation of high-dimensionality data sets. Machine learning and artificial intelligence (ML/AI) workflows have permeated into nearly all aspects of daily life in the developed world but have not been implemented routinely in neurophysiological analyses. The power of these workflows includes the speed at which they can be deployed, their availability of open-source programming languages, and the objectivity permitted in their data analysis. We used classification-based algorithms, including random forest, gradient boosted machines, support vector machines, and neural networks, to test the hypothesis that the animal genotypes could be separated into their genotype based on interpretation of neurophysiological recordings. We then interrogate the models to identify what were the major features utilized by the algorithms to designate genotype classification. By using raw EEG and respiratory plethysmography data, we were able to predict which recordings came from genotype class with accuracies that were significantly improved relative to the no information rate, although EEG analyses showed more overlap between groups than respiratory plethysmography. In comparison, conventional methods where single features between animal classes were analyzed, differences between the genotypes tested using baseline neurophysiology measurements showed no statistical difference. However, ML/AI workflows successfully were capable of providing successful classification, indicating that interactions between features were different in these genotypes. ML/AI workflows provide new methodologies to interrogate neurophysiology data. However, their implementation must be done with care so as to provide high rigor and reproducibility between laboratories. We provide a series of recommendations on how to report the utilization of ML/AI workflows for the neurophysiology community.NEW & NOTEWORTHY ML/AI classification workflows are capable of providing insight into differences between genotypes for neurophysiology research. Analytical techniques utilized in the neurophysiology community can be augmented by implementing ML/AI workflows. Random forest is a robust classification algorithm for respiratory plethysmography data. Utilization of ML/AI workflows in neurophysiology research requires heightened transparency and improved community research standards.

The BRCA1 c. 5096G>A p.Arg1699Gln (R1699Q) intermediate risk variant: breast and ovarian cancer risk estimation and recommendations for clinical management from the ENIGMA consortium.

BACKGROUND: We previously showed that the BRCA1 variant c.5096G>A p.Arg1699Gln (R1699Q) was associated with an intermediate risk of breast cancer (BC) and ovarian cancer (OC). This study aimed to assess these cancer risks for R1699Q carriers in a larger cohort, including follow-up of previously studied families, to further define cancer risks and to propose adjusted clinical management of female BRCA1*R1699Q carriers. METHODS: Data were collected from 129 BRCA1*R1699Q families ascertained internationally by ENIGMA (Evidence-based Network for the Interpretation of Germline Mutant Alleles) consortium members. A modified segregation analysis was used to calculate BC and OC risks. Relative risks were calculated under both monogenic model and major gene plus polygenic model assumptions. RESULTS: In this cohort the cumulative risk of BC and OC by age 70 years was 20% and 6%, respectively. The relative risk for developing cancer was higher when using a model that included the effects of both the R1699Q variant and a residual polygenic component compared with monogenic model (for BC 3.67 vs 2.83, and for OC 6.41 vs 5.83). CONCLUSION: Our results confirm that BRCA1*R1699Q confers an intermediate risk for BC and OC. Breast surveillance for female carriers based on mammogram annually from age 40 is advised. Bilateral salpingo-oophorectomy should be considered based on family history.

Polygenic risk scores for prostate cancer: testing considerations.

Genome-wide association studies (GWAS) have identified more than 170 single nucleotide variants (SNVs) associated with prostate cancer risk. Each variant is associated with only small increases in risk and is not predictive of an individuals' overall risk of developing prostate cancer. Polygenic risk scores (PRS) combining these variants are now clinically available and may improve predictive value of other factors such as PSA. This overview reviews the current state of PRS for prostate cancer including testing considerations.

Exploring genetic counselors' perceptions of usefulness and intentions to use refined risk models in clinical care based on the Technology Acceptance Model (TAM).

Pathogenic germline mutations in the BRCA1 or BRCA2 genes are associated with an elevated lifetime risk for breast (50%-85% risk) and ovarian cancer (20%-40% risk). Genome-wide association studies have identified over 100 genetic variants associated with modified breast and/or ovarian cancer risk in BRCA1 and BRCA2 carriers. Risk models generated based on these variants have shown that these genetic modifiers strongly influence absolute risk of developing breast or ovarian cancer in BRCA mutation carriers. There is a lack of understanding, however, about the clinical applicability and utility of these risk models. To investigate this gap, we collected survey data from 274 cancer genetic counselors (GCs) through the National Society of Genetic Counselors Cancer Special Interest Group. Questions assessed perceptions of usefulness and intentions of genetic counselors to use these refined risk models in clinical care based on the Technology Acceptance Model (TAM). We found that GCs' reactions to the estimates were largely positive, though they thought the possibility of changing management based on results was unlikely. Additionally, we found that more experienced GCs were more likely to consider refined risk estimates in clinic. Support also was provided for core predictions within the TAM, whereby the perceived usefulness (indirect effect est. = 0.08, 95% CI: [0.04, 0.13]) and perceived ease of use (indirect effect est. = 0.078, 95% CI: [0.04, 0.13]) of refined risk estimates were indirectly associated with intentions to use via attitudes.

DNA repair-related functional assays for the classification of BRCA1 and BRCA2 variants: a critical review and needs assessment.

Mutation of BRCA1 and BRCA2 is the most common cause of inherited breast and ovarian cancer. Genetic screens to detect carriers of variants can aid in cancer prevention by identifying individuals with a greater cancer risk and can potentially be used to predict the responsiveness of tumours to therapy. Frequently, classification cannot be performed based on traditional approaches such as segregation analyses, including for many missense variants, which are therefore referred to as variants of uncertain significance (VUS). Functional assays provide an important alternative for classification of BRCA1 and BRCA2 VUS. As reviewed here, both of these tumour suppressors promote the maintenance of genome stability via homologous recombination. Thus, related assays may be particularly relevant to cancer risk. Progress in implementing functional assays to assess missense variants of BRCA1 and BRCA2 is considered here, along with current limitations and the path to more impactful assay systems. While functional assays have been developed to independently evaluate BRCA1 and BRCA2 VUS, high-throughput assays with sufficient sensitivity to characterise the large number of identified variants are lacking. Additionally, because of relatively low conservation of certain domains of BRCA1, and of BRCA2, between humans and rodents, heterologous expression in rodent cells may have limited reliability or capacity to assess variants present throughout either protein. Moving forward, it will be important to perform assays in human cell lines with relevance to particular tumour types, and to strengthen risk predictions based on multifactorial statistical analyses that also include available data on cosegregation and tumour pathology.

Involvement and Influence of Healthcare Providers, Family Members, and Other Mutation Carriers in the Cancer Risk Management Decision-Making Process of BRCA1 and BRCA2 Mutation Carriers.

Deciding between increased cancer screening or prophylactic surgery and the timing of such procedures can be a difficult and complex process for women with BRCA mutations. There are gaps in our understanding of involvement of others in the decision-making process for women with BRCA mutations. This study evaluated the management decision-making process of women with BRCA mutations, focusing on the involvement of others. Grounded theory was used to analyze and code risk management decision-making information from interviews with 20 BRCA mutation carriers. Unaffected at-risk participants with a BRCA mutation, those under age 40, and those with no children described having a difficult time making risk management decisions. Physicians were an integral part of the decision-making process by providing decisional support and management recommendations. Family members and other mutation carriers filled similar yet distinct roles by providing experiential information as well as decisional and emotional support for carriers. Participants described genetic counselors as short-term providers of risk information and management recommendations. The study findings suggest that unaffected at-risk women, women under 40, and those who do not have children may benefit from additional support and information during the decision-making process. Genetic counselors are well trained to help women through this process and connect them with resources, and may be under-utilized in long-term follow-up for women with a BRCA mutation.

Differential mutation frequencies in metastatic cutaneous squamous cell carcinomas versus primary tumors.

BACKGROUND: Exome and targeted sequencing studies have identified potential driver mutations for a variety of tumor types. Cutaneous squamous cell carcinoma (cSCC) is one of the most highly mutated cancers but typically is associated with low rates of metastasis and high survival rates. Nevertheless, metastatic cSCC is a significant health threat; up to 8800 individuals die each year of this disease. METHODS: Because it is difficult to predict which cSCCs are more likely to metastasize, and because to the best of the authors' knowledge there are no targeted therapies specifically designated for patients with metastatic cSCC, exome and/or targeted sequencing of 18 metastatic and 10 primary cSCCs was performed to identify mutations that were more frequent in metastatic tumors and might be targeted for therapeutic benefit. The authors compared their results with published sequencing results of an additional 223 primary tumors and 68 metastatic cSCCs. RESULTS: The authors identified genes demonstrating higher mutation frequencies in metastatic cSCC compared with primary tumors, including the chromatin remodeling gene lysine methyltransferase 2D (KMT2D) and the classic skin tumor suppressor tumor protein p53 (TP53), which was found to be mutated in 54% of primary tumors compared with 85% of metastatic tumors (P<.0001). CONCLUSIONS: These studies appear to uncover potential pathways that are important in metastatic cSCC and that broaden understanding of the biology contributing to aggressive tumor behavior. These results may lead to new therapeutic strategies. Cancer 2017;123:1184-1193. © 2016 American Cancer Society.

Outcomes of a Randomized Controlled Trial of Genomic Counseling for Patients Receiving Personalized and Actionable Complex Disease Reports.

There has been very limited study of patients with chronic disease receiving potentially actionable genomic based results or the utilization of genetic counselors in the online result delivery process. We conducted a randomized controlled trial on 199 patients with chronic disease each receiving eight personalized and actionable complex disease reports online. Primary study aims were to assess the impact of in-person genomic counseling on 1) causal attribution of disease risk, 2) personal awareness of disease risk, and 3) perceived risk of developing a particular disease. Of 98 intervention arm participants (mean age = 57.8; 39% female) randomized for in-person genomic counseling, 76 (78%) were seen. In contrast, control arm participants (n = 101; mean age = 58.5; 54% female) were initially not offered genomic counseling as part of the study protocol but were able to access in-person genomic counseling, if they requested it, 3-months post viewing of at least one test report and post-completion of the study-specific follow-up survey. A total of 64 intervention arm and 59 control arm participants completed follow-up survey measures. We found that participants receiving in-person genomic counseling had enhanced objective understanding of the genetic variant risk contribution for multiple complex diseases. Genomic counseling was associated with lowered participant causal beliefs in genetic influence across all eight diseases, compared to control participants. Our findings also illustrate that for the majority of diseases under study, intervention arm participants believed they knew their genetic risk status better than control arm subjects. Disease risk was modified for the majority during genomic counseling, due to the assessment of more comprehensive family history. In conclusion, for patients receiving personalized and actionable genomic results through a web portal, genomic counseling enhanced their objective understanding of the genetic variant risk contribution to multiple common diseases. These results support the development of additional genomic counseling interventions to ensure a high level of patient comprehension and improve patient-centered health outcomes.

Male breast cancer in BRCA1 and BRCA2 mutation carriers: pathology data from the Consortium of Investigators of Modifiers of BRCA1/2.

BACKGROUND: BRCA1 and, more commonly, BRCA2 mutations are associated with increased risk of male breast cancer (MBC). However, only a paucity of data exists on the pathology of breast cancers (BCs) in men with BRCA1/2 mutations. Using the largest available dataset, we determined whether MBCs arising in BRCA1/2 mutation carriers display specific pathologic features and whether these features differ from those of BRCA1/2 female BCs (FBCs). METHODS: We characterised the pathologic features of 419 BRCA1/2 MBCs and, using logistic regression analysis, contrasted those with data from 9675 BRCA1/2 FBCs and with population-based data from 6351 MBCs in the Surveillance, Epidemiology, and End Results (SEER) database. RESULTS: Among BRCA2 MBCs, grade significantly decreased with increasing age at diagnosis (P = 0.005). Compared with BRCA2 FBCs, BRCA2 MBCs were of significantly higher stage (P for trend = 2 × 10(-5)) and higher grade (P for trend = 0.005) and were more likely to be oestrogen receptor-positive [odds ratio (OR) 10.59; 95 % confidence interval (CI) 5.15-21.80] and progesterone receptor-positive (OR 5.04; 95 % CI 3.17-8.04). With the exception of grade, similar patterns of associations emerged when we compared BRCA1 MBCs and FBCs. BRCA2 MBCs also presented with higher grade than MBCs from the SEER database (P for trend = 4 × 10(-12)). CONCLUSIONS: On the basis of the largest series analysed to date, our results show that BRCA1/2 MBCs display distinct pathologic characteristics compared with BRCA1/2 FBCs, and we identified a specific BRCA2-associated MBC phenotype characterised by a variable suggesting greater biological aggressiveness (i.e., high histologic grade). These findings could lead to the development of gender-specific risk prediction models and guide clinical strategies appropriate for MBC management.

Variants in an Hdac9 intronic enhancer plasmid impact Twist1 expression in vitro.

Skin tumor susceptibility 5 (Skts5) was previously mapped to mouse chromosome 12 through linkage analysis of skin tumor susceptible Mus musculus (NIH/Ola-S) and skin tumor resistant outbred Mus spretus (SPRET/Out-R) mice. Hdac9 was identified as a potential candidate for Skts5 based on conserved non-synonymous sequence variants and expression analyses. Studies by others identified an enhancer in human HDAC9 that correlated with TWIST1 expression. We identified 45 sequence variants between NIH/Ola-S and SPRET/Out-R mice from the orthologous region of the human HDAC9 enhancer. Variants mapping to intron 18 differentially affected luciferase expression in vitro. NIH/Ola-S clones showed an approximate 1.7-fold increased luciferase expression relative to vector alone or the equivalent clones from SPRET/Out-R-R. Furthermore, cells transfected with a portion of the NIH/Ola-S intron induced 2.2-fold increases in Twist1 expression, but the same region from SPRET/Out-R mice resulted in no up-regulation of Twist1. In silico transcription factor analyses identified multiple transcription factors predicted to differentially bind NIH/Ola-S and SPRET/Out-R polymorphic sites. Chromatin immunoprecipitation studies of two transcription factors, Gata3 and Oct1, demonstrated differential binding between NIH/Ola-S and SPRET/Out-R plasmids that corroborated the in silico predictions. Together these studies provide evidence that the murine orthologous region to a human HDAC9 enhancer also acts as a transcriptional enhancer for mouse Twist1. As ectopic sequence variants between NIH/Ola-S and SPRET/Out-R differentially impacted luciferase expression, correlated with Twist1 expression in vitro, and affected Gata3 and Oct1 binding, these variants may explain part of the observed differences in skin tumor susceptibility at Skts5 between NIH/Ola-S and SPRET/Out-R.

mrSNP: software to detect SNP effects on microRNA binding.

BACKGROUND: MicroRNAs (miRNAs) are short (19-23 nucleotides) non-coding RNAs that bind to sites in the 3'untranslated regions (3'UTR) of a targeted messenger RNA (mRNA). Binding leads to degradation of the transcript or blocked translation resulting in decreased expression of the targeted gene. Single nucleotide polymorphisms (SNPs) have been found in 3'UTRs that disrupt normal miRNA binding or introduce new binding sites and some of these have been associated with disease pathogenesis. This raises the importance of detecting miRNA targets and predicting the possible effects of SNPs on binding sites. In the last decade a number of studies have been conducted to predict the location of miRNA binding sites. However, there have been fewer algorithms published to analyze the effects of SNPs on miRNA binding. Moreover, the existing software has some shortcomings including the requirement for significant manual labor when working with huge lists of SNPs and that algorithms work only for SNPs present in databases such as dbSNP. These limitations become problematic as next-generation sequencing is leading to large numbers of novel variants in 3'UTRs. RESULT: In order to overcome these issues, we developed a web-server named mrSNP which predicts the impact of a SNP in a 3'UTR on miRNA binding. The proposed tool reduces the manual labor requirements and allows users to input any SNP that has been identified by any SNP-calling program. In testing the performance of mrSNP on SNPs experimentally validated to affect miRNA binding, mrSNP correctly identified 69% (11/16) of the SNPs disrupting binding. CONCLUSIONS: mrSNP is a highly adaptable and performing tool for predicting the effect a 3'UTR SNP will have on miRNA binding. This tool has advantages over existing algorithms because it can assess the effect of novel SNPs on miRNA binding without requiring significant hands on time.

Allele-specific imbalance mapping identifies HDAC9 as a candidate gene for cutaneous squamous cell carcinoma.

More than 3.5 million nonmelanoma skin cancers were treated in 2006; of these 700,000 were cutaneous squamous cell carcinomas (cSCCs). Despite clear environmental causes for cSCC, studies also suggest genetic risk factors. A cSCC susceptibility locus, Skts5, was identified on mouse chromosome 12 by linkage analysis. The orthologous locus to Skts5 in humans maps to 7p21 and 7q31. These loci show copy number increases in ∼10% of cSCC tumors. Here, we show that an additional 15-22% of tumors exhibit copy-neutral loss of heterozygosity. Furthermore, our previous data identified microsatellite markers on 7p21 and 7q31 that demonstrate preferential allelic imbalance (PAI) in cSCC tumors. On the basis of these results, we hypothesized that the human orthologous locus to Skts5 would house a gene important in human cSCC development and that tumors would demonstrate allele-specific somatic alterations. To test this hypothesis, we performed quantitative genotyping of 108 single nucleotide polymorphisms (SNPs) mapping to candidate genes at human SKTS5 in paired normal and tumor DNAs. Nine SNPs in HDAC9 (rs801540, rs1178108, rs1178112, rs1726610, rs10243618, rs11764116, rs1178355, rs10269422 and rs12540872) showed PAI in tumors. These data suggest that HDAC9 variants may be selected for during cSCC tumorigenesis.

Expression of cancer-testis antigens MAGEA1, MAGEA3, ACRBP, PRAME, SSX2, and CTAG2 in myxoid and round cell liposarcoma.

Myxoid and round-cell liposarcoma is a frequently encountered liposarcoma subtype. The mainstay of treatment remains surgical excision with or without chemoradiation. However, treatment options are limited in the setting of metastatic disease. Cancer-testis antigens are immunogenic antigens with the expression largely restricted to testicular germ cells and various malignancies, making them attractive targets for cancer immunotherapy. Gene expression studies have reported the expression of various cancer-testis antigens in liposarcoma, with mRNA expression of CTAG1B, CTAG2, MAGEA9, and PRAME described specifically in myxoid and round-cell liposarcoma. Herein, we further explore the expression of the cancer-testis antigens MAGEA1, ACRBP, PRAME, and SSX2 in myxoid and round-cell liposarcoma by immunohistochemistry in addition to determining mRNA levels of CTAG2 (LAGE-1), PRAME, and MAGEA3 by quantitative real-time PCR. Samples in formalin-fixed paraffin-embedded blocks (n=37) and frozen tissue (n=8) were obtained for immunohistochemistry and quantitative real-time PCR, respectively. Full sections were stained with antibodies to MAGEA1, ACRBP, PRAME, and SSX2 and staining was assessed for intensity (1-2+) and percent tumor positivity. The gene expression levels of CTAG2, PRAME, and MAGEA3 were measured by quantitative real-time PCR. In total, 37/37 (100%) of the samples showed predominantly strong, homogenous immunoreactivity for PRAME. There was a variable, focal expression of MAGEA1 (11%) and SSX2 (16%) and no expression of ACRBP. Quantitative real-time PCR demonstrated PRAME and CTAG2 transcripts in all eight samples: six tumors with high mRNA levels; two tumors with low mRNA levels. The gene expression of MAGEA3 was not detected in the majority of cases. In conclusion, myxoid and round-cell liposarcomas consistently express PRAME by immunohistochemistry as well as CTAG2 and PRAME by qualitative real-time PCR. This supports the use of cancer-testis antigen-targeted immunotherapy in the treatment of this malignancy.

Immunotherapy for colorectal cancer: insight from inherited genetics.

Immunotherapy shows efficacy for multiple cancer types and potential for expanded use. However, current immune checkpoint inhibitors (ICIs) are ineffective against microsatellite-stable colorectal cancer (CRC), which is more commonly diagnosed. Immunotherapy strategies for non-responsive CRC, including new targets and new combination therapies, are being tested to address this need. Importantly, a subset of inherited germline genetic variants associated with CRC risk are predicted to regulate genes with immune functions, including genes related to existing ICIs, as well as new potential targets in the major histocompatibility complex (MHC) region and immunoregulatory cytokines. We review discoveries in the inherited genetics of CRC related to the immune system and draw connections with ongoing developments and emerging immunotherapy targets.