The current state of molecular testing in the treatment of patients with solid tumors, 2019

Precision medicine in breast cancer (Review)

Precision medicine in breast cancer is a revolutionary approach that customizes diagnosis and treatment based on individual and tumor characteristics, departing from the traditional one-size-fits-all approach. Breast cancer is diverse, with various subtypes driven by distinct genetic mutations. Understanding this diversity is crucial for tailored treatment strategies that target specific vulnerabilities in each tumor. Genetic testing, particularly for mutations in breast cancer gene (BRCA) DNA repair-associated genes, helps assess hereditary risks and influences treatment decisions. Molecular subtyping guides personalized treatments, such as hormonal therapies for receptor-positive tumors and human epidermal growth factor receptor 2 (HER2)-targeted treatments. Targeted therapies, including those for HER2-positive and hormone receptor-positive breast cancers, offer more effective and precise interventions. Immunotherapy, especially checkpoint inhibitors, shows promise, particularly in certain subtypes such as triple-negative breast cancer, with ongoing research aiming to broaden its effectiveness. Integration of big data and artificial intelligence enhances personalized treatment strategies, while liquid biopsies provide real-time insights into tumor dynamics, aiding in treatment monitoring and modification. Challenges persist, including accessibility and tumor complexity, but emerging technologies and precision prevention offer hope for improved outcomes. Ultimately, precision medicine aims to optimize treatment efficacy, minimize adverse effects and enhance the quality of life for patients with breast cancer.

Disparities in postoperative adjuvant therapy utilization and factors impacting survival among anaplastic thyroid cancer patients

BACKGROUND

Anaplastic thyroid cancer (ATC) is highly aggressive with a poor prognosis. Adjuvant systemic therapy and radiation post-surgery are endorsed by NCCN and ATA guidelines. Our study aimed to identify those at risk of forgoing postoperative adjuvant treatment and to determine survival predictors.

METHODS

We used the National Cancer Database (NCDB) to identify ATC patients who underwent upfront thyroidectomy from 2010 to 2017, excluding those opting for palliative care. We compared demographics, characteristics, treatments, and outcomes between those who received adjuvant therapy and those who did not. Predictors of receiving adjuvant therapy were identified using logistic regression, while Cox regression identified survival factors.

RESULTS

Of 563 patients, 160 received no adjuvant treatment, 82 received radiation only, 16 received systemic therapy only, and 305 received combination therapy. Notably, over 75 ​% of patients who did not receive adjuvant treatment had it excluded from their treatment plan, not due to refusal. Older age (OR 0.92) and non-white race/ethnicity (OR 0.33) were significant predictors of not receiving adjuvant therapy. Undergoing a total thyroidectomy, an R0 or R1 resection, and radiation or combination therapy were associated with better survival, while non-metropolitan location, primary tumor size >7.5 ​cm, and stage IVC disease were negative factors.

CONCLUSION

Total thyroidectomy, R0/R1 resection, and adjuvant therapy reduce mortality in ATC patients. However, older patients and minorities are less likely to receive adjuvant therapy, underscoring disparities in treatment adherence.

Advances in the Diagnosis and Treatment of Follicular Thyroid Carcinoma: A Comprehensive Review

Follicular thyroid carcinoma (FTC) is the second most common type of thyroid cancer, presenting unique diagnostic and therapeutic challenges. This review provides a comprehensive analysis of the recent advancements in the diagnosis and treatment of FTC, emphasizing the significance of these developments in improving patient outcomes. We discuss the evolution of diagnostic techniques, including advancements in imaging modalities, fine needle aspiration biopsy, and molecular diagnostics, which have enhanced the accuracy of FTC detection and differentiation from benign conditions. The review also evaluates current treatment strategies, including surgical interventions, radioactive iodine therapy, and targeted therapies, examining their effectiveness and impact on patient prognosis. Additionally, we address ongoing challenges in FTC management, such as variability in treatment guidelines and disparities in care. Finally, the review explores emerging therapies and future research directions, highlighting innovations that may further optimize FTC management. By synthesizing current knowledge and identifying future research opportunities, this review aims to contribute to refining diagnostic and therapeutic approaches for FTC.

Fusion Challenges in Solid Tumors: Shaping the Landscape of Cancer Care in Precision Medicine

Targeting actionable fusions has emerged as a promising approach to cancer treatment. Next-generation sequencing (NGS)-based techniques have unveiled the landscape of actionable fusions in cancer. However, these approaches remain insufficient to provide optimal treatment options for patients with cancer. This article provides a comprehensive overview of the actionability and clinical development of targeted agents aimed at driver fusions. It also highlights the challenges associated with fusion testing, including the evaluation of patients with cancer who could potentially benefit from testing and devising an effective strategy. The implementation of DNA NGS for all tumor types, combined with RNA sequencing, has the potential to maximize detection while considering cost effectiveness. Herein, we also present a fusion testing strategy aimed at improving outcomes in patients with cancer.

Cancer mutational signatures identification in clinical assays using neural embedding-based representations

While mutational signatures provide a plethora of prognostic and therapeutic insights, their application in clinical-setting, targeted gene panels is extremely limited. We develop a mutational representation model (which learns and embeds specific mutation signature connections) that enables prediction of dominant signatures with only a few mutations. We predict the dominant signatures across more than 60,000 tumors with gene panels, delineating their landscape across different cancers. Dominant signature predictions in gene panels are of clinical importance. These included UV, tobacco, and apolipoprotein B mRNA editing enzyme, catalytic polypeptide (APOBEC) signatures that are associated with better survival, independently from mutational burden. Further analyses reveal gene and mutation associations with signatures, such as SBS5 with TP53 and APOBEC with FGFR3S249C. In a clinical use case, APOBEC signature is a robust and specific predictor for resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs). Our model provides an easy-to-use way to detect signatures in clinical setting assays with many possible clinical implications for an unprecedented number of cancer patients.

Near-Infrared Spectroscopy for Distinguishing Malignancy in Thyroid Nodules

Thyroid nodules are common clinical entities, with a significant proportion being malignant. Early, accurate, and non-invasive tools to differentiate benign and malignant nodules can optimize patient management and reduce unnecessary surgery. This study aimed to evaluate the efficacy and accuracy of near-infrared spectroscopy (NIRS) in distinguishing benign from malignant thyroid nodules. A diffuse reflectance spectrum for a total of 20 thyroid nodule samples (10 samples as colloid goiter and 10 samples as thyroid cancer), were acquired in the wavelength range from 1000 to 2500 nm. Spectral data from NIRS were analyzed by means of principal component analysis (PCA), quadratic discriminant analysis (QDA), and linear discriminant analysis (LDA) to classify and differentiate thyroid nodule samples. The present study found that NIRS effectively distinguished colloid goiter and thyroid cancer using the first two principal components (PCs), explaining 90% and 10% of the variance, respectively. QDA discrimination plot displayed a clear separation between colloid goiter and thyroid cancer with minimal overlap, aligning with reported 95% accuracy. Additionally, applying LDA to seven PCs from PCA achieved a 100% accuracy rate in classifying colloid goiter and thyroid cancer from near-infrared spectral data. In conclusion, NIRS offers a promising, non-invasive complementing diagnostic tool for differentiating benign from malignant thyroid nodules with high accuracy. Future work should integrate these results into predictive model development, emphasizing external validation, alternative performance metrics, and protecting against potential overfitting translation of a machine learning model to a clinical setting.

Deprivation of methionine inhibits osteosarcoma growth and metastasis via C1orf112-mediated regulation of mitochondrial functions

Osteosarcoma is a malignant bone tumor that primarily inflicts the youth. It often metastasizes to the lungs after chemotherapy failure, which eventually shortens patients' lives. Thus, there is a dire clinical need to develop a novel therapy to tackle osteosarcoma metastasis. Methionine dependence is a special metabolic characteristic of most malignant tumor cells that may offer a target pathway for such therapy. Herein, we demonstrated that methionine deficiency restricted the growth and metastasis of cultured human osteosarcoma cells. A genetically engineered Salmonella, SGN1, capable of overexpressing an L-methioninase and hydrolyzing methionine led to significant reduction of methionine and S-adenosyl-methionine (SAM) specifically in tumor tissues, drastically restricted the growth and metastasis in subcutaneous xenograft, orthotopic, and tail vein-injected metastatic models, and prolonged the survival of the model animals. SGN1 also sharply suppressed the growth of patient-derived organoid and xenograft. Methionine restriction in the osteosarcoma cells initiated severe mitochondrial dysfunction, as evident in the dysregulated gene expression of respiratory chains, increased mitochondrial ROS generation, reduced ATP production, decreased basal and maximum respiration, and damaged mitochondrial membrane potential. Transcriptomic and molecular analysis revealed the reduction of C1orf112 expression as a primary mechanism underlies methionine deprivation-initiated suppression on the growth and metastasis as well as mitochondrial functions. Collectively, our findings unraveled a molecular linkage between methionine restriction, mitochondrial function, and osteosarcoma growth and metastasis. A pharmacological agent, such as SGN1, that can achieve tumor specific deprivation of methionine may represent a promising modality against the metastasis of osteosarcoma and potentially other types of sarcomas as well.

The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings

PURPOSE

Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner.

METHODS

We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported.

RESULTS

The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing).

CONCLUSION

Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

Comprehensive pan-cancer analysis identifies the RNA-binding protein LRPPRC as a novel prognostic and immune biomarker

AIMS

RNA-binding proteins (RBPs) play pivotal roles in carcinogenesis and immunotherapy. Leucine-rich pentapeptide repeat-containing protein (LRPPRC) is crucial for RNA polyadenylation, transport, and stability. Although recent studies have suggested LRPPRC's potential role in tumor progression, its significance in tumor prognosis, diagnosis, and immunology remains unclear.

MAIN METHODS

We comprehensively analyzed LRPPRC expression in tumors using various databases, including Human Transcriptome Cell Atlas (HTCA), University of California Santa Cruz (UCSC), Human Protein Atlas (HPA), Sangerbox, TISIDB, GeneMANIA, GSCALite, and CellMiner. We examined the correlation between LRPPRC expression level and prognosis, immune infiltration, immunotherapy, methylation, biological function, and drug sensitivity. Single-cell analysis was performed using Tumor Immune Single Cell Hub (TISCH) and CancerSEA software. Patients with acute myeloid leukemia (AML) were categorized based on LRPPRC levels for functional and immune infiltration analyses. The role of LRPPRC in cancer was validated using in vitro experiments.

KEY FINDINGS

Our findings revealed that LRPPRC was highly expressed in almost all cancer types, indicating its significant prognostic and diagnostic potential. Notably, LRPPRC was associated with diverse immune features, such as immune cell infiltration, immune checkpoint genes, tumor mutational burden, and microsatellite instability, suggesting its value in guiding immunotherapy strategies. Within AML, the high-expression group had lower levels of immune cells, including CD8+ T cells. In vitro experiments confirmed the inhibitory effects of LRPPRC knockdown on AML cell proliferation.

SIGNIFICANCE

This study highlights LRPPRC as a reliable pan-cancer prognostic and immune biomarker, particularly in AML. It lays the groundwork for future research on LRPPRC-targeted cancer therapies.

Identification and validation of serum metabolite biomarkers for endometrial cancer diagnosis

Endometrial cancer (EC) stands as the most prevalent gynecological tumor in women worldwide. Notably, differentiation diagnosis of abnormity detected by ultrasound findings (e.g., thickened endometrium or mass in the uterine cavity) is essential and remains challenging in clinical practice. Herein, we identified a metabolic biomarker panel for differentiation diagnosis of EC using machine learning of high-performance serum metabolic fingerprints (SMFs) and validated the biological function. We first recorded the high-performance SMFs of 191 EC and 204 Non-EC subjects via particle-enhanced laser desorption/ionization mass spectrometry (PELDI-MS). Then, we achieved an area-under-the-curve (AUC) of 0.957-0.968 for EC diagnosis through machine learning of high-performance SMFs, outperforming the clinical biomarker of cancer antigen 125 (CA-125, AUC of 0.610-0.684, p < 0.05). Finally, we identified a metabolic biomarker panel of glutamine, glucose, and cholesterol linoleate with an AUC of 0.901-0.902 and validated the biological function in vitro. Therefore, our work would facilitate the development of novel diagnostic biomarkers for EC in clinics.

Cholangiocarcinoma: Pathologic and Molecular Classification in the Era of Precision Medicine

CONTEXT.—

Cholangiocarcinoma (CCA) is a heterogeneous cancer of the bile duct, and its diagnosis is often challenging.

OBJECTIVE.—

To provide insights into state-of-the-art approaches for the diagnosis of CCA.

DATA SOURCES.—

Literature review via PubMed search and authors' experiences.

CONCLUSIONS.—

CCA can be categorized as intrahepatic or extrahepatic. Intrahepatic CCA is further classified into small-duct-type and large-duct-type, whereas extrahepatic CCA is classified into distal and perihilar according to site of origin within the extrahepatic biliary tree. Tumor growth patterns include mass forming, periductal infiltrating, and intraductal tumors. The clinical diagnosis of CCA is challenging and usually occurs at an advanced tumor stage. Pathologic diagnosis is made difficult by tumor inaccessibility and challenges in distinguishing CCA from metastatic adenocarcinoma to the liver. Immunohistochemical stains can assist in differentiating CCA from other malignancies, such as hepatocellular carcinoma, but no distinctive CCA-specific immunohistochemical profile has been identified. Recent advances in next-generation sequencing-based high-throughput assays have identified distinct genomic profiles of CCA subtypes, including genomic alterations that are susceptible to targeted therapies or immune checkpoint inhibitors. Detailed histopathologic and molecular evaluations of CCA by pathologists are critical for correct diagnosis, subclassification, therapeutic decision-making, and prognostication. The first step toward achieving these goals is to acquire a detailed understanding of the histologic and genetic subtypes of this heterogeneous tumor group. Here, we review state-of-the-art approaches that should be applied to establish a diagnosis of CCA, including clinical presentation, histopathology, staging, and the practical use of genetic testing methodologies.

Liquid biopsy: New opportunities for precision medicine in hepatocellular carcinoma care

Liquid biopsy, specifically the analysis of circulating tumor DNA (ctDNA), offers a non-invasive approach for hepatocellular carcinoma (HCC) diagnosis and management. However, its implementation in the clinical setting is difficult due to challenges such as low ctDNA yield and difficulty in understanding the mutation signals from background noise. This review highlights the crucial role of artificial intelligence (AI) in addressing these limitations and in improving discoveries in the field of liquid biopsy for HCC care. Combining AI with liquid biopsy data can offer a promising future for the discovery of novel biomarkers and an AI-powered clinical decision support system (CDSS) can turn liquid biopsy into an important tool for personalized management of HCC. Despite the current challenges, the integration of AI shows promise to significantly improve patient outcomes and revolutionize the field of oncology.

Circulating miRNAs as biomarkers for the diagnosis in patients with melanoma: systematic review and meta-analysis

Objective: Melanoma is the most aggressive and deadly form of skin cancer, especially at later stages. There is currently no excellent diagnostic test established for the diagnosis of melanoma; however, circulating microRNAs (miRNAs) have shown some promise. We seek to conduct a systematic review and meta-analysis to establish the clinical utility of circulating miRNAs in diagnosing melanoma. Methods: PubMed, Wiley, and Web of Science were searched for studies that determined miRNA sensitivity and specificity in patients with melanoma. The included studies were assessed in Stata, and the sensitivity, specificity, summary receiver operating characteristic (SROC), positive likelihood ratio, negative likelihood ratio, and the area under the SROC curve (AUC) were calculated. Results: 9 studies with 898 melanoma patients were included in the meta-analysis. The circulating miRNAs showed high diagnostic accuracy with a sensitivity of 0.89 (p < 0.001), specificity of 0.85 (p < 0.001), diagnostic odds ratio of 45, and an area under the curve of 0.93. Conclusion: Circulating miRNAs have shown a high diagnostic power in detecting melanoma.

Understanding communication between patients and healthcare professionals regarding comprehensive biomarker testing in precision oncology: A scoping review

BACKGROUND

Precision oncology, using comprehensive biomarker testing (cBT) to inform individual cancer diagnosis, prognosis and treatment, includes increasingly complex technology and clinical data sets. People impacted by cancer (patients and caregivers) and healthcare professionals (HCPs) face distinct challenges in navigating the cBT and personalized treatment landscape. This review summarizes evidence regarding cBT-related communication between people impacted by cancer and HCPs and identifies important avenues for future research in precision oncology.

METHODS

A scoping review was conducted using records published in PubMed during January 2017-August 2022, focusing on the breadth of topics on patient-HCP communication and knowledge resources used by HCPs as guidance in cBT-related communication. Data were extracted from records meeting inclusion criteria, and findings were summarized according to main topics.

RESULTS

The search identified 287 unique records and data were extracted from 42 records, including nine from expert input. Most records originated from the United States included patients with different types of cancer, and oncologists were the main HCPs. Patients' motivation for undergoing cBT and receiving results was generally high in different settings. However, patients' understanding of cBT-related concepts was limited, and their knowledge and information preferences changed based on cBT implications and significance to family members. HCPs were valued by patients as a trusted source of information. Limited evidence was available on HCPs' information-seeking behavior and factors influencing cBT-related knowledge and confidence, often self-reported as insufficient.

CONCLUSIONS

Patient education by knowledgeable and confident HCPs, information management and a caring patient-HCP relationship communicating continuity of care regardless of cBT results are crucial to empower patients and shared decision-making in precision oncology. More data on the process and structure of cBT-related communication, distinction between and characterization of different timepoints of patient-HCP interactions are needed.

Incorporating Novel Technologies in Precision Oncology for Colorectal Cancer: Advancing Personalized Medicine

Colorectal cancer (CRC) is one of the most heterogeneous and deadly diseases, with a global incidence of 1.5 million cases per year. Genomics has revolutionized the clinical management of CRC by enabling comprehensive molecular profiling of cancer. However, a deeper understanding of the molecular factors is needed to identify new prognostic and predictive markers that can assist in designing more effective therapeutic regimens for the improved management of CRC. Recent breakthroughs in single-cell analysis have identified new cell subtypes that play a critical role in tumor progression and could serve as potential therapeutic targets. Spatial analysis of the transcriptome and proteome holds the key to unlocking pathogenic cellular interactions, while liquid biopsy profiling of molecular variables from serum holds great potential for monitoring therapy resistance. Furthermore, gene expression signatures from various pathways have emerged as promising prognostic indicators in colorectal cancer and have the potential to enhance the development of equitable medicine. The advancement of these technologies for identifying new markers, particularly in the domain of predictive and personalized medicine, has the potential to improve the management of patients with CRC. Further investigations utilizing similar methods could uncover molecular subtypes specific to emerging therapies, potentially strengthening the development of personalized medicine for CRC patients.

Epithelioid angiomyolipoma of the liver in a patient with Li-Fraumeni syndrome: a case report

BACKGROUND

Epithelioid angiomyolipoma (EAML) is a rare variant of angiomyolipoma that predominantly consists of epithelioid cells and belongs to the perivascular epithelioid cell neoplasm (PEComa) family. The majority of EAMLs arise in the kidneys, and primary hepatic EAML appears to be much less common than renal EAML. Most PEComas arise sporadically, but may be associated with tuberous sclerosis complex (TSC), an autosomal dominant genetic disorder characterized by germline mutations in the TSC1 or TSC2 genes. However, PEComas have previously been reported in five patients with Li-Fraumeni syndrome (LFS), which is an inherited cancer susceptibility disorder resulting from germline mutations in the TP53 tumor suppressor gene.

CASE PRESENTATION

We report a 49-year-old female patient with hepatic EAML and pancreatic cancer. Because she had previously been diagnosed with bilateral breast cancer at the age of 30, we performed a comprehensive genetic analysis to identify genetic alterations associated with any cancer predisposition syndrome. Whole-exome sequencing of a blood sample identified a heterozygous germline variant of TP53 (NM_000546.5):c.708C>A, and targeted next-generation sequencing of liver EAML and pancreatic cancer tissue samples demonstrated the same TP53 (NM_000546.5):c.708C>A variant in both. This, plus the patient's history of early-onset breast cancer, met the 2015 version of the Chompret criteria for diagnosis of LFS.

CONCLUSIONS

There have been very few case reports regarding the presence of PEComa in LFS, and to the best of our knowledge, this is the first report of EAML of the liver in a patient with LFS.

Diagnosis of Esophageal Squamous Cell Carcinoma by High-Performance Serum Metabolic Fingerprints: A Retrospective Study

Esophageal squamous cell carcinoma (ESCC) is a highly prevalent and aggressive malignancy, and timely diagnosis of ESCC contributes to an increased cancer survival rate. However, current detection methods for ESCC mainly rely on endoscopic examination, limited by a relatively low participation rate. Herein, ferric-particle-enhanced laser desorption/ionization mass spectrometry (FPELDI MS) is utilized to record the serum metabolic fingerprints (SMFs) from a retrospective cohort (523 non-ESCC participants and 462 ESCC patients) to build diagnostic models toward ESCC. The PFELDI MS achieved high speed (≈30 s per sample), desirable reproducibility (coefficients of variation < 15%), and high throughput (985 samples with ≈124 200 data points for each spectrum). Desirable diagnostic performance with area-under-the-curves (AUCs) of 0.925-0.966 is obtained through machine learning of SMFs. Further, a metabolic biomarker panel is constructed, exhibiting superior diagnostic sensitivity (72.2-79.4%, p < 0.05) as compared with clinical protein biomarker tests (4.3-22.9%). Notably, the biomarker panel afforded an AUC of 0.844 (95% confidence interval [CI]: 0.806-0.880) toward early ESCC diagnosis. This work highlighted the potential of metabolic analysis for accurate screening and early detection of ESCC and offered insights into the metabolic characterization of diseases including but not limited to ESCC.

Somatic mutations in a multigene panel and impact on prognosis based on TP53 status in Chinese HER2-positive patients undergoing neoadjuvant therapy: A single-institution retrospective cohort

BACKGROUND

Gene mutations play a crucial role in the occurrence and development of tumors, particularly in breast cancer (BC). Neoadjuvant therapy (NAT) has shown greater clinical benefit in HER2-positive breast cancer. However, further clinical investigation is needed to fully understand the correlation between genetic mutations and NAT efficacy and the long-term prognosis in HER2-positive BC.

METHODS

This was a retrospective cohort study of 222 patients receiving NAT between 2017 and 2021 in the Department of Breast Surgery of Fudan University Shanghai Cancer Center. Tumor samples from these patients were subjected to Next Generation Sequencing (NGS) to analyze mutations in 513 cancer-related genes. This study aimed to investigate the association between these genetic mutations and postoperative pathological complete response (pCR), as well as their impact on disease-free survival (DFS).

RESULTS

In total, 48.65% patients reached pCR, ER-negative status (p < 0.001), PR-negative status (p < 0.001), Ki67 ≥ 20 (p = 0.011), and dual-targeted therapy (p < 0.001) were all associated with enhanced pCR rates. The frequency of somatic alterations in TP53 (60%), PIK3CA (15%), and ERBB2 (11%) was highest. In the HER2+/HR- cohort, patients who achieved pCR had a significant benefit in prognosis (HR = 3.049, p = 0.0498). KMT2C (p = 0.036) and TP53 (p = 0.037) mutations were significantly increased in patients with DFS events. Moreover, TP53 mutations had prognostic significance in HER2-positive BC patients with HR-negative (HR = 3.712, p = 0.027) and pCR (HR = 6.253, p = 0.027) status and who received herceptin-only targeted therapy (HR = 4.145, p = 0.011).

CONCLUSIONS

The genetic mutation profiles of Chinese HER2+ patients who received NAT were discrepant with respect to HR status or DFS events. TP53 mutations have significant prognostic value in patients with NAT for HER2-positive BC and patients benefit differently depending on HR status, the neoadjuvant regimen and response, which highlights the significance of genetic factors in treatment customization based on individual genetic and clinical characteristics.

The Landscape of BRCA Mutations among Egyptian Women with Breast Cancer

BACKGROUND

Deleterious germline mutations in BRCA1 and BRCA2 genes are associated with a high risk of breast and ovarian cancer. In many developing countries, including Egypt, the prevalence of BRCA1/2 mutations among women with breast cancer (BC) is unknown.

AIM

We aimed to determine the prevalence of deleterious germline BRCA mutations in Egyptian patients with breast cancer.

METHODS

We report the results of a cohort study of 81 Egyptian patients with breast cancer who were tested for germline BRCA1/2 mutations during routine clinical practice, mostly for their young age of presentation, BC subtype, or presence of family history. In addition, we searched five databases to retrieve studies that reported the prevalence of BRCA1/2 mutation status in Egyptian women with BC. A systematic review of the literature was performed, including prospective and retrospective studies.

RESULTS

In our patient cohort study, 12 patients (14.8%) were positive for either BRCA1/2 deleterious mutations. Moreover, 13 (16.1%) patients had a variant of unknown significance (VUS) of BRCA1/2 genes. Twelve studies were eligible for the systematic review, including 610 patients. A total of 19 deleterious germline mutations in BRCA1/2 were identified. The pooled prevalence of BRCA1/2 mutations was 40% (95% confidence interval 1-80%).

CONCLUSION

The reported prevalence was highly variable among the small-sized published studies that adopted adequate techniques. In our patient cohort, there was a high incidence of VUS in BRCA1/2 genes. Accordingly, there is an actual demand to conduct a prospective well-designed national study to accurately estimate the prevalence of BRCA1/2 mutations among patients with BC in Egypt.

Efficient plasma metabolic fingerprinting as a novel tool for diagnosis and prognosis of gastric cancer: a large-scale, multicentre study

OBJECTIVE

Metabolic biomarkers are expected to decode the phenotype of gastric cancer (GC) and lead to high-performance blood tests towards GC diagnosis and prognosis. We attempted to develop diagnostic and prognostic models for GC based on plasma metabolic information.

DESIGN

We conducted a large-scale, multicentre study comprising 1944 participants from 7 centres in retrospective cohort and 264 participants in prospective cohort. Discovery and verification phases of diagnostic and prognostic models were conducted in retrospective cohort through machine learning and Cox regression of plasma metabolic fingerprints (PMFs) obtained by nanoparticle-enhanced laser desorption/ionisation-mass spectrometry (NPELDI-MS). Furthermore, the developed diagnostic model was validated in prospective cohort by both NPELDI-MS and ultra-performance liquid chromatography-MS (UPLC-MS).

RESULTS

We demonstrated the high throughput, desirable reproducibility and limited centre-specific effects of PMFs obtained through NPELDI-MS. In retrospective cohort, we achieved diagnostic performance with areas under curves (AUCs) of 0.862-0.988 in the discovery (n=1157 from 5 centres) and independent external verification dataset (n=787 from another 2 centres), through 5 different machine learning of PMFs, including neural network, ridge regression, lasso regression, support vector machine and random forest. Further, a metabolic panel consisting of 21 metabolites was constructed and identified for GC diagnosis with AUCs of 0.921-0.971 and 0.907-0.940 in the discovery and verification dataset, respectively. In the prospective study (n=264 from lead centre), both NPELDI-MS and UPLC-MS were applied to detect and validate the metabolic panel, and the diagnostic AUCs were 0.855-0.918 and 0.856-0.916, respectively. Moreover, we constructed a prognosis scoring system for GC in retrospective cohort, which can effectively predict the survival of GC patients.

CONCLUSION

We developed and validated diagnostic and prognostic models for GC, which also contribute to advanced metabolic analysis towards diseases, including but not limited to GC.

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

The application of long-read sequencing in clinical settings

Long-read DNA sequencing technologies have been rapidly evolving in recent years, and their ability to assess large and complex regions of the genome makes them ideal for clinical applications in molecular diagnosis and therapy selection, thereby providing a valuable tool for precision medicine. In the third-generation sequencing duopoly, Oxford Nanopore Technologies and Pacific Biosciences work towards increasing the accuracy, throughput, and portability of long-read sequencing methods while trying to keep costs low. These trades have made long-read sequencing an attractive tool for use in research and clinical settings. This article provides an overview of current clinical applications and limitations of long-read sequencing and explores its potential for point-of-care testing and health care in remote settings.

Artificial Intelligence-Driven Morphology-Based Enrichment of Malignant Cells from Body Fluid

Cell morphology is a fundamental feature used to evaluate patient specimens in pathologic analysis. However, traditional cytopathology analysis of patient effusion samples is limited by low tumor cell abundance coupled with the high background of nonmalignant cells, restricting the ability of downstream molecular and functional analyses to identify actionable therapeutic targets. We applied the Deepcell platform that combines microfluidic sorting, brightfield imaging, and real-time deep learning interpretations based on multidimensional morphology to enrich carcinoma cells from malignant effusions without cell staining or labels. Carcinoma cell enrichment was validated with whole genome sequencing and targeted mutation analysis, which showed a higher sensitivity for detection of tumor fractions and critical somatic variant mutations that were initially at low levels or undetectable in presort patient samples. Our study demonstrates the feasibility and added value of supplementing traditional morphology-based cytology with deep learning, multidimensional morphology analysis, and microfluidic sorting.

ANO1-Mediated Inhibition of Cancer Ferroptosis Confers Immunotherapeutic Resistance through Recruiting Cancer-Associated Fibroblasts

The application of immunotherapy in gastrointestinal (GI) cancers remains challenging because of the limited response rate and emerging therapeutic resistance. Combining clinical cohorts, multi-omics study, and functional/molecular experiments, it is found that ANO1 amplification or high-expression predicts poor outcomes and resistance to immunotherapy for GI cancer patients. Knocking-down or inhibiting ANO1 suppresses the growth/metastasis/invasion of multiple GI cancer cell lines, cell-derived xenograft, and patient-derived xenograft models. ANO1 contributes to an immune-suppressive tumor microenvironment and induces acquired resistance to anti-PD-1 immunotherapy, while ANO1 knockdown or inhibition enhances immunotherapeutic effectiveness and overcomes resistance to immunotherapy. Mechanistically, through inhibiting cancer ferroptosis in a PI3K-Akt signaling-dependent manner, ANO1 enhances tumor progression and facilitates cancer-associated fibroblast recruitment by promoting TGF-β release, thus crippling CD8+ T cell-mediated anti-tumor immunity and generating resistance to immunotherapy. This work highlights ANO1's role in mediating tumor immune microenvironment remodeling and immunotherapeutic resistance, and introduces ANO1 as a promising target for GI cancers' precision treatment.

Targeted molecular profiling of solid tumours-Indian tertiary cancer centre experience

PURPOSE

Molecular Profiling of solid tumours is extensively used for prognostic, theranostic, and risk prediction. Next generation sequencing (NGS) has emerged as powerful method for molecular profiling. The present study was performed to identify molecular alterations present in solid tumours in Indian tertiary cancer centre.

METHODS

Study included 1140 formalin Fixed paraffin embedded samples. NGS was performed using two targeted gene panels viz. Ampliseq Focus panel and Sophia Solid Tumor Plus Solution. Data was analyzed using Illumina's Local Run Manager and SOPHiA DDM software. Variant interpretation and annotations were done as per AMP/ACMG guidelines.

RESULTS

Total 896 cases were subjected to NGS after excluding cases with suboptimal nucleic acid quality/quantity. DNA alterations were detected in 64.9% and RNA fusions in 6.9% cases. Among detected variants, 86.7% were clinically relevant aberrations. Mutation frequency among different solid tumours was 70.8%, 67.4%, 64.4% in non-small cell lung (NSCLC), lung squamous cell carcinomas and head neck tumours respectively. EGFR, KRAS, BRAF, ALK and ROS1were commonly altered in NSCLC. Gastrointestinal tumours showed mutations in 63.6% with predominant alterations in pancreatic (88.2%), GIST (87.5%), colorectal (78.7%), cholangiocarcinoma (52.9%), neuroendocrine (45.5%), gall bladder (36.7%) and gastric adenocarcinomas (16.7%). The key genes affected were KRAS, NRAS, BRAF and PIK3CA. NGS evaluation identified co-occurring alterations in 37.7% cases otherwise missed by conventional assays. Resistance mutations were detected in progressive lung tumours (39.5%) against EGFR TKIs and ALK/ROS inhibitors.

CONCLUSION

This is the largest Indian study on molecular profiling of solid tumours providing extensive information about mutational signatures using NGS.

Harnessing the value of TCTP in breast cancer treatment resistance: an opportunity for personalized therapy

Early identification of breast cancer (BC) patients at a high risk of progression may aid in therapeutic and prognostic aims. This is especially true for metastatic disease, which is responsible for most cancer-related deaths. Growing evidence indicates that the translationally controlled tumor protein (TCTP) may be a clinically relevant marker for identifying poorly differentiated aggressive BC tumors. TCTP is an intriguing protein with pleiotropic functions, which is involved in multiple signaling pathways. TCTP may also be involved in stress response, cell growth and proliferation-related processes, underlying its potential role in the initiation of metastatic growth. Thus, TCTP marks specific cancer cell sub-populations with pronounced stress adaptation, stem-like and immune-evasive properties. Therefore, we have shown that in vivo phospho-TCTP levels correlate with the response of BC cells to anti-HER2 agents. In this review, we discuss the clinical relevance of TCTP for personalized therapy, specific TCTP-targeting strategies, and currently available therapeutic agents. We propose TCTP as an actionable clinically relevant target that could potentially improve patient outcomes.

Molecular profiling of solid tumors by next-generation sequencing: an experience from a clinical laboratory

Background

Personalized targeted therapies have transformed management of several solid tumors. Timely and accurate detection of clinically relevant genetic variants in tumor is central to the implementation of molecular targeted therapies. To facilitate precise molecular testing in solid tumors, targeted next-generation sequencing (NGS) assays have emerged as a valuable tool. In this study, we provide an overview of the technical validation, diagnostic yields, and spectrum of variants observed in 3,164 solid tumor samples that were tested as part of the standard clinical diagnostic assessment in an academic healthcare institution over a period of 2 years.

Methods

The Ion Ampliseq™ Cancer Hotspot Panel v2 assay (ThermoFisher) that targets ~2,800 COSMIC mutations from 50 oncogenes and tumor suppressor genes was validated, and a total of 3,164 tumor DNA samples were tested in 2 years. A total of 500 tumor samples were tested by the comprehensive panel containing all the 50 genes. Other samples, including 1,375 lung cancer, 692 colon cancer, 462 melanoma, and 135 brain cancer, were tested by tumor-specific targeted subpanels including a few clinically actionable genes.

Results

Of 3,164 patient samples, 2,016 (63.7%) tested positive for at least one clinically relevant variant. Of 500 samples tested by a comprehensive panel, 290 had a clinically relevant variant with TP53, KRAS, and PIK3CA being the most frequently mutated genes. The diagnostic yields in major tumor types were as follows: breast (58.4%), colorectal (77.6%), lung (60.4%), pancreatic (84.6%), endometrial (72.4%), ovary (57.1%), and thyroid (73.9%). Tumor-specific targeted subpanels also demonstrated high diagnostic yields: lung (69%), colon (61.2%), melanoma (69.7%), and brain (20.7%). Co-occurrence of mutations in more than one gene was frequently observed.

Conclusions

The findings of our study demonstrate the feasibility of integrating an NGS-based gene panel screen as part of a standard diagnostic protocol for solid tumor assessment. High diagnostic rates enable significant clinical impact including improved diagnosis, prognosis, and clinical management in patients with solid tumors.

AMG-510 and cisplatin combination increases antitumor effect in lung adenocarcinoma with mutation of KRAS G12C: a preclinical and translational research

BACKGROUND

The efficacy of monotherapy of AMG-510 is limited. This study explored whether the AMG-510 and cisplatin combination increases the anti-tumor effect in lung adenocarcinoma with the mutation of Kirsten rat sarcoma viral oncogene (KRAS) G12C.

METHODS

Patients' data were used to analyze the proportion of KRAS G12C mutation. Besides, the next-generation sequencing data was used to uncover information about co-mutations. The cell viability assay, the concentration inhibiting 50% of cell viability (IC50) determination, colony formation, and cell-derived xenografts were conducted to explore the anti-tumor effect of AMG-510, Cisplatin, and their combination in vivo. The bioinformatic analysis was conducted to reveal the potential mechanism of drug combination with improved anticancer effect.

RESULTS

The proportion of KRAS mutation was 2.2% (11/495). In this cohort with KRAS mutation, the proportion of G12D was higher than others. Besides, KRAS G12A mutated tumors had the likelihood of concurrent serine/threonine kinase 11 (STK11) and kelch-like ECH-associated protein 1 (KEAP1) mutations. KRAS G12C and tumor protein p53 (TP53) mutations could appear at the same time. In addition, KRAS G12D mutations and C-Ros oncogene 1 (ROS1) rearrangement were likely to be present in one tumor simultaneously. When the two drugs were combined, the respective IC50 values were lower than when used alone. In addition, there was a minimum number of clones among all wells in the drug combination. In in vivo experiments, the tumor size reduction in the drug combination group was more than twice that of the single drug group (p < 0.05). The differential expression genes were enriched in the pathways of phosphatidylinositol 3 kinase-protein kinase B (PI3K-Akt) signaling and extracellular matrix (ECM) proteoglycans compared the combination group to the control group.

CONCLUSIONS

The anticancer effect of the drug combination was confirmed to be better than monotherapy in vitro and in vivo. The results of this study may provide some information for the plan of neoadjuvant therapy and the design of clinical trials for lung adenocarcinoma patients with KRAS G12C mutation.

Establishing an RNA fusions panel in soft tissue sarcoma with clinical validation

The diagnosis and classification of soft tissue sarcomas (STS) remain challenging because of the rarity and overlapping morphologic manifestations of diverse STS subtypes. Characteristic gene fusions are commonly detected in STS and represent useful diagnostic markers. This study established and validated a custom-designed RNA sequencing panel that identified 64 gene fusions in STS. The analytical performance validation yielded excellent accuracy, with 100% (95% CI, 94.40%-100%) sensitivity and 93.33% (95% CI, 68.05%-99.83%) specificity. Clinical performances were further confirmed with 145 clinical formalin-fixed and paraffin-embedded (FFPE) samples from STS patients. Fusions were detected in 40% of samples (58/145). The common fusions SS18-SSX family, EWSR1-related fusions, COL1A1-PDGFB, FOXO1-associated fusions, and FUS-associated fusions were identified in corresponding STS subtypes. The RNA panel detected specific fusions in several cases where no conclusive diagnosis can be made based on the morphology and immunohistochemistry results. Data collected in this study demonstrate that the RNA fusions panel can better classify STS subtypes and serve as a good supplement for histopathology, exhibiting a great potential for the STS precise diagnosis.

Comparison of two next-generation sequencing-based approaches for liquid biopsy analysis in patients with non-small cell lung cancer: a multicentre study

In the era of personalised medicine, testing for an increasing number of predictive biomarkers is becoming a priority. However, tissue biopsies from these patients are oftentimes insufficient for conventional approaches, a common issue that deprives them of the clinical benefits of biomarker-directed treatments. To tackle this problem, many clinical laboratories are resorting to circulating tumour DNA (ctDNA), which is becoming increasingly appreciated as a valuable source for biomarker testing. In this context, next-generation sequencing (NGS) has become essential. Indeed, different NGS systems are able to detect several clinically relevant low-frequency hot-spot mutations simultaneously in a single run. However, their reproducibility in the analysis of ctDNA has not yet been investigated. The purpose of this study was to evaluate the reproducibility of using Illumina MiSeq and Thermo Fisher Ion S5 Plus platforms to assess pathogenic alterations in non-small cell lung cancer (NSCLC) liquid biopsy specimens. Using the in vitro diagnostic (IVD) NGS panel Myriapod NGS Cancer panel DNA (Diatech Pharmacogenetics) on MiSeq platform (Illumina), we reanalysed ctDNA extracted from a retrospective series of n=40 patients with advanced NSCLC previously tested with a custom NGS panel (SiRe) on Thermo Fisher Ion S5 Plus system. Overall, 13 out of 40 (32.5%) ctDNA samples displayed pathogenic alterations in at least two genes, namely, EGFR and KRAS A concordance rate of 100% was identified between the two methodologies in terms of sample mutational status and total number of detected variables. All NGS platforms featured a high degree of concordance.

AIMedGraph: a comprehensive multi-relational knowledge graph for precision medicine

The development of high-throughput molecular testing techniques has enabled the large-scale exploration of the underlying molecular causes of diseases and the development of targeted treatment for specific genetic alterations. However, knowledge to interpret the impact of genetic variants on disease or treatment is distributed in different databases, scientific literature studies and clinical guidelines. AIMedGraph was designed to comprehensively collect and interrogate standardized information about genes, genetic alterations and their therapeutic and diagnostic relevance and build a multi-relational, evidence-based knowledge graph. Graph database Neo4j was used to represent precision medicine knowledge as nodes and edges in AIMedGraph. Entities in the current release include 30 340 diseases/phenotypes, 26 140 genes, 187 541 genetic variants, 2821 drugs, 15 125 clinical trials and 797 911 supporting literature studies. Edges in this release cover 621 731 drug interactions, 9279 drug susceptibility impacts, 6330 pharmacogenomics effects, 30 339 variant pathogenicity and 1485 drug adverse reactions. The knowledge graph technique enables hidden knowledge inference and provides insight into potential disease or drug molecular mechanisms. Database URL: http://aimedgraph.tongshugene.net:8201.

Comprehensive genomic profiling: Does timing matter?

Purpose

There is variability in utilization of Comprehensive Genomic Profiling (CGP) in most of the metastatic solid tumors (MST). We evaluated the CGP utilization patterns and its impact on outcomes at an academic tertiary center.

Patients and Methods

Institutional database was reviewed for CGP data in adult patients with MST between 01/2012 - 04/2020. Patients were categorized based on interval between CGP and metastatic diagnosis; 3 tertiles of distribution (T1-earliest to the diagnosis, T3-furthest), and pre-mets (CGP performed prior to diagnosis of metastasis). Overall survival (OS) was estimated from the time of metastatic diagnosis with left truncation at the time of CGP. Cox regression model was used to estimate the impact of timing of CGP on survival.

Results

Among 1,358 patients, 710 were female, 1,109 Caucasian, 186 Afro-Americans, and 36 Hispanic. The common histologies were lung cancer (254; 19%), colorectal cancer (203; 15%), gynecologic cancers (121; 8.9%), and pancreatic cancer (106; 7.8%). Time interval between diagnosis of metastatic disease and CGP was not statistically significantly different based on sex, race and ethnicity after adjusting for histologic diagnoses with 2 exceptions - Hispanics with lung cancer had delayed CGP compared to non-Hispanics (p =0.019) and females with pancreas cancer had delayed CGP compared to males (p =0.025). Lung cancer, gastro-esophageal cancer and gynecologic malignancies had better survival if they had CGP performed during the first tertile after metastatic diagnosis.

Conclusion

CGP utilization across cancer types was equitable irrespective of sex, race and ethnicity. Early CGP after metastatic diagnosis might have effect on treatment delivery and clinical outcomes in cancer type with more actionable targets.

Pan-cancer analyses reveal IGSF10 as an immunological and prognostic biomarker

Background: IGSF10 is a member of the immunoglobulin superfamily. Over the previous decade, growing proof has validated definitive correlations between individuals of the immunoglobulin superfamily and human diseases. However, the function of IGSF10 in pan-cancer stays unclear. We aimed to analyze the immunological and prognostic value of IGSF10 in pan-cancer. Methods: We utilized a vary of bioinformatic ways to inspect the function of IGSF10 in pan-cancer, including its correlation with prognosis, immune cell infiltration, tumor mutational burden (TMB), microsatellite instability (MSI), mismatch repair (MMR), DNA methyltransferases, genetic alteration, drug sensitivity, etc. Results: We noticed low expression of IGSF10 in most cancer types. IGSF10 expression in tumor samples correlates with prognosis in most cancers. In most cancer types, IGSF10 expression was strongly related to immune cells infiltration, immune checkpoints, immune modulators, TMB, MSI, MMR, and DNA methyltransferases, among others. Functional enrichment analyses indicated that IGSF10 expression was involved in lymphocyte differentiation, cell molecules adhesion, etc. Furthermore, low IGSF10 expression could increase the drug sensitivity of many drugs. Conclusion: IGSF10 could serve as a novel prognostic marker and attainable immunotherapy target for several malignancies.

A systematic review on the association between ovarian and prostate cancer with <I>BRCA1</I> and <I>BRCA2</I> gene

Background. BRCA1 and BRCA2 were discussed as the basis of inherited adenocarcinoma and breast and ovarian malignancy. Ovarian cancer is uncommon in women below 40 years of age, and prostate cancer mainly occurs in older men cause 90 % in those above sixty-fve.

Objective. The main objective of this paper is to investigate the relationship between ovarian and prostate cancer with the BRCA1 and BRCA2 genes.

Material and Methods. The ovarian and prostate cancer mechanism is discussed in detail, and their preventive measures with screening techniques are also demonstrated. This systematic review collected the related articles from online databases using the key terms ovarian cancer, prostate cancer, BRCA genes, mutation, polymorphism, carcinoma, sarcoma, and genetic association.

Results. Based on the obtained information, it is found that the BRCA genes are highly associated with prostate cancer in men, and in women, it is significantly linked with breast cancer than ovarian cancer.

Conclusion. Therefore, early diagnosis and genetic testing for BRCA1&BRCA2 genes in both men and women are necessary. In some cases, these genes might even cause different types of cancer like pancreatic cancers. Identifying individuals with tumour-HRD through mutations in the homologous repair pathway and determining this gene expression is essential to improve treatment techniques developed during the previous decade and rapidly make their way into clinical trials practice. However, the safe introduction of these medicines into everyday practice will require a thorough understanding of treatment targets and associated adverse effects. 

Healthcare professionals' perspectives on implementation of universal tumor DNA testing in ovarian cancer patients: multidisciplinary focus groups

Universal tumor DNA testing in epithelial ovarian cancer patients can function not only as an efficient prescreen for hereditary cancer testing, but may also guide treatment choices. This innovation, introduced as Tumor-First workflow, offers great opportunities, but ensuring optimal multidisciplinary collaboration is a challenge. We investigated factors that were relevant and important for large-scale implementation. In three multidisciplinary online focus groups, healthcare professionals (gynecologic oncologists, pathologists, clinical geneticists, and clinical laboratory specialists) were interviewed on factors critical for the implementation of the Tumor-First workflow. Recordings were transcribed for analysis in Atlas.ti according to the framework of Flottorp that categorizes seven implementation domains. Healthcare professionals from all disciplines endorse implementation of the Tumor-First workflow, but more detailed standardization and advice regarding the logistics of the workflow were needed. Healthcare professionals explored ways to stay informed about the different phases of the workflow and the results. They emphasized the importance of including all epithelial ovarian cancer patients in the workflow and monitoring this inclusion. Overall, healthcare professionals would appreciate supporting material for the implementation of the Tumor-First workflow in the daily work routine. Focus group discussions have revealed factors for developing a tailored implementation strategy for the Tumor-First workflow in order to optimize care for epithelial ovarian cancer patients. Future innovations affecting multidisciplinary oncology teams including clinical geneticists can benefit from the lessons learned.

An innovative single-base extension method for synchronous detection of point mutations and MSI status in colorectal cancer

BACKGROUND

An accurate genotyping analysis is one of the critical prerequisites for patients with colorectal cancer receiving matched therapies. Conventional genotyping analysis is currently used to detect either gene mutations or MSI status, delaying the detection of critical tumor biomarkers and thus the optimal time for treatment. An assay that analyzes both biomarkers in a streamlined process is eagerly needed.

METHODS

We developed an assay combining Multiplex PCR Amplification, Single-base Extension and capillary electrophoresis (CE) analysis (MASE-CE) for synchronous detection of KRAS/NRAS/BRAF mutations and MSI status. In a 190 colorectal cancer cohort, we identified seven somatic mutations in KRAS, NRAS and BRAF as well as five MSI loci (D2S123/D5S346/D17S250/BAT-25/BAT-26) simultaneously. KRAS/NRAS/BRAF mutations were detected by NGS and MASE-CE, and MSI status were detected by PCR-CE and MASE-CE methods.

RESULTS

The MASE-CE method showed high consistency with NGS for mutation detection (Kappa value ≥0.8) and PCR-CE (Kappa value = 0.79). In addition, the limits of detection (LOD) of MASE-CE assay for MSI and somatic mutation were 5% and 2%, respectively.

CONCLUSIONS

In somatic mutation detection and MSI detection, the LOD of MASE-CE assay was superior to that of qPCR and NGS. MASE-CE assay is a highly sensitive, time-saving and specimen-saving method, which can greatly avoid the cumbersome testing process and provide clinical decision for doctors in time.

Molecular characterization of genomic breakpoints of ALK rearrangements in non-small cell lung cancer

ALK rearrangement is called the 'diamond mutation' in non-small cell lung cancer (NSCLC). Accurately identifying patients who are candidates for ALK inhibitors is a key step in making clinical treatment decisions. In this study, a total of 783 ALK rearrangement-positive NSCLC cases were identified by DNA-based next-generation sequencing (NGS), including 731 patients with EML4-ALK and 52 patients with other ALK rearrangements. Diverse genomic breakpoints of ALK rearrangements were identified. Approximately 94.4% (739/783) of the cases carried ALK rearrangements with genomic breakpoints in the introns of ALK and its partner genes, and 2.8% (21/739) of these cases resulted in frameshift transcripts of ALK. Meanwhile, 5.6% (44/783) of the ALK rearrangement-positive cases had breakpoints in the exons that would be expected to result in abnormal transcripts. RNA-based NGS was performed to analyse the aberrant fusions at the transcript level. Some of these rearranged DNAs were not transcribed, and the others were fixed by some mechanisms so that the fusion kinase proteins could be expressed. Altogether, these findings emphasize that, when using DNA-based NGS, functional RNA fusions should be confirmed in cases with uncommon/frameshift rearrangement by RNA-based assays.

Exploiting the Molecular Basis of Oesophageal Cancer for Targeted Therapies and Biomarkers for Drug Response: Guiding Clinical Decision-Making

Worldwide, oesophageal cancer is the sixth leading cause of deaths related to cancer and represents a major health concern. Sub-Saharan Africa is one of the regions of the world with the highest incidence and mortality rates for oesophageal cancer and most of the cases of oesophageal cancer in this region are oesophageal squamous cell carcinoma (OSCC). The development and progression of OSCC is characterized by genomic changes which can be utilized as diagnostic or prognostic markers. These include changes in the expression of various genes involved in signaling pathways that regulate pathways that regulate processes that are related to the hallmarks of cancer, changes in the tumor mutational burden, changes in alternate splicing and changes in the expression of non-coding RNAs such as miRNA. These genomic changes give rise to characteristic profiles of altered proteins, transcriptomes, spliceosomes and genomes which can be used in clinical applications to monitor specific disease related parameters. Some of these profiles are characteristic of more aggressive forms of cancer or are indicative of treatment resistance or tumors that will be difficult to treat or require more specialized specific treatments. In Sub-Saharan region of Africa there is a high incidence of viral infections such as HPV and HIV, which are both risk factors for OSCC. The genomic changes that occur due to these infections can serve as diagnostic markers for OSCC related to viral infection. Clinically this is an important distinction as it influences treatment as well as disease progression and treatment monitoring practices. This underlines the importance of the characterization of the molecular landscape of OSCC in order to provide the best treatment, care, diagnosis and screening options for the management of OSCC.

Neurotransmitters: Potential Targets in Glioblastoma

Simple Summary

Aiming to discover potential treatments for GBM, this review connects emerging research on the roles of neurotransmitters in the normal neural and the GBM microenvironments and sheds light on the prospects of their application in the neuropharmacology of GBM. Conventional therapy is blamed for its poor effect, especially in inhibiting tumor recurrence and invasion. Facing this dilemma, we focus on neurotransmitters that modulate GBM initiation, progression and invasion, hoping to provide novel therapy targeting GBM. By analyzing research concerning GBM therapy systematically and scientifically, we discover increasing insights into the regulatory effects of neurotransmitters, some of which have already shown great potential in research in vivo or in vitro. After that, we further summarize the potential drugs in correlation with previously published research. In summary, it is worth expecting that targeting neurotransmitters could be a promising novel pharmacological approach for GBM treatment.

Abstract

For decades, glioblastoma multiforme (GBM), a type of the most lethal brain tumor, has remained a formidable challenge in terms of its treatment. Recently, many novel discoveries have underlined the regulatory roles of neurotransmitters in the microenvironment both physiologically and pathologically. By targeting the receptors synaptically or non-synaptically, neurotransmitters activate multiple signaling pathways. Significantly, many ligands acting on neurotransmitter receptors have shown great potential for inhibiting GBM growth and development, requiring further research. Here, we provide an overview of the most novel advances concerning the role of neurotransmitters in the normal neural and the GBM microenvironments, and discuss potential targeted drugs used for GBM treatment.

Protein Regulator of Cytokinesis 1 (PRC1) Upregulation Promotes Immune Suppression in Liver Hepatocellular Carcinoma

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with widespread prevalence. The suppressive immune environment causes largely refractory to current treatment. The protein regulator of cytokinesis 1 (PRC1) is an essential gene for cytokinesis and is involved in cancer pathogenesis. However, the functions of PRC1 have been barely clarified, especially in LIHC. Here, we investigated the expression, prognostic value, and functions of PRC1 in LIHC. Pan-cancer analysis revealed the overexpression of PRC1 in the Cancer Genome Atlas (TCGA) database. Four LIHC datasets from the Gene Expression Omnibus (GEO) database confirmed the PRC1 overexpression in LIHC. The mRNA and protein levels of PRC1 in LIHC cells were higher than in normal liver cells. The overexpression of PRC1 predicted progressed clinical stage and poor prognosis of LIHC. We further investigated the functions of PRC1 by performing the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, and Gene Set Enrichment Analysis (GSEA) of its coexpressing genes. High PRC1 expression was associated with increased genome instability of LIHC. Moreover, PRC1 was positively correlated with the infiltration of suppressive immune cells like T regulatory cells (Tregs) and polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) and was negatively correlated with the effector immune cells' infiltration, including B cells and CD8+ T cells. In addition, PRC1 was positively correlated with the expression of tumor immune checkpoint molecules. Taken together, PRC1 overexpression contributes to the genome instability and the suppressive immune microenvironment of LIHC. Thus, PRC1 has the potential to be a prognostic marker and therapeutic target of LIHC.

Frequently Expressed Glypican-3 As A Promising Novel Therapeutic Target for Osteosarcomas

Osteosarcoma (OS) is the most common bone malignancy without a reliable therapeutic target. Glypican-3 (GPC3) mutation and upregulation have been detected in multi-drug resistant OS, and anti-GPC3 immunotherapy can effectively suppress the growth of organoids. Further profiling of GPC3 mutations and expression patterns in OS is of clinical significance. To address these issues, fresh OS specimens were collected from 24 patients for cancer-targeted next-generation sequencing (NGS) and three-dimensional patient-derived organoid (PDO) culture. A tumor microarray was prepared using 37 archived OS specimens. Immunohistochemical (IHC) staining was performed on OS specimens and microarrays to profile GPC3 and CD133 expression as well as intratumoral distribution patterns. RT-PCR was conducted to semi-quantify GPC3 and CD133 expression levels in the OS tissues. Anti-GPC3 immunotherapy was performed on OS organoids with or without GPC3 expression and its efficacy was analyzed using multiple experimental approaches. No OS cases with GPC3 mutations were found, except for the positive control (OS-08). IHC staining revealed GPC3 expression in 73.77% (45/61) of OSs in weak (+; 29/45), moderate (++; 8/45), and strong (+++; 8/45) immunolabeling densities. The intratumoral distribution of GPC3-positive cells was variable in the focal (+; 10-30%; 8/45), partial (++; 31-70%; 22/45), and the most positive patterns (+++; > 71%; 15/45), which coincided with CD133 immunolabeling (P = 9.89×10^-10 ). The anti-GPC3 antibody efficiently inhibits Wnt/β-catenin signaling and induces apoptosis in GPC3-positive PDOs and PDXs, as opposed to GPC3-negative PDOs and PDXs. The high frequency of GPC3 and CD133 co-expression and the effectiveness of anti-wildtype GPC3-ab therapy in GPC3-positive OS models suggest that GPC3 is a novel prognostic parameter and a promising therapeutic target for osteosarcoma.

Organoids as a Model for Precision Medicine in Malignant Pleural Mesothelioma: Where Are We Today?

MPM is an aggressive tumor originating from pleural mesothelial cells. A characteristic feature of the disease is the dominant prevalence of therapeutically intractable inactivating alterations in TSGs, making MPM one of the most difficult cancers to treat and the epitome of a cancer characterized by a significant lack of therapy options and an extremely poor prognosis (5-year survival rate of only 5% to 10%). Extensive interpatient heterogeneity poses another major challenge for targeted therapy of MPM, warranting stratified therapy for specific subgroups of MPM patients. Accurate preclinical models are critical for the discovery of new therapies and the development of personalized medicine. Organoids, an in vitro 'organ-like' 3D structure derived from patient tumor tissue that faithfully mimics the biology and complex architecture of cancer and largely overcomes the limitations of other existing models, are the next-generation tumor model. Although organoids have been successfully produced and used in many cancers, the development of MPM organoids is still in its infancy. Here, we provide an overview of recent advances in cancer organoids, focusing on the progress and challenges in MPM organoid development. We also elaborate the potential of MPM organoids for understanding MPM pathobiology, discovering new therapeutic targets, and developing personalized treatments for MPM patients.

Alteration in the Immune Microenvironment Based on APC Status in MSS/pMMR Colon Cancer

Introduction. Immunotherapy is currently the most promising antitumor treatment approach. However, the colon cancer immunotherapy indication dMMR/MSI-H do not cover all colon cancer patients suitable for immunotherapy. We performed transcriptome-wide expression profile analyses of pMMR/MSS colon adenocarcinoma (COAD) specimens from TCGA database to identify a genetype signature associated with tumor immune microenvironment types (TIMTs). Methods. TCGA database was used to identify tumor genotypes suitable for antitumor immunotherapy. We analyzed RNA-sequencing profiles of 338 COAD targeted to the pMMR/MSS group from TCGA public dataset. The ESTIMATE and the CIBERSORT were used to analyze the pMMR/MSS COAD immune microenvironment between APC wild and APC mutation. Furthermore, we further verified the relationship between APC genotype and TIMTs and the efficacy of immunotherapy in 42 colon cancer specimens. Results. We identified that in APC-wt/MSS colon cancer, the expressions of PD-1, PD-L1, CTLA4, and CYT (GZMA and PRF1) were increased. The TMB, Immunoscore, and the proportion of CT8+ T cell infiltration also were identified increasing in these patients. And pathway enrichment analysis for differentially expressed genes (DEGs) between APC-wt and APC-mt MSS COAD was done to further explore their biological function. Similarly, the significant pathways for DEGs were mainly enriched in the immune response, extracellular matrix, and cell adhesion which involved in immune response. Specimens from 42 colon cancer patients, including 22 APC-mt/MSS and 20 APC-wt/MSS, were immunohistochemically evaluated for expression of CD8 and PD-L1. And APC-wt/MSS tumors showed significantly higher expression of CD8 and PD-L1 than APC-mt/MSS tumor. Moreover, APC-wt was compared with APC-mt MSS/pMMR colon cancer (DOR, 45% and 26.7%, respectively; $P<0.05$ ). Conclusion. Based on the results, we found that more colon cancers of APC-wt/MSS are classified by TMIT I. And APC-wt/MSS colon cancer patients are more likely to benefit from antitumor immunotherapy.

"Doing Good" in U.S. Cancer Genomics? Valuation practices across the boundaries of research and care in rural community oncology

Genomic Tumour Testing (GTT) is an emerging site of "experimental care" in oncology [Cambrosio, Alberto, Peter Keating, Etienne Vignola-Gagné, Sylvain Besle, and Pascale Bourret. 2018a. "Extending Experimentation: Oncology's Fading Boundary Bbetween Research and Care." New Genetics and Society 37 (3): 207-226. doi: 10.1080/14636778.2018.1487281]. Few efforts to implement GTT have reached community oncology practices or patients living in rural communities within the US. Drawing on interdisciplinary research on a state-wide cancer genomics initiative in the rural US state of Maine, this paper explores the valuation practices within community oncologist and cancer stakeholders accounts of "doing good" within genomic science and care. We contribute to STS literatures on the bio-economy by highlighting the affective dimensions of strategies for managing economic and non-economic values. Clinician and stakeholders negotiated de-economizing and capitalizing modes of doing good as they built local genomic platforms "for Maine." These situated modes of doing good and feeling good via cancer genomics shaped how they navigated the ethical ambiguities of US biomedical markets across the boundaries of research and care.

Personalized treatment for hepatocellular carcinoma: Current status and future perspectives

Systemic treatment for hepatocellular carcinoma (HCC) has been advancing rapidly over the last decade. More novel agents, including both targeted agents and immune checkpoint inhibitors, are available for physicians to use sequentially or concurrently for patients with advanced HCC. Despite more options, only a proportion of patients benefit from each regimen. Therefore, clinicians are facing challenges on how to choose the right regimen for the right patient with HCC, which raises the importance of personalized treatment approach. To advance personalized treatment for HCC, one approach relies on the acquisition of biomarker data from clinical trials to evaluate clinical parameters or genotypes in association with outcomes of selected drugs. This approach has led to finding of high baseline alpha-fetoprotein levels in association with benefits of ramucirumab. Cumulative findings from multiple clinical trials and translational studies also suggest that selected etiology and/or genotype of HCC could predict resistance to immune checkpoint inhibitors. The second approach is to decipher the tumor heterogeneity of HCC with an aim to identify clinically relevant patterns to guide clinical decisions. Tumor heterogeneity could exist within a single tumor (intra-tumoral heterogeneity), among different tumors in the same patient (inter-tumoral heterogeneity) or between primary and recurrent tumors (temporal tumor heterogeneity). The analyses of tumor heterogeneity have also been powered by coverage of tumor immune environment and incorporation of circulating tumor nucleic acid technology. Emerging publications have been reported above tumor heterogeneity exist in HCC, which is potentially clinically impactful.

Drug Resistance in Colorectal Cancer: From Mechanism to Clinic

Colorectal cancer (CRC) is one of the leading causes of death worldwide. The 5-year survival rate is 90% for patients with early CRC, 70% for patients with locally advanced CRC, and 15% for patients with metastatic CRC (mCRC). In fact, most CRC patients are at an advanced stage at the time of diagnosis. Although chemotherapy, molecularly targeted therapy and immunotherapy have significantly improved patient survival, some patients are initially insensitive to these drugs or initially sensitive but quickly become insensitive, and the emergence of such primary and secondary drug resistance is a significant clinical challenge. The most direct cause of resistance is the aberrant anti-tumor drug metabolism, transportation or target. With more in-depth research, it is found that cell death pathways, carcinogenic signals, compensation feedback loop signal pathways and tumor immune microenvironment also play essential roles in the drug resistance mechanism. Here, we assess the current major mechanisms of CRC resistance and describe potential therapeutic interventions.

Modeling colorectal cancer: A bio-resource of 50 patient-derived organoid lines

BACKGROUND AND AIM

Colorectal cancer (CRC) is the second leading cause of cancer death worldwide. To improve outcomes for these patients, we need to develop new treatment strategies. Personalized cancer medicine, where patients are treated based on the characteristics of their own tumor, has gained significant interest for its promise to improve outcomes and reduce unnecessary side effects. The purpose of this study was to examine the potential utility of patient-derived colorectal cancer organoids (PDCOs) in a personalized cancer medicine setting.

METHODS

Patient-derived colorectal cancer organoids were derived from tissue obtained from treatment-naïve patients undergoing surgical resection for the treatment of CRC. We examined the recapitulation of key histopathological, molecular, and phenotypic characteristics of the primary tumor.

RESULTS

We created a bio-resource of PDCOs from primary and metastatic CRCs. Key histopathological features were retained in PDCOs when compared with the primary tumor. Additionally, a cohort of 12 PDCOs, and their corresponding primary tumors and normal sample, were characterized through whole exome sequencing and somatic variant calling. These PDCOs exhibited a high level of concordance in key driver mutations when compared with the primary tumor.

CONCLUSIONS

Patient-derived colorectal cancer organoids recapitulate characteristics of the tissue from which they are derived and are a powerful tool for cancer research. Further research will determine their utility for predicting patient outcomes in a personalized cancer medicine setting.

An Idealized Clinicogenomic Registry to Engage Underrepresented Populations Using Innovative Technology

Current best practices in tumor registries provide a glimpse into a limited time frame over the natural history of disease, usually a narrow window around diagnosis and biopsy. This creates challenges meeting public health and healthcare reimbursement policies that increasingly require robust documentation of long-term clinical trajectories, quality of life, and health economics outcomes. These challenges are amplified for underrepresented minority (URM) and other disadvantaged populations, who tend to view the institution of clinical research with skepticism. Participation gaps leave such populations underrepresented in clinical research and, importantly, in policy decisions about treatment choices and reimbursement, thus further augmenting health, social, and economic disparities. Cloud computing, mobile computing, digital ledgers, tokenization, and artificial intelligence technologies are powerful tools that promise to enhance longitudinal patient engagement across the natural history of disease. These tools also promise to enhance engagement by giving participants agency over their data and addressing a major impediment to research participation. This will only occur if these tools are available for use with all patients. Distributed ledger technologies (specifically blockchain) converge these tools and offer a significant element of trust that can be used to engage URM populations more substantively in clinical research. This is a crucial step toward linking composite cohorts for training and optimization of the artificial intelligence tools for enhancing public health in the future. The parameters of an idealized clinical genomic registry are presented.

Association Between the TP53 Polymorphisms and Breast Cancer Risk: An Updated Meta-Analysis

Background: The relationship of TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms with breast cancer (BC) risk has been analyzed in seventeen published meta-analyses. However, the credibility of statistically significant associations was ignored and many new studies have been reported on these themes.

Objectives: To explore whether TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms are associated with BC risk and the clinical phenomena.

Methods: To comprehensively search the data (through October 25, 2021), we provided a clear search strategy and reviewed the references of published meta-analyses. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) were used.

Results: The current meta-analysis had a larger sample size than the previous ones: 99 studies with 43,951 BC and 48,479 controls for TP53 codon 72 polymorphism, 35 studies with 8,705 BC and 7,516 controls for IVS3 16 bp polymorphism, and 25 studies with 12,222 BC and 12,895 controls for IVS6+62A > G polymorphism. Five gene models were used to explore the association between the three polymorphisms and BC risk, and partial positive results were similar to published meta-analyses results. However, a large number of significant results were considered to be unreliable after correcting with Bayesian false-discovery probability (BFDP), except for the association between TP53 IVS3 16 bp polymorphism and BC risk in overall analysis (GG vs. CC: BFDP = 0.738), matched studies (GG vs. CC: BFDP = 0.173; GG vs. CC + CG: BFDP = 0.447), and tumor size below 2 cm (GG vs. CC: BFDP = 0.088; GG + CG vs. CC: BFDP = 0.730; GG vs. CC + CG: BFDP = 0.311). These unreliable results were confirmed again without new solid results emerging in further sensitivity analysis (only studies in compliance with the quality assessment standard).

Conclusion: After considering the quality of the included studies and the reliability of the results, the present meta-analysis suggested that TP53 codons 72, IVS3 16 bp, and IVS6+62A > G polymorphisms were not significantly associated with the BC risk. Those results which prove that these three polymorphisms increase BC risk are more likely to be false-positive results due to various confounding factors.