Development and clinical application of an integrative genomic approach to personalized cancer therapy

Platinum nanoparticles in cancer therapy: chemotherapeutic enhancement and ROS generation

Platinum nanoparticles (PtNPs) offer significant promise in cancer therapy by enhancing the therapeutic effects of platinum-based chemotherapies like cisplatin. These nanoparticles improve tumor targeting, reduce off-target effects, and help overcome drug resistance. PtNPs exert their anti-cancer effects primarily through the generation of reactive oxygen species (ROS), which induce oxidative stress and apoptosis in cancer cells. Additionally, PtNPs interact with cellular signaling pathways such as PI3K/AKT and MAPK, sensitizing cancer cells to chemotherapy. Advances in PtNP synthesis focus on optimizing size, shape, and surface modifications to enhance biocompatibility and targeting. Functionalization with biomolecules allows selective tumor delivery, while smart release systems enable controlled drug release. In vivo studies have shown that PtNPs significantly inhibit tumor growth and metastasis. Ongoing clinical trials are evaluating their safety and efficacy. This review explores PtNPs' mechanisms of action, nanotechnology advancements, and challenges in biocompatibility, with a focus on their potential integration into cancer treatments.

Small molecules targeting mitochondria as an innovative approach to cancer therapy

Cellular death evasion is a defining characteristic of human malignancies and a significant contributor to therapeutic inefficacy. As a result of oncogenic inhibition of cell death mechanisms, established therapeutic regimens seems to be ineffective. Mitochondria serve as the cellular powerhouses, but they also function as repositories of self-destructive weaponry. Changes in the structure and activities of mitochondria have been consistently documented in cancer cells. In recent years, there has been an increasing focus on using mitochondria as a targeted approach for treating cancer. Considerable attention has been devoted to the development of delivery systems that selectively aim to deliver small molecules called "mitocans" to mitochondria, with the ultimate goal of modulating the physiology of cancer cells. This review summarizes the rationale and mechanism of mitochondrial targeting with small molecules in the treatment of cancer, and their impact on the mitochondria. This paper provides a concise overview of the reasoning and mechanism behind directing treatment towards mitochondria in cancer therapy, with a particular focus on targeting using small molecules. This review also examines diverse small molecule types within each category as potential therapeutic agents for cancer.

BRCA loss of function including BRCA1 DNA-methylation, but not BRCA-unrelated homologous recombination deficiency, is associated with platinum hypersensitivity in high-grade ovarian cancer

BACKGROUND

In high-grade ovarian cancer (HGOC), determination of homologous recombination deficiency (HRD) status is commonly used in routine practice to predict response to platinum-based therapy or poly (ADP-ribose) polymerase inhibitors (PARPi). Here we tested the hypothesis that BRCA loss of function (LOF) due to epigenetic or genetic aberrations is a better predictor for the clinical outcome than HRD. One hundred thirty-one HGOC tissues were tested for BRCA DNA-methylation, BRCA mutations, HRD and BRCA1 mRNA expression, followed by a comprehensive survival analysis.

RESULTS

BRCA1-methylation was detected in 11% of the tumors, exclusively in BRCA1-wild-type (wt) HGOCs. BRCA1-methylated tumors (BRCA1-meth) had HRD-scores similar to those of BRCA-mutated (mut) tumors, and higher compared to unmethylated-BRCA-wt tumors (BRCA-wt-unmeth; P < 0.001). Platinum-refractory or -resistant HGOCs at first recurrence were all BRCA-unmeth cancers. Only one of the BRCA-mut cancers had a platinum-resistant recurrence. Thus, 99% of relapses in cancers with epigenetic or genetic BRCA-alterations were platinum-sensitive. Multivariate analysis confirmed BRCA-LOF as an independent predictor of progression-free survival (PFS) and overall survival (OS), whereas HRD-status had no predictive value for PFS and OS. Patients with BRCA-wt-unmeth cancers had the worst outcome compared to patients with cancers harboring epigenetic or genetic BRCA-alterations (PFS: P = 0.007; OS: P = 0.022). Most importantly, the BRCA-wt-unmeth subfraction of HRD-positive HGOCs exhibited the same poor survival as the entire HRD-negative cohort.

CONCLUSION

In HGOC BRCA mutational status together with BRCA1-methylation exhibit the best predictive power for favorable clinical outcome and thus high sensitivity to platinum-based therapy, whereas BRCA-unrelated HRD positivity was not associated with improved platinum sensitivity.

Multimodal scanning of genetic variants with base and prime editing

Mutational scanning connects genetic variants to phenotype, enabling the interrogation of protein functions, interactions and variant pathogenicity. However, current methodologies cannot efficiently engineer customizable sets of diverse genetic variants in endogenous loci across cellular contexts in high throughput. Here, we combine cytosine and adenine base editors and a prime editor to assess the pathogenicity of a broad spectrum of variants in the epithelial growth factor receptor gene (EGFR). Using pooled base editing and prime editing guide RNA libraries, we install tens of thousands of variants spanning the full coding sequence of EGFR in multiple cell lines and assess the role of these variants in tumorigenesis and resistance to tyrosine kinase inhibitors. Our EGFR variant scan identifies important hits, supporting the robustness of the approach and revealing underappreciated routes to EGFR activation and drug response. We anticipate that multimodal precision mutational scanning can be applied broadly to characterize genetic variation in any genetic element of interest at high and single-nucleotide resolution.

Breast cancer genomic analyses reveal genes, mutations, and signaling networks

Breast cancer (BC) is the most commonly diagnosed cancer and the predominant cause of death in women. BC is a complex disorder, and the exploration of several types of BC omic data, highlighting genes, perturbations, signaling and cellular mechanisms, is needed. We collected mutational data from 9,555 BC samples using cBioPortal. We classified 1174 BC genes (mutated ≥ 40 samples) into five tiers (BCtier_I-V) and subjected them to pathway and protein‒protein network analyses using EnrichR and STRING 11, respectively. BCtier_I possesses 12 BC genes with mutational frequencies > 5%, with only 5 genes possessing > 10% frequencies, namely, PIK3CA (35.7%), TP53 (34.3%), GATA3 (11.5%), CDH1 (11.4%) and MUC16 (11%), and the next seven BC genes are KMT2C (8.8%), TTN (8%), MAP3K1 (8%), SYNE1 (7.2%), AHNAK2 (7%), USH2A (5.5%), and RYR2 (5.4%). Our pathway analyses revealed that the five top BC pathways were the PI3K-AKT, TP53, NOTCH, HIPPO, and RAS pathways. We found that BC panels share only seven genes. These findings show that BC arises from genetic disruptions evident in BC signaling and protein networks.

Stratification of Homologous Recombination Deficiency-Negative High-Grade Ovarian Cancer by the Type of Peritoneal Spread into Two Groups with Distinct Survival Outcomes

BACKGROUND

Homologous recombination deficiency (HRD) has evolved into a major diagnostic marker in high-grade ovarian cancer (HGOC), predicting the response to poly (adenosine diphosphate-ribose) polymerase inhibitors (PARPi) and also platinum-based therapy. In addition to HRD, the type of peritoneal tumor spread influences the treatment response and patient survival; miliary type tumor spread has a poorer predicted outcome than non-miliary type tumor spread.

METHODS

Known methods for HRD assessment were adapted for our technical requirements and the predictive-value integrated genomic instability score (PIGIS) for HRD assessment evolved as an outcome. PIGIS was validated in HGOC samples from 122 patients. We used PIGIS to analyze whether the type of tumor spread correlated with HRD status and whether this had an impact on survival.

RESULTS

We demonstrated that PIGIS can discriminate HRD-positive from HRD-negative samples. Tumors with a miliary tumor spread are HRD-negative and have a very bad prognosis with a progression-free survival (PFS) of 15.6 months and an overall survival (OS) of 3.9 years. However, HRD-negative non-miliary spreading tumors in our cohort had a much better prognosis (PFS 35.4 months, OS 8.9 years); similar to HRD-positive tumors (PFS 34.7 months, OS 8.9 years).

CONCLUSIONS

Our results indicate that in a predominantly PARPi naïve cohort, the type of tumor spread and concomitant cytoreduction efficiency is a better predictor of survival than HRD and that HRD may be an accidental surrogate marker for tumor spread and concomitant cytoreduction efficiency. It remains to be determined whether this also applies for sensitivity to PARPi.

The Scarface Score: Deciphering Response to DNA Damage Agents in High-Grade Serous Ovarian Cancer-A GEICO Study

Genomic Instability (GI) is a transversal phenomenon shared by several tumor types that provide both prognostic and predictive information. In the context of high-grade serous ovarian cancer (HGSOC), response to DNA-damaging agents such as platinum-based and poly(ADP-ribose) polymerase inhibitors (PARPi) has been closely linked to deficiencies in the DNA repair machinery by homologous recombination repair (HRR) and GI. In this study, we have developed the Scarface score, an integrative algorithm based on genomic and transcriptomic data obtained from the NGS analysis of a prospective GEICO cohort of 190 formalin-fixed paraffin-embedded (FFPE) tumor samples from patients diagnosed with HGSOC with a median follow up of 31.03 months (5.87-159.27 months). In the first step, three single-source models, including the SNP-based model (accuracy = 0.8077), analyzing 8 SNPs distributed along the genome; the GI-based model (accuracy = 0.9038) interrogating 28 parameters of GI; and the HTG-based model (accuracy = 0.8077), evaluating the expression of 7 genes related with tumor biology; were proved to predict response. Then, an ensemble model called the Scarface score was found to predict response to DNA-damaging agents with an accuracy of 0.9615 and a kappa index of 0.9128 (p < 0.0001). The Scarface Score approaches the routine establishment of GI in the clinical setting, enabling its incorporation as a predictive and prognostic tool in the management of HGSOC.

The Potential Role of Genomic Signature in Stage II Relapsed Colorectal Cancer (CRC) Patients: A Mono-Institutional Study

Purpose

The absolute benefit of adjuvant chemotherapy in stage II CRC is only 3–4%. The identification of biomarkers through molecular profiling could identify patients who will more benefit from adjuvant chemotherapy.

Patients and Methods

This retrospective analysis examined tissue blocks from 17 patients affected by relapsed stage II CRC, whose comprehensive genomic profiling of tumors was conducted through next-generation sequencing (NGS) via Roche-FoundationOne^®.

Results

Mutations were found in APC (76.5%), TP53 (58.8%) and KRAS (52.9%). Only KRAS wild-type samples showed FBXW7. APC frameshift mutations and MLH1 splice variant were conversely significant correlated (7% v 93%, P = 0.014). The median number of gene mutations reported was 6 (range 2–14). The TP53 mutation was associated most frequently with lung metastasis (P = 0.07) and high tumor budding (P = 0.03). Despite no statistical significance, lung recurrence, LVI/Pni, MSI and more than 6 genetic mutations were correlated to worse DFS and OS. Patients carried co-mutations of TP53-FBXW7 reported the worse DFS (4 v 14 months) and OS (4 v 65 months) compared to the other patients.

Conclusion

According to the present analysis, the setting of relapsed CRC emerges as one of the fields of greatest utility for NGS, looking at personalized cancer care.

Oncogenic Neuregulin 1 gene (NRG1) fusions in cancer: A potential new therapeutic opportunities

It is widely established that chromosomal rearrangements induce oncogenesis in solid tumors. However, discovering chromosomal rearrangements that are targetable and actionable remains a difficulty. Targeting gene fusion or chromosomal rearrangement seems to be a powerful strategy to address malignancies characterized by gene rearrangement. Oncogenic NRG1 fusions are relatively rare drivers that infrequently occur across most tumor types. NRG1 fusions exhibit unique biological properties and are difficult to identify owing to their large intronic regions. NRG1 fusions can be detected using a variety of techniques, including fluorescence in situ hybridization, immunohistochemistry, or next-generation sequencing (NGS), with NGS-based RNA sequencing being the most sensitive. Previous studies have shown that NRG1 fusion protein induces tumorigenesis, and numerous therapies targeting the ErbB signaling pathway, such as ErbB kinase inhibitors and monoclonal antibodies, have initially demonstrated encouraging anticancer efficacy in malignant tumors carrying NRG1 fusions. In this review, we present the characteristics and prevalence of NRG1 fusions in solid tumors. Additionally, we discuss the laboratory approaches for diagnosing NRG1 gene fusions. More importantly, we outline promising strategies for treating malignancies with NRG1 fusion.

Integrative Genomic Analysis of Pediatric Myeloid-Related Acute Leukemias Identifies Novel Subtypes and Prognostic Indicators

Integrating somatic mutation analysis and gene expression profiling distinguishes pediatric AML subtypes with differential prognoses and clinical risks.

Genomic characterization of pediatric patients with acute myeloid leukemia (AML) has led to the discovery of somatic mutations with prognostic implications. Although gene-expression profiling can differentiate subsets of pediatric AML, its clinical utility in risk stratification remains limited. Here, we evaluate gene expression, pathogenic somatic mutations, and outcome in a cohort of 435 pediatric patients with a spectrum of pediatric myeloid-related acute leukemias for biological subtype discovery. This analysis revealed 63 patients with varying immunophenotypes that span a T-lineage and myeloid continuum designated as acute myeloid/T-lymphoblastic leukemia (AMTL). Within AMTL, two patient subgroups distinguished by FLT3-ITD and PRC2 mutations have different outcomes, demonstrating the impact of mutational composition on survival. Across the cohort, variability in outcomes of patients within isomutational subsets is influenced by transcriptional identity and the presence of a stem cell–like gene-expression signature. Integration of gene expression and somatic mutations leads to improved risk stratification.

Merkel Cell Polyomavirus‒Negative Merkel Cell Carcinoma Originating from In Situ Squamous Cell Carcinoma: A Keratinocytic Tumor with Neuroendocrine Differentiation

Although virus-negative Merkel cell carcinoma (MCC) is characterized by a high frequency of UV-induced mutations, the expression of two viral oncoproteins is regarded as a key mechanism driving Merkel cell polyomavirus‒positive MCC. The cells in which these molecular events initiate MCC oncogenesis have yet not been identified for both MCC subsets. A considerable proportion of virus-negative MCC is found in association with squamous cell carcinoma (SCC), suggesting (i) coincidental collision, (ii) one providing a niche for the other, or (iii) one evolving from the other. Whole-exome sequencing of four combined tumors consisting of SCC in situ and Merkel cell polyomavirus‒negative MCC showed many mutations shared between SCC and MCC in all cases, indicating a common ancestry and thereby a keratinocytic origin of these MCCs. Moreover, analyses of the combined cases as well as of pure SCC and MCC suggest that RB1 inactivation in SCC facilitates MCC development and that epigenetic changes may contribute to the SCC/MCC transition.

Analysis of Intestinal Metaplasia Without Dysplasia in the Urinary Bladder Reveal Only Rare Mutations Associated With Colorectal Adenocarcinoma

Intestinal metaplasia (IM) is a rare finding in urinary bladder specimens. It is unclear whether IM without dysplasia is a precursor of malignancy in the urinary system. We retrospectively selected 9 cases of IM of bladder (1 case harboring high-grade dysplasia), and performed mutation analysis for genes frequently mutated in colon cancer including BRAF, APC, KRAS, MET, NRAS, PIK3CA, CTNNB1, FBXW7, and TP53 using validated clinical tests. Control groups included 7 colonic tubular adenomas, 10 high-grade papillary urothelial carcinomas. One IM case revealed an APC mutation and another showed an NRAS mutation. Among the tubular adenomas cases, 6 of 7 (85.7%) harbored KRAS mutations and 3 of 7 (42%) APC mutations. Among urothelial carcinomas cases, 1 revealed a KRAS mutation, 2 had PIK3CA mutations, and all cases were negative for APC mutations. Clinical follow-up for the IM patients was available with a median follow-up of 70 months. One patient-without any mutation in the genes investigated-developed invasive bladder adenocarcinoma with intestinal differentiation with metastasis to the liver and lung. Neither of the 2 patients harboring mutations developed any malignancy. In conclusion, a minority of cases with IM without dysplasia bear mutations in the genes commonly associated with colonic adenocarcinoma, suggesting a premalignant potential for such lesions possibly following the classic multistep chromosomal instability pathway of carcinogenesis. A larger cohort of patients with longer follow-up is needed to better establish whether close follow-up is warranted for mutation-harboring IM of the bladder.

Targeted and immuno-based therapies in sarcoma: mechanisms and advances in clinical trials

Sarcomas represent a distinct group of rare malignant tumors with high heterogeneity. Limited options with clinical efficacy for the metastatic or local advanced sarcoma existed despite standard therapy. Recently, targeted therapy according to the molecular and genetic phenotype of individual sarcoma is a promising option. Among these drugs, anti-angiogenesis therapy achieved favorable efficacy in sarcomas. Inhibitors targeting cyclin-dependent kinase 4/6, poly-ADP-ribose polymerase, insulin-like growth factor-1 receptor, mTOR, NTRK, metabolisms, and epigenetic drugs are under clinical evaluation for sarcomas bearing the corresponding signals. Immunotherapy represents a promising and favorable method in advanced solid tumors. However, most sarcomas are immune "cold" tumors, with only alveolar soft part sarcoma and undifferentiated pleomorphic sarcoma respond to immune checkpoint inhibitors. Cellular therapies with TCR-engineered T cells, chimeric antigen receptor T cells, tumor infiltrating lymphocytes, and nature killer cells transfer show therapeutic potential. Identifying tumor-specific antigens and exploring immune modulation factors arguing the efficacy of these immunotherapies are the current challenges. This review focuses on the mechanisms, advances, and potential strategies of targeted and immune-based therapies in sarcomas.

Feasibility of high-throughput sequencing in clinical routine cancer care: lessons from the cancer pilot project of the France Genomic Medicine 2025 plan

Background

Whole exome sequencing and RNA sequencing (WES/RNASeq) should now be implemented in the clinical practice in order to increase access to optimal care for cancer patients. Providing results to Tumour Boards in a relevant time frame—that is, compatible with the clinical pathway—is crucial. Assessing the feasibility of this implementation in the French care system is the primary objective of the Multipli study, as one of the four pilot projects of the national France Genomic Medicine 2025 (FGM 2025) plan. The Multipli study encompasses two innovative trials which will be driven in around 2400 patients suffering from a soft-tissue sarcoma (Multisarc) or a metastatic colorectal carcinoma (Acompli).

Methods

Prior to launching the FGM 2025 cancer pilot study itself, the performance of the Multipli genomic workflow has been evaluated through each step, from the samples collection to the Molecular Tumour Board (MTB) report. Two Multipli-assigned INCa-labelled molecular genetics centres, the CEA-CNRGH sequencing platform and the Institut Bergonié’s Bioinformatics Platform were involved in a multicentric study. The duration of each step of the genomic workflow was monitored and bottlenecks were identified.

Results

Thirty barriers which could affect the quality of the samples, sequencing results and the duration of each step of the genomic pathway were identified and mastered. The global turnaround time from the sample reception to the MTB report was of 44 calendar days.

Conclusion

Our results demonstrate the feasibility of tumour genomic analysis by WES/RNASeq within a time frame compatible with the current cancer patient care. Lessons learnt from the Multipli WES/RNASeq Platforms Workflow Study will constitute guidelines for the forthcoming Multipli study and more broadly for the future clinical routine practice in the first two France Genomic Medicine 2025 platforms.

Personalized Medicine in Ovarian Cancer: A Perspective From Mexico

Ovarian cancer (OC) represents a serious health problem worldwide. In Mexico, most OC patients are detected at late stages, consequently making OC one of the leading causes of death in women after reaching puberty. Personalized medicine (PM) provides an individualized therapeutic opportunity for treating each patient relying on “omic” tools to match the correct drug with the specific pathogenic genomic signature. PM can help predict the best therapeutic option for each affected woman suffering from OC. In recent years, Mexico has made contributions to the PM of OC; however, it still has a long way to go for its full implementation in the country’s health system.

Elastic Net Models Based on DNA Copy Number Variations Predicts Clinical Features, Expression Signatures, and Mutations in Lung Adenocarcinoma

In the precision medicine of lung adenocarcinoma, the identification and prediction of tumor phenotypes for specific biomolecular events are still not studied in depth. Various earlier researches sheds light on the close correlation between genetic expression signatures and DNA copy number variations (CNVs), for which analysis of CNVs provides valuable information about molecular and phenotypic changes in tumorigenesis. In this study, we propose a comprehensive analysis combining genome-wide association analysis and an Elastic Net Regression predictive model, focus on predicting the levels of many gene expression signatures in lung adenocarcinoma, based upon DNA copy number features alone. Additionally, we predicted many other key phenotypes, including clinical features (pathological stage), gene mutations, and protein expressions. These Elastic Net prediction methods can also be applied to other gene sets, thereby facilitating their use as biomarkers in monitoring therapy.

Intratumoral Heterogeneity in Differentiated Thyroid Tumors: An Intriguing Reappraisal in the Era of Personalized Medicine

Differentiated thyroid tumors (DTTs) are characterized by significant molecular variability in both spatial and temporal intra-tumoral heterogeneity (ITH), that could influence the therapeutic management. ITH phenomenon appears to have a relevant role in tumor growth, aggressive behavior and drug resistance. Accordingly, characteristics and consequences of ITH in DTTs should be better analyzed and understood in order to guide clinical practice, improving survival. Consequently, in the present review, we investigated morphological and molecular ITH of DTTs in benign, borderline neoplasms and in malignant entities, summarizing the most significant data. Molecular testing in DTTs documents a high risk for recurrence of cancer associated with BRAF^V600E, RET/PTC 1/3, ALK and NTRK fusions, while the intermediate risk may be related to BRAF^K601E, H/K/N RAS and PAX8/PPARγ. In addition, it may be suggested that tumor genotype is associated with peculiar phenotype.

Recent Advances in Integrative Multi-Omics Research in Breast and Ovarian Cancer

The underlying molecular heterogeneity of cancer is responsible for the dynamic clinical landscape of this disease. The combination of genomic and proteomic alterations, including both inherited and acquired mutations, promotes tumor diversity and accounts for variable disease progression, therapeutic response, and clinical outcome. Recent advances in high-throughput proteogenomic profiling of tumor samples have resulted in the identification of novel oncogenic drivers, tumor suppressors, and signaling networks; biomarkers for the prediction of drug sensitivity and disease progression; and have contributed to the development of novel and more effective treatment strategies. In this review, we will focus on the impact of historical and recent advances in single platform and integrative proteogenomic studies in breast and ovarian cancer, which constitute two of the most lethal forms of cancer for women, and discuss the molecular similarities of these diseases, the impact of these findings on our understanding of tumor biology as well as the clinical applicability of these discoveries.

Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine

INTRODUCTION

Precision or personalized Medicine (PM) is used for the prevention and treatment of diseases by considering a huge amount of information about individuals variables. Due to high volume of information, AI-based computational models are required. A large set of studies conducted to examine the PM approach to improve childhood clinical outcomes. Thus, the main goal of this study was to review the application of health information technology and especially artificial intelligence (AI) methods for the treatment of childhood disease using PM.

METHODS

PubMed, Scopus, Web of Science, and EMBASE databases were searched up to December 18, 2019. Articles that focused on informatics applications for childhood disease PM included in this study. Included papers were classified for qualitative analysis and interpreting results. The results were analyzed using Microsoft Excel 2019.

RESULTS

From 341 citations, 62 papers met our inclusion criteria. The number of published papers that used AI methods to apply for PM in childhood diseases increased from 2010 to 2019. Our results showed that most applied methods were related to machine learning discipline. In terms of clinical scope, the largest number of clinical articles are devoted to oncology. Besides, the analysis showed that genomics was the most PM approach used regarding childhood disease.

CONCLUSION

This systematic review examined papers that used AI methods for applying PM approaches in childhood diseases from medical informatics perspectives. Thus, it provided new insight to researchers who are interested in knowing research needs in this field.

A robust method for the rapid detection of microsatellite instability in colorectal cancer

Although several computational tools using next-generation sequencing (NGS) data have been proposed to detect microsatellite instability (MSI) status, they still have limitations and need improvement. We developed a NovoPM-MSI method to detect MSI status based on NGS data. This method evaluated target mononucleotide microsatellite loci that were sequenced during targeted gene enrichment analysis and reported sample instability score as the fraction of unstable loci within the target set after assessing locus instability by comparing length distribution in paired tumor-normal samples. We validated this method against the conventional MSI-PCR method in 113 paired colorectal cancer (CRC) specimens and compared the performance of NovoPM-MSI to that of mSINGS and MANTIS in accuracy and runtime efficiency. By using the MSI status from MSI-PCR as the gold standard, the three computational methods showed the same sensitivity of 88.9% but different specificities (NovoPM-MSI 97.1%, MANTIS 86.5% and mSINGS 99.0%). Only NovoPM-MSI could greatly improve both the sensitivity and specificity by setting an ambiguous interval. MANTIS had the shortest average runtime (16.3 sec), followed by NovoPM-MSI (18.3 sec) and mSINGS (109.0 sec). In short, the NovoPM-MSI method provides a fast and reliable MSI detection method with accuracy comparable to MSI-PCR in paired CRC samples.

Conditionally reprogrammed colorectal cancer cells combined with mouse avatars identify synergy between EGFR and MEK or CDK4/6 inhibitors

Preclinical models, including patient-derived xenograft (PDX) and organoid and primary cell culture, are essential for studies of cancer cell biology and facilitate translational research and individualization of therapy. We explored the optimum preclinical model by modifying the conventional conditional reprogramming (CR) system followed by screening effective targeted drug combinations against colorectal cancer (CRC). By modifying the ingredients of the culture medium used in a conventional CR system, a novel individualized CR system (termed i-CR) was established. Tumor samples from CRC patients were collected and PDX models were derived followed by high-throughput i-CR drug screening and validation of the effective targeted drug combinations. The i-CR system selectively expanded tumor cells rather than normal epithelial cells and facilitated high-throughput drug screening when combined with high-content imaging and quantitative analysis of cell proliferation. Using inhibitors targeting multiple signaling pathways identified by high-throughput i-CR drug screening, we discovered that inhibition of the EGFR and MEK or CDK4/6 pathways exerted a synergistic inhibitory effect against CRC, and we noted super-synergistic effects when EGFR, MEK, and CDK4/6 inhibitors were used simultaneously. These data were validated using paired PDX models, which showed marked inhibition of tumor growth. The novel i-CR system combined with PDX models will enable individualization of therapy and drug discovery, and strategies combining EGFR, MEK, and CDK4/6 inhibitors warrant clinical validation.

Genomic Analysis of Metastatic Solid Tumors in Veterans: Findings From the VHA National Precision Oncology Program

PURPOSE

The Veterans Health Administration (VHA) is the largest cancer care provider in the United States, with the added challenge of serving more than twice the percentage of patients with cancer in rural areas than the national average. The VHA established the National Precision Oncology Program in 2016 to implement and standardize the practice of precision oncology across the diverse VHA system.

METHODS

Tumor or peripheral blood specimens from veterans with advanced solid tumors who were eligible for treatment were submitted for next-generation sequencing (NGS) at two commercial laboratories. Annotated results were generated by the laboratories and independently using IBM Watson for Genomics. Levels-of-evidence treatment recommendations were based on OncoKB criteria.

RESULTS

From July 2016 to June 2018, 3,698 samples from 72 VHA facilities were submitted for NGS testing, of which 3,182 samples (86%) were successfully sequenced. Most samples came from men with lung, prostate, and colorectal cancers. Thirty-four percent of samples were from patients who lived in a rural area. TP53, ATM, and KRAS were among the most commonly mutated genes. Approximately 70% of samples had at least one actionable mutation, with clinical trials identified as the recommended option in more than 50%. Mutations in genes associated with a neuroendocrine prostate cancer phenotype were expressed at increased frequency among veterans than in the general population. The most frequent therapies prescribed in response to NGS testing were immune checkpoint inhibitors, EGFR kinase inhibitors, and PARP inhibitors.

CONCLUSION

Clinical implementation of precision oncology is feasible across the VHA health care system, including rural sites. Veterans have unique occupational exposures that might inform the nature of the mutational signatures identified here. Importantly, these results underscore the importance of increasing clinical trial availability to veterans.

Precision oncology: lessons learned and challenges for the future

The decreasing cost of and increasing capacity of DNA sequencing has led to vastly increased opportunities for population-level genomic studies to discover novel genomic alterations associated with both Mendelian and complex phenotypes. To translate genomic findings clinically, a number of health care institutions have worked collaboratively or individually to initiate precision medicine programs. These precision medicine programs involve designing patient enrollment systems, tracking electronic health records, building biobank repositories, and returning results with actionable matched therapies. As cancer is a paradigm for genetic diseases and new therapies are increasingly tailored to attack genetic susceptibilities in tumors, these precision medicine programs are largely driven by the urgent need to perform genetic profiling on cancer patients in real time. Here, we review the current landscape of precision oncology and highlight challenges to be overcome and examples of benefits to patients. Furthermore, we make suggestions to optimize future precision oncology programs based upon the lessons learned from these "first generation" early adopters.

A personalized platform identifies trametinib plus zoledronate for a patient with KRAS-mutant metastatic colorectal cancer

Colorectal cancer remains a leading source of cancer mortality worldwide. Initial response is often followed by emergent resistance that is poorly responsive to targeted therapies, reflecting currently undruggable cancer drivers such as KRAS and overall genomic complexity. Here, we report a novel approach to developing a personalized therapy for a patient with treatment-resistant metastatic KRAS-mutant colorectal cancer. An extensive genomic analysis of the tumor's genomic landscape identified nine key drivers. A transgenic model that altered orthologs of these nine genes in the Drosophila hindgut was developed; a robotics-based screen using this platform identified trametinib plus zoledronate as a candidate treatment combination. Treating the patient led to a significant response: Target and nontarget lesions displayed a strong partial response and remained stable for 11 months. By addressing a disease's genomic complexity, this personalized approach may provide an alternative treatment option for recalcitrant disease such as KRAS-mutant colorectal cancer.

Drug sensitivity testing on patient-derived sarcoma cells predicts patient response to treatment and identifies c-Sarc inhibitors as active drugs for translocation sarcomas

Background

Heterogeneity and low incidence comprise the biggest challenge in sarcoma diagnosis and treatment. Chemotherapy, although efficient for some sarcoma subtypes, generally results in poor clinical responses and is mostly recommended for advanced disease. Specific genomic aberrations have been identified in some sarcoma subtypes but few of them can be targeted with approved drugs.

Methods

We cultured and characterised patient-derived sarcoma cells and evaluated their sensitivity to 525 anti-cancer agents including both approved and non-approved drugs. In total, 14 sarcomas and 5 healthy mesenchymal primary cell cultures were studied. The sarcoma biopsies and derived cells were characterised by gene panel sequencing, cancer driver gene expression and by detecting specific fusion oncoproteins in situ in sarcomas with translocations.

Results

Soft tissue sarcoma cultures were established from patient biopsies with a success rate of 58%. The genomic profile and drug sensitivity testing on these samples helped to identify targeted inhibitors active on sarcomas. The cSrc inhibitor Dasatinib was identified as an active drug in sarcomas carrying chromosomal translocations. The drug sensitivity of the patient sarcoma cells ex vivo correlated with the response to the former treatment of the patient.

Conclusions

Our results show that patient-derived sarcoma cells cultured in vitro are relevant and practical models for genotypic and phenotypic screens aiming to identify efficient drugs to treat sarcoma patients with poor treatment options.

Next-generation sequencing in precision oncology: Patient understanding and expectations

BACKGROUND

Implementation of precision oncology interventions poses several challenges to informed consent and patient education. This study assessed cancer patients' understanding, expectations, and outcomes regarding participation in research examining the impact of matched tumor and germline sequencing on their clinical care.

METHODS

A total of 297 patients (mean age: 59 years; 50% female; 96% white) with refractory, metastatic cancer were surveyed, including 217 who completed surveys both before and after undergoing integrated whole exome and transcriptome sequencing as part of a larger clinical research study.

RESULTS

At baseline, the vast majority of patients expected to receive several potential direct benefits from study participation, including written reports of sequencing findings (88%), greater understanding of the causes of their cancer (74%), and participation in clinical trials for which sequencing results would make them eligible (84%). In most cases, these benefits were not realized by study completion. Despite explanations from study personnel to the contrary, most participants (67%-76%) presumed that incidental germline sequencing findings relevant to noncancerous health conditions (eg, diabetes) would automatically be disclosed to them. Patients reported low levels of concern about study risks at baseline and low levels of regret about study participation at follow-up.

CONCLUSIONS

Findings suggest that cancer patients participating in precision oncology intervention research have largely unfulfilled expectations of direct benefits related to their study participation. Increased focus on patient education to supplement the informed consent process may help manage patients' expectations regarding the extent and likelihood of benefits received as a result of undergoing genomic sequencing.

Genomics-Enabled Precision Medicine for Cancer

Genomic information is increasingly being incorporated into clinical cancer care. Large-scale sequencing efforts have deepened our understanding of the genomic landscape of cancer and contributed to the expanding catalog of alterations being leveraged to aid in cancer diagnosis, prognosis, and treatment. Genomic profiling can provide clinically relevant information regarding somatic point mutations, copy number alterations, translocations, and gene fusions. Genomic features, such as mutational burden, can also be measured by more comprehensive sequencing strategies and have shown value in informing potential treatment options. Ongoing clinical trials are evaluating the use of molecularly targeted agents in genomically defined subsets of cancers within and across tumor histologies. Continued advancements in clinical genomics promise to further expand the application of genomics-enabled medicine to a broader spectrum of oncology patients.

A multi-omics approach for identifying important pathways and genes in human cancer

Background

Cancer develops when pathways controlling cell survival, cell fate or genome maintenance are disrupted by the somatic alteration of key driver genes. Understanding how pathway disruption is driven by somatic alterations is thus essential for an accurate characterization of cancer biology and identification of therapeutic targets. Unfortunately, current cancer pathway analysis methods fail to fully model the relationship between somatic alterations and pathway activity.

Results

To address these limitations, we developed a multi-omics method for identifying biologically important pathways and genes in human cancer. Our approach combines single-sample pathway analysis with multi-stage, lasso-penalized regression to find pathways whose gene expression can be explained largely in terms of gene-level somatic alterations in the tumor. Importantly, this method can analyze case-only data sets, does not require information regarding pathway topology and supports personalized pathway analysis using just somatic alteration data for a limited number of cancer-associated genes. The practical effectiveness of this technique is illustrated through an analysis of data from The Cancer Genome Atlas using gene sets from the Molecular Signatures Database.

Conclusions

Novel insights into the pathophysiology of human cancer can be obtained from statistical models that predict expression-based pathway activity in terms of non-silent somatic mutations and copy number variation. These models enable the identification of biologically important pathways and genes and support personalized pathway analysis in cases where gene expression data is unavailable.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2476-8) contains supplementary material, which is available to authorized users.

Harnessing formal concepts of biological mechanism to analyze human disease

Mechanism is a widely used concept in biology. In 2017, more than 10% of PubMed abstracts used the term. Therefore, searching for and reasoning about mechanisms is fundamental to much of biomedical research, but until now there has been almost no computational infrastructure for this purpose. Recent work in the philosophy of science has explored the central role that the search for mechanistic accounts of biological phenomena plays in biomedical research, providing a conceptual basis for representing and analyzing biological mechanism. The foundational categories for components of mechanisms-entities and activities-guide the development of general, abstract types of biological mechanism parts. Building on that analysis, we have developed a formal framework for describing and representing biological mechanism, MecCog, and applied it to describing mechanisms underlying human genetic disease. Mechanisms are depicted using a graphical notation. Key features are assignment of mechanism components to stages of biological organization and classes; visual representation of uncertainty, ignorance, and ambiguity; and tight integration with literature sources. The MecCog framework facilitates analysis of many aspects of disease mechanism, including the prioritization of future experiments, probing of gene-drug and gene-environment interactions, identification of possible new drug targets, personalized drug choice, analysis of nonlinear interactions between relevant genetic loci, and classification of diseases based on mechanism.

CancerLinQ: Origins, Implementation, and Future Directions

Rapid-learning health systems have been proposed as a potential solution to the problem of quality in medicine, by leveraging data generated from electronic health systems in near-real time to improve quality and reduce cost. Given the complex, dynamic nature of cancer care, a rapid-learning health system offers large potential benefits to oncology practice. In this article, we review the rationale for developing a rapid-learning health system for oncology and describe the sequence of events that led to the development of ASCO’s CancerLinQ (Cancer Learning Intelligence Network for Quality) initiative, as well as the current state of CancerLinQ, including its importance to efforts such as the Beau Biden Cancer Moonshot. We then review the considerable challenges facing optimal implementation of a rapid-learning health system such as CancerLinQ, including integration of rapidly expanding multiomic data, capturing big data from a variety of sources, an evolving competitive landscape, and implementing a rapid-learning health system in a way that satisfies many stakeholders, including patients, providers, researchers, and administrators.

Improved molecular karyotyping in glioblastoma

Uneven replication creates artifacts during whole genome amplification (WGA) that confound molecular karyotype assignment in single cells. Here, we present an improved WGA recipe that increased coverage and detection of copy number variants (CNVs) in single cells. We examined serial resections of glioblastoma (GBM) tumor from the same patient and found low-abundance clones containing CNVs in clinically relevant loci that were not observable using bulk DNA sequencing. We discovered extensive genomic variability in this class of tumor and provide a practical approach for investigating somatic mosaicism.

DNA Repair Molecular Beacon assay: a platform for real-time functional analysis of cellular DNA repair capacity

Numerous studies have shown that select DNA repair enzyme activities impact response and/or toxicity of genotoxins, suggesting a requirement for enzyme functional analyses to bolster precision medicine or prevention. To address this need, we developed a DNA Repair Molecular Beacon (DRMB) platform that rapidly measures DNA repair enzyme activity in real-time. The DRMB assay is applicable for discovery of DNA repair enzyme inhibitors, for the quantification of enzyme rates and is sufficiently sensitive to differentiate cellular enzymatic activity that stems from variation in expression or effects of amino acid substitutions. We show activity measures of several different base excision repair (BER) enzymes, including proteins with tumor-identified point mutations, revealing lesion-, lesion-context- and cell-type-specific repair dependence; suggesting application for DNA repair capacity analysis of tumors. DRMB measurements using lysates from isogenic control and APE1-deficient human cells suggests the major mechanism of base lesion removal by most DNA glycosylases may be mono-functional base hydrolysis. In addition, development of a microbead-conjugated DRMB assay amenable to flow cytometric analysis further advances its application. Our studies establish an analytical platform capable of evaluating the enzyme activity of select DNA repair proteins in an effort to design and guide inhibitor development and precision cancer therapy options.

Integration of Germline Pharmacogenetics Into a Tumor Sequencing Program

PURPOSE

Evidence-based guidelines inform treatment decisions for patients for whom germline genetic information is available. Our real-time tumor sequencing program, which makes precision treatment decisions for patients with cancer, produces matched germline information, providing a unique opportunity to efficiently implement pharmacogenetics and benefit patients.

METHODS

The germline genetic database from the Michigan Oncology Sequencing (MI-Oncoseq) program was searched for 21 clinically actionable polymorphisms in five cancer-relevant genes: TPMT, DPYD, CYP2C19, CYP3A5, and UGT1A1. Residual germ line DNA was sent to an external Clinical Laboratory Improvement Amendments-approved laboratory for confirmatory genotyping. The medical records of MI-Oncoseq patients with actionable phenotypes were searched for receipt of relevant drugs and to determine whether having genetic information at the time of treatment would have led to a treatment recommendation.

RESULTS

All nine variants in TPMT, DPYD, and CYP2C19 that were detected in MI-Oncoseq were confirmed by external genotyping. Genotype determinations could not be made for CYP3A5*3, UGT1A1*28, or UGT1A1*80. On the basis of retrospective assessment of 115 adult and pediatric patient records, 4.3% (n = 5) had a potentially clinically actionable phenotype for TPMT, DPYD, or CYP2C19 and received a relevant medication. After accounting for differences in adult and pediatric recommendations, three of these patients could have received a treatment recommendation at the time of prescribing.

CONCLUSION

Germline genotype determinations for TPMT, DPYD, and CYP2C19 can be used to make evidence-based treatment recommendations in MI-Oncoseq patients. Although the proportion of patients for whom recommendations can be made is small, this added value to MI-Oncoseq and patient care comes at no additional genotyping cost. Pharmacogenetic assessment should be integrated into tumor sequencing programs that genotype matched germline DNA; however, the complexity and additional cost of implementing pharmacogenetics remain challenging.

Implementation of genomic medicine for gastrointestinal tumors

Genomic medicine is an approach to take advantage of genomic data in medical practice and health care. The advancement of sequencing technologies has enabled the determination of individual genomes as well as the genome in neoplasms. In the field of human cancer, understanding genomic alterations in tumors and variations associated with drug responses has paved the way towards the development of new drugs and personalized medicine. International collaborations of cancer genome analyses have accumulated a huge body of information about somatic mutations, and identified new driver mutations and pathways in a wide range of cancers. In particular, a growing body of evidence has shown that information about mutations in neoplasms helps to assess the efficacy and resistance of anti-cancer drugs. Information about germline mutations associated with hereditary cancer has been shown to benefit patients by enabling early detection of their tumors and disease-specific treatment, as well as reducing the risk for those at risk. To promote personalized medicine in a more cost-effective and personalized way, further inter-institutional, nationwide, and international collaboration is needed. This article summarizes the background and current situation of genomic medicine in the field of gastrointestinal tumors to help physicians and medical coworkers by assisting their better understanding of genomic medicine and strengthening their confidence of its clinical use.

Precision Oncology Decision Support: Current Approaches and Strategies for the Future

With the increasing availability of genomics, routine analysis of advanced cancers is now feasible. Treatment selection is frequently guided by the molecular characteristics of a patient's tumor, and an increasing number of trials are genomically selected. Furthermore, multiple studies have demonstrated the benefit of therapies that are chosen based upon the molecular profile of a tumor. However, the rapid evolution of genomic testing platforms and emergence of new technologies make interpreting molecular testing reports more challenging. More sophisticated precision oncology decision support services are essential. This review outlines existing tools available for health care providers and precision oncology teams and highlights strategies for optimizing decision support. Specific attention is given to the assays currently available for molecular testing, as well as considerations for interpreting alteration information. This article also discusses strategies for identifying and matching patients to clinical trials, current challenges, and proposals for future development of precision oncology decision support. Clin Cancer Res; 24(12); 2719-31. ©2018 AACR.

Full genetic analysis for genome-wide association study of Fangji: a powerful approach for effectively dissecting the molecular architecture of personalized traditional Chinese medicine

Elucidation of the systems biology foundation underlying the effect of Fangji, which are multi-herbal traditional Chinese medicine (TCM) formulas, is one of the major aims in the field. The numerous bioactive ingredients of a Fangji deal with the multiple targets of a complex disease, which is influenced by a number of genes and their interactions with the environment. Genome-wide association study (GWAS) is an unbiased approach for dissecting the genetic variants underlying complex diseases and individual response to a given treatment. GWAS has great potential for the study of systems biology from the point of view of genomics, but the capacity using current analysis models is largely handicapped, as evidenced by missing heritability. Recent development of a full genetic model, in which gene-gene interactions (dominance and epistasis) and gene-environment interactions are all considered, has addressed these problems. This approach has been demonstrated to substantially increase model power, remarkably improving the detection of association of GWAS and the construction of the molecular architecture. This analysis does not require a very large sample size, which is often difficult to meet for a GWAS of treatment response. Furthermore, this analysis can integrate other omic information and allow for variations of Fangji, which is very promising for Fangjiomic study and detection of the sophisticated molecular architecture of the function of Fangji, as well as for the delineation of the systems biology of personalized medicine in TCM in an unbiased and comprehensive manner.

Moving From Mutation to Actionability

The diffusion of high-throughput next-generation sequencing technologies has sustained massive parallel sequencing of tumor tissue providing a deep insight into tumor biology and advancement of personalized medicine. A substantial number of targeted agents have been investigated in gynecologic cancer and some have received U.S. Food and Drug Administration approval, like PARP inhibitors in ovarian cancer, bevacizumab in ovarian and cervical cancers, and pembrolizumab in microsatellite-unstable or mismatch repair-deficient endometrial cancer. To improve effectiveness of targeted therapy, identification of predictive biomarkers able to guide the selection of the correct drug for the correct patient is crucial. Different limitations must be addressed to favor a more rapid implementation of a genotyping approach in treatment selection, such as the possibility to easily assess tumor heterogeneity and clonal evolution along the disease trajectory and the need for innovative trial designs like adaptive or basket trials incorporating molecular features as selection criteria. A deep dive into the genomic features of exceptional responders may also favor better understanding of tumor biology, mechanism of action of a specific target agent, and identification or predictive biomarkers for subsequent tailored studies.

Host-dependent variables: The missing link to personalized medicine

Individualized medicine has the potential to tailor anticancer therapy with the best response and highest safety margin to provide better patient care. However, modern targeted therapies are still being tested through clinical trials comparing preselected patient cohorts and assessed upon behaviour of group averages. Clinically manifesting malignant disease requires identification of host- and tumour-dependent variables such as biological characteristics of the tumour and its microenvironment including immune response features, and overall capacity of the host to receive, tolerate and efficiently utilize treatment. Contemporary medical oncology including clinical trial design need to refocus from assessing group averages to individuality taking into consideration time dependent host-associated characteristics and reinventing outliers to be appreciated as naturally occurring variables collectively determining the ultimate outcome of malignant disease.

Overview on Clinical Relevance of Intra-Tumor Heterogeneity

Today, clinical evaluation of tumor heterogeneity is an emergent issue to improve clinical oncology. In particular, intra-tumor heterogeneity (ITH) is closely related to cancer progression, resistance to therapy, and recurrences. It is interconnected with complex molecular mechanisms including spatial and temporal phenomena, which are often peculiar for every single patient. This review tries to describe all the types of ITH including morphohistological ITH, and at the molecular level clonal ITH derived from genomic instability and nonclonal ITH derived from microenvironment interaction. It is important to consider the different types of ITH as a whole for any patient to investigate on cancer progression, prognosis, and treatment opportunities. From a practical point of view, analytical methods that are widely accessible today, or will be in the near future, are evaluated to investigate the complex pattern of ITH in a reproducible way for a clinical application.

Using SAAS-CNV to Detect and Characterize Somatic Copy Number Alterations in Cancer Genomes from Next Generation Sequencing and SNP Array Data

Somatic copy number alterations (SCNAs) are profound in cancer genomes at different stages: oncogenesis, progression, and metastasis. Accurate detection and characterization of SCNA landscape at genome-wide scale are of great importance. Next-generation sequencing and SNP array are current technology of choice for SCNA analysis. They are able to quantify SCNA with high resolution and meanwhile raise great challenges in data analysis. To this end, we have developed an R package saasCNV for SCNA analysis using (1) whole-genome sequencing (WGS), (2) whole-exome sequencing (WES) or (3) whole-genome SNP array data. In this chapter, we provide the features of the package and step-by-step instructions in detail.

Reduced Retinoblastoma Protein Expression Is Associated with Decreased Patient Survival in Medullary Thyroid Cancer

BACKGROUND

The retinoblastoma (RB) transcriptional corepressor 1 protein functions to slow cell-cycle progression. Inactivation of RB by reduced expression and/or hyperphosphorylation allow for enhanced progression through the cell cycle. Murine models develop medullary thyroid carcinoma (MTC) after generalized loss of RB. However, RB expression in MTC has only been evaluated in a small number of tumors, with differing results. The objective of this study was to determine whether reduced expression of RB and/or overexpression of hyperphosphorylated RB predict MTC aggressive behavior.

METHODS

Formalin-fixed, paraffin-embedded primary thyroid tumors and lymph node metastases from MTC patients were evaluated for calcitonin, RB, and phosphorylated RB (pRB) expression by immunohistochemistry. Two expert pathologists evaluated the slides in a blinded manner, and the immunohistochemistry results were compared to disease-specific survival as a primary endpoint.

RESULTS

Seventy-four MTC samples from 56 patients were analyzed in this study, including 51 primary tumors and 23 lymph node metastases. The median follow-up time was 6.75 years after surgery (range 0.64-24.30 years), and the median primary tumor size was 30 mm (range 6-96 mm). Sixty-six percent of cases were classified as stage IV. RB nuclear expression was diffusely present in 88% of primary tumors and 78% of lymph node metastases. Nuclear pRB expression was present in 22% of primary tumors and 22% of lymph node metastases. On univariate analysis, reduced RB (<75% tumor cell staining) trended with lower MTC-specific survival for primary tumor and metastatic nodes (primary tumor hazard ratio = 3.54 [confidence interval 0.81-15.47], p = 0.08; and lymph node hazard ratio = 4.35 [confidence interval 0.87-21.83], p = 0.05). For primary tumors, multivariable analysis showed that low nuclear RB expression was independently associated with worse disease-specific (p = 0.01) and overall (p = 0.02) survival. pRB levels were not associated with survival for either primary tumor or lymph node metastases.

CONCLUSIONS

Reduced RB expression is associated with decreased patient survival in univariate and multivariable analyses, independent from patient age at surgery or advanced TNM stage. Future studies involving larger MTC patient populations are warranted to determine if lower RB expression levels may serve as a biomarker for aggressive disease in patients with MTC.

CASTLE tumor of the parotid: First documented case, literature review, and genetic analysis of the cancer

BACKGROUND

Carcinoma showing thymus-like elements (CASTLE) is a rare tumor that normally affects the thyroid gland and was thought to arise from either the remnants of the branchial pouch or the ectopic cervical thymic tissue. These tumors show strong immunopositivity for CD5, P63, and CD117. Most CASTLE of the thyroid gland is treated with surgery with or without adjuvant radiotherapy or chemotherapy.

METHOD

A 55-year-old woman presented with a slow-growing right parotid mass. A right total parotidectomy and ipsilateral selective neck dissection were performed and the diagnosis of CASTLE was made after confirmation with an immunohistochemistry test. She received radiotherapy postoperatively.

RESULTS

Genetic sequencing showed alterations in the PPARG, BRCA2, and NOTCH1 genes. She remained disease free for >1 year after treatment.

CONCLUSION

We believe that this is the first reported case of CASTLE in the parotid gland. Clinicians should be aware of this rare entity and consider this differential diagnosis after ruling out other common parotid lesions.

Institutional profile: translational pharmacogenomics at the Icahn School of Medicine at Mount Sinai

For almost 50 years, the Icahn School of Medicine at Mount Sinai has continually invested in genetics and genomics, facilitating a healthy ecosystem that provides widespread support for the ongoing programs in translational pharmacogenomics. These programs can be broadly cataloged into discovery, education, clinical implementation and testing, which are collaboratively accomplished by multiple departments, institutes, laboratories, companies and colleagues. Focus areas have included drug response association studies and allele discovery, multiethnic pharmacogenomics, personalized genotyping and survey-based education programs, pre-emptive clinical testing implementation and novel assay development. This overview summarizes the current state of translational pharmacogenomics at Mount Sinai, including a future outlook on the forthcoming expansions in overall support, research and clinical programs, genomic technology infrastructure and the participating faculty.

Insights into beta cell regeneration for diabetes via integration of molecular landscapes in human insulinomas

Although diabetes results in part from a deficiency of normal pancreatic beta cells, inducing human beta cells to regenerate is difficult. Reasoning that insulinomas hold the “genomic recipe” for beta cell expansion, we surveyed 38 human insulinomas to obtain insights into therapeutic pathways for beta cell regeneration. An integrative analysis of whole-exome and RNA-sequencing data was employed to extensively characterize the genomic and molecular landscape of insulinomas relative to normal beta cells. Here, we show at the pathway level that the majority of the insulinomas display mutations, copy number variants and/or dysregulation of epigenetic modifying genes, most prominently in the polycomb and trithorax families. Importantly, these processes are coupled to co-expression network modules associated with cell proliferation, revealing candidates for inducing beta cell regeneration. Validation of key computational predictions supports the concept that understanding the molecular complexity of insulinoma may be a valuable approach to diabetes drug discovery.

Diabetes results in part from a deficiency of functional pancreatic beta cells. Here, the authors study the genomic and epigenetic landscapes of human insulinomas to gain insight into possible pathways for therapeutic beta cell regeneration, highlighting epigenetic genes and pathways.

Resources for Interpreting Variants in Precision Genomic Oncology Applications

Precision genomic oncology-applying high throughput sequencing (HTS) at the point-of-care to inform clinical decisions-is a developing precision medicine paradigm that is seeing increasing adoption. Simultaneously, new developments in targeted agents and immunotherapy, when informed by rich genomic characterization, offer potential benefit to a growing subset of patients. Multiple previous studies have commented on methods for identifying both germline and somatic variants. However, interpreting individual variants remains a significant challenge, relying in large part on the integration of observed variants with biological knowledge. A number of data and software resources have been developed to assist in interpreting observed variants, determining their potential clinical actionability, and augmenting them with ancillary information that can inform clinical decisions and even generate new hypotheses for exploration in the laboratory. Here, we review available variant catalogs, variant and functional annotation software and tools, and databases of clinically actionable variants that can be used in an ad hoc approach with research samples or incorporated into a data platform for interpreting and formally reporting clinical results.