Low-Cost, Transcriptional Diagnostic to Accurately Categorize Lymphomas in Low- and Middle-Income Countries

Valvert, Fabiola; Silva, Oscar; Solorzano, Elizabeth; Puligandla, Mäneka; Tala, Marcos Mauricio Siliézar; Guyon, Timothy; Dixon, Samuel L.; López, Nelly; López, Francisco J.; Terbrueggen, Robert; Stevenson, Kristen E.; Natkunam, Yasodha; Weinstock, David M.; Briercheck, Edward L.

doi:10.2139/ssrn.3564407

Cited by 4 publications

(6 citation statements)

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“…This low-cost mRNA profiling approach differs distinctively from other work in developing novel diagnostic tools with potential applications in LMICs, such as parsimonious transcript expression measurement, fusion detection through PCR or Nanostring, or point-of-care replacements for flow cytometry. [48][49][50][51][52] First, this approach obviates the requirement of disease-specific reagents and primers and the associated creation of new supply chains. Second, this strategy allows for iterative improvement of classification algorithms, hosted in the cloud, rather than relying on hardware improvements or adjustments to primers.…”

Section: Discussionmentioning

confidence: 99%

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing

Wang

Bhakta

Miller³

et al. 2022

JCO Precision Oncology

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PURPOSE Most cases of pediatric acute leukemia occur in low- and middle-income countries, where health centers lack the tools required for accurate diagnosis and disease classification. Recent research shows the robustness of using unbiased short-read RNA sequencing to classify genomic subtypes of acute leukemia. Compared with short-read sequencing, nanopore sequencing has low capital and consumable costs, making it suitable for use in locations with limited health infrastructure. MATERIALS AND METHODS We show the feasibility of nanopore mRNA sequencing on 134 cryopreserved acute leukemia specimens (26 acute myeloid leukemia [AML], 73 B-lineage acute lymphoblastic leukemia [B-ALL], 34 T-lineage acute lymphoblastic leukemia, and one acute undifferentiated leukemia). Using multiple library preparation approaches, we generated long-read transcripts for each sample. We developed a novel composite classification approach to predict acute leukemia lineage and major B-ALL and AML molecular subtypes directly from gene expression profiles. RESULTS We demonstrate accurate classification of acute leukemia samples into AML, B-ALL, or T-lineage acute lymphoblastic leukemia (96.2% of cases are classifiable with a probability of > 0.8, with 100% accuracy) and further classification into clinically actionable genomic subtypes using shallow RNA nanopore sequencing, with 96.2% accuracy for major AML subtypes and 94.1% accuracy for major B-lineage acute lymphoblastic leukemia subtypes. CONCLUSION Transcriptional profiling of acute leukemia samples using nanopore technology for diagnostic classification is feasible and accurate, which has the potential to improve the accuracy of cancer diagnosis in low-resource settings.

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Section: Discussionmentioning

confidence: 99%

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing

Wang

Bhakta

Miller³

et al. 2022

JCO Precision Oncology

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“…Additionally, the re‐excision rates in her department have been trending down from 24% to 11%; because there is a minimal need for a second surgery to be performed, the overall cost for the patient decreases as well. Incorporation of machine learning algorithms to classify gene expression in low‐cost transcriptional diagnostics has accelerated the diagnosis of lymphomas in LMICs 105 …”

Section: Immunohistochemistry Other Molecular Diagnostic Techniquesmentioning

confidence: 99%

Technological advancements in cancer diagnostics: Improvements and limitations

et al. 2023

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Background: Cancer is characterized by the rampant proliferation, growth, and infiltration of malignantly transformed cancer cells past their normal boundaries into adjacent tissues. It is the leading cause of death worldwide, responsible for approximately 19.3 million new diagnoses and 10 million deaths globally in 2020. In the United States alone, the estimated number of new diagnoses and deaths is 1.9 million and 609 360, respectively. Implementation of currently existing cancer diagnostic techniques such as positron emission tomography (PET), X-ray computed tomography (CT), and magnetic resonance spectroscopy (MRS), and molecular diagnostic techniques, have enabled early detection rates and are instrumental not only for the therapeutic management of cancer patients, but also for early detection of the cancer itself. The effectiveness of these cancer screening programs are heavily dependent on the rate of accurate precursor lesion identification; an increased rate of identification allows for earlier onset treatment, thus decreasing the incidence of invasive cancer in the long-term, and improving the overall prognosis. Although these diagnostic techniques are advantageous due to lack of invasiveness and easier accessibility within the clinical setting, several limitations such as optimal target definition, high signal to background ratio and associated artifacts hinder the accurate diagnosis of specific types of deep-seated tumors, besides associated high cost. In this review we discuss various imaging, molecular, and low-cost diagnostic tools and related technological advancements, to provide a better understanding of cancer diagnostics, unraveling new opportunities for effective management of cancer, particularly in low-and middle-income countries (LMICs).Recent Findings: Herein we discuss various technological advancements that are being utilized to construct an assortment of new diagnostic techniques that incorporate hardware, image reconstruction software, imaging devices, biomarkers, and even artificial intelligence algorithms, thereby providing a reliable diagnosis and analysis of the tumor. Also, we provide a brief account of alternative low cost-effective cancer therapy devices (CryoPop ® , LumaGEM ® , MarginProbe ® ) and picture archiving and communication systems (PACS), emphasizing the need for multi-disciplinary

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“…Similarly, there are other molecular diagnostic technologies proving to have value for management of other cancers in LMICs, including the diagnosis and classification of lymphoma. [20][21][22][23] The Path Forward for Molecular Diagnostics and Global Oncology Our experience with on-site diagnostics for the management of CML has shown that molecular technologies can be leveraged to advance cancer care in LMICs. The question that remains is how and to what extent.…”

Section: Molecular Diagnostics In Infectious Diseasementioning

confidence: 99%

Leveraging Molecular Diagnostic Technologies to Close the Global Cancer Pathology Gap

Erfani

Bates²,

Garcia-Gonzalez³

et al. 2022

JCO Global Oncology

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Low-Cost, Transcriptional Diagnostic to Accurately Categorize Lymphomas in Low- and Middle-Income Countries

Cited by 4 publications

References 0 publications

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing

Acute Leukemia Classification Using Transcriptional Profiles From Low-Cost Nanopore mRNA Sequencing

Technological advancements in cancer diagnostics: Improvements and limitations

Leveraging Molecular Diagnostic Technologies to Close the Global Cancer Pathology Gap

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